Development and Evaluation of a Computerised and Individualised intervention for increasing Physical...

Faculty of Medicine and Health Sciences

Department of Movement and Sport Sciences

Development and Evaluation of a Computerised and Individualised intervention for increasing Physical Activity

and decreasing Fat Intake

Corneel Vandelanotte Thesis submitted in fulfilment of the requirements for the degree of Doctor in Physical Education

Promotor: Prof.Dr. I. De Bourdeaudhuij

Ghent 2004

Promotor Prof. Dr. I. De Bourdeaudhuij Universiteit Gent Leden van de Begeleidingscommisie Prof. Dr. G. De Backer Universiteit Gent Prof. Dr. J. Bouckaert Universiteit Gent Prof. Dr. P. Van Oost Universiteit Gent Prof. Dr. R. Philippaerts Universiteit Gent Leden van de Examencommissie Prof. Dr. Ir. J. Brug Erasmus MC Rotterdam Prof. Dr. Y. Vanden Auweele Katholieke Universiteit Leuven Prof. Dr. G. Beunen Katholieke Universiteit Leuven Prof. Dr. L. Maes Universiteit Gent Dr. V. Stevens Vlaams Instituut voor Gezondheidspromotie Dit project werd gefinancierd door het Bijzonder Onderzoeksfonds. ISBN 90-8090841-X © Corneel Vandelanotte, Ghent, 2004. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanically, by photocopy, by recording or otherwise, without the permission from the author.

Contents

Contents

Summary

Chapter 1. General Introduction 1

Chapter 2. Reliability and validity of a computerised and 23

Dutch version of the international physical activity

questionnaire (IPAQ)

Chapter 3. Reliability and validity of a computerised questionnaire 39

to measure fat intake in Belgium

Chapter 4 Acceptability and feasibility of a computer-tailored 51

physical activity intervention using stages of change

Chapter 5. Acceptability and feasibility of an interactive 65

computer-tailored fat intake intervention in Belgium

Chapter 6. Efficacy of sequential or simultaneous interactive 73

computer-tailored interventions for increasing physical

activity and decreasing fat intake

Chapter 7. General discussion 95

Publications 111

Acknowledgements 113

Appendix Addendum 1: CD-rom both interventions 115

Addendum 2: IPAQ 116

Addendum 3: GVET 123

Summary

Summary

There is a large body of epidemiological evidence showing the health benefits of regular

physical activity and a low fat diet. A reduced risk of premature mortality, cardiovascular

disease, diabetes, several types of cancer and obesity are among the most important to note.

In order to obtain these benefits health authorities recommend to accumulate at least 30

minutes of moderate-intensity physical activity on most, preferably all, days of the week and

to consume less than 30% energy from fat. However, in most western countries most people

are inactive and eat too much fat. It is very clear that there is a strong need for effective

primary prevention interventions aimed at increasing physical activity and decreasing fat

intake in the general population. However, reaching large populations at an individual level is

very costly and time consuming and, on the other hand, the use of mass media has often

showed to be of limited effect. These barriers might be overcome by using interactive

computer-tailored interventions. Tailored interventions provide respondents with personally

adapted feedback about their present health behavior and/or the behavioral determinants, as

well as personally adapted suggestions to change behaviors. The purpose of our project was

to develop and evaluate a computerised and individualised intervention for increasing

physical activity and decreasing fat intake. Further we also wished to examine whether

computer-tailored interventions can be used in a sequential or simultaneous intervening

mode.

In developing the computer-tailored physical activity intervention a computerised and Dutch

version of the International Physical Activity Questionnaire was tested on reliability and

validity; the questionnaire showed to be acceptable for further use. In developing the

computer-tailored fat intake intervention a new food frequency questionnaire measuring fat

intake needed to be developed and tested on reliability and validity; this measurement tool

showed to be acceptable for further use. Immediately after developing both interventions an

extensive acceptability and feasibility testing was executed; the results indicated that both

interventions could be used in a general public. Finally, in a randomised pretest-posttest

control group study evaluating the efficacy of the interventions it was concluded that both the

interactive computer-tailored physical activity and fat intake intervention can be applied

successfully to change behaviors. Further, both sequential and simultaneous intervening

modes can be used. From a public health point of view and because the simultaneous

intervention mode was superior for fat intake we recommend to implement the interventions

simultaneously.

Summary

Samenvatting

Verschillende studies tonen aan dat regelmatig fysiek actief zijn en het eten van een voeding

met weinig vet vele gezondheidsvoordelen heeft. De voornaamste zijn een verminderd risico

op vroegtijdig sterven, cardiovasculaire ziekten, verschillende kankers en zwaarlijvigheid.

Om van deze gezondheidsvoordelen te kunnen genieten wordt aangeraden om op zijn minst

30 minuten fysiek actief te zijn aan een matige intensiteit en dit op de meeste dagen van de

week en een energieopname te hebben waarvan minder dan 30% van het totaal uit vet

bestaat. In de praktijk blijkt echter dat slechts een klein deel van de bevolking aan deze

normen voldoet. Daarom is er een grote nood aan effectieve gezondheidspromotie

campagnes, enerzijds voor het verhogen van de fysieke activiteit en anderzijds voor het

verlagen van de vetinname. Het is echter duur en tijdrovend om grote groepen mensen op

een individuele manier te bereiken. Daarom kunnen computergestuurde en

geïndividualiseerde interventies een oplossing bieden, de zogenaamde

‘tailoringsinterventies’. In dit soort interventies krijgen de deelnemers persoonlijk aangepast

advies in verband met hun gezondheidsgedrag. Het doel van ons project was het ontwikkelen

en evalueren van een computergestuurde en geïndividualiseerde interventie enerzijds voor het

verhogen van de fysieke activiteit en anderzijds voor het verlagen van de vetinname.

Vervolgens wensten we ook na te gaan of deze interventies al dan niet gelijktijdig of na

elkaar (interval van drie maanden) aangeboden konden worden.

Gedurende de ontwikkeling van de fysieke activiteitsinterventie werd een computergestuurde

en Nederlandstalige versie van de internationale fysieke activiteitsvragenlijst getest op

betrouwbaarheid en validiteit; deze parameters bleken goed genoeg te zijn om de vragenlijst

verder te kunnen gebruiken. Gedurende de ontwikkeling van de vetinname interventie werd

een nieuwe vragenlijst voor het meten van de vetinname ontwikkeld en getest op

betrouwbaarheid en validiteit; opnieuw bleken deze parameters goed genoeg te zijn om de

vragenlijst verder te kunnen gebruiken. Onmiddellijk na het ontwikkelen van beide

interventies werd een uitgebreide gebruiksvriendelijkheidtest uitgevoerd; uit de resultaten

bleek dat beide interventies ruim voldoende scoren om gebruikt te kunnen worden. Tenslotte

werd in een effectenstudie (met pretest-posttest en controle-experimentele groep) duidelijk

dat beide interventies succesvol kunnen gebruikt worden om gedrag te veranderen. Verder

bleek ook dat de interventies zowel gelijktijdig als na elkaar (met interval van drie maanden)

kunnen gebruikt worden. Vanuit een gezondheidspromotie standpunt raden wij daarom aan

om de fysieke activiteit en vetinname interventie gelijktijdig aan te bieden, dat is handiger en

goedkoper.

Chapter 1

1

CHAPTER 1

General Introduction Problem analysis

There is a large body of epidemiological evidence showing the health benefits of regular

physical activity and, on the other hand, the negative effects of physical inactivity.1-3 Regular

participation in physical activity reduces the risk of premature mortality, coronary heart

disease, hypertension, colon cancer, diabetes mellitus, obesity, osteoporosis, osteoarthritis

and low back pain.4,5 Physical activity also appears to reduce depression and anxiety; and to

improve mood, functional capacity and the ability to perform daily tasks throughout the life

span.5 The Surgeon General report 5, the book by Hardman and Stensel 6 and the book by

Bouchard et al.7 all present a very extensive literature study about the relation between

physical activity and health; their main findings are outlined below. Higher levels of regular

physical activity are associated with lower mortality rates for both older and younger adults,

even for those who are moderately active. Regular physical activity also decreases the risk of

cardiovascular disease mortality in general and of coronary heart disease in particular. The

level of decreased risk attributable to regular physical activity is similar to that of other

lifestyle factors, such as keeping free from cigarette smoking. Physical activity prevents or

delays the development of high blood pressure, and reduces blood pressure in people with

hypertension. Regular physical activity is associated with a decreased risk of colon cancer,

however there is no association between physical activity and rectal cancer and data are to

sparse to draw conclusions regarding the relationship between physical activity and

endometrial, ovarian or testicular cancers. Despite numerous studies on the subject, the

existing data are inconsistent regarding an association between physical activity and breast or

prostate cancer. Regular physical activity is important for weight control and might increase

the use of kilocalories (also in rest by increasing muscle mass) over the amount of

kilocalories consumed, which might prevent or delay the development of obesity. Physical

General Introduction

2

activity also appears to favourably affect body fat distribution. The epidemiologic literature

strongly supports a protective effect of physical activity on the likelihood of developing type

2 diabetes. This is caused by an increased sensitivity to insulin, a reduced risk for

atherosclerosis (which decreases the risk of macrovascular or atherosclerotic complications

of diabetes) and by reducing total body fat or specifically intra-abdominal fat which is a

known risk factor for insulin resistance. Regular physical activity is necessary for

maintaining normal muscle strength, joint structure and joint function and may be beneficial

for many people with osteoarthritis. Weight-bearing physical activity is essential for normal

skeletal development during childhood and adolescence and for achieving and maintaining

peak bone mass in young adults. In doing so physical activity prevents osteoporosis. There is

promising evidence that strength training and other forms of exercise in older adults preserve

the ability to maintain independent living status and reduce the risk of falling. Physical

activity appears to relieve the symptoms of depression and anxiety and improve mood.

Regular physical activity may reduce the risk of developing depression, although further

research is needed on this topic. Physical activity appears to improve health-related quality of

life by enhancing psychological well-being and by improving physical functioning in persons

compromised by poor health. How much physical activity is needed to obtain these health

benefits has been questioned. For long scientists believed that health benefits could only be

obtained if an increase in physical fitness was accomplished.8 Such an increase can only be

established by doing intense physical activities. However, in 1995 it was agreed, based upon

a large amount of evidence, that an increase in physical fitness and intense physical activities

are not needed to obtain health benefits. According to the consensus statement significant

health benefits can be obtained by including at least 30 minutes of moderate-intensity

physical activity on most, preferably all, days of the week.9-11 Intermittent or shorter bouts of

activity (at least 10 minutes) also have similar cardiovascular and health benefits if performed

at a level of moderate intensity and if accumulated to at least 30 minutes a day.9,11 Additional

health benefits can be gained through greater amounts of physical activity. People who can

maintain a regular regime of activity that is of long duration or of vigorous intensity are

likely to derive greater benefits. Despite the well-documented health benefits and public

health efforts to increase physical activity, most adults remain under-active and only a limited

proportion of the population comply with these recommendations. World-wide only 15 to 25

% of the adult population engage in vigorous physical activity, about 35 to 50 % engage in

some physical activity of moderate intensity, and 30 to 45 % are completely inactive.5,12-17

Similar results have been found for Europe and Belgium.18-26 In 1997 and 2001 large

Chapter 1

3

population surveys on physical activity were executed in Belgium, the results showed that

only 33 % of the Belgian population engages in an activity that makes them sweat for at least

once a week. The authors conclude that at least half of the population does not do enough

activity to have any health benefit and they also note that there is no improvement in physical

activity levels from 1997 to 200121,22 Although physical activity levels within Europe are

comparable to each other, physical activity levels in Belgium are lower compared to most

other European countries.23-25,27

Similar to physical activity there is a lot of evidence showing the benefits of a low fat diet

and the adverse effects of a high fat diet. Diets which are high in fat intake, and especially

those having a high intake of saturated fats, are associated with an increased risk of

cardiovascular disease,28-31 several types of cancer,29,32 obesity33,34 and diabetes.35

Epidemiological studies show a strong, positive relationship between plasma cholesterol

concentrations and the incidence of atherosclerotic cardiovascular disease, with coronary

heart disease as one of the major causes of premature death.28,29 It has been shown that the

high plasma cholesterol levels are mainly caused by environmental rather than genetic

factors, this supports the notion that nutrition plays a major role. Many studies have

confirmed a strong association between fat intake, specifically saturated fat, mean total

cholesterol levels and rates of coronary heart disease mortality worldwide.29,30 Further,

studies have shown an association between fat intake and body mass index.36 The

consumption of a high fat diet increases the likelihood of obesity and that the risk of obesity

is low in individuals consuming low fat diets. A major argument for low fat diets is that

excess of fat intake itself and overweight are also associated with higher rates of coronary

heart disease. Obesity is associated with a negative effect on all major coronary heart disease

risk factors: cholesterol and triglyceride levels are raised, high density lipoprotein cholesterol

is lowered, blood pressure is increased and type 2 diabetes can be induced.35 Not only

obesity, which is the single most important determinant of type 2 diabetes, but a high fat diet

itself can induce type 2 diabetes, which may differentially affect insulin resistance. Finally, in

the past several studies have shown that total fat intake of a population is related to prostate,

colon, breast and ovarian cancers.29 However, many questions remain unanswered

concerning this topic and there is currently a strong debate ongoing to determine whether a

high intake of total fat and saturated fat influences the risk of developing cancer or not. The

current state of evidence suggests that there is no strong support for a direct relationship

between high intakes of total fat and saturated fat and the risk of cancer.37 In order to reduce


4

the risks of developing this kind of diseases most western countries formulated national

dietary guidelines. The first dietary guidelines were formulated by the American Heart

Association in 1957, at first they were vague, but as evidence grew during the years they

became more and more detailed.38 In Belgium the first dietary guidelines were formulated by

the National Council on Nutrition in March 1997.39 They are very similar to the American

Heart Association guidelines38 and are largely adopted from countries surrounding Belgium,

the WHO40 and the European Union.41 The guidelines recommend a total fat intake lower

than 30 % of total energy intake; the intake of saturated fatty acids should not exceed 10% of

total energy intake; and the intake of poly-unsaturated fatty acids should not exceed 7%.39

Despite the benefits of a low fat diet the guidelines also mention that total fat intake should

never be lower than 15%, since that is associated with other health problems, such as

potential nutrient deficiencies.38 Worldwide comparisons for fat intake are difficult because

dietary habits and available foods differ considerably between countries. Total fat intake

averages between 29% and 45% of total energy intake for men and woman.42-51 It is

important to note that total fat intake has declined in several countries, especially in the

United States and Canada, during the last two decades and now averages around 35%.45,49,50

Although, at first sight, these figures might not seem to alarming, one must not forget that

50% of the people have a fat intake that is higher than the reported average value, and that the

average values themselves are almost always above the recommended fat intake of 30% of

total energy intake. This indicates that in most western countries the vast majority of people

do not comply with the guidelines. Overall the situation in Europe is more or less

comparable, however large differences between the European countries are noted.42-44,46,47,51

The only large nationwide food consumption survey carried out in Belgium (BIRNH) shows

that only a limited proportion of the Belgian population complies to the fat intake

guideline.32,52-54 An average total fat intake of 41.8 energy% for men and 42.6 energy% for

women has been reported.54 In addition, the prevalence of obesity (BMI ≥ 30 kg/m²) is

particular high in Belgium, 12.1 % for men and 18.4 % for women.33 The BIRNH-study was

carried out between 1980 and 1985, and it might seem not very up-to-date. However,

comparisons with more recent but smaller studies, focusing on subgroups, show no evidence

of major changes in fat consumption.55-58 This is not consistent with some other countries that

show a remarkable decline in total fat intake.45,49,50 The Belgian Food patterns correspond to

the typical Western so-called affluent diet, which is characterised by an excessive fat intake

and a poor intake of complex carbohydrates, fibre, fruits and vegetables.54 At this moment a

new nation wide food consumption survey is carried out by the federal government in

Chapter 1

5

Belgium, about 3200 people are expected to participate and the results are expected by the

end of 2005. This study will give new and reliable information about foot patterns and

current fat intake levels.

From what is described above it becomes very clear that there is a strong need for effective

primary prevention interventions aimed at increasing physical activity and decreasing fat

intake in the general population. However, reaching large populations at an individual level is

very costly and time consuming and, on the other hand, the use of mass media has often

showed to be of limited effect.59 This calls for a new form of intervening which combines the

efficacy of interventions targeted at individuals with the advantage of reaching large

populations in mass media campaigns. Computer-tailored interventions might be promising.

By using a computerized approach this type of intervention is able to provide large numbers

of respondents with personally adapted feedback about their present health behaviour and/or

the behavioural determinants, as well as personally adapted tips and suggestions to change

behaviours.59-61 Computerised questionnaires targeting a health behaviour, such as fat intake

or physical activity, obtain specific personal information. This information is processed by

the computer and personally adapted feedback is generated immediately on the computer

screen. One-to-one counselling is thus mimicked by using an expert interactive computer.

