Listening to patients’ needs to improve theirsubjective quality of life

ANTONIO LASALVIA* , CHIARA BONETTO, FRANCESCA MALCHIODI ,GIOVANNI SALVI , ALBERTO PARABIAGHI , MICHELE TANSELLA

AND MIRELLA RUGGERI

Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology,University of Verona, Verona, Italy

ABSTRACT

Background. Subjective quality of life has gained a crucial role as a global measure of outcome inmental health care. This study aimed to investigate the impact of meeting needs for care, as assessedby both patients and mental health professionals, to improve the subjective quality of life in asample of patients receiving community-based psychiatric care.

Method. The study was conducted using a 4-year prospective longitudinal design. A cohort ofpatients from the South-Verona Community-based Mental Health Service (CMHS) was assessed atbaseline and follow-up using, among other social and clinical measures, the CamberwellAssessment of Need (both staff and patient versions) and the Lancashire Quality of Life Profile.Predictors of changes of subjective quality of life were explored using block-stratified multipleregression procedures.

Results. Improvement in patients’ clinical conditions as well as the reduction in patient-rated unmetneeds in the social domain predicted an increase in subjective quality of life over 4 years ; changes instaff-rated needs did not show any association with changes in subjective quality of life.

Conclusions. Meeting self-perceived social needs, beyond symptoms reduction, seems to be ofparticular importance for ensuring a better quality of life for people with mental disorders. If themain goal of mental health care is to improve the quality of life of users, a policy of activelyaddressing patient-rated needs should be implemented.

INTRODUCTION

Over the last decade there has been a growingconsensus that mental health care should beprovided on the basis of patients’ needs, with theintended goal of improving their quality of life(QoL) (Thornicroft & Tansella, 1999; Priebeet al. 1999; Slade, 2002).

The relationship between needs and QoL forpeople with mental disorders has been inves-tigated in a number of studies. The UK700

(1999) has shown that subjective QoL in patientswith psychosis is more clearly associated withstaff-rated unmet needs in basic, social andfunctioning domains than with any otherclinical or social variable. Bengtsson-Tops &Hansson (1999) reported that higher levels ofpatient-rated social and basic needs were asso-ciated with a worse subjective QoL in patientswith schizophrenia. Similarly, Wiersma & vanBusschbach (2001) found that the most import-ant predictors of QoL in a sample of severelymentally ill patients were patient-rated unmetneeds, particularly in the area of health andsocial relations. More recently, a Nordic multi-site study on patients with schizophrenia(Hansson et al. 2003) showed that higher unmet

* Address for correspondence: Dr Antonio Lasalvia,Dipartimento di Medicina e Sanita Pubblica, Sezione di Psichiatria ePsicologia Clinica, Policlinico ‘G.B. Rossi ’, Piazzale L.A. Scuro, 10,37134 Verona, Italia.(Email : antonio.lasalvia@medicina.univr.it)

Psychological Medicine, 2005, 35, 1–11. f 2005 Cambridge University Pressdoi:10.1017/S0033291705005611 Printed in the United Kingdom

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patient-rated needs in the social domain wereassociated with a worse subjective QoL.

However, these studies have two majorlimitations: (1) the cross-sectional design, whichdid not allow for the provision of any infor-mation on the predictive value of needs on QoLover time; (2) the need assessment being per-formed according to just one single perspective.Regarding the latter, research (Slade et al. 1998;Lasalvia et al. 2000a ; Hansson et al. 2001) hasconsistently shown that professionals andservice users have different perceptions on needsfor care and that there is not a single correctperspective in need assessment: both staff’s andpatients’ views are necessary in order to provideneeds-led rational interventions and bothshould be taken into account when planningshared individualized care strategies (Thorni-croft & Slade, 2002; Simpson & House, 2003).Studies aiming to explore the relative contri-bution of both staff-rated and patient-ratedneeds on QoL (Slade et al. 1999; Ochoa et al.2003) found that the total number of unmetneeds was inversely associated with QoL, withthe association being more robust for patient-rated needs; however, they were conducted witha cross-sectional design.

