Different recruitment methods identify different individuals

7Different recruitment methods

identify different individuals

Joke Fleer

Harald J Hoekstra

Roy E Stewart

Raoul E Nap

Dirk Th Sleijfer

Josette EHM Hoekstra-Weebers

Submitted

FYN Werk-Fleer proefschrift.indb119 119 11-1-2006 23:44:09

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Introduction

Since the number of cancer survivors is growing, there is an increasing interest in how cancer patients progress with their lives after treatment, and how they regain a reasonable quality of life (QoL) [1]. Therefore, QoL has become an important outcome variable in medical and psychosocial oncology research [2]. Conclusions about the QoL of cancer patients are always based on data obtained from patients who participate in studies. In order to extrapolate results to the overall population of cancer patients, both adequate sample sizes and samples representative of the total population are needed [3;4]. In QoL studies, different methods are used to recruit patients. Many studies recruit pa-tients through hospital databases. By using postal questionnaires, researchers can easily invite all patients treated at a clinic within a certain time period to participate. When the response rate is high, it is likely that the sample is representative of the total population of patients. Unfortunately, response rates of studies in which postal questionnaires are used are often under 70% [5]. There are also studies that approach support groups, that use the internet or an advertisement in papers or magazines for the recruitment of patients [6]. Yet, it is possible that these methods identify atypical groups of patients, even if a high response rate is achieved. Consequently, the validity of results may be influenced by the source from which patients are recruited. There are indications from the literature that recruitment through different sources in-deed identifies populations with different characteristics. For example, it has been found that members from patient support groups reported less anxiety, depression, stress, and a better QoL than non-members [7;8]. However, members from a patient association were found to experience more distress than those recruited through a hospital database [9]. It is not clear what causes these differences in outcomes, but it may have to do with the fact that patients who become member of a patient association have a greater need to receive support from and offer support to their fellow cancer survivors [10]. A higher likelihood to seek support has been associated with several sociodemographic- and cancer-related characteristics, such as being female, being unmarried, being closer to diagnosis, and a higher educational level [7;8;11;12]. Thus, it could be that members from a patient as-sociation have specific sociodemographic and cancer-related characteristics. Because so-ciodemographic- and cancer-related characteristics have also been found to relate to QoL outcomes in cancer survivors (e.g., [13-15]), it may very well be that the comparability of QoL of patients recruited through a patient association from those recruited through a hospital database is affected by the differences in these characteristics.This study aims to gain insight into (1) the types of individuals that different recruitment sources identify and (2) the effect of recruitment source on QoL outcomes. To do so, we will compare testicular cancer survivors (TCSs) recruited through a patient association with those recruited through a hospital database on sociodemographics, cancer-related data and QoL. Based on the literature, we hypothesize that the two groups will differ on sociodemographic- and cancer-related characteristics. We think that the members from the patient association will be younger, more often unmarried, higher educated and closer to treatment completion. We also hypothesized that the patient association group will be a more specific group compared to those recruited through the hospital database, and thus show less variance in sociodemographic- and cancer-related characteristics. Further-


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more, we assume that the two groups will differ in QoL. However, we do not hypothesize on the direction of this difference, as published literature on this topic is contradictory [7]. If the groups differ in QoL, we will investigate the effect of recruitment source on QoL.

Patients and methods

Respondents

Respondents were approached through two recruitment sources:1. The Groningen University Medical Center. 701 men treated for testicular cancer (TC)

between 1977 and 2003 were invited to participate in a QoL study. Fifty percent (n = 354) of the TCSs agreed to participate and completed the questionnaire. Comparison of patients who participated in the study with those who did not showed that the two groups did not differ in age, time since diagnosis, and type of treatment received.

2. The Dutch patient association for TC patients and survivors. The main goal of this association is to provide an opportunity for men treated for TC to get in touch with each other and to provide and receive information about their disease. Eighty-five of the 116 members (73.3%) completed the questionnaire. No information was available on sociodemographic and treatment-related characteristics of the non-responders.

Questionnaires

Sociodemographic and treatment-related characteristicsThe following sociodemographic and treatment-related characteristics were assessed: age at time of study, age at time of diagnosis, time since diagnosis, educational level, marital status, employment status, type of treatment received, and experience of a second cancer event. The highest level of education completed was measured along the following seven-point scale: primary school (1), lower vocational (2), lower secondary (3), middle secon-dary (4), high secondary (5), higher vocational (6), and advanced university (7).