Through the use of the internet and CD-rom health care professionals are able to reach many

individuals in a cheap way;60 and in contrast to traditional mass media approaches, tailoring

gives less redundant and more personal relevant information.59,60 According to the

’Elaboration Likelihood Model’ it are these factors which make tailored information to be

processed more thoughtfully62 and which drive the underlying mechanism that make tailored

health communications effective.59,63 In a number of well-designed studies addressing a range

of health-related behaviours and other outcomes, tailored health communication materials

outperformed non-tailored materials.59,64 Several tailored interventions have indicated to be

successful for increasing physical activity65-69 as well as for decreasing fat intake.61,70-75 It has

also been shown that compared with non-tailored messages, tailored messages are more

likely to be read and remembered, saved and discussed with others, perceived as interesting,

personally relevant and written especially for them.63,64 However, most of the computer-

tailored interventions used to date have been defined as first generation tailored

interventions.60,61 These first generation interventions are characterised by the fact that

computer technology is used relatively sparsely. Written questionnaires are used and it often

takes several weeks for participants to receive their tailored feedback letter from the research


6

team. This feedback is generated by a computer program and printed in a personal letter

format. In second generation interventions, interactive computer programs are used,

participants feed their answers to the diagnostic questions directly into a computer and

feedback is directly provided on the computer screen.61 To date only a few second generation

interventions were evaluated. Furthermore, in a recent study from Oenema et al.,76 a second

generation computer-tailored fat intake intervention showed no behaviour change. This

stresses the need for more research on the effectiveness of these interventions. Moreover,

computer-tailored interventions for increasing physical activity or decreasing fat intake have

typically focused on a single behaviour. Nevertheless many individuals have multiple health

risk behaviours77 and it has been reported that physical activity and fat intake are correlated

to each other.78-80 There may be additive or even synergistic effects of designing health

promotion interventions that focus on two behaviours at the same time.79 It is not clear if

targeting multiple health behaviours improves or decreases the effectiveness of interventions

and if it is best done simultaneously or sequentially.80 It has been suggested that intervention

effects may not be ‘diluted’ when they focus on more than one behaviour simultaneously,81

but others suggest that changing more than one habit at a time may be very difficult and

should better be done sequentially.77,80

To our knowledge no second-generation computer-tailored interventions for increasing

physical activity and decreasing fat intake have been reported in Belgium. Neither could we

find a direct test of the differences between sequential or simultaneous computer-tailored

interventions. Therefore the purpose of our project (also called FAITH project: Fat and

Activity Interventions Tailored to Health) was to develop and evaluate a computerised and

individualised intervention for increasing physical activity and decreasing fat intake; and to

examine whether they can be used in a sequential or simultaneous intervening mode.

Methods

For this research we had to develop a physical activity and a fat intake intervention. These

interventions used questionnaires that had to be tested on validity and reliability and the new

interventions also needed to be tested on acceptability and feasibility. This section provides

more information regarding these topics.

Chapter 1

7

The interventions

The main purpose of the interactive computer-tailored physical activity and fat intake

interventions (see CD-rom addendum 1) we developed was to help participants reach the

current public health recommendations for physical activity and fat intake by means of

specific individualized feedback. Both the physical activity and the fat intake intervention

had the same line-up and belong to the second generation of tailoring interventions, in which

interactive computer programs are used to provide immediate feedback on the computer

screen.61 An introduction page, which explains the nature and purpose of the intervention,

leads participants to an electronic questionnaire which had to be completed in order to

receive the personal advice, also called feedback. For both the physical activity and the fat

intake intervention this questionnaire consisted of three parts: demographics, health

behaviour and psychosocial determinants. For measuring health behaviour the International

Physical Activity Questionnaire (IPAQ) was used in the physical activity intervention and a

newly developed fat intake questionnaire was used in the fat intake intervention. In both

interventions the psychosocial determinant questionnaires had questions concerning

knowledge, social support, self-efficacy, attitudes, perceived benefits and barriers, intentions

and environment. After completing the questionnaire tailored feedback was displayed

immediately on the screen. This feedback was selected from a database filled with messages

that match any possible combination of answers. For each intervention this message database

contains hundreds of text messages, of which only a very limited and relevant selection is

presented to the participants. The answers of the participants are linked to the correct

messages using special software that operates by means of so-called ‘If-Then statements’ that

decide who gets what message. In both interventions the tailored feedback was based on the

theory of planned behaviour82 and the stages of change concept from the trans-theoretical

model.83 These health psychological models take the determinants of the behaviour at study

into account. The most important determinants of physical activity are self-efficacy (this is a

person’s confidence in his or her abilities to do physical activities in specific circumstances),

the intention to be active or not, the attitude towards physical activity, and the benefits and

barriers of physical activity.17 According to Sallis and Owen17 table 2 summarises some 300

studies that studied the associations between physical activity and determinants in adults.


8

Table 2: Associations of determinants with physical activity in adults.

Determinant

Associations with activity in supervised

program

Associations with overall

physical activity

Demographic and biological factors Age Blue-collar occupation Education Gender (male) Genetic factors High risk for heart disease Income/socio-economic status Injury history Overweight/obesity

00 -- + -

0

-- -

++ ++ ++ -

++ + 00

Psychological, cognitive and emotional factors Attitudes Barriers to exercise Control over exercise Enjoyment of exercise Expect Benefits Intention to exercise Knowledge of health and exercise Lack of time Normative beliefs Perceived health or fitness Personality variables Psychological health Self-efficacy Self-motivation Stages of change Stress Susceptibility to illness/seriousness of illness

+ -

+ + 0 0 -- 0

++

0 ++ ++

0

0 -- +

++ ++ ++ 00 -

00 ++ + +

++ ++ ++

0 00

Behavioural attitudes and skills Activity history during childhood/youth Activity history during adulthood Contemporary exercise program Dietary habits (quality) Past exercise program Processes of change Skills for coping with barriers Decision balance sheet

++ 0

00 ++

+

00 ++ 0

++ +

++ +

Social and cultural factors Social support from friends/peers Social support from spouse/family Social support from staff/instructor

+

++ +

++ ++

Physical environment factors Access to facilities: actual Access to facilities: perceived Climate/season

+ + -

+ 00 --

KEY: ++ = repeatedly documented positive association with physical activity; + = weak or mixed evidence of positive association with physical activity; 00 = repeatedly documented lack of association with physical activity; 0 = weak or mixed evidence of no association with physical activity; -- = repeatedly documented negative association with physical activity; - = weak or mixed evidence of negative association with physical activity. Blank spaces indicate no data available.

Chapter 1

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The most important determinants of the intention and the actual consumption of fat are

attitude, taste, health beliefs, normative beliefs, modelling and self-efficacy expectations;

they have an explained variance of 20-50%.84 The explained variance has proved to be

greater for intention than for fat intake itself. It is important to note that most people

underestimate their fat intake, which reflects a lack of awareness of people’s own dietary

intake. And since self-rated intake is predictive of the intention to change, it was concluded

that lack of awareness is a major barrier for the intention to change to healthier diets. Only

after elimination of this barrier attitude, social influences and self-efficacy expectations

towards a lower fat intake can become relevant.85,86 Both the theory of planned behaviour and

the stages of change theory have convincingly proven to be effective and useful in health

promotion interventions and are therefore very common in use.87-93 The theory of planned

behaviour was considered by giving the participants personal relevant feedback about

intentions, attitudes, self-efficacy, social support, knowledge, benefits and barriers of the

behaviour to change (physical activity or fat intake). The stages of changes were considered

in two ways. First, the content differed between stages. Precontemplators mainly received

general information and information about the benefits of the behaviour to change.

Contemplators received the same information, although not so extensively, and it was

mentioned that they might benefit from a behaviour change themselves. In the preparation

stage, the emphasis really was on changing the behaviour in order to comply with the

recommendations. In the action stage, the emphasis was on maintaining the newly adopted

behaviour and relapse prevention. In the maintenance stage feedback was reduced to saying

that they were doing well and that they should carry on. Second, the way in which the

participants were approached also differed between stages. Information for precontemplators

was presented in an impersonal way (e.g. people could...) in order to avoiding resistance.

Contemplators were approached in a personal way (e.g. you could…), but not in a decisive

way which was used for preparators (e.g. you should…) or a supporting way used for people

in the action or maintenance phase (e.g. you do…). In practice the feedback consisted of

three parts: a general introduction; normative feedback which related participants’ physical

activity or fat intake to current recommendations; and tips and suggestions on how to

increase physical activity or decrease fat intake. This part of the advice, only presented when

recommendations were not met, also incorporated feedback on the participant’s psychosocial

attitudes, perceived benefits and barriers, social support, and self-efficacy related to physical

activity or fat intake. Altogether feedback can amount to as much as five or six pages of


10

advice, but only in cases of very high fat intake or very sedentary behaviours. The tailored

feedback displayed on the computer screen could be printed and taken home.

The physical activity intervention also had an extra module, called ‘action plan’, which was

not present in the fat intake intervention. The action plan operated independently of the

physical activity advice, and was meant only for those participants who are not in the

maintenance stage and are also motivated to become more active. It consisted of a

questionnaire that was used to transform physical activity intentions into specific acts, and

therefore asked people what activity they want to do when, where, how long and with whom.

The questions aimed to start a process of thought which directs people how to become more

active (implementation intentions). The action plan itself was an exact reproduction of the

answers participants gave and can be used to remind them of their physical activity

intentions.

Several health promotion experts specialised in fat intake and/or physical activity and a

number of computer experts gave advice when the interventions were developed and

extensively examined the interventions once they were finished. Numerous tests were run to

ensure that the feedback matched with the answers given on the questionnaires. This avoided

incorrect decision rules (so-called ‘If-Then statements’ that decide who gets what message)

or wrong cut-off scores which can cause that participants receive feedback that is not

correctly tailored. A specialised company was hired to design graphics and lay-out. These

efforts allowed us to improve the quality of the interventions before they were presented to a

general public in a formal acceptability and feasibility testing.

Reliability and validity testing

The International Physical Activity Questionnaire (IPAQ) used in the physical activity

intervention (see addendum 2) was developed by a working group, initiated by the World

Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC),

attending a physical activity standardisation meeting in Geneva, Switzerland, in April 1998.94

It is argued that the value of a self-assessed physical activity measurement would increase if

international comparisons could be made.95 However, this is mostly impossible since

numerous and often incomparable operalizations of physical activity are being used. The

‘International Consensus Group for Physical Activity Measurement’ realized the need for the

development of an international standardized assessment technique, and therefore it

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developed the International Physical Activity Questionnaire (IPAQ).94,95 The advantage of

having international comparable physical activity data when using the IPAQ was an

important reason for choosing this measurement tool above others. The fact that this

questionnaire is primarily aimed at measuring physical activity and not exercise or sports

participation, as is the case in most other questionnaires, was another reason for choosing this

instrument. The questionnaire consists of five categories: Job-related physical activity

(vigorous, moderate and walking), Transportation physical activity (motor vehicle, cycling

and walking), Housework, house maintenance and caring for family (vigorous and moderate

in garden, moderate inside home), Recreation, sport and leisure-time physical activity

(vigorous, moderate and walking) and Time spent sitting (week day, weekend day). For each

topic in each category, respondents reported the number of days per week and the time per

day they usually spent doing the activity. For walking and cycling an additional question on

pace was added. In order to be reported, an activity should have lasted for at least ten minutes

continuously. An international reliability and validity testing of the IPAQ has been done, and

the results were acceptable.94 However, when our physical activity intervention was

developed a Dutch nor a Computerised IPAQ version had ever been used before and

consequently a thorough reliability and validity testing was needed before this instrument

could be integrated into our physical activity intervention. CSA accelerometers (Actigraph

monitor) and seven day physical activity diaries were used to obtain validity. The

reproducibility of the questionnaire is assessed by means of a test-retest procedure.96

The fat intake questionnaire used in the fat intake intervention (see addendum 3) was newly

developed especially for this research in cooperation with the Flemish Institute for Health

promotion (VIG). A new instrument was created because there was no Flemish fat intake

questionnaire available and since dietary habits are geographically bounded it was not

possible to use a foreign fat intake questionnaire. We wished to develop a measurement tool

that could fit in an acceptable and appropriate way into our computer-tailored fat intake

intervention. Therefore we did not use a food frequency questionnaire measuring total food

intake (instead of only fat intake), a 24hr recall or a diet diary in our intervention. The

computerised fat intake questionnaire consists of 48 questions divided in seven categories of

food items (bread and cereals; spreads fillings and butter; milk and milk products; prepared

meals; meat, fish and eggs; sauce gravy and dressing; snacks cake and biscuits) and takes

about 20 minutes to administer. Participants were asked how frequently they consumed the

food products during a usual day, week or month. Each question was guided by several


12

examples of the food product, mostly including brand names, and an average portion size. A

reliability and validity testing of this questionnaire, before it was integrated into the fat intake

intervention, was needed since it was a newly developed measurement tool that was never

tested before. The relative validity of this questionnaire was examined in relation to a seven

day estimated diet record. The reproducibility of the questionnaire is assessed by means of a

test-retest procedure.96

Acceptability and Feasibility testing

Interactive computer tailored interventions may have some specific drawbacks which argue

for extensive acceptability and feasibility testing before implementation. The construction of

a computer tailored program implies the development of hundreds of messages, which are

written to be specifically relevant for every single participant. In this respect, feedback

messages create the illusion of personal interaction and tailoring. However, in reality

everything is computer controlled and there is no one to assist participants or to make

adjustments whenever something goes wrong or a computer error appears. Moreover, Tones

and Tilford97 underline that acceptability and feasibility testing (also called pre-testing) must

form part in the development of any well-designed health education programme and that it is

also an integral part of the process of evaluation. As Kreuter et al.59 argue, acceptability and

feasibility testing of computer tailored messages is different and more complex than

acceptability and feasibility testing of non-tailored materials. If tailored messages are

evaluated by a person for who the message was not meant, they will be rated as unsuitable

and irrelevant.59 It is clear that acceptability and feasibility testing does not guarantees that a

program will be effective, but it increases the likelihood that the intervention is

comprehensive, relevant, noticeable, memorable, credible, acceptable and attractive which

are prerequisites for attitude and behaviour change.98 Finally, an acceptability and feasibility

testing targeted at several subgroups, such as different age, gender, education and stage of

change groups, might prevent implementing an intervention that only applies to small

subgroups, such as people that are already motivated to change their behaviour or moderate

to high social class people.99 All this argues for extensive acceptability and feasibility testing

of computer-tailored interventions.

Chapter 1

13

Objectives and outline of this dissertation

This dissertation is primary a collection of articles which are already published or in press.

All articles were written to stand alone, and each of them proceeded from a specific research

question. Consequently, this may lead to some discontinuity or repetition in the manuscripts.

Outlined below is an overview of the chapters combined with an overview of the objectives

of this dissertation.

- Chapter 2 investigates the reliability and validity of the International Physical Activity

Questionnaire. This physical activity measurement tool was integrated in the computer-

tailored physical activity intervention. This questionnaire is a very important part of the

intervention since it is used to measure whether participants comply to the international

physical activity recommendation and consequently need feedback on increasing physical

activity or not. However, before integrating the questionnaire it was needed to obtain

reliability and validity measures as it was the first computerised and Dutch version to be

used. Therefore the objectives of the study described in chapter 2 were to examine the

reliability and validity of a Dutch computerized version of the IPAQ in a sample of adults,

using CSA accelerometers and seven day physical activity diaries. Further, it was aimed to

examine the comparability of computerized and paper-and-pencil formats of the IPAQ.

- Chapter 3 examines validity and reliability of the computerised fat intake questionnaire

that was developed especially to be integrated into the computer-tailored fat intake

intervention. This questionnaire is a very important part of the intervention since it is used

to measure whether participants comply to the international fat intake recommendation and

consequently need feedback on decreasing fat intake or not. However, before integrating

this questionnaire it was needed to obtain reliability and validity measures as it was the first

version ever to be used. Therefore the objectives of the study described in chapter 3 were to

examine the reliability and validity of a newly developed fat intake questionnaire in a

sample of adults. The relative validity of this questionnaire was examined in relation to a

seven day estimated diet record. The reproducibility of the questionnaire is assessed by

means of a test-retest procedure.

- Chapter 4 deals with the newly developed computer-tailored intervention for increasing

physical activity. Before computer-tailored interventions can be used or even evaluated

they need a thorough acceptability and feasibility testing. Therefore the objectives of the

study described in chapter 4 were to investigate acceptability and feasibility of a recently


14

developed computer-tailored intervention promoting physical activity in participants in

different stages of change. Further, we wished to test usability, user-friendliness,

credibility, feasibility, comprehensibility, readability and related factors in a general

population. We especially wished to explore whether there are differences in the reported

feasibility and acceptability of the computer intervention between individuals of different

stages of change, genders, age groups, education levels and familiarity with computer use.

- Chapter 5 deals with the newly developed computer-tailored intervention for decreasing

fat intake. Before computer-tailored interventions can be used or even evaluated they need

a thorough acceptability and feasibility testing. Therefore the objectives of the study

described in chapter 5 were to investigate acceptability and feasibility of a recently

developed interactive computer-tailored fat intake intervention in a general population.

Further, we wished to test usability, user-friendliness, credibility, feasibility,

comprehensibility, readability and related factors. We especially wished to explore whether

there are differences in the reported feasibility and acceptability of the computer

intervention between individuals of different stages of change, sexes, age groups, education

levels and computer literacy.

- Chapter 6 describes the efficacy of the newly developed physical activity and fat intake

intervention. The purpose of these new interventions is to be implemented in Flanders.