Two studies conducted with a longitudinaldesign (Bjorkman & Hansson, 2002; Fakhouryet al. 2002) found that a decrease in the totalnumber of needs predicted QoL improvementover time. However, these studies did not dif-ferentiate between met and unmet needs, theydid not investigate the relative impact of bothclinician-rated and self-rated needs, neither didthey assess the impact of meeting needs inspecific need domains, and, moreover, the timeperiod consideredwas no longer than 18months.

The only study which combined a longitudi-nal design and the assessment of both staff’s andpatients’ perceptions of needs has been con-ducted in South-Verona (Slade et al. 2004) andprovided evidence that a high number of self-rated unmet needs predicts lower levels of sub-jective QoL at 1 year. However, this study didnot explore how changes in needs would impacton changes in subjective QoL over time, neitherdid it assess the effect of meeting needs inspecific need domains ; moreover, the study wasconducted on a cohort of regular service atten-ders and it did not assess at follow-up patientswho were no longer in contact with service.

In the present paper we aim, by using alongitudinal design, to explore the impact ofneeds, assessed according to the perspectivesof both staff and patients, on subjective QoL ofpeople with mental disorders.

Specifically, we hypothesized that in a sampleof patients with the full spectrum of psychiatricconditions receiving community-based mentalhealth care : (1) levels of subjective QoL at4 years are predicted by the baseline number ofpatient-rated unmet needs and, to a lesser extent,by staff-rated needs; (2) improvement in sub-jective QoL over 4 years is predicted by areduction in number of unmet self-rated needsrather than staff-rated needs; (3) specific re-duction of unmet needs in the social domainplays a major role in improving subjective QoLover 4 years.

METHOD

Setting

This study was conducted in the South-VeronaCommunity-based Mental Health Service(CMHS), the main agency providing psychiatriccare for the adult population in South-Verona(y100 000 inhabitants), which supplies a widerange of comprehensive and well-integratedprogrammes, including in-patient, day-care, re-habilitation, out-patient care, home visits, a24-hour emergency service, and residential facili-ties for long-term patients (Tansella et al. 1998).

Design

This is a naturalistic 4-year prospective longi-tudinal study, conducted within the context ofthe South-Verona Outcome Project (SVOP)(Ruggeri et al. 1998, 2001, 2004; Lasalvia etal. 2000a, 2002, 2004). The 3-month-treatedprevalence cohort attending the CMHS between1 October and 31 December 1996 was assessedat two time points, at baseline (T0) and at4 years (T1) : at follow-up, all patients werereassessed, including those no longer in contactwith the service. All patients were only inter-viewed after informed consent had been gained.Research staff explained the purpose of thestudy, gave full details to each patient in writingand made clear that participation was entirelyvoluntary; potential participants were told thatthey could chose whether to participate or not,or to participate and withdraw at a later time,

2 A. Lasalvia et al.

without any detriment to their clinical care.Confidentiality was fully preserved.

Measures

Needs for care were assessed using the Italianversion of the Camberwell Assessment of Needs(CAN) (Phelan et al. 1995; Ruggeri et al. 1999),an interview developed for the use of patients(CAN-P) and staff (CAN-S), which comprises22 items grouped into five conceptual domains:health (physical health, psychotic symptoms,drugs, alcohol, safety to self, safety to others,psychological distress), basic (accommodation,food, daytime activities), social (sexual ex-pression, social networks, intimate relationships),service (information, telephone, transport, ben-efits), and functioning (basic education, money,childcare, self-care, looking after the home).Each item is assessed on a 3-point scale [0=noproblem, 1=no/moderate problem because ofcontinuing interventions (met need), 2=currentserious problem (unmet need)].

Subjective QoL was measured by the Italianversion of the Lancashire Quality of Life Profile(LQoLP) (Oliver, 1991; Lasalvia et al. 2000b),which elicits subjective QoL appraisal in ninelife domains: general well-being, work/education,leisure, finances, living situation, legal/safety,family relations, social relations and health.Subjective satisfaction ratings in each domainare reported on a 7-point Likert scale, rangingfrom 1 (‘my life could not be worse ’) to 7 (‘mylife could not be better ’). The life satisfactionscores for each domain can be reported individ-ually or combined into a total mean QoL score.