Quality of lifeThe RAND-36 [16] is an internationally used valid and reliable generic self-report ques-tionnaire to assess QoL. The Dutch version of the RAND-36 [17] was used. It contains eight subscales: physical functioning (10 items), social functioning (2 items), role limitations due to physical problems (4 items), role limitations due to emotional problems (3 items), mental health (5 items), vitality (4 items), pain (2 items), general health perception (5 items), and one item on health change. After transformation, scores on the subscales vary from 0 to 100, with a higher score indicating a better health status. In the present study, internal consistency of the subscales for the total sample was good (varying from 0.80 to 0.92).


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Statistical analyses

Dichotomous variables were created for marital status, employment status and type of treatment. Marital status consisted of the categories “no partner” (consisting of single, divorced and separated patients) and “partner” (consisting of those who were married or cohabiting). Employment status included the categories of “not employed for wages” (consisting of students, unemployed persons, those who were unable to work, and reti-rees) and “employed for wages” (consisting of those who were employed for wages). The following categories were used for type of treatment: “surgical treatment (consisting of the categories orchidectomy and orchidectomy + retroperitoneal lymph node dissection) and “combined treatment” (consisting of the categories orchidectomy + radiotherapy, or-chidectomy + chemotherapy, and orchidectomy + chemotherapy + surgical resection of residual tumor mass). Levene’s test for homogeneity of variance was used to examine the equality of variance between the patient association and the hospital database. Unpaired T-tests and Chi2 tests were performed to study the hypothesis that the two groups differ on sociodemographics, cancer-related characteristics and QoL. Analyses of covariance were used to examine the effect of recruitment source on QoL. Analyses of covariance also enable us to investigate if the differences in QoL between the two groups remain after controlling for sociodemographic and cancer-related variables. The covariates were those sociodemographic- and cancer-related characteristics on which the groups differed significantly.Results were considered statistically significant if the probability of occurrence was 0.05 or less.

Results

Comparison of sociodemographic and cancer-related characteristics

Levene’s test for homogeneity of variance showed that the variances in age, age at diagno-sis, and time since diagnosis were not equal for the two groups. Inspection of the standard deviations and ranges of the continuous variables showed less variance in scores in the patient association group than in the hospital group. T-tests showed that the patient as-sociation group was younger, more recently diagnosed and higher educated. Levene’s test for homogeneity of variance also showed that the variances in marital status, type of treatment, and second cancer event were not equal for the two groups. Inspection of the ratio’s of the dichotomous variables showed that the ratio’s of (1) having a partner to not having a partner, (2) surgical to combined treatment, and (3) having experienced a second cancer event to not having experienced a second cancer event were different for the groups. Members from the patient association had received more extensive treatment, and had more often experienced a second cancer event than the patients from the hospital group (Table 1).


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Hos

pita

l gro

upN

= 3

54*

Pati

ent a

ssoc

iati

on g

roup

N =

85*

Lev

ene’s

test

for

hom

ogen

eity

Com

pari

son

betw

een

grou

ps

MSD

(ran

ge)

MSD

(ran

ge)

Fp

tp

Age

(in

year

s) 43

.712

.1 (1

8-79

)40

.88.

7 (1

9-62

)11.

910.

001

2.58

0.01

Age

at d

iagn

osis

(in y

ears)

32

.910

.4 (1

6-72

)34

.37.8

(17-

55)

7.65

0.00

6-1

.43

0.16

Tim

e sin

ce d

iagn

osis

(in y

ears)

10.7

6.8

(0.3

-25)

6.5

4.4

(0.7

-25)

44.8

4<

0.00

17.1

6<

0.00

1

Educ

atio

nal l

evel

4.2

1.7 (1

-7)

5.0

1.5 (2

-7)

1.90

0.17

-3.9

6<

0.00

1

N%

N%

Fp

Chi

2p

Mar

ital s

tatu

s4.

030.

051.0

90.

30

Part

ner

298

84.7

6880

.0

No

part

ner

5415

.317

20.0

Empl

oym

ent s

tatu

s1.0

00.

320.

270.

61

Em

ploy

ed fo

r wag

es27

577

.964

75.3

Not

em

ploy

ed fo

r wag

es78

22.1

2124

.7

Tre

atm

ent

42.4

7<

0.00

17.2

20.

007

Surg

ical

100

28.6

1214

.3

Com

bine

d25

071

.472

85.7

Seco

nd ca

ncer

even

t 37

.62

<0.

001

10.5

90.

001

Yes

318.