However, it is not acceptable and not tolerable to spend a lot of money and time

implementing new interventions before it is proven that they are effective in changing

health behaviours. Further, we wished to have more insight into tailored interventions that

target multiple health behaviours. There is no information in the literature about which

mode of intervening on multiple health behaviours is most effective, namely tailored

interventions that are presented in a simultaneous or a sequential intervening mode.

Therefore the objectives of the study presented in chapter 6 were to examine the

effectiveness of two interactive computer-tailored interventions targeting high priority

health behaviours: increasing physical activity and decreasing fat intake. Further, we

wanted to investigate the effect of implementing two tailored interventions in a sequential

or simultaneous mode.

- Finally in Chapter 7 the most important findings and conclusions of all of our studies

presented in this dissertation are summarised and guidelines for future research are

outlined.

Chapter 1

15

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Chapter 2

23

CHAPTER 2

Reliability and validity of a computerised and Dutch version of the international physical activity questionnaire (IPAQ)

Corneel Vandelanotte, Ilse De Bourdeaudhuij, Renaat Philippaerts, Michael Sjörström and James Sallis

Journal of Physical Activity and Health, in press

Abstract Background: The international physical activity questionnaire (IPAQ) was developed by the

‘International Consensus Group for Physical Activity Measurement’ to provide a common

instrument that can be used internationally to obtain physical activity surveillance data. The

purpose of this study was to examine the reliability and validity of a new developed

computerized Dutch version of the IPAQ. Methods: Participants (N = 53) completed the

computerized IPAQ (long, self-administered, usual week version) at three specified times.

Starting at baseline, participants wore a CSA activity monitor during seven full days and

simultaneously completed a seven day physical activity diary. Finally, respondents filled out

a paper-and-pencil IPAQ. All calculations were expressed in minutes of activity (min.) and

kilocalories of energy expenditure (kcal.). Results: Reliability measures were moderate to

high; intraclass correlation coefficient ranged from .60 to .83. Correlations for ‘total physical

activity’ between the computerized IPAQ and the CSA activity counts were moderate (min.:

r = .38; kcal.: r = .43). Correlations with the physical activity diary were also moderate (min.:

r = .39; kcal.: r = .46). Correlations between the computerized and the paper-and-pencil

IPAQ were high (min.: r = .80; kcal.: r = .84). Correlations for high intensity and leisure-time

physical activity on the computerized IPAQ were high against all validation measures.

Conclusions: The computerized Dutch IPAQ is a reliable and reasonably valid physical

activity measurement tool for the general adult population.

IPAQ Rzliability and Validity

24

Introduction

Self-administered questionnaires are a popular method of assessing physical activity. They

can reach large populations at low cost, they do not alter the behavior under study, they can

reach a wide range of ages and target groups, and they can assess all the dimensions of

physical activity.1 Computerized assessment can further increase these advantages. Rapid

development of information technology makes this new form of questionnaire administration

possible. Computerized assessment has time saving potential since data can be automatically

stored on file, reducing hours of data entry and the risk of lost data.2,3 A major advantage of

computerized questionnaires, in comparison to hard copy questionnaires, is that they can be

programmed to eliminate missing data, forcing participants to answer all questions.2 Complex

skip-patterns can be used to help participants and to avoid superfluous questions.3 Internet

mediated assessment enables researchers to reach large populations quickly 2 and may even

be more effective in reaching certain target populations, otherwise not interested in the

assessment of physical activity.4

Despite the advantages of computerized assessment, self-reporting still has several

drawbacks. Many participants have difficulty estimating the intensity in which they engage in

activities.5 This kind of inaccurate perception 5, together with recall errors 6 and social

desirability bias 1 can lead to over-reporting in physical activity.1,6 Physical activity

questionnaires may be less accurate in assessing light to moderate activities compared to high

intensity activities.5,7,8 Further, physical activity is a complex behavior with considerable day-

to-day variation, which self-assessment questionnaires can not reflect.6 These drawbacks

stress the importance of assessing the validity and reliability of newly developed

questionnaires in the population for which they will be used.

Motions sensors, and in particular the CSA 9 accelerometer, have proven to produce a valid

and objective measure of physical activity.10-13 Due to their small size, unobtrusive nature and

ease of use 14,15, their ability to store data over long periods 7,14, and their capability of

providing objective estimates of the frequency, intensity and duration of physical activity 7,16,

they can be used as a good reference method to assess validity of physical activity

questionnaires.8 An other approach, often used in validating physical activity recalls, is the

Chapter 2

25

use of a diary, in which participants continuously record their activities during several

days.5,17,18

It is argued that the value of a self-assessed physical activity measurement would increase if

international comparisons could be made.19 However, this is mostly impossible since

numerous and often incomparable operalizations of physical activity are being used. The

‘International Consensus Group for Physical Activity Measurement’ realized the need for the

development of an international standardized assessment technique, and therefore it

developed the International Physical Activity Questionnaire (IPAQ).19,20 The purpose of the

IPAQ is to provide a common instrument that can be used internationally to obtain physical

activity surveillance data. A international reliability and validity testing of the IPAQ has been

done, and the results were acceptable.20 The IPAQ produced repeatable data (Spearman’s ρ

clustered around .8) and criterion validity had a median ρ of about .3, which was comparable

to most other self-report validation studies. However, a European study 21,22 was less positive

about the IPAQ and indicated that more research is needed to further investigate and improve

the quality of the IPAQ for use in Europe. The purpose of this study was to examine the

reliability and validity of a newly developed Dutch computerized version of the IPAQ in a

sample of adults, using CSA accelerometers and seven day physical activity diaries. Further,

it was aimed to examine the comparability of computerized and paper-and-pencil formats of

the IPAQ.

Method

Participants

Participants, aged from 25 to 55 years, were recruited in and around the city of Ghent

(Belgium). Sixty-three participants volunteered for this study, of which five dropped out

during data gathering (due to time constraints and lack of motivation). Three participants had

very high physical activity measures (mean + 3 SD) and were defined as outliers. One was

excluded because of insufficient CSA data: days with less than 600 minutes of registration

were removed and all data were removed if less than 5 days were registered. One participant

was excluded due to technical problems concerning the computerized questionnaire, leaving

53 participants that complied to all requirements. Table 1 presents an overview of their

descriptive data and physical activity measures. When procedures were explained, each


26

participant signed an informed consent statement approved by the Ghent University Ethics

Committee.

Table 1: Means and Standard Deviations (SD) for Participants Age, Height, Weight, Body

Mass Index, Total Physical Activity (low + moderate + high intensity physical activity), High

Intensity Physical Activity and Moderate Intensity Physical Activity

Total Sample (N = 53)

Men (N = 23)

Women (N = 30)

Characteristic Mean SD Mean SD Mean SD

Age (yr) 30.9 11.0 31.2 11.4 30.7 10.9 Height (m) 1.73 .01 1.82 .08 1.67 .06 Weight (kg) 68.9 13.1 80.2 11.5 60.2 5.3 Body Mass Index (kg/m2) 22.8 2.9 24.1 2.8 21.6 2.5 Computerized IPAQ (min.) : - Contact 1 Total PA 552.6 437.3 589.6 433.2 524.3 445.6 High intensity PA 149.8 197.7 207.4 226.8 105.6 162.6 Moderate intensity PA 200.9 272.6 253.0 380.8 161.0 139.6 - Contact 2 Total PA 506.8 365.1 589.1 424.8 443.6 304.5 High intensity PA 137.4 191.6 203.0 232.6 87.0 136.9 Moderate intensity PA 172.3 196.9 206.1 257.5 146.3 132.8 - Contact 3 Total PA 527.9 383.8 561.8 419.1 503.0 360.9 High intensity PA 125.6 162.3 152.3 170.4 106.0 156.2 Moderate intensity PA 206.3 263.7 218.2 323.7 197.6 215.0 Paper and pencil IPAQ (min.) Total PA 539.1 389.9 593.5 422.5 497.4 364.7 High intensity PA 136.8 204.0 206.5 259.0 83.3 129.9 Moderate intensity PA 202.8 218.9 225.6 242.7 185.3 201.8 7 day diary last week activity (min.) Total PA 1736.9 591.0 1499.2 509.2 1919.3 591.9 High intensity PA 108.1 155.6 141.7 176.0 82.3 135.4 Moderate intensity PA 338.8 356.8 276.6 302.1 386.6 391.9 CSA last week activity (min.) Total PA 4690.3 790.6 4608.6 871.8 4757.4 726.4 High intensity PA 33.8 41.3 50.3 48.2 20.3 29.0 Moderate intensity PA 286.4 165.9 368.0 169.8 219.2 130.8 Note. PA = Physical Activity

Chapter 2

27

Study protocol

The same protocol as outlined in the IPAQ reliability, validity and prevalence studies manual

of operation (version 8, March 3, 2000; University of South Carolina) was used in this study.

The data collection comprised three contacts with participants, called contact 1, 2 and 3.

Contacts were at the university or participants’ homes (a portable computer was provided by

the research team). A member of the research team was present during all three contacts,

regardless of location.

At contact 1 (day 0), the protocol was outlined, the informed consent signed, and the

participants’ tracking form was obtained. An appointment form was used to ensure that

participants would be present at contacts 2 and 3. Participants’ weight and height were

measured. Next, a computerized demographics form and computerized IPAQ were

administered. Further, participants were familiarized with the CSA accelerometer. To ensure

seven full days of recording, they were instructed to wear the CSA from then on until contact

2. The CSA’s were programmed to start recording at 07:00:00 the day after contact 1 (at day

1). Participants were also given a form on which they had to record each activity performed

without wearing the CSA (e.g. swimming, shower) and they were given a CSA instruction

form to ensure correct CSA use. Finally, participants were asked to complete a seven day

physical activity diary during the CSA recording period (thus also starting at day 1).

Contact 2 was a full week after contact 1 (at day 8). Participants turned in the CSA’s, the

recording form and the physical activity diary. CSA data were downloaded and stored

immediately. Next, the computerized IPAQ was administered again.

Contact 3 was more than three days after contact 2 (at day 11, 12, 13 or 14). For their

convenience participants could choose between four days. Again, participants completed the

computerized IPAQ. Participants who complied with the study protocol were rewarded with

four movie theater tickets.

Participants completed a paper-and-pencil IPAQ three days after contact 3. The paper-and-

pencil questionnaire was given at contact 3 and they were instructed to wait exactly three

days before completing it and to send it immediately back to the research-team (envelope and

stamps were provided).


28

Instruments

Computerized IPAQ

The computerized IPAQ used in this study was entirely based on the long, self-administered,

usual week IPAQ found in the IPAQ manual of operation. The questionnaire consists of five

categories: Job-related physical activity (vigorous, moderate and walking), Transportation

physical activity (motor vehicle, cycling and walking), Housework, house maintenance and

caring for family (vigorous and moderate in garden, moderate inside home), Recreation,

sport and leisure-time physical activity (vigorous, moderate and walking) and Time spent

sitting (week day, weekend day). For each topic in each category, respondents reported the

number of days per week and the time per day they usually spent doing the activity. For

walking and cycling an additional question on pace was added. In order to be reported, an

activity should have lasted for at least ten minutes continuously.

A Dutch translation was made by two independent translators and according to the ‘translate

and back-translate’ protocol. Next, this Dutch version was computerized, in which no

alteration of original item sequence was made. Each ‘computer-page’ contained only one

question and skip patterns were used to eliminate questions that did not need to be answered.

All questions had to be answered before the participants could move on. Energy expenditure

was calculated using a MET (multiples of resting metabolic rate) value for each activity

category on the questionnaire. These MET values were based on the physical activity

compendium by Ainsworth et al. 23, 24 and equal to those reported by Craig et al.20

Paper-and-pencil IPAQ

The paper-and-pencil IPAQ used in this study was a Dutch version of the long, self-

administered, usual week IPAQ. The translation process was identical as described above.

This questionnaire was used as a reference measure to assess the comparability of the

computerized IPAQ.

CSA accelerometer

The computer Science and Applications, Inc. Model 7164 9 accelerometer was used as an

objective reference method. It is a uniaxial accelerometer that measures

acceleration/deceleration in the vertical direction and is designed to detect acceleration

ranging in magnitude from .05 and 2.0 G with a frequency response between .25 and 2.5 Hz.

Chapter 2

29

These frequencies were chosen to detect normal body movement and to filter out high

frequency movement, for example whilst riding in a car. 9 The CSA is small, light (5 x 4 x

1.5 cm, 43 g) and unobtrusive to wear. Activity counts, resulting from a piezo-electric bender

element, are summed over a user-defined sampling period (epoch). At the end of each epoch

the activity counts are stored and the accumulator resets itself to zero. For the present study a

1 min epoch was used. At the end of the seven day recording period, stored data were

downloaded to a desktop computer, and then converted into an Excel file for subsequent

analysis. A complete technical description of the CSA has been published. 25 Monitors were

worn just above the right hipbone and firmly held in place by an elastic belt. Participants

were requested to wear the CSA during waking hours, removing the monitor only for water

based activities and sleeping.

Physical Activity Diary

A seven day physical activity diary was another reference method used to assess validity of

the computerized IPAQ. It was designed for this study and similar to other often used

physical activity diaries. 5 Together with an instruction form, participants were given seven

physical activity monitoring forms (one for each day). For each hour participants documented

the amount of time spent within the same five categories found on the computerized IPAQ

(see above); only ‘sleeping’ was added as a sixth category. For each activity registered on the

diary, participants had to record the following information: a letter indicating the physical

activity category (e.g. T for transportation), a short description of the activity, a subjective

estimate of the intensity of the activity (light, moderate or hard), and the duration of the

activity in minutes. Similar to the computerized IPAQ, participants were asked to only

register activities that lasted for at least ten minutes. To calculate energy expenditure (Kcal.)

MET values were based on the physical activity compendium by Ainsworth et al. 23,24

Data-reduction

The CSA data were reduced with custom software. Minute-by-minute activity counts were

summed for each day, and daily activity counts were summed into total weekly activity

counts. Total weekly activity counts of participants missing one or two day of CSA

registration were extrapolated to seven days, in this way CSA activity counts of all

participants are comparable to each other. Total weekly activity counts were also calculated

for intensity categories, namely: low, moderate and high intensity physical activity, moderate

and high intensity physical activity together, and total physical activity. This split into


30

categories was done using cut off scores published by Freedson et al.10: less than 1952 CSA

counts per minute is light physical activity (< 3.00 MET’s), between 1952 and 5724 counts is

moderate physical activity (3.00-5.99 MET’s), between 5725 and 9498 counts is hard

physical activity (6.00-8.99 MET’s) and more than 9498 counts is very hard physical activity

(> 8.99 MET’s). This subdividing into categories also allowed the calculation of time spent in

each category. Activity counts in the different categories were directly used to analyze the

validity, since it has been suggested that a conversion of CSA activity counts into energy

expenditure may produce significant error. 10

Statistics

All analyses were performed using SPSS 10.0. 26 Test-retest reliability coefficients were

determined using single measure intraclass correlation coefficients (ICC) computed between

the computerized IPAQ administration at contacts 1, 2 and 3 together. For validity, Spearman

rank-order correlation coefficients were computed to compare the computerized IPAQ

administered at contact 2 with CSA activity counts, the seven day physical activity diary and

paper-and-pencil IPAQ. Spearman correlation coefficients were chosen since self reported

physical activity data were not normally distributed. All reported correlations are between

corresponding physical activity categories, e.g. CSA high intensity physical activity was

correlated with computerized IPAQ high intensity physical activity, Diary job-related

physical activity was correlated with computerized IPAQ job-related physical activity, and so

on. Paired sample t-tests were used to verify if there were differences between the

computerized IPAQ at contact two with the paper-and-pencil IPAQ, the physical activity

diary and the CSA minutes. Statistical significance was set at an alpha level of .05.

Results

Reliability

Single measure intraclass correlation coefficients (ICC), expressed in minutes of physical

activity (min.) or in kilocalories energy expenditure (kcal.), for the three computerized IPAQ

administrations are given in table 2. These correlations ranged from ICC = .60 to .83. The

ICC for total PA was .69 when expressed in minutes and kilocalories. Highest ICC’s were for

high intensity (min.: ICC = .81, kcal.: ICC = .82), job-related (min.: ICC = .83, kcal.: ICC =

.80) and leisure-time (min.: ICC = .82, kcal.: ICC = .81) physical activity. Lowest ICC’s were

Chapter 2

31

for moderate intensity (min.: ICC = .62, kcal.: ICC = .63) and transportation (min.: ICC =

.60, kcal.: ICC = .60) physical activity.

Table 2: Single Measure Intraclass Correlations (ICC) for the Computerized IPAQ

administered at Contact 1, 2 and 3, expressed in Minutes of Physical Activity (min.) or in

Kilocalories Energy Expenditure (kcal.)

Min. Kcal.