Other measures included the Italian versionsof the Brief Psychiatric Rating Scale (BPRS)‘expanded version’ (Ventura et al. 1993;Roncone et al. 1999) for psychopathology, theDisability Assessment Schedule (DAS) (WHO,1988; Ruggeri & Nicolaou, 2000) for the dis-ability in social roles, and the Global As-sessment of Functioning (GAF) (APA, 1994)for global functioning.

Sociodemographic, service utilization and di-agnostic data were extracted from the South-Verona Psychiatric Case Register (PCR)(Tansella et al. 1998).

Statistical analyses

To explore the effect of needs on QoL, weperformed a series of multiple block-stratified

regression analyses (Ruggeri et al. 2001) withfollow-up total and subscores in the various lifedomains as dependent variables and levels ofmet and unmet needs in the five need domainsmeasured at baseline as predictors. Separatemodels, including in turn, number of needs asperceived by patients and by clinical staff, wereperformed. The number of met and unmet needswithin each area were pro-rated with referenceto the number of items pertaining to the areaitself (for example, a patient with two met needsin the health area would have an adjusted scoreof 2/7=0.29). In order to control for socio-demographic characteristics (gender, age,marital status, living condition, educationallevel, employment status), illness related vari-ables (psychotic and length of illness), clinicalassessments (GAF, BPRS, DAS) and serviceutilization (number of admissions, out-patientcontacts, day-care contacts, community careinterventions), these variables were enteredinto the first four blocks in all multiple block-stratified regression models.

Subsequently, in order to investigate therelationship between changes over 4 years inmet and unmet needs for care in the five needdomains and changes in subjective QoL dimen-sions during the follow-up period, a series ofmultiple block-stratified regression analyses,using changes in QoL scores as dependent vari-ables and changes in met and unmet needs forcare as predictors, were performed. Due to alack of significant correlations (Pearson co-efficient, p<0.05) between changes in QoLdomains and changes inmet and unmet needs forcare as perceived by staff, only models includingneeds as perceived by patients were estimated.

In order to control for sociodemographiccharacteristics at baseline (gender, age, maritalstatus, living condition, educational level,employment status), illness-related variables atbaseline (psychotic and length of illness), chan-ges in clinical assessments (DGAF, DBPRS,DDAS) and changes in service utilization(D number of admissions, D out-patient con-tacts, D day-care contacts, D community careinterventions), these variables were enteredinto the first four blocks in all multiple block-stratified regression models.

For the regression analyses, we used residualchange scores to obtain change measures un-correlated with baseline status ; residual change

Needs and quality of life 3

scores were assessed by estimating the standard-ized residuals obtained in the regression of thefollow-up level on baseline status: they are in-tended to describe the change that each patientwould have experienced if everyone had ‘startedout equal ’.

The statistical software used was SPSS 11.5for Windows (SPSS Inc., Chicago, IL, USA).

RESULTS

Characteristics of the cohort

At baseline, 251 patients completed the entireset of instruments. At 4 years, 10 patients fromthe baseline cohort had died, one was excludeddue to development of severe cognitive impair-ment. Of the 240 patients eligible, 14 could notbe located and 188 (78%) completed bothclinical evaluations (BPRS, GAF and DAS) andself-rated measures (LQoLP and CAN-P) atfollow-up; this cohort included both subjects incontact (n=110) and not in contact (n=78)with the service. Sociodemographic, serviceutilization and diagnostic characteristics of thecohort are reported in Table 1.

For all the patients still in contact with theservice (n=110) after 4 years the CAN-Sconcerning the follow-up period was also com-pleted. As expected, this subgroup of patientsdiffered from the whole cohort (n=188) withregard to most illness-related and clinicalvariables measured at baseline : they were older(46.03 v. 41.70 years), more often psychotic(82.4% v. 44.5%), with higher levels ofpsychopathology (1.57 v. 1.38) and disability(0.80 v. 0.29), and lower levels of functioning(56.00 v. 64.96) (Pearson, x2 andMann–WhitneyU test, where appropriate, p<0.05).