818

21.2

No

322

91.2

6778

.8

Tab

le 1.

Soc

iode

mog

raph

ic a

nd c

ance

r-re

late

d ch

arac

teri

stic

s of t

he tw

o gr

oups

and

com

pari

son

betw

een

the

grou

ps

*N is

sligh

tly v

aria

ble b

ecau

se o

f miss

ing d

ata


7

125

Qua

lity

of li

feH

ospi

tal g

roup

N =

354

*Pa

tien

t ass

ocia

tion

gro

upN

= 8

5*L

even

e’s te

st fo

r ho

mog

enei

tyT

-tes

ts fo

r co

mpa

riso

n be

twee

n gr

oups

MSD

MSD

Fp

tp

Phys

ical

func

tioni

ng88

.219

.287

.617

.61.1

90.

340.

250.

80

Soci

al fu

nctio

ning

85.8

19.9

77.2

22.8

1.30

0.11

3.48

<0.

001

Rol

e lim

itatio

ns (p

hysic

al)

84.0

30.7

71.1

40.4

1.74

<0.

001

2.73

0.00

7

Rol

e lim

itatio

ns (e

mot

iona

l)85

.431

.175

.737

.91.4

90.

022.

190.

03

Men

tal h

ealth

76.9

15.9

72.8

19.1

1.44

0.03

1.83

0.07

Vita

lity

64.3

19.5

39.2

16.1

1.48

0.03

12.3

4<

0.00

1

Pain

88.3

18.7

89.8

18.2

1.05

0.80

-0.6

30.

53

Gen

eral

hea

lth p

erce

ptio

n71

.419

.663

.223

.21.4

00.

043.

030.

003

Hea

lth c

hang

e52

.417

.555

.117

.31.0

30.

89-1

.28

0.20

Tab

le 2

. Des

crip

tives

on

qual

ity

of li

fe su

bsca

les f

or th

e tw

o gr

oups

and

com

pari

son

betw

een

the

grou

ps

*N is

sligh

tly v

aria

ble b

ecau

se o

f miss

ing d

ata


126

7

Comparison of the two groups on QoL

Levene’s test for homogeneity of variance showed that the variances in the subscales role limitations due to physical and emotional problems, mental health, vitality and general health perception were not equal for the two groups. T-tests showed that the two groups differed in means on the subscales social functioning, role limitations due to physical and emotional problems, vitality and general health perception. The patient association group showed more variance and lower means on the subscales (Table 2).

Comparison of the two groups on QoL after controlling for sociodemographic and cancer-related characteristics

Analyses of covariance were used to examine if the differences in QoL remained after controlling for sociodemographic and cancer-related variables. The covariates were the sociodemographic- and cancer-related characteristics on which the groups differed sig-nificantly: age, time since diagnosis, educational level, type of treatment, and second cancer event (see Table 1). Still significantly more variance was found in the scores of the members from the patient association on the subscales role limitations due to physi-cal and emotional problems, mental health and vitality than of the hospital group. Also, lower mean scores on the subscales social functioning, role limitations due to physical and emotional problems, vitality and general health perception were found in the patient association group than in the hospital group (Table 3).

Discussion

One of the prerequisites for a methodologically strong study is adequate recruitment of patients in order to obtain a representative sample of the population of patients. If recruitment is not optimal, it may have an impact on the generalizability of study re-sults [18]. Although this is common scientific knowledge, there is surprisingly little em-pirical research available on the comparability of patient populations included through different types of recruitment. As a consequence, researchers may underestimate the impact of recruitment source on outcomes. Therefore, we have compared testicular cancer survivors (TCSs) recruited through a patient association with those recruited through a hospital database on sociodemographic- and cancer-related characteristics and on QoL. The first aim was to examine if the two recruitment sources represented different types of individuals. Based on the literature [7;8;11;12] we hypothesized that sociodemographic- and cancer-related characteristics of the two groups would differ. Furthermore, we hy-pothesized that the members from the patient association would be a more specific group compared to those recruited through the hospital database, and thus show less variance in characteristics. Our results confirm these hypotheses. Members from the patient associa-tion were significantly younger, more recently treated, higher educated, more often treated with extensive treatment, and had more often experienced a second cancer event than


7

127

Qua

lity

of li

feH

ospi

tal g

roup

N =

354

*Pa

tien

t ass

ocia

tion

gro

upN

= 8

5*L

even

e’s te

st fo

r ho

mog

enei

tyT

-tes

ts fo

r co

mpa

riso

n be

twee

n gr

oups

MSD

MSD

Fp

tp

Phys

ical

func

tioni

ng90

.218

.188

.015

.61.3

50.