Total PA .69 .69 High + Moderate PA .66 .69 High intensity PA .81 .82 Moderate intensity PA .62 .63 Low intensity PA .73 .76

Job-Related PA .83 .80 Transportation PA .60 .60 Household PA .74 .71 Leisure-Time PA .82 .81 Note. PA = Physical Activity

Validity

Spearman correlation coefficients between the computerized IPAQ at contact 2 and CSA

measures can be found in table 3. The correlation for total physical activity was .38 (P < .01)

when expressed in minutes and .43 (P < .01) when expressed in kilocalories. The highest

correlations were found for high intensity physical activity (min.: r = .42, P < .01; kcal. : r =

.45, P < .01). Non-significant correlations were found for low (min.: r = .01 ; kcal. : r = .01)

and moderate (min.: r = .13 ; kcal. : r = .19) intensity physical activity.

Also shown in table 3 are the correlations between the computerized IPAQ and the seven day

physical activity diary. These correlations were similar to CSA activity count correlations.

For total physical activity a correlation of .39 (P < .01) when expressed in minutes and .46

(P < .01) when expressed in kilocalories was found. Again, non-significant correlations were

found for low intensity (min.: r = .21, ns.; kcal. : r = .15, ns.) and moderate intensity (kcal. : r

= .23, ns.) physical activity. The highest correlations were for high intensity (min.: r = .79, P


32

< .01; kcal.: r = .79, P < .01) and leisure-time (min.: r = .63, P < .01; kcal.: r = .67, P < .01)

physical activity.

Table 3: Spearman Correlations between the Computerized IPAQ at contact 2 and CSA

Activity Counts, the 7 Day Physical Activity Diary and the Paper and Pencil IPAQ, expressed

in Minutes of Physical Activity or in Kilocalories Energy Expenditure CSA Activity

counts Physical Activity

Diary Paper and pencil

IPAQ Min. Kcal. Min. Kcal. Min. Kcal.

Total PA .38** .43** .39** .46** .80** .84**

High + Moderate PA .37** .42** .45** .46** .80** .86** High intensity PA .42** .45** .79** .79** .87** .93** Moderate intensity PA .13 .19 .32* .23 .77** .78** Low intensity PA .01 .01 .21 .15 .86** .84** Job-Related PA .22 .23 .85** .85** Transportation PA .50** .52** .80** .84** Household PA .42** .53** .88** .87** Leisure-Time PA .63** .67** .93** .95** Note. PA = Physical Activity * P< .05 ** P< .01

High correlations were found between the computerized IPAQ and the paper-and-pencil

IPAQ (table 3), ranging from r = .77 to r = .95 (P <.01). Highest correlations were found for

leisure-time physical activity (min.: r = .93, P < .01; kcal.: r = .95, P < .01).

Paired samples t-test showed no significant differences between total physical activity on the

computerized IPAQ [t(52) = .78, ns.] and total physical activity on the paper-and-pencil

IPAQ. No significant difference was found between ‘moderate + high’ intensity physical

activity on the computerized IPAQ and ‘moderate + high’ intensity physical activity on the

physical activity diary [t(52) = 1.42, ns.]. This was also the case when ‘moderate + high’

intensity physical activity computerized IPAQ was compared to ‘moderate + high’ intensity

physical activity in minutes on the CSA [t(52) = .61, ns.].

Chapter 2

33

Discussion

This study examined the reliability and validity of a newly developed Dutch computerized

IPAQ. When measuring the test-retest reliability of a questionnaire, intraclass correlation

coefficients (ICC) from .75 or higher are considered good to very good.3 In this study the

ICC reliability measures ranged from .60 to .83, thus showing a moderate to high reliability

for the computerized IPAQ. Reliability of the total physical activity was .69. The reliability

of high intensity and leisure-time physical activity (ICC from .81 to .82) was better than the

reliability of moderate intensity physical activity (ICC from .62 to .63). This is probably

caused by the more unstable nature of moderate intensity physical activity resulting in a

recall bias as compared to high intensity or leisure-time physical activity which is more

structured.5,17 The reliability values found in this study are comparable with those found in

the study from Craig et al.,20 they found values ranging from .96 to .46, but most were around

.80. In a review1 containing reliability results for seven self-report physical activity measures,

values ranged from .34 to .89.

Correlations between computerized IPAQ and CSA activity (min.: r = .38, kcal.: r = .43)

supported the validity of the IPAQ. These correlations are at least as good as other self-report

physical activity measures evaluated in adults,27,28 and are also comparable with the

international IPAQ validity study, which found a correlation of about .33 for the long IPAQ

version. 20 In a review, containing the validation results for seven self-report physical activity

measures, Sallis and Saelens 1 reported validity correlations ranging from .14 to .53, with a

median of about .30. Nevertheless, most of our correlations were moderate and several causes

might explain this. First, the computerized IPAQ hardly measures low intensity physical

activity, yet a large portion of the day is spent in sedentary or light activity, and thus a large

part of the CSA activity counts represent physical activity at low intensity. Second, several

authors state that it is very difficult to obtain a good measure of low and moderate physical

activity using self-administered questionnaires. 5,17 These activities are being accumulated

throughout the day and the number and diversity of these activities is large, causing a very

poor recall. Further these authors state that high intensity physical activities, being more

structured and stable over time, are much easier recalled. The higher correlations, in this

study, for high intensity and leisure-time physical activity compared to low and moderate

intensity physical activity illustrate this point. Third, it has been reported that people tend to


34

over report the time spent in high intensity physical activity and underreport the time spend in

light activity. 1,13 CSA accelerometers are known to do the opposite: they underreport high

intensity physical activities and over report low intensity physical activities.13 Fourth, the

computerized IPAQ version used in this study measured usual week physical activity

whereas the CSA measured last week physical activity.

When the computerized IPAQ at contact 2 was compared to the seven day physical activity

diary higher correlations were found. The correlations for total physical activity (min.: r =

.39, kcal.: r = .46) supported the validity of the IPAQ. Especially leisure-time and high

intensity physical activity correlated very well with the physical activity diary. Further, it was

found that the total week (min) physical activity recorded using the physical activity diary

was more than three times higher as compared to total week physical activity recored using

the computerized IPAQ. A similar pattern was observed with the CSA total minutes of

activity, with CSA total activity minutes being much higher than those reported on the

computerized IPAQ. The discrepancy was caused by the overrepresentation of low intensity

physical activity on the diary and the CSA. This overrepresentation of low physical activity

was also observed by other researchers.29 When the low intensity physical activity minutes

were removed from all measures, similar physical activity values were obtained. Since the

aim of the computerized IPAQ is to measure moderate to high intensity physical activity, it

could be argued that the validity of the computerized IPAQ is expressed more accurately by

omitting low intensity physical activity from the correlations. Finally, the slightly higher

correlations obtained by the physical activity diary as compared to the CSA activity counts

are probably due to shared method variance since the IPAQ and diary were both self-

reports.30

The correlations between the computerized IPAQ and the paper-and-pencil IPAQ were all

very high, and there were no significant differences in means. These results demonstrate that

the computerized IPAQ is generally equivalent to the hard copy IPAQ. Taking into account

the advantages of computerized questionnaires, mentioned earlier, the computerized version

may be preferable. However, computerized assessment has also some drawbacks. Paper-and-

pencil questionnaires allow participants to see how many items there are and pace themselves

accordingly; to skip around, rather than answering the questions in sequence; and to go back

easily to earlier questions, in order to change them or check for their own consistency.3

Further, a selection bias is possible since not everybody can handle a computer or is willing

Chapter 2

35

to do so. However, computerized questionnaires, like the one in this study, can be developed

so that they are simple and well explained. Studies have also found that most people are

comfortable in front of a computer.3 Despite these drawbacks we believe computerized

assessment of physical activity has the potential to become a very important assessment

technique in the future.

Considering the minutes spend in total usual week physical activity, compared to CSA data it

appears that the computerized IPAQ overestimates the amount of high intensity physical

activity while underestimating moderate intensity physical activity. This complex pattern has

been seen in several previous studies.1 A limitation of this study is that this overestimation

can not be confirmed nor refuted because there are know limitations to using accelerometers

as validity criteria.6 Another limitation might be the small sample size, which makes it

difficult to generalize these results to larger populations. A strength of this study is that it is

one of the first to examine the reliability and validity of a computerized physical activity

questionnaire. It is of particular value to evaluate a computerized version of the international

physical activity questionnaire because present results suggest researchers from other

countries can develop equivalent versions of hard copy and computerized IPAQ surveys.

In summary, our results indicate that the computerized IPAQ is a reliable and reasonable

valid physical activity measurement tool for the adult population. Additional research should

be conducted to determine the reliability and validity of computerized IPAQ’s in other

languages and to determine population subgroups for whom the computerized version may

not be appropriate.

Acknowledgements

This study was financially supported by the Ghent University and the Flemish Fund for

Scientific Research. The authors would like to thank the Maastricht University for supplying

the software used for computerizing the IPAQ questionnaire, the IPAQ reliability and validity

committee for providing the IPAQ manual of operation for reliability, validity and prevalence

studies (version 8, March 3, 2000; University of South Carolina), the Centers for Disease

Control and Prevention in Atlanta USA for loaning 20 CSA’s, and the Karolinska Institute in

Stockholm for the use of their CSA data-reduction software.


36

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CHAPTER 3

Reliability and Validity Fat Intake Questionnaire

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Chapter 4

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CHAPTER 4

Acceptability and Feasibility Physical Activity Intervention

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Chapter 4

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Chapter 4

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Chapter 4

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Chapter 4

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Chapter 4

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Chapter 5

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CHAPTER 5

Acceptability and Feasibility Fat Intake Intervention

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Chapter 5

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Chapter 6

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CHAPTER 6

Efficacy of sequential or simultaneous interactive computer-tailored interventions for increasing physical activity and decreasing fat

intake

Corneel Vandelanotte, Ilse De Bourdeaudhuij, James Sallis, Heleen Spittaels and Johannes Brug

Anneals of Behavioral Medicine, in press

Abstract

Little evidence exists about the effectiveness of ‘interactive’ computer-tailored interventions,

and about the combined effectiveness of tailored interventions on physical activity and diet.

Furthermore, it is unknown whether they should be executed sequential or simultaneous. The

purpose of this study was to examine (1) effectiveness of interactive computer-tailored

interventions for increasing physical activity and decreasing fat intake; and (2) which

intervening mode, sequential or simultaneous, is most effective in behavior change.

Participants (N = 771) were randomly assigned to receive (1) the physical activity and fat

intake interventions simultaneously at baseline; (2) the physical activity intervention at

baseline and the fat intake intervention three months later; (3) the fat intake intervention at

baseline and the physical activity intervention three months later; (4) or to a control group.

Six months post-baseline the results showed that the tailored interventions produced

significantly higher physical activity scores [F(2,573) = 11,4; p < 0.001] and lower fat intake

scores [F(2,565) = 31,4; p < 0.001] in the experimental groups when compared to the control

group. For both behaviours the sequential and simultaneous intervening modes showed to be

effective, however for the fat intake intervention and for the participants who did not meet

the recommendation in the physical activity intervention the simultaneous mode appeared to

work better than the sequential mode.

Efficacy of Simultaneous or Sequential Tailored Interventions

74

Introduction

There is ample evidence that shows that regular physical activity and eating a low fat diet

promotes health (1-4). However, in most western countries most people are inactive and eat

too much fat (4, 5-7). Health authorities recommend to accumulate at least 30 minutes of

moderate-intensity physical activity on most, preferably all, days of the week (8-9) and to

consume less than 30% energy from fat (10-11).

Tailored interventions provide respondents with personally adapted feedback about their

present health behavior and/or the behavioral determinants, as well as personally adapted

suggestions to change behaviors (12-14). An intervention is ‘tailored’ when participants are

approached individually, mostly using computerised information technologies, so that the

intervention materials are specific for each participant (13). Computer-tailored interventions

can provide individualized behavior change information to many individuals at low costs

(14). In a growing number of well-designed studies addressing a range of health-related

behaviours and other outcomes, tailored health communication materials outperformed non-

tailored materials (13,15). Compared with non-tailored messages, tailored messages are more

likely to be read and remembered, saved and discussed with others, perceived as interesting,

personally relevant and written especially for them (15,16). In the past, tailored interventions,

targeting a single behavior, have proven to be successful for increasing physical activity (17-

21) as well as for decreasing fat intake (22-28).

Although computer-tailored physical activity and nutrition interventions showed promising

effects, most of the interventions used to date have been defined as first generation tailored

interventions (14,25). In these interventions computer technology is used relatively sparsely.

Participants complete written questionnaires and it often takes several weeks before they

receive their tailored feedback letter from the research team. This feedback is generated by a

computer program in the lab, printed and then sent to the participants in a personal letter

format. In second generation interventions, interactive computer programs are used,

participants feed their answers to the diagnostic questions directly into a computer and

feedback is directly provided on the computer screen (25). To date almost no ‘interactive’

computer-tailored interventions were evaluated.

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Interventions for increasing physical activity or decreasing fat intake have typically focused

on a single behaviour. However, since many individuals have multiple health risk behaviours

(29) and it has been reported that physical activity and fat intake are correlated to each other

(30-32) there may be additive or even synergistic effects of designing health promotion

interventions that focus on both behaviours at the same time (31). However, according to

Emmons et al. (32), who investigated the relations between multiple risk factors, it is not

clear if changing multiple health behaviours improves or decreases the effectiveness of

interventions and if it is best done simultaneously or sequentially. In a review by Wilcox et

al. (33), which evaluated physical activity, nutritional and combined interventions, it is

suggested that intervention effects are not ‘diluted’ when they focus on more than one

behaviour simultaneously, since the combined interventions had similar effects on physical

activity and dietary fat compared to the single-behaviour interventions. The PREMIER

collaborative research group (34), showed that the simultaneous implementing of multiple

lifestyle modification interventions to lower blood pressure, was more effective than using

only one intervention, however they did not research the effects of sequential

implementation, which might be even more effective. Nevertheless, several others (29,32) are

convinced that changing more than one habit at a time may be extraordinarily difficult to do

and that, from a behavioural perspective, habit breaking might best be accomplished when

focusing on one behaviour at a time. They support the need for a sequenced behaviour

change process and state that simultaneous action would be overwhelming.

According to Boudreaux et al. (35) people differ considerably in their ‘readiness to change’

physical activity and fat intake and therefore multiple health behavior interventions should be

tailored specific for each behavior. To date, however, only few studies have investigated the

impact of tailored interventions aimed both at physical activity and fat intake. Campbell et al.

(36) studied the effects of sequential tailored dietary and physical activity advice in

combination with social support. The study was moderately successful in changing both

behaviors, but was unable to attribute the effects to the tailored parts of the intervention.

Calfas et al. (37) provided tailored dietary and physical activity advice simultaneous in

primary health care settings. Short-term improvements in both dietary and physical activity

were reported. To our knowledge, no study ever provided a direct test of the differences

between sequential or simultaneous computer-tailored interventions.


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The aim of the present study was to examine the effectiveness of two interactive computer-

tailored interventions targeting high priority health behaviors: increasing physical activity

and decreasing fat intake. Further, we wanted to investigate the preferred way of

implementation of multiple health behavior tailoring: sequential or simultaneous. We

hypothesized that: (1) The interactive computer-tailored interventions will be effective in

producing behaviour change; and (2) the sequential intervening mode will be more effective

than the simultaneous mode to change behaviour.

Method

Participants

Participants were recruited in and around the city of Ghent (Belgium) using local media

(television, radio, newspapers, magazines), posters, leaflets and e-mail. People could react by

phone or e-mail and were, if interested, inserted into a database to be contacted at the end of

the recruitment period. Participants had to be between 20 and 60 years of age and without

medical complaints related to physical activity or fat intake (such as cardiovascular disease,

diabetes, anorexia or problems with stomach, liver, gall bladder and intestine). To encourage

participation, a bicycle, a gift coupon and film tickets were raffled among study participants.

Of the 1164 people who responded to the recruitment notices 1023 actually participated at

baseline. At post-test 771 participants had complied to all study requirements and were

included in the analyses (drop-out = 24.6%). Drop-out analysis showed that men and younger

participants were more likely to have dropped out. No differences were found for education,

body mass index, employment, total physical activity, moderate + high intensity physical

activity, total fat intake and percent energy from fat.

Procedure

The study was approved by the Ghent University Ethics Committee and an informed consent

statement was obtained from each participant. After baseline measurement participants were

assigned at random into one of four conditions: group 1 received both the tailored physical

activity and the tailored fat intake interventions at baseline; group 2 received the tailored

physical activity intervention at baseline and the tailored fat intake intervention three months

later; group 3 received the tailored fat intake intervention at baseline and the tailored physical

activity intervention three months later; group 4 was the waiting list control group and

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received both tailored interventions after post-test measurement six months post-baseline.

The participants in the experimental groups (groups 1, 2 and 3) received their computer-

tailored interventions at a university computer lab. Each participant received each

intervention (physical activity and fat intake) only once during the entire course of the

research and it took about 50 minutes to go through one intervention (physical activity or fat

intake), however there was a large variation in time spent between the participants. Each

intervention group was invited on a separate day in order to avoid possible ‘contamination’

between groups. Six months after baseline post-test questionnaires were mailed to home

addresses with a stamped return envelop. All baseline measures and interventions took place

during the fall, while post-test measures were obtained during spring.

Interventions

The interactive computer-tailored physical activity and fat intake interventions used in this

study are part of the FAITH-project (Fat and Activity Tailored to Health). An extensive pre-

testing of these interventions showed good acceptability and feasibility (38-39). The purpose

of the interventions was to help participants reach the current public health recommendations

for physical activity (accumulate at least 30 minutes of moderate-intensity physical activity

on all days of the week) and fat intake (to consume less than 30% energy from fat) (8-11).

Both the physical activity and the fat intake intervention had the same line-up and were

entirely computerized. After reading an introduction page, which explains the nature and

purpose of the intervention, participants had to fill out an electronic questionnaire consisting

of three parts: demographics, health behavior and psychosocial variables. After completing

the questionnaire tailored feedback was displayed immediately on the screen. The feedback

was based on the theory of planned behavior (40) and the stages of change concept from the

trans-theoretical model (41). The theory of planned behaviour was considered by giving the

participants personal relevant feedback about intentions, attitudes, self-efficacy, social

support, knowledge, benefits and barriers of the behaviour to change (physical activity or fat

intake). The stages of changes were considered in two ways. First, the content differed

between stages. Precontemplators mainly received general information and information about

the benefits of the behaviour to change. Contemplators received the same information,

although not so extensively, and it was mentioned that they might benefit from a behaviour

change themselves. In the preparation stage, the emphasis really was on changing the

behaviour in order to comply with the recommendations. In the action stage, the emphasis


78

was on maintaining the newly adopted behaviour and relapse prevention. In the maintenance

stage feedback was reduced to saying that they were doing well and that they should carry on.

Second, the way in which the participants were approached also differed between stages.

Information for precontemplators was presented in an impersonal way (e.g. people could...)

in order to avoiding resistance. Contemplators were approached in a personal way (e.g. you

could…), but not in a decisive way which was used for preparators (e.g. you should…) or a

supporting way used for people in the action or maintenance phase (e.g. you do…). In

practice the feedback consisted of three parts: a general introduction; normative feedback

which related participants’ physical activity or fat intake to current recommendations; and

tips and suggestions on how to increase physical activity or decrease fat intake. This part of

the advice, only presented when recommendations were not met, also incorporated feedback

on the participant’s psychosocial attitudes, perceived benefits and barriers, social support,

and self-efficacy related to physical activity or fat intake. After reading the tailored feedback

from the computer screen, the advice was printed and taken home. A more detailed

description of the physical activity intervention has been published by Vandelanotte et al.

(38). The fat intake intervention was an adaptation from interventions used by Brug et al. (42-

43) and Oenema et al. (23), for a more detailed description see Vandelanotte et al. (39).

Measures

For the assessment of physical activity the IPAQ (International Physical Activity

Questionnaire) was used. This 31 item questionnaire (long self-administered version)

measured physical activity at work, transportation, household and leisure time. For each topic

in each category, respondents reported the number of days and the number of minutes per day

spent doing the activity. An individual total physical activity score, expressed in minutes of

activity per week, was obtained when all questions were summed. Validity of a computerized

and Dutch version of the IPAQ questionnaire was tested using CSA accelerometers and a

seven day physical activity diary. Correlations of respectively 0.38 and 0.39 indicated a

reasonable validity, and were comparable with the results obtained in the 12-country IPAQ

validity study (44). Detailed descriptions of the IPAQ have been published elsewhere (44-

45).

For measuring fat intake a 48 item food frequency questionnaire was used, assessing

frequency and amounts of the most important sources of fat in the Belgian diet: bread and

cereals; spreads, fillings and butter; milk and milk products; prepared meals; meat, fish and

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eggs; sauce, gravy and dressing; snacks, cake and biscuits. Participants were asked about

usual portion sizes and how frequently they consumed these food products during a usual

day, week or month. For each product a coefficient was calculated based on fat content and

portion size of the food product. This coefficient was multiplied by the frequency of

consumption and summed for all questions, leading to an individual total fat intake score,

expressed in grams of fat per day. Validity of this questionnaire was measured using seven

days of diet records. Correlations of 0.67 for fat intake and 0.60 for percent energy from fat

and a gross misclassification of 5.8% were found, indicating acceptable validity. For more

details on this questionnaire and it’s validation see Vandelanotte et al. (46).

Statistics

For physical activity, analyses were executed on two outcome measures: ‘total physical

activity’ and ‘moderate + high intensity physical activity’. ‘Moderate + high intensity

physical activity’ is a representation of all physical activity that meets with requirements of

the current public health recommendations (in minutes/week). This includes all physical

activity corresponding with a MET estimate from 3.5 or higher as described in the

compendium of physical activities (47,48). For fat intake analyses were also executed on two

outcome measures: ’total fat intake’ and ‘percent energy from fat’. Percent energy from fat

was calculated using standard ‘recommended energy intake tables’ based on height, weight,

sex, age and activity level (49).

To evaluate the effects on physical activity a repeated measure ANOVA, with time (pre-post

test) as within subjects factor and group (groups 1, 2 and 4) as between subjects factor, was

used. To evaluate the effects on fat intake a repeated measure ANOVA, with time as within

subjects factor and group (groups 1, 3 and 4) as between subjects factor, was used. These

repeated measure ANOVA’s were executed on three different (sub)groups: total group,

participants not meeting the current health recommendation at baseline and participants

meeting the recommendation at baseline.

In addition, repeated measure ANOVA’s with time, group and recommendation (participants

who did or did not met the current recommendation at baseline) were also executed on all

outcome measures to investigate the three-way interaction. Covariates in the repeated

measure ANOVA analyses (sex, age, education, body mass index and employment) did not

significantly interact with the intervention and were thus excluded from all reported analyses.


80

All analyses were performed using SPSS 11.0. Statistical significance was set at a level of

0.05.

Results

Participant characteristics

As shown in table 1, the majority of participants were female (64.5 %), had high education

(69.6 %) and were employed (86.3 %). Total physical activity was 569 ± 450 minutes a week

and moderate + high intensity physical activity was 340 ± 307 minutes a week for the total

group. At baseline 62.2 % of men and 53.9 % of women met the physical activity

recommendation. Total group fat intake was 109.2 ± 41 grams a week and energy from fat

was 37.6 ± 13 grams a week. At baseline only 38.5% of men and 30.5% of women met the

fat intake recommendation. At post-test, 95.3% and 96.2% of the participants, respectively

for the physical activity and the fat intake intervention, indicated that they had read the

printed advice which was taken home.

Table 1: Total sample baseline characteristics for men and women (mean ± SD or %)

Total Sample (N = 771)

Men (N = 274)

Women (N = 497)

Demographics : Age (yr) 39.1 ± 9.6 39.9 ± 9.5 38.6 ± 9.7 Height (m) 170.1 ± 8.7 177.6 ± 7.0 165.8 ± 6.5 Weight (kg) 71.3 ± 14.5 81.1 ± 13.8 65.9 ± 11.7 Body Mass Index (kg/m2) 24.5 ± 4.1 25.7 ± 4.2 23.9 ± 4.0 College or university degree (%) 69.6 67.7 70.5 Employed (%) 86.3 85.8 86.6

Physical activity (PA) : Total PA (min/week) 569.0 ± 450.4 568.3 ± 470.1 611.0 ± 439.5 Moderate + high intensity PA (min/week) 340.3 ± 307.1 388.1 ± 337.9 314.6 ± 286.3 30 min of PA on most days (%) 56.8 62.2 53.9

Fat intake : Total fat intake (g/day) 109.2 ± 41.6 127.7 ± 47.1 98.8 ± 34.0 Recommended energy intake (kcal) 2633.6 ± 545.0 3240.9 ± 428.9 2298.7 ±209.8 Energy from fat (%) 37.6 ±13.0 35.7 ± 12.6 38.6 ± 13.2 Less than 30% energy from fat (%) 33.5 38.9 30.5

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Changes in Physical Activity

In table 2 an overview is given of the effects of the sequential and simultaneous interventions

on physical activity. For the total group a significant interaction effect (time * group) was

found (p < 0.001). Post-hoc follow-up test showed that both the sequential and simultaneous

intervention groups significantly increased participants’ total physical activity when

compared to the no-intervention group. There was no significant difference between the

sequential and simultaneous intervention groups themselves. In contrast, no significant

effects were found for moderate + high intensity physical activity.

Table 2: Effects of the sequential and simultaneous interventions on total physical activity

(minutes/week) and moderate + high intensity physical activity (minutes/week) for total

group and for participants meeting or not meeting the recommendation for physical activity

at baseline Total group (N = 573)

Meeting the PA recommendation (N = 325)

Not meeting the PA recommendation (N = 248)

Total PA (min/w)

Mod + high PA (min/w)

Total PA (min/w)


Total PA (min/w)


Simultaneous interventions Group 1 (N = 189)

Baseline 532 ± 519 325 ± 312 796 ± 445 538 ± 300 248 ± 210 95 ± 58 Post-test 705 ± 519 386 ± 329 836 ± 502 481 ± 327 563 ± 502 284 ± 301 Difference + 173 +61 + 40 - 57 + 315 + 189

Sequential interventions Group 2 (N = 180)

Baseline 514 ± 367 295 ± 249 694 ± 386 456 ± 244 313 ± 208 116 ± 60 Post-test 727 ± 492 388 ± 306 904 ± 540 528 ± 323 530 ± 340 232 ± 189 Difference + 213 + 93 + 210 + 72 + 217 + 116

No intervention Group 4 (N = 204)

Baseline 720 ± 485 392 ± 340 884 ± 492 552 ± 323 418 ± 290 99 ± 63 Post-test 734 ± 516 437 ± 348 850 ± 545 550 ± 363 523 ± 380 230 ± 191 Difference + 14 + 45 - 34 - 2 + 105 + 131 F Time 54.2*** 28.1*** 7.4** 0.6 87.1*** 98.7*** F Group 4.2** 3.7* 0.7 1.4 1.1 0.7 F Time*Group 11.4*** 1.2 7.5*** 3.7* 7.1*** 2.5(*)

Post Hoc a, b a, c c a, b c Note. PA = Physical Activity Post Hoc: a = significant difference between sequential interventions and no intervention; b = significant difference between simultaneous interventions and no intervention; c = significant difference between sequential interventions and simultaneous interventions (*) P < 0.1 * P < 0.05 ** P < 0.01 *** P < 0.001


82

For total physical activity there were significant interaction effects both for participants not

meeting (p < 0.001) and participants meeting (p < 0.001) the physical activity

recommendation. For participants not meeting the recommendation, post-hoc test showed

that the sequential and simultaneous intervention group significantly increased total physical

activity compared to the no-intervention group. For participants meeting the

recommendation, post-hoc test showed that only the sequential intervention groups

significantly increased total physical activity compared to the no-intervention group. For the

moderate + high intensity physical activity a significant interaction effect (p < 0.05) was

found for participants meeting the recommendation. However, post-hoc tests showed that, for

participants that did or did not met the recommendation, there were no significant effects for

either the sequential or simultaneous intervention groups when compared to the no-

intervention group.

No significant three-way interaction effects (time * group * recommendation) were found for

total physical activity and moderate + high intensity physical activity.

Changes in Fat Intake

Table 3 shows the effects of the interventions on fat intake. For total group a significant

interaction effect (time * group) was found for total fat intake (p < 0.001) and energy from fat

(p < 0.001). Post-hoc follow-up tests showed that both the sequential and simultaneous

intervention groups significantly decreased participants’ total fat intake and energy from fat

when compared with the no-intervention group. There was also a significant difference

between the sequential and simultaneous intervention groups themselves: fat intake and

energy from fat decreased more in the simultaneous group.

For participants meeting the fat intake recommendation there were no significant interaction

effects for total fat intake and energy from fat: all groups more or less stayed at baseline

levels. However, for participants not meeting the fat intake recommendation a significant

interaction effect was found for total fat intake (p < 0.001) and energy from fat (p < 0.001).

Post-hoc tests showed that all groups significantly differed from each other for total fat intake

and energy from fat. Both intervention groups decreased fat intake more compared to the no-

intervention group. The simultaneous intervention group decreased fat intake more when

compared to the sequential intervention group.

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Table 3: Effects of the sequential and simultaneous interventions on total fat intake

(grams/day) and percent energy from fat (%) for total group and for participants meeting or

not meeting the recommendation for fat intake at baseline

Total group (N = 565)

Meeting the fat intake recommendation (N = 182)

Not meeting the fat intake recommendation (N = 383)

Total Fat Intake (g/d)

Energy from fat (%)


Energy from fat (%)


Energy from fat (%)

Simultaneous interventions Group 1 (N = 176)

Baseline 118 ± 43 40.8 ± 13.2 76 ± 19 24.4 ± 3.8 134 ± 38 46.7 ± 10.0 Post-test 85 ± 28 29.3 ± 9.1 75 ± 24 24 ± 7.8 89 ± 28 31.1 ± 8.8 Difference - 33 - 11.5 - 1 - 0.4 - 45 - 15.6

Sequential interventions Group 3 (N = 194)

Baseline 110 ± 39 38.0 ± 12.7 73 ± 17 24.2 ± 3.8 127 ± 35 44.2 ± 10.2 Post-test 85 ± 30 29.4 ± 10.8 69 ± 18 23.4 ± 7.0 91 ± 32 32.2 ± 11.2 Difference - 25 - 8.6 - 4 - 0.8 - 36 - 12

No intervention Group 4 (N = 195)

Baseline 101 ± 39 35.3 ± 12.2 70 ± 16 23.9 ± 3.9 121 ± 36 42.4 ± 10.0 Post-test 94 ± 33 33.2 ± 12.0 74 ± 21 25.4 ± 7.4 107 ± 33 38.0 ± 11.6 Difference - 7 - 2.1 + 4 + 1.5 - 14 - 4.4 F Time 252.1*** 256.4*** 0.7 .01 346.0*** 382.7*** F Group 1.0 0.7 0.8 0.5 0.7 1.6 F Time*Group 31.4*** 36.2*** 2.0 1.8 29.2*** 36.3*** Post Hoc a,b,c a,b,c a,b,c a,b,c

Note. Post Hoc: a = significant difference between sequential interventions and no intervention; b = significant difference between simultaneous interventions and no intervention; c = significant difference between sequential interventions and simultaneous interventions (*) P < 0.1 * P < 0.05 ** P < 0.01 *** P < 0.001

Significant three-way interaction effects (time * group * recommendation) were found for

total fat intake [F(2,565) = 8.2; p < 0.001] and percent energy from fat [F(2,565) = 10.1; p <

0.001].

Meeting the public health recommendations

Figures 2 and 3 express the impact of the sequential and simultaneous interventions on the

percentage of participants who achieved the public health recommendations. At baseline

about 52.6% and 52.1% of the participants, respectively for the sequential and simultaneous

interventions, met the physical activity recommendation, while at post-test this was 66.7% for

both intervention groups. For fat intake, 31.5% of the sequential and 28.8% of the

simultaneous group met with the recommendation at baseline, while at post-test this was

respectively 60.3% and 57.8. The interventions resulted in a 14% increase for physical

activity and a 29% increase for fat intake, regardless of intervention mode. The impact on the


84

percentage meeting recommendations was thus twice as large for the fat intake intervention

when compared to the physical activity intervention. The no-intervention group showed a

smaller increase in participants meeting recommendations: 7.4 % for physical activity and 9.1

% for fat intake.

52.666.7

52.1

66.7 64.772.1

0

20

40

60

80

Perc

ent

Sequential Simultaneous No Intervention

Physical ActivityBaselinePost-test

Figure 1. Percent of participants meeting the 30 minutes of physical activity on most days of the week recommendation at baseline and post-test across the different intervention conditions

31.5

60.3

28.8

57.8

40.149.2

0

20

40

60

80

Perc

ent

Sequential Simultaneous No Intervention

Fat Intake BaselinePost-test

Figure 2. Percent of participants meeting the 30 % energy from fat recommendation at baseline and post-test across the different intervention conditions

Discussion

The interactive computer-tailored physical activity and fat intake interventions evaluated in

this study were effective in inducing healthy behavior changes. It is noticeable that a single

exposure to tailored printed information was sufficient to produce substantial changes that

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persisted for at least several months. In general, both sequential and simultaneous approaches

to change health behaviors were shown to have efficacy.

For both sequential and simultaneous interventions a significant increase was found for total

physical activity when compared to the no-intervention group. These results are in line with

other computer-tailored physical activity interventions (17-21). No significant impact of

tailoring on moderate + high intensity physical activity was found, probably because the

participants in the control group also increased moderate and high intensity physical activity.

However, in both experimental groups there still was a 14% increase in participants meeting

the physical activity recommendation. Further, it appears that the present physical activity

intervention especially caused large increases on the light physical activities. This increase is

relevant, since there are a substantial number of studies which report the positive health

benefits associated with walking and low intensity physical activities (50-52).

The absence of a significant three-way interaction effect for physical activity (time * group *

recommendation) showed that there were similar effects for participants meeting and not

meeting the recommendation. The further increase in physical activity for participants

already meeting the recommendation at baseline can be explained by the fact that these

participants were not only told that they are doing fine, but were also encouraged to stay

active and do more if possible.

The computer-tailored fat intake intervention caused large and significant reductions in total

fat intake and percent energy from fat for both experimental groups. The number of people

that met the fat intake recommendation almost doubled, from about 30% to 60%. This

intervention thus demonstrated to be very effective. The results in this study compare

favorably to other computer-tailored fat intake interventions (22-28). The ‘interactive’ and

immediate fat intake feedback and advice might explain why this intervention outperformed

other computer-tailored interventions that were not interactive. One explanation for the

sizable effects is that no major efforts to reduce fat intake have been undertaken in the

country.