101.0

20.

31

Soci

al fu

nctio

ning

85.0

19.9

76.7

22.2

1.24

0.19

3.31

0.00

1

Rol

e lim

itatio

ns (p

hysic

al)

78.2

30.3

66.4

38.2

1.59

0.00

52.

600.

01

Rol

e lim

itatio

ns (e

mot

iona

l)84

.331

.274

.538

.21.5

00.

012.

170.

03

Men

tal h

ealth

73.1

15.8

69.2

19.5

1.53

0.01

1.71

0.09

Vita

lity

59.8

19.3

35.7

15.2

1.61

0.01

12.2

4<

0.00

1

Pain

93.9

18.0

94.2

17.6

1.04

0.84

-0.15

0.88

Gen

eral

hea

lth p

erce

ptio

n61

.118

.754

.721

.41.3

20.

102.

710.

007

Hea

lth c

hang

e67

.117

.167

.517

.31.0

20.

88-0

.170.

86

Tab

le 3

. Des

crip

tives

and

com

pari

son

of th

e tw

o gr

oups

on

qual

ity

of li

fe, a

fter

con

trol

ling

for

soci

odem

ogra

phic

s and

can

cer-

rela

ted

char

acte

rist

ics o

n w

hich

the

two

grou

ps d

iffer

ed si

gnifi

cant

ly

*N is

sligh

tly v

aria

ble b

ecau

se o

f miss

ing d

ata


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7

those recruited through the hospital group. Also, patients within the patient association were more alike than patients within the hospital database. These findings support the hypothesis that different recruitment sources identify populations with dissimilar patient characteristics. These results also strengthen the notion that recruitment through patient associations leads to the identification of a population with more specific characteristics than recruitment through hospital databases. We also compared the QoL of the two groups. Although we assumed that the two groups would differ in QoL, we did not hypothesize on the direction of this difference, as pu-blished literature on this topic contradicts [7-9]. The results of the present study show that members from the patient association reported a worse functioning on most of the QoL domains. However, this group also had larger variances in scores, which indicates that within the patient association the reports on QoL were more heterogeneous than in the hospital group. An explanation for the greater variety in QoL scores of the members of the patient association may lie in the motives of patients to become and remain a mem-ber of a patient association. People may become a member because they have problems adapting to the cancer experience and feel a need to receive psychosocial support from fellow cancer survivors [10;11]. After they have regained a satisfactory QoL, some remain a member of the patient association to give psychosocial support to new members [10]. This line of reasoning is supported by a study on correlates of participation in a breast cancer support group, that showed that new members reported higher levels of anxiety, depression and stress than established members [7]. The smaller variety in QoL scores in the hospital group may, in part, be the result of the 50% response rate. Considering the high mean scores of this group, it may be that those with a less favorable QoL were less willing to participate in our study. The second aim of the study was to investigate the impact of recruitment source on QoL. No considerable changes in QoL were found after controlling for the sociodemographic- and cancer-related variables on which the two groups differed significantly. The two groups still had unequal means and variances on the same subscales. This indicates that there must be other factors that affect the differences in QoL between the groups. It has been suggested that subjective perceptions, such as anxiety for a recurrence of a tumor, experience of higher impact of the illness on daily lives, and anxiety for the long-term consequences of treatment can influence levels of distress [19-22]. It would be plausible if patients who perceive more anxiety, distress, and a negative impact on daily living are more likely to become a member of a patient association [9]. As a matter of fact, cancer patients have indeed indicated that one of the reasons to become a member of a patient association was the experience of feelings of powerlessness in the situation and for their future lives [10].In conclusion, the results of this study support the notion that different recruitment sources identify different patient populations and that this has quite an impact on out-come variables. However, differences in sociodemographic and cancer-related characteris-tics appear not to determine the differences in QoL. Further empirical research is needed to investigate which other factors may explain the differing QoL scores. The results of this study do allow us to warn researchers to be careful with recruitment, because it may lead to selection bias that has consequences for the generalizability of the results. Findings of the present study are based on a QoL study but may be relevant for all research in which


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patients are recruited. At least, researchers should always present information about the recruitment strategies that they used, because it gives the reader the opportunity to value a study at its true worth [23]. If results are not generalizable it is not possible for the on-cologist to give solid advice to patients on relevant issues [24].


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Different recruitment methods identify different individuals

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