In contrast with physical activity results, no intervention effects were found for participants

already meeting the fat intake recommendation. In this line, a significant three-way

interaction effect (time * group * recommendation) was found, which indicates differences


86

between participants who did or did not meet with the recommendation. This is probably

because participants meeting the recommendation were not adviced to further reduce their fat

intake. Furthermore participants with a fat intake below 20% energy from fat were even

advised to increase fat intake and seek contact with a general practitioner.

Overall, the computer-tailored fat intake and physical activity intervention, tested in the

present study, used the same theoretical backgrounds and were presented to participants in

the same way. However, the increase in the number of participants meeting the

recommendation from baseline to post-test was twice as large in the fat intake intervention

(29%) when compared to the physical activity intervention (14%). Overall, this pattern is also

seen when comparing other computer tailored fat intake and physical activity interventions to

each other (53). At baseline only 33.5% of the participants met the fat intake

recommendation, while 56.8% were meeting the physical activity recommendation. Second,

Brug et al. (54) stated that fat intake is different from other behaviors associated with chronic

disease as individuals are often unaware of their dietary risk behavior, because dietary

behavior is very complex and fat content can be hidden. The normative feedback used in our

interventions aimed to motivate a behavior change by means of increasing awareness levels.

This might have had a larger impact on fat intake, since awareness of physical activity was

probably higher at baseline.

Our results clearly indicated that both the simultaneous and the sequential intervening modes

showed to be effective and can be used in health promotion. Only a few studies reported

either simultaneous or sequential multiple behavior change interventions (33,36-37) and

regardless of intervention mode (simultaneous or sequential) they all found positive results.

In this way these studies are, although indirectly, in line with our results. However, there are

important differences to note between the simultaneous and sequential intervening modes in

this study. These differences are most clearly expressed in the fat intake intervention:

although the sequential intervening mode showed to be effective, the simultaneous mode

preformed significantly better. For physical activity the differences between intervening

modes were less straight forward and more difficult to interpret. The sequential intervention

mode seemed to work similar for participants meeting and not meeting the physical activity

recommendation. However, the simultaneous intervening mode appeared to work even better

for participants not meeting the recommendation, whereas for participants meeting the

recommendation it appeared to work worse. It is difficult to explain why the simultaneous

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intervention mode was most effective for the fat intake intervention and only partialy

effective for the physical activity intervention as there are no studies to compare them to.

These findings are in contrast to our hypothesis and also seem to contradict the position stand

from some authors who indicated that changing multiple behaviors at once might create an

‘overload’ and would thus be more difficult to be done (29,32). It is possible that people who

try to change several health behaviors at a time are totally absorbed by the process and are

really motivated to completely go for this healthy lifestyle. When people only have to change

one behavior they might be less focused. Further, it still remains puzzling as to why the

simultaneous intervening mode for physical activity worked less good for people who already

met the recommendations. It could be that they just chose to change their fat intake behavior

and decided to do less for physical activity as they were already meeting the physical activity

recommendation. Finally, given our results and from a public health perspective, we suggest

that it is better to implement simultaneous interventions at one point in time, which is a much

more cost-effective approach compared to the implementation of several interventions at

different points in time. But these effects may not be generalized to underserved populations

as our sample did not represent those groups.

It is important to note some limitations of the present study. First, the findings are based on

self-report information, which can be subject to response bias. Self-reports of physical

activity typically show overreporting, and this problem has been reported for the IPAQ as

well (45). Self-reports of fat intake are known for underreporting (55). Second, drop-out

analysis showed that more men and young people dropped out compared to women and older

participants, and this might have introduced some bias. However, this finding is not

surprising, because women typically show more interest in health, weight and fat intake (56).

Older people encounter more health problems, consequently they are more motivated to take

action to improve their health (57). Third, physical activity levels in this study are slightly

higher at baseline when compared to normal population activity levels in Belgium (56,8 %

complies with the physical activity recommendation versus 50.1%) (58). In addition, physical

activity at baseline was remarkably higher in the no-intervention condition (group 4), despite

that the same recruitment procedures were used for all participants and they were assigned at

random into one of four groups. Furthermore, physical activity levels at post-test were still

slightly higher in the no-intervention group when compared to the experimental groups. We

can not explain the baseline differences between our groups, however, we are aware that this

might have influenced our results. The increase of physical activity in the no-intervention


88

group might have been tempered by the fact that they already had very high baseline activity

levels, whereas this might not have been the case when baseline activity levels were

comparable to the other groups. Fourth, it is a limitation that our food frequency

questionnaire only measured fat intake and not total energy uptake. Therefore percent

calories was calculated based on recommended energy intake tables and not on actual energy

intake. Fifth, it is difficult to generalize our results to underserved populations, such as ethnic

minorities and low socioeconomic status people. Sixth, our results in the sequential

intervening mode might have been better using a shorter or longer interval between

interventions. However the optimal interval between intervention contacts is not known.

Neither is there any literature about intervening on more than two health behaviors,

sequentially or simultaneously. It is possible that intervening simultaneously on three or more

health behaviors indeed does create an overload of information in participants, as suggested

by several authors (29,32), but this remains to be studied.

In conclusion, both the interactive computer-tailored physical activity and fat intake

intervention can be applied successfully to change behaviors. Further, both sequential and

simultaneous intervening modes can be used. From a public health point of view and because

the simultaneous intervention mode was superior for fat intake we recommend to implement

the interventions simultaneously in populations similar to the one studied in the present

study.

Acknowledgments

This study was financially supported by the Ghent University and the Flemish Fund for

Scientific Research. The authors would like to thank Katrien Bogaert, Griet Bonamie, Nele

Callewaert, Hilde Decrop, Evelyn Vanbesien and Els Van Cleemput, for their cooperation in

data gathering.

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CHAPTER 7

General discussion

This dissertation describes the research that was needed to produce a computer-tailored

intervention for increasing physical activity and a computer-tailored intervention for

decreasing fat intake. This comprised acceptability, feasibility and efficacy testing of both

interventions and validity and reliability testing of the questionnaires used for measuring

physical activity and fat intake. Further, we wished to investigate in which modality these

newly developed interventions could be used best, in a simultaneous or a sequential

intervening mode. This chapter starts with an overview of the main findings, followed by

practical implications, methodological limitations and finally recommendations for further

research are made.

Main findings

IPAQ reliability and validity

This study examined the reliability and validity of a newly developed Dutch computerized

IPAQ using CSA accelerometers and physical activity diaries. In this study the ICC test-

retest reliability measures ranged from .60 to .83 showing a moderate to high reliability for

the computerized IPAQ. The reliability values found in this study are comparable with those

found in the study from Craig et al.,1 they found values ranging from .46 to .96, but most

were around .80. In a review2 containing reliability results for seven self-report physical

activity measures, values ranged from .34 to .89. Correlations between computerized IPAQ

and CSA activity (min.: r = .38, kcal.: r = .43) supported the validity of the IPAQ. These

correlations are at least as good as other self-report physical activity measures evaluated in

adults,3,4 and are also comparable with the international IPAQ validity study, which found a

correlation of about .33 for the long IPAQ version. 1 In a review, containing the validation

results for seven self-report physical activity measures, Sallis and Saelens 2 reported validity

correlations ranging from .14 to .53, with a median of about .30 The slightly higher

General discussion

96

correlations between the computerized IPAQ and the seven day physical activity diary (min.:

r = .39, kcal.: r = .46) also supported the validity of the IPAQ. Especially leisure-time and

high intensity physical activity correlated very well with the physical activity diary, this was

also seen in the CSA correlations. Finally, the correlations between the computerized IPAQ

and the paper-and-pencil IPAQ were all very high, and there were no significant differences

in means. These results demonstrate that the computerized IPAQ is generally equivalent to

the hard copy IPAQ. Taking into account the advantages of computerized questionnaires,

mentioned earlier, the computerized version may be preferable.

Reliability and validity of the fat intake questionnaire

In this study the reliability and validity of a computerised questionnaire to measure fat intake

was evaluated in relation to a seven day diet record. Correlations between our questionnaire

and the diet records of 0.67 and 0.60 were found respectively for total fat intake and for

‘percentage energy’ from fat. Several authors reported that correlations greater than 0.5

support the validity of a FFQ,5-8 which confirms the validity of our questionnaire.

Correlations in a review of validation studies of fat intake questionnaires were generally

lower than the correlations found in this study.9 In this study we found that for total fat intake

51% of the participants were correctly classified in tertiles and 52 % of the participants for

percent energy from fat. For fat intake and for percent energy from fat 5.8% of the

participants were grossly misclassified. These results further support the validity of the

computerised fat intake questionnaire, and are in line with other validation studies.5,9-11 The

Kappa statistics, however, showed only fair agreement for total fat (0.27) and for percent

energy from fat (0.29). Several other validation studies also have difficulties finding

acceptable Kappa values above 0.4.5,9,10 This is in line with Portney and Watkins12 who state

that this statistic is usually an underestimate of true reliability if used for continuous data as

in our study. When measuring the reliability of a questionnaire, intraclass correlation

coefficients (ICC) from 0.75 or higher are considered good to very good.13 For total fat intake

we found 0.86 and for percent energy from fat 0.81, indicating excellent reliability. This

finding is strengthened by a very low gross misclassification and kappa’s showing good

agreement.

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Acceptability and feasibility of the physical activity intervention

The aims of this study were to test feasibility and acceptability of a computer-tailored

intervention promoting physical activity and to explore whether there were differences in the

reported feasibility and acceptability between different stages of change, genders, age groups,

education levels and familiarity with computer use. Generally speaking, the data showed that

the tailored physical activity intervention is a feasible and acceptable tool for intervening in a

general population. Participants reported having no problems with the intervention questions,

and nearly all participants accepted aspects related to appearance as well as to content.

However, more than a third of them indicated that there are too many questions to be

answered before the physical activity advice appeared. Most participants indicated that the

physical activity advice is interesting, logical, instructive, comprehensible, well styled and

complete. Only a small group of participants indicated that the advice is too long, confusing

or that it gives too much information. The action plan was included in the intervention was to

transform physical activity intentions into specific acts. In general, participants were positive

about the appearance and content of the action plan. The results concerning the use of a

computer suggested that this aspect of the intervention is acceptable and feasible. Advantages

of computer-assisted administration, such as using skip patterns13 and receiving feedback

immediately,14 are clearly appreciated. On the whole, only a few significant differences were

found for stages of change, gender, age groups, education levels and familiarity with

computer. This leads to an important conclusion, namely that this intervention tailored well

for respondents in different stages of change, for men as well as for women, for younger and

older participants, for the higher and lower-educated, for those who are or are not used to

working with a computer. This was one of the major aims when developing the intervention.

The stages of changes were considered in two ways when writing feedback messages, it

seems that this strategy succeeded in constructing feedback tailored optimally to most

participants and probably explains why few differences in acceptability and feasibility scores

were found between groups.

Acceptability and feasibility of the fat intake intervention

The results of this study indicated that the interactive fat intake intervention is a feasible and

acceptable tool for intervening in a general population. When compared to our physical

activity feasibility and acceptability study almost all feasibility and acceptability scores in

General discussion

98

this study are higher. That is probably due to some specific changes made to this intervention

based on the acceptability and feasibility testing of the physical activity intervention.

Participants did not report to have problems with the fat intake questionnaire. The

appearance and the content of the questions was accepted by nearly all participants. However,

almost 20 % of them indicated that they had to answer too many questions before the fat

intake advice appeared. The majority of participants reported that the appearance as well as

content and credibility of the Fat Intake Advice were good, and consequently only a small

amount of participants indicated that the advice was too long or confusing. However, a small

group of about 15 %, reported that the fat intake advice is not correct at all. This is probably

due to the fact that a lot of people believe that their fat intake is not too high, while in reality

it is.15,16 This lack of fat intake awareness is present among lots of people and is a major

barrier in interventions aimed at reducing fat intake.15 Results concerning the use of a

computer indicate that this aspect of the intervention is also acceptable and feasible, all scores

were very high. Participants clearly appreciate the use of a computer, which ensures, in a fast

and simple way, an immediate and reliable fat intake advice that can be printed and taken

home at once. This intervention was especially designed to tailor for people from different

demographics and stages of change. Derived from the few significant differences between

groups for sex, education and computer literacy we can conclude that this intervention tailors

well for these groups. Concerning the age groups and stages of changes it is clear that the

differences found are logical and in concordance with theories.17-20

Efficacy of simultaneous or sequential tailored interventions

In this study the efficacy of our interactive computer-tailored physical activity and fat intake

interventions were evaluated. Furthermore, we wished to examine which intervening mode

would be more effective: a sequential or a simultaneous intervening mode.

For both sequential and simultaneous interventions a significant increase was found for total

physical activity when compared to the no-intervention group. These results are line with

other computer-tailored physical activity interventions.21-25 In both experimental groups there

was a 14% increase in participants meeting the physical activity recommendation. Further, it

appears that the present physical activity intervention especially caused large increases on the

light physical activities. This increase is relevant, since there are a substantial number of

studies which report the positive health benefits associated with walking and low intensity

physical activities.26-28

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The computer-tailored fat intake intervention caused large and significant reductions in total

fat intake and percent energy from fat for both experimental groups. The number of people

that met the fat intake recommendation almost doubled, from about 30% to 60%. This

intervention thus demonstrated to be very effective. The results in this study compare

favorably to other computer-tailored fat intake interventions.29-34 The ‘interactive’ and

immediate fat intake feedback and advice might explain why this intervention outperformed

other computer-tailored interventions that were not interactive. Another explanation for the

sizable effects is that no major efforts to reduce fat intake have been undertaken in the

country.

Our results clearly indicated that both the simultaneous and the sequential intervening modes

showed to be effective and can be used in health promotion. Only a few studies reported

either simultaneous or sequential multiple behaviour change interventions35-37 and regardless

of intervention mode (simultaneous or sequential) they all found positive results. In this way

these studies are, although indirectly, in line with our results. However, there are important

differences to note between the simultaneous and sequential intervening modes in this study.

These differences are most clearly expressed in the fat intake intervention: although the

sequential intervening mode showed to be effective, the simultaneous mode preformed

significantly better. For physical activity the differences between intervening modes were

less straight forward and more difficult to interpret. The sequential intervention mode seemed

to work similar for participants meeting and not meeting the physical activity

recommendation. However, the simultaneous intervening mode appeared to work even better

for participants not meeting the recommendation, whereas for participants meeting the

recommendation it appeared to work worse. It is difficult to explain why the simultaneous

intervention mode was more effective for the fat intake intervention and partly for the

physical activity intervention as there are no studies to compare them to. These findings seem

to contradict the position stand from some authors who indicated that changing multiple

behaviours at once might create an ‘overload’ and would thus be more difficult to be

done.38,39 It is possible that people who try to change several health behaviours at a time are

totally absorbed by the process and are really motivated to completely go for this healthy

lifestyle. Our results in the sequential intervening mode might have been better using a

shorter or longer interval between interventions. However the optimal interval between

intervention contacts is not known. Neither is there any literature about intervening on more

than two health behaviours, sequentially or simultaneously. It is possible that intervening

General discussion

100

simultaneously on three or more health behaviours indeed does create an overload of

information in participants, but this remains to be studied.

In conclusion, both the interactive computer-tailored physical activity and fat intake

intervention can be applied successfully to change behaviours. Further, both sequential and

simultaneous intervening modes can be used. From a public health point of view and because

the simultaneous intervention mode was superior for fat intake we recommend to implement

the interventions simultaneously, which is a much more cost-effective approach compared to

the implementation of several interventions at different points in time.

Practical Implications

From this research it becomes clear that intervention programmes for changing health

behaviours aimed at large populations can be effective. Moreover, a computerised approach

seems to work in Belgium, and it might be interesting to use this knowledge in other types of

health behavioural interventions. As outlined in the general introduction, there is a great need

for intervention programmes that increase physical activity and decrease fat intake in

Belgium. However, almost none have been executed. Furthermore, it has been suggested that

the effectiveness of our programs may be partly due to the lack health promotion

programmes in Belgium, again stressing the need for more health promotion efforts. Our

research produced two science based ‘ready-to-use’ interventions that have proven to be

effective.

The value and relevance of health promotion in Belgium, and more particular in Flanders, is

seriously underestimated. On a population wide level and in long term perspective health

promotion efforts can significantly increase quality of life and lifespan, and decrease

mortality and health care costs. Our computer-tailored interventions for increasing physical

activity and decreasing fat intake have proven to be effective and are available, so they can

make a difference. However, they only form a small part of the health promotion spectrum

and the effects of our interventions will not last forever. It is important to note that there are a

lot of other health behaviours, which are at least as important as physical activity and fat

intake (smoking, HIV, traffic safety, fruit and vegetable intake,…), but it is also very

important to intervene in a number of different ways. Health promotion interventions need to

be as diverse as possible. Each individual reacts differently on health promotion initiatives

and diversity is the only guarantee of reaching the widest population possible. A

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computerised approach, like ours, might be effective for many people but should definitely

not be the only available health promotion effort for physical activity and fat intake;

computerised intervening will not be effective for everyone and excludes certain sub-samples

in the population. Therefore interventions should not only target individuals in a number of

different ways, but should also affect the policy and the environment. This research also

demonstrates that a scientific approach is an absolute must in promoting health, as changing

health behaviours is very difficult and sometimes almost impossible. A lot of time and money

has been wasted in local and unscientific projects which did not work at all. Despite a lot of

good intentions this might partly explain the reticent attitude of policymakers whenever they

have to decide whether or not to spend money on health promotion projects such as ours.

Decent and good guidance from experienced professionals for implementing our

interventions is an absolute necessity. It is therefore that the role of the Flemish Institute for

Health Promotion (Vlaams Instituut voor Gezondheidspromotie, VIG), as expertise centrum,

and the tasks of the local health initiatives (LOkaal GezondheidsOverleg, LOGO), for

implementing interventions, are very important and should be further expanded. Moreover,

the Flemish Institute for Health Promotion, the Local Health Initiatives and general

practitioners can play an active role in guiding and promoting the implementation of our

physical activity and fat intake interventions. The Flemish Institute for Health Promotion can

be used to educate people from the Local Health Initiatives and general practitioners about

the rationale, theoretical backgrounds, and correct implementation modes of our

interventions. They can present information on how to use local government, local and

national associations, worksite computer networks or how to organise an intervention for

parents in the computer classes at the schools of their children. In this respect the two small

scaled implementation studies that have been executed using Local Health Initiatives were

very promising. Finally, we must mention that we do not recommend an implementation of

our interventions via the internet yet as more research is needed on that topic (see future

research).

Limitations and Methodological Issues

This research extensively used self-administered questionnaires, not only for calculation the

levels of physical activity and fat intake in our participants, presented in the physical activity

and fat intake advice, but also to investigate whether our interventions were effective in

General discussion

102

changing these health behaviours. Dispensing wrong advice, based on invalid physical

activity or fat intake measurements will decrease the effectiveness of our interventions,

furthermore using wrong measurements to evaluate interventions will lead to wrong

interpretations concerning effectiveness of our interventions. However, extensive testing

showed that both the IPAQ and the fat intake questionnaire were reliable and valid

measurement tools. Nevertheless, self-administered questionnaires can be subject to response

bias. Self-reports of physical activity typically show overreporting, and this problem has been

reported for the IPAQ as well.40 Self-reports of fat intake are known for underreporting.13

The use of more objective measures could largely solve these problems. It would be possible

to make more valuable interpretations about the effectiveness of the interventions and it

would allow to verify whether or not the computerised feedback that is presented to the

participants (which is also questionnaire based) is correct. However, the use of objective

measures usually involves a much greater cost and time investment, increases the burden of

the participants and are only usable in small samples. Moreover, the objective measurement

techniques available today in the field of physical activity and fat intake have their own

methodological problems and disadvantages.

Most studies presented in this research had relative small sample sizes, which makes it

difficult to generalize these results to larger populations. Generalisation is also difficult for

underserved populations, such as ethnic minorities and low socioeconomic status people.

Furthermore, only volunteers participated in all of our studies. This might have caused

selection bias as people that are not interested in physical activity or fat intake are less likely

to participate. This selection bias might even been enlarged by the fact that all of our studies

used computer technology, which might have discouraged people that are not used to work

with a computer. However, during recruitment procedures we tried to reduce these kinds of

selection bias by stressing that an interest in changing physical activity or fat intake was not

needed, nor that computer literacy is needed. Furthermore, implementation of our

interventions will most likely attract similar participants as people not motivated to change

behaviour will still not be interested to participate. If we would wish to increase

generalisability towards the total population a representative and randomised sample should

be selected. However, this is a difficult, timely and costly matter, and it would increase drop-

out rates dramatically, which would again affect the generalisability of the results.

Furthermore, a small pilot study (not reported) in which all the employees of a company had

to participate by their supervision showed no effect at all and a substantial portion of the

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participants showed very high resistance against the intervention materials. It is not at all

possible to impose health promotion programs.

Our interventions are pointed at the general public, however people willing to participate but

having medical complaints related to physical activity and fat intake, such as cardiovascular

disease, diabetes, anorexia and other medical problems, had to be turned down. This might

seem strange as an individualised physical activity or fat intake advice could be very

beneficial for them. However, we did not feel qualified enough to give advice to patients.

Moreover, we developed primary prevention interventions; thus preventing healthy people

from developing disease such as CVD or diabetes; and not helping individuals already having

a disease to become healthy again. Nevertheless, given a lot of consideration and carefulness

it is possible to extend our computer-tailored interventions in such ways that they could apply

for persons having medical complaints (that can be treated using behavioural modification

interventions) as well.

The fat intake intervention aimed to reduce total fat intake, a specific reduction of saturated

fats was not aimed. However, it is generally accepted that especially a high intake of the

saturated fats is harmful for health.41-45 There are several reasons why we choose not to

intervene on saturated fats. First, when this project was written most intervention studies

were pointed at total fat intake, whereas today this is shifting towards saturated fats. Second,

lowering total fat intake will also favourably affect intake of saturated fats. Third, changing

complex behaviours using complex messages simply does not work. In order to keep things

as simple as possible it might be that trying to reduce total fat intake could have more effect

on saturated fats compared to trying to reduce saturated fats directly. Fourth, if we wanted to

have a good measure of saturated fat intake, a far more detailed and longer fat intake

questionnaire would be required, which would increase participants’ burden. However, if

future research would clearly indicate that health promotion interventions should only be

directed at reducing saturated fats and not at reducing total fat, then it is, given some efforts,

possible to adjust the program.

Another limitation is that our fat intake questionnaire can not estimate total energy intake, as

it would require an unacceptable increase of questions, including a lot of questions not related

to fat intake. Therefore % calories from fat had to be calculated on recommended caloric

intake as opposed to actual caloric intake. During acceptability and feasibility testing of the

fat intake intervention already several people indicated that they had to answer too much

questions. A further increase of questions would decrease the attractiveness of the

intervention (and probably indirectly the effectiveness as well) and participants would have

General discussion

104

to answer a lot of questions of which they would get no feedback on (the advice is only about

fat intake). Nevertheless, given a lot of effort it is perfectly possible to measure total fat

intake, using a questionnaire, and create feedback that is based on this measure, but only for

research or scientific purposes.

Our results in the intervention study might have been influenced by the absence of health

promotion initiatives trying to reduce fat intake or increase physical activity. Any health

promotion initiative might have been successful, whether it is tailored or not. To clarify this a

standard intervention, which ignores interpersonal differences, should be compared to our

computer-tailored interventions. However, we chose not to do so as this would almost double

the number of conditions in our experimental study. We would have to create one

simultaneous condition receiving a standard intervention and two sequential conditions also

receiving standard interventions. Not only would this increase complexity of our statistic

procedures, it would also decrease our statistical power. Therefore we chose to use a simple

no-intervention waiting list control group. Similarly our results in the intervention study

might have been influenced by the physical activity levels of our control group, which were

remarkably higher compared to experimental groups. We can not explain these differences.

The increase of physical activity during the intervention period in the no-intervention group

might have been tempered by the fact that they already had very high baseline activity levels,

whereas this might not have been the case when baseline activity levels were comparable to

the other groups.

Recommendations for future research

As suggested earlier there is limited information on the optimal interval between

interventions when they are presented sequentially, nor is there information on the optimal or

maximal number of behaviours on which it is possible to intervene before creating an

overload of information in participants. More research on these topics is needed.

At first sight the implementation of interactive computer-tailored interventions using the

Internet might seem a logical next step. However, the Internet is a very special and specific

context for health promotion interventions. It is a very dynamic and fast changing

environment. Information is scanned instead of read, users want full control, they want to

skip from one ‘page’ or question to another whenever they feel like doing so and do mostly

not feel like staying on one website for a long time. It might be that the static and very

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structural approach which is used in our interventions on the CD-rom does not work on the

internet. Further, what information is to be trusted on the Internet and how does one make a

website visible for the right audience. Only a limited number of computer-tailored

interventions have been tested on the Internet with varied success.46-49 In short, there is a lot

of research needed before computer-tailored interventions can be implemented on the

internet.

Little is known about the specific mechanisms that drive the effectiveness of tailoring. A

possible explanation is presented by the elaboration likelihood model50, which suggests that

people are more likely to thoughtfully process information when they perceive it to be

personally relevant. However, previous studies have also been open to other explanations of

their effect. It could be argued that tailored interventions often simply provide participants

with more information or it might just be the ‘active participation’ (participants filling in

questions about the health behaviour) that is causing the effect.51 Therefore some authors call

for studies to explore what is in the ‘black box’ of tailored interventions.52

The computer-tailored interventions presented in this dissertation were aimed at the general

population, several subgroups, such as ethnic minorities or people with chronic illnesses,

were not considered due to a lack of time, money and expertise. Little evidence exists about

the effectiveness of computer-tailored interventions for increasing physical activity and

decreasing fat intake among these subgroups. Future studies should make efforts to examine

this.

General discussion

106

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General discussion

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Publications

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Publications Vandelanotte C. and I. De Bourdeaudhuij (2003). Acceptability and feasibility of a

computer-tailored physical activity intervention using stages of change project faith.

Health Education Research, 18 (3): 304-317.

De Bourdeaudhuij I., J. Sallis and C. Vandelanotte (2002). Tracking and explanation of

physical activity in young adults over a 7-year period. Research Quarterly for Exercise

and Sports, 73 (4): 376-385.

De Bourdeaudhuij I., J. Brug, C. Vandelanotte and P. Van Oost (2002). Differences in

impact between a family- versus an individual-based tailored intervention to reduce fat

intake. Health education Research, 17(4): 435-449.

Vandelanotte C., I. De Bourdeaudhuij and J. Brug (2004). Acceptability and Feasibility of

an Interactive Computer-Tailored Fat Intake Intervention in Belgium. Health

Promotion International, 19(4): ? -? . (in press).

Vandelanotte C., C. Matthys and I. De Bourdeaudhuij (2004). Reliability and validity of a

computerised questionnaire to measure fat intake in Belgium. Nutrition Research, 24(8):

621-631.

Vandelanotte C., I. De Bourdeaudhuij, J. Brug, J. Sallis and H. Spittaels. Efficacy of

Sequential or Simultaneous Interactive Computer-Tailored Interventions for Increasing

Physical Activity and Decreasing Fat Intake. Annals of behavioral medicine (in press).

Vandelanotte C., I. De Bourdeaudhuij, J. Sallis, R. Philippaerts and M. Sjöström. Reliability

and Validity of a Computerised and Dutch version of the International Physical Activity

Questionnaire (IPAQ). Journal of physical activity and health (in press).

Acknowledgements

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Acknowledgements The completion of my doctorate was not a ‘stand alone’ task. Lots of people have in some

kind of way assisted me and therefore I wish to thank them.

First of all, I would like to thank my promotor Professor Ilse De Bourdeaudhuij, without who

I would never have been able to make this dissertation. Ilse, you were the one that believed in

me and who gave me the chance to make a doctorate. Doing so you gave me confidence in

my own abilities and possibilities. You trusted me and gave me every possible independence

and freedom for doing my work, which fits perfectly with my personality and character. You

taught me how to do sciences and showed me the importance of collaborating with others.

You were always very busy and had dozens of different tasks to do, nevertheless you were

always there when I needed you to help me with some kind of problem, for which you almost

always had an instant solution. Ilse, you are a very nice person to work with and I hope that

finishing my doctorate does not put an end to our collaboration.

I also wish to thank Professor James Sallis from California and Professor Johannes Brug

from the Netherlands. They are some of the greatest experts worldwide on my topic and

despite their busy schedules they were always very cooperative and eager to help me. They

showed me what a good and international cooperation can stand for. I also want to thank

Christophe Matthys and Michael Sjörström for sharing their knowledge and expertise with

me.

I want to thank the members of the guidance commission for making sure that my work went

in the right direction and that the relevance of it all was maintained: Professor Jacques

Bouckaert, Professor Guy De Backer, Professor Paulette Van Oost and Professor Renaat

Philippaerts.

I’m also very thankful to all my colleagues for making me feel ‘at home’ at the institute. I

really loved working at the HILO and I will miss it when it is all over. I especially want to

114

thank my collegues at the top floor: again Ilse, your loud laughs put a smile on everybody’s

face; Benedicte and Greet, sharing the office with you both was really fantastic; Daniël,

making fun about nothing or talking about ‘serious politics’ formed an excellent brake in a

day of hard work; and of course all the others: Heleen, Katrien, Jacques, Inne, Renaat,

Margueritte and Anja.

And finally this work would not have been possible without all the people that participated in

my research and the licentiate students (Elke, Karen, Sabine, Kathleen, Els, Hilde, Evelyn,

Nele, Katrien and Griet) that helped me collect data. Thanks for that, every single one of you.

Addendum

115

Addendum Addendum 1: CD-rom with the computer tailored physical activity and fat intake

intervention (to protect the contents of the CD-rom against copying it was not included in

this edition of the doctorate, however the Ghent University can always be contacted for more information)

Addendum 2: computerised IPAQ (hard copy version!) Addendum 3: GVET (hard copy version!)

IPAQ

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Internationale Vragenlijst in verband met Fysieke Activiteiten

Wij willen onderzoeken welke lichaamsbeweging mensen doen in hun dagelijkse

leven. Deze enquête maakt deel uit van een onderzoek dat in een groot aantal landen over de hele wereld wordt uitgevoerd. Aan de hand van uw antwoorden kunnen we ons actief-zijn vergelijken met dat in andere landen.

De vragen gaan over uw fysieke activiteit in een doorsnee week. Er zitten vragen bij

over de lichaamsbeweging op uw werk, over uw verplaatsingen, over uw werk in huis en in de tuin, en over uw vrije tijd in verband met ontspanning, lichaamsbeweging en sport.

Uw antwoorden zijn belangrijk. Probeer op alle vragen te antwoorden, zelfs als u

vindt dat u niet erg actief bent.

Dank voor uw medewerking

Een toelichting bij het beantwoorden van de volgende vragen: ♦ zware fysieke activiteiten verwijzen naar activiteiten die een zware

lichamelijke inspanning vereisen en waarbij u veel sneller en dieper ademt dan normaal.

♦ matige fysieke activiteiten verwijzen naar activiteiten die een matige lichamelijke inspanning vereisen en waarbij u iets sneller en dieper ademt dan normaal.

Addendum

117

Deel 1: Fysieke activiteiten tijdens uw werk

Deel 1 gaat over uw werk. Onder werk verstaan we: betaald werk, werk op de boerderij, vrijwilligerswerk, studiewerk en ander onbetaald werk dat u buitenshuis verricht. Thuiswerk zoals huishoudelijk werk, tuinieren, klusjes en gezinstaken horen hier niet bij. Dat komt aan bod in deel 3. 1a Hebt u momenteel een baan of doet u onbetaald werk buitenshuis? Ja Nee (Ga naar Deel 2: Vervoer) De volgende vragen handelen over alle fysieke activiteiten die u tijdens een gewone week verricht als deel van uw betaald of onbetaald werk. De verplaatsing van en naar het werk hoort hier niet bij. Het gaat hier alleen om de fysieke activiteiten die u gedurende minstens 10 minuten aan één stuk doet. 1b Op hoeveel dagen in een gewone werkweek doet u zware fysieke activiteiten zoals

zwaar tilwerk, spitten, bouwwerken of trappen oplopen als deel van uw werk? ________ dagen per week Geen (Ga naar vraag 1d.) 1c Hoeveel tijd in totaal besteedt u op zo’n dag gewoonlijk aan zware fysieke

activiteiten als deel van uw werk? ____ uur ___ minuten /dag 1d Op hoeveel dagen in een gewone werkweek doet u matige fysieke activiteiten zoals

het dragen van lichte lasten als deel van uw werk? ________ dagen per week Geen (Ga naar vraag 1f.) 1e Hoeveel tijd in totaal besteedt u op zo’n dag gewoonlijk op aan matige fysieke

activiteiten als deel van uw werk? ____ uur ___ minuten /dag 1f Op hoeveel dagen in een gewone werkweek wandelt u gedurende minstens 10

minuten aan één stuk als deel van uw werk Opgelet, de verplaatsing te voet van en naar het werk hoort hier niet bij ! ________ dagen per week

IPAQ

118

Geen (Ga naar Deel 2: Vervoer) 1g Hoeveel tijd in totaal wandelt u op zo’n dag als deel van uw werk ? ____ uur ___ minuten /dag 1h Indien u wandelt als deel van uw werk, in welk tempo is dat dan meestal ? Wandelt u in : een hoog tempo? een middelmatig tempo? een laag tempo? Deel 2: Fysieke activiteiten die verband houden met vervoer

Nu volgen enkele vragen over hoe u zich verplaatst naar het werk, om boodschappen te doen, naar de film te gaan enzovoort. 2a Op hoeveel dagen in een gewone week verplaatst u zich met een motorvoertuig

zoals de trein, de bus, de wagen of de tram? ________ dagen per week Geen (Ga naar vraag 2c) 2b Hoeveel tijd in totaal besteedt u op zo’n dag gewoonlijk aan verplaatsingen met de

wagen, de bus, de trein of een ander motorvoertuig? ____ uur ___ minuten / dag Denk nu alleen aan het fietsen en het wandelen dat u doet om naar het werk te gaan, te winkelen of gewoon om ergens heen te gaan. 2c Op hoeveel dagen in een gewone week fietst u gedurende minstens 10 minuten aan

één stuk om ergens heen te gaan? ________ dagen per week. Geen (Ga naar vraag 2f) 2d Hoeveel tijd in totaal fietst u op zo’n dag om ergens heen te gaan ? ____ uur ___ minuten /dag

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119

2e Als u zich verplaatst per fiets, in welk tempo fietst u dan meestal? Fietst u in : een hoog tempo een middelmatig tempo of een laag tempo 2f. Op hoeveel dagen in een gewone week wandelt u gedurende minstens 10 minuten

aan één stuk om ergens heen te gaan ? ________ dagen per week Geen (Ga naar Deel 3: Huishoudelijk Werk, Klusjes en Gezinstaken) 2g Hoeveel tijd in totaal wandelt u op zo’n dag om ergens heen te gaan ? ____ uur ___ minuten /dag 2h Als u wandelt om ergens heen te gaan, in welk tempo is dat dan meestal ? Wandelt u in : een hoog tempo een middelmatig tempo of een laag tempo

Deel 3. Huishoudelijk werk, klusjes en gezinstaken

Dit deel gaat over de fysieke activiteiten die u tijdens een gewone week doet in en rond het huis, bijvoorbeeld huishoudelijk werk, tuinieren, onderhoudswerk of voor het gezin zorgen. Nogmaals, denk alleen aan die fysieke activiteiten die u gedurende minstens 10 minuten aan één stuk verricht. 3a Op hoeveel dagen in een gewone week doet u zware fysieke activiteiten zoals zwaar

tilwerk, houthakken, sneeuwruimen of spitten in de tuin of moestuin ? ________ dagen per week

IPAQ

120

Geen (Ga naar vraag 3c) 3b Hoeveel tijd in totaal besteedt u op zo’n dag gewoonlijk aan zware fysieke

activiteiten in de tuin of moestuin ? ____ uur ___ minuten /dag 3c Op hoeveel dagen in een gewone week doet u matige fysieke activiteiten zoals lichte

lasten dragen, ruiten wassen, vegen of harken in de tuin of moestuin ? ________ dagen per week Geen (Ga naar vraag 3e) 3d Hoeveel tijd in totaal besteedt u op zo’n dag gewoonlijk aan matige fysieke

activiteiten in de tuin of moestuin ? ____ uur ___ minuten /dag 3e Op hoeveel dagen in een gewone week doet u matige fysieke activiteiten zoals lichte

lasten dragen, ruiten wassen, vloeren schrobben of vegen binnenshuis ? ________ dagen per week Geen (Ga naar Deel 4: Fysieke Activiteiten die verband houden met Sport, Ontspanning en Vrije Tijd) 3f Hoeveel tijd in totaal besteedt u gewoonlijk op zo’n dag aan matige fysieke

activiteiten binnenshuis? ____ uur ___ minuten /dag

Deel 4: Fysieke activiteiten die verband houden met sport, ontspanning en vrije tijd

Dit deel gaat over alle fysieke activiteiten die u tijdens een gewone week doet, maar dan uitsluitend als recreatie, sport, training of vrijetijdsbesteding. Nogmaals, denk alleen aan die fysieke activiteiten die u gedurende minstens 10 minuten aan één stuk verricht. Gelieve geen activiteiten mee te rekenen die u reeds vermeld hebt. 4a Zonder het wandelen dat u reeds vermeld hebt, op hoeveel dagen in een gewone

week wandelt u gedurende minstens 10 minuten aan één stuk in uw vrije tijd ? ________ dagen per week

Addendum

121

Geen (Ga naar vraag 4d) 4b Hoeveel tijd wandelt u in totaal op zo’n dag in uw vrije tijd? ____ uur ___ minuten /dag 4c Als u wandelt in uw vrije tijd, in welk tempo is dat dan meestal? Wandelt u in : een hoog tempo een middelmatig tempo of een laag tempo 4d Op hoeveel dagen in een gewone week doet u zware fysieke activiteiten zoals

bijvoorbeeld aerobics, lopen, snel fietsen, snel zwemmen of andere intense activiteiten, in uw vrije tijd ?

________ dagen per week Geen (Ga naar vraag 4f) 4e Hoeveel tijd in totaal besteedt u op zo’n dag gewoonlijk aan zware fysieke

activiteiten in uw vrije tijd? ____ uur ___ minuten /dag 4f Op hoeveel dagen in een gewone week doet u matige fysieke activiteiten zoals

bijvoorbeeld fietsen aan een middelmatig tempo, zwemmen aan een middelmatig tempo, tennis dubbelspel of andere activiteiten aan een matige intensiteit, in uw vrije tijd ?

________ dagen per week Geen (Ga naar Deel 5: De tijd die u zittend doorbrengt) 4g Hoeveel tijd in totaal besteedt u op zo’n dag gewoonlijk aan matige fysieke

activiteiten in uw vrije tijd? ____ uur ___ minuten /dag

IPAQ

122

Deel 5: De tijd die u zittend doorbrengt De laatste vragen gaan over de tijd die u elke dag zittend doorbrengt op het werk, thuis, tijdens studiewerk of in uw vrije tijd. Hierbij hoort ook de tijd dat u achter een bureau zit, bezoek krijgt, zit te lezen, of naar televisie zit of ligt te kijken. De tijd die u zittend doorbrengt in een motorvoertuig, die u reeds vermeld hebt, komt hier niet in aanmerking. 5a Hoeveel tijd in totaal brengt u gewoonlijk zittend door op een weekdag ? ____ uur ___ minuten /dag 5b Hoeveel tijd in totaal brengt u gewoonlijk zittend door op een weekenddag ? ____ uur ___ minuten /dag

Addendum

123

Vetinname De volgende vragen gaan over uw vetinname. In deze vragenlijst komen alleen vetrijke producten voor, producten zonder vet zijn weggelaten. Vul de vragen in door op de juiste plaats een kruisje te plaatsen ! Wanneer u een bepaald product nooit eet, zet dan zeker ook een kruisje bij ‘0’ keer. Opgelet : ! Deze vragen gaan niet altijd over een gewone WEEK (= weekdagen + weekenddagen), maar soms ook over een gewone DAG of MAAND. Wanneer de portiegrote, die bij verschillende producten aangegeven staat in de vragenlijst, bij u veel groter is, reken dan dubbel zoveel porties per week of per maand aan. Brood en ontbijtgranen

0 per dag

1 per dag

2 per dag

4 per dag

6 per dag

8 per dag

10 per dag

12 per dag

14 per dag

16 per dag

18 of meer per dag

Hoeveel sneden brood zoals wit brood, tarwebrood, volkorenbrood, ... eet u op een gewone DAG ?

0

per week

1 per

week

2 per

week

4 per

week

6 per

week

8 per

week

10 per

week

12 per

week

14 per

week

16 per

week

18 of meer

per week Hoeveel beschuiten of crackers, ... eet u in een gewone WEEK ? Hoeveel pistolets, piccolo's of stokbrood (1/4), ... eet u in een gewone WEEK ?

Hoeveel sandwiches eet u in een gewone WEEK ? Hoeveel koffiekoeken met chocolade eet u in een gewone WEEK ? Hoeveel koffiekoeken (met abrikoos, aardbei, rozijnen, …), croissants of suises, … eet u in een gewone WEEK ?

Hoeveel kommen muesli eet u in een gewone WEEK ? Hoeveel kommen cruesli (krokante muesli met chocolade, honing en/of vruchten, …) eet u in een gewone WEEK ?

Fat Intake Questionnaire

124

Broodbeleg 0

per week

1 per

week

2 per

week

4 per

week

6 per

week

8 per

week

10 per

week

12 per

week

14 per

week

16 per

week

18 of meer per

week Hoeveel sneden of porties (1 portie = 30 g) vette kaas eet u in een gewone WEEK ? Vette kaassoorten (ook wel 48+, 50+, 60+ en 70+ kazen genoemd)zijn onder meer : gouda (jonge kaas), zachte roomkaas, Boursin, Maaslander, Passendale, Rocquefort, Père Joseph, volle smeerkazen, ... .

Hoeveel sneden of porties (1 portie = 30 g.) half vette kaas eet u in een gewone WEEK ? Half vette kaassoorten (ook wel 40+ en 45+ kazen genoemd) zijn ondermeer : Trenta, Petrus, halfvolle smeerkaas, Franse kazen (Chaumes, Camembert, Brie, ...), ... .

Hoeveel sneden of porties (1 portie = 25 g.) magere kaas of light kaas eet u in een gewone WEEK ? Magere kaassoorten (ook 20+ en 30+ kazen genoemd) zijn ondermeer : Westlite, St-Maarten, Milner, Samsoe, Philadelphia light, Belleligne

Hoeveel sneden of porties (1 portie = 25 g.) vette vleeswaren en salades eet u in een gewone WEEK ? Vette vleeswaren zijn ondermeer : paté, salami, ontbijtspek, worstensoorten (zoals boterhamworst), vleessalade, tonijnsalade, krabsalade, ... .

Hoeveel sneden of porties (1 portie = 25 g.) halfvette vleeswaren eet u in een gewone WEEK ? Halfvette vleeswaren zijn ondermeer : filet americain bereid, vleesbrood, ... ?

Hoeveel sneden of porties (1 portie = 25 g.) magere vleeswaren eet u in een gewone WEEK ? Magere vleeswaren zijn ondermeer : schouderham, achterham, rauwe ham,filet americain puur, kippewit, kalkoenham, gekookte hesp, ... ?

Hoeveel sneden brood, beschuiten, sandwiches of broodjes besmeert of bestrooit u in een gewone WEEK met choco of chocoladekorrels ?

Addendum

125

0

per week

1 per

week

2 per

week

4 per

week

6 per

week

8 per

week

10 per

week

12 per

week

14 per

week

16 per

week

18 of meer per

week Hoeveel sneden brood, beschuiten, sandwiches of broodjes besmeert u in een gewone WEEK met boter of margarine zoals : melkerijboter, boerenboter, planta, rhoda, vitelma gezond smeren, benecol margarine, bertolli, butella, ... ?

Hoeveel sneden brood, beschuiten, sandwiches of broodjes besmeert u in een gewone WEEK met minarine zoals : effi, alpro soyaminarine, becel control, minelma, benecol minarine, spring, …

Hoeveel sneden brood, beschuiten, sandwiches of broodjes besmeert u in een gewone WEEK met smeervet met verlaagd vetgehalte zoals : becel essential, balade light, ... ?

Melk en melkprodukten 0

per week

1 per

week

2 per

week

4 per

week

6 per

week

8 per

week

10 per

week

12 per

week

14 per

week

16 per

week

18 of meer

per week Hoeveel glazen of potjes volle melkprodukten zoals :volle (choco)melk, volle yoghurt, volle vla of pudding, ... drinkt/eet u op een gewone WEEK ? (1 glas is ongeveer 150 ml.)

Hoeveel glazen of potjes halfvolle melkprodukten zoals : halfvolle (choco)melk, halfvolle yoghurt, halfvolle vla of pudding, ..drinkt/eet u op een gewone WEEK ?

Hoeveel glazen of potjes magere melkprodukten zoals : magere (choco)melk, magere yoghurt, magere vla of pudding, karnemelk,.. drinkt/eet u op een gewone WEEK ?


126

Bereide gerechten 0

porties per

maand

1 porties

per maand

2 porties

per maand

3 porties

per maand

4 porties

per maand

5 porties

per maand

6 porties

per maand

7 porties

per maand

8 porties

per maand

9 of meer p/p

maand Hoeveel keer in een gewone MAAND eet u pizza (1 portie = 350 g.) ?

Hoeveel keer in een gewone MAAND eet u lasagne (1 portie = 400 g.) ?

Hoeveel keer in een gewone MAAND eet u spaghetti bolognaise (1 portie = 450 g.) ?

Hoeveel keer in een gewone MAAND eet u aardappelkroketten (1 portie = 6 kroketten = 150 g.) ?

Hoeveel keer in een gewone MAAND eet u gebakken aardappelen en aardappelpuree (1 portie = 150 g.) ?

Hoeveel keer in een gewone MAAND eet u een klein pakje frieten (1 portie = 1/3 bord =150 g.) ?

Vlees, vis en eieren 0

porties per

maand

1 porties

per maand

2 porties

per maand

3 porties

per maand

4 porties

per maand

5 porties

per maand

6 porties

per maand

7 porties

per maand

8 porties

per maand

9 of meer p/p

maand Hoeveel keer in een gewone MAAND eet u stukken vette vis zoals : zalm, maatje, haring, makreel, rivierpaling, .... (1 portie = 150 g.) ?

Hoeveel keer in een gewone MAAND eet u stukken magere vis zoals : forel, grijze garnalen, tong, kabeljauw, tonijn, ... (1 portie = 150 g.) ?

Addendum

127

0 per

week

1 per

week

2 per

week

3 per

week

4 per

week

5 per

week

6 per

week

7 per

week

8 per

week

9 of meer

per week Hoeveel keer in een gewone WEEK eet u stukken vet vlees zoals : gehakt, worst, spek, vet rundsvlees, vet lamsvlees, ... (1 portie = 150 g.) ?

Hoeveel keer in een gewone WEEK eet u stukken gemiddeld vet vlees zoals : hamburgers (ook fastfood burgers zoals : kippeburger, cheeseburger, ...), schapenvlees, varkenskarbonade, lamsvlees, ossentong, vet kalfsvlees, ... (1 portie = 150 g.) ?

Hoeveel keer in een gewone WEEK eet u stukken mager vlees zoals : kip, kalkoen, varkensfiletlap, runderbiefstuk, haas, lever, ... (1 portie = 150 g.) ?

Hoeveel keer in een gewone WEEK eet u vervangproducten of vegetarische voeding zoals : quorn, tofu, vegetarische burger, tempeh, ..(1 portie =100 g.)?

Hoeveel eieren eet u in een gewone WEEK ?

Sauzen 0

per week

1 per

week

2 per

week

4 per

week

6 per

week

8 per

week

10 per

week

12 per

week

14 per

week

16 per

week

18 of meer

per week Hoeveel eetlepels mayonnaise (1 lepel = 20 g.) eet u in een gewone WEEK ?

Hoeveel eetlepels andere sauzen zoals : cocktailsaus, béarnaisesaus, tartaar, ... (1 lepel = 20 g.) eet u in een gewone WEEK ?

Hoeveel eetlepels room, slagroom, dressing en slasaus (1 lepel = 15 g.) eet u in een gewone WEEK ?

Hoeveel eetlepels onverdunde (geen water toegevoegd) vleessaus (of jus) (1 lepel = 10 g.) eet u in een gewone WEEK ?

Hoeveel eetlepels verdunde (water toegevoegd) vleessaus (of jus)(1 lepel = 10 g.) eet u in een gewone WEEK ?


128

0 per

maand

1 per

maand

2 per

maand

4 per

maand

6 per

maand

8 per

maand

10 per

maand

12 per

maand

14 per

maand

16 per

maand

18 of meer per maand

Hoeveel eetlepels kaassaus bijvoorbeeld bij prei, bloemkool, schorseneer, witloof met hesp,... (1 lepel = 20 g.) eet u in een gewone MAAND ?

Tussendoortjes 0

per week

1 per

week

2 per

week

4 per

week

6 per

week

8 per

week

10 per

week

12 per

week

14 per

week

16 per

week

18 of meer

per week Hoeveel sneden cake en aantal wafels (Brusselse wafel, Luikse wafel, suikerwafel, chocoladewafel, ...) eet u in een gewone WEEK ?

Hoeveel stukken taart (fruittaart, rijsttaart, flantaart, chocoladetaart, ...) en stukken gebak (zoals frangipane, ...) eet u in een gewone WEEK ?

Hoeveel koekjes (droog) en kinderkoeken eet u in een gewone WEEK? (15 g. per koekje)

Hoeveel koekjes met chocolade, honing, vanille, noten, rozijnen ...zoals : mueslikoek (grany), chocoladekoek, haverkoek, vanillekoek (princekoek) notenkoek (balisto), speculaaskoek, rozijnenkoek (sultana), honingkoek, ... eet u in een gewone WEEK ?(15 g. per koekje)

Hoeveel repen chocolade (côte d'or, zero, ...), mars, snickers, leo, twix, milky way, bounty, cha cha, pralines, ... en potjes chocolademousse eet u in een gewone WEEK ?

Hoeveel kleine zakjes chips (alle varianten !) en handjes noten (alle soorten, ook borrelnootjes) eet u in een gewone WEEK ? (1 grote zak chips = 3 kleine zakjes chips, 1 handje noten = de hoeveelheid noten die in 1 handpalm past)

Addendum

129

0 per

maand

1 per

maand

2 per

maand

4 per

maand

6 per

maand

8 per

maand

10 per

maand

12 per

maand

14 per

maand

16 per

maand

18 of meer per

maand Hoeveel bollen roomijs eet u in een gewone MAAND ? (ijshoorntje = 2 of 3 bollen, frisco, ijsstick of cornetto = 2 bollen)

Hoeveel blokjes kaas en sneetjes vleeswaren eet u in een gewone MAAND tussendoor (bijvoorbeeld ook op een receptie of aperitief) ?

Development and Evaluation of a Computerised and Individualised intervention for increasing Physical...

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