Baseline levels of needs as predictors of levelsof subjective QoL at follow-up

In order to explore the longitudinal associationsbetween needs and QoL, we first assessed theimpact of both patient-rated and staff-ratedneeds measured at baseline on levels of QoL atfollow-up (see Table 2).

Controlling for sociodemographic, clinicalseverity and service utilization variables atbaseline, patient-rated needs andQoL showed aninverse relationship, with higher levels of needsat baseline predicting poorer subjective QoL atfollow-up: specifically, levels of patient-rated

met needs accounted for a fraction of varianceranging from 1.7% to 4.9%, while patient-ratedunmet needs were the best predictors, account-ing for up to 10.5% of the variance in the

Table 1. Sociodemographic, service utilizationand clinical characteristics of the study cohort atbaseline (n=188)

Gender, n (%)Female 120 (63.8)

Marital status, n (%)Single, widowed, divorced, separated 103 (54.8)Married 85 (45.2)

Age, years [mean (S.D.)] 44.23 (14.40)

Education, n (%)Elementary/junior high school/without a degree 136 (72.3)Secondary school/university degree 52 (27.7)

Working status, n (%)Employed 68 (36.2)Unemployed 34 (18.1)Housewife, student, retired, seek for job, other 86 (45.7)

Living condition, n (%)Alone 27 (14.4)With family or relatives 156 (83.0)Hospital, hostel, community 5 (2.7)

Service utilization, previous yearPatients with any admission to hospital, n (%) 31 (16.5)Patients with any admission to shelteredapartments, n (%)

2 (1.1)

Patients with any day-care contacts, n (%) 51 (27.1)Patients with any out-patient contacts, n (%) 186 (98.2)Patients with any community carecontacts, n (%)

38 (20.2)

Time since first contact with our service,years [mean (S.D.)]

5.12 (5.93)

Diagnostic group, n (%)PsychoticSchizophrenia and other functional psychosisa 51 (27.1)Affective psychosisb 16 (8.5)

Non-psychoticDepressive neurosisc 61 (32.4)Other neurosisd 30 (16.0)Personality disorderse 10 (5.3)Other 20 (10.6)

BPRS total [mean (S.D.)] (1=no symptom;7=very severe symptom)

1.49 (0.45)

GAF total [mean (S.D.)] (0=very severedysfunction; 90=very good functioning)

59.72 (15.27)

DAS total [mean (S.D.)] (0=no disability,5=maximum disability)

0.59 (0.92)

BPRS, Brief Psychiatric Rating Scale ; GAF, Global Assessmentof Functioning; DAS, Disability Assessment Schedule.

a Includes the following ICD-10 diagnoses : F20, F21, F22, F23,F24, F25, F28, F84.

b Includes the following ICD-10 diagnoses: F30, F31, F32.2,F33.3.

c Includes the following ICD-10 diagnoses : F32 (.0, .1, .2, .8, .9),F33 (.0, .1, .2, .9), F43.1, F41.2, F43 (.20, .21, .22).

d Includes the following ICD-10 diagnoses : F40, F41 (.0, .1, .3, .8,.9), F42, F44, F45, F48, F54.

e Includes the following ICD-10 diagnoses : F34, F52, F60, F61,F62, F63, F64, F65, F66, F68, F69.

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Table 2. Predictors of levels in subjective QoL at 4 years, with baseline levels of patient-rated (n=188) and staff-rated (n=110) needsamong independent variables. Multiple block-stratified regression models : estimated b coefficients and adjusted R squares are reported.Only variables with significant coefficients are reported ; non-significant values indicate that those variables significantly improve theadjusted R square of the previous blocks, but lost their significance when variables from the further blocks were added

Baseline variables

Quality of life at follow-up

Globalwell-being Work Leisure Finance

Livingsituation Legal/safety

Familyrelations

Socialrelations Health Total QoL

Patient Staff Patient Staff Patient Staff Patient Staff Patient Staff Patient Staff Patient Staff Patient Staff Patient Staff Patient Staff

Sociodemographics at BLBeing female x0.174a x0.263a x0.139b x0.299a x0.198b x0.137b x0.232a x0.276a

Being married 0.070c 0.106c 0.171a 0.150b 0.128c 0.110c

Being unemployed x0.300a x0.297a x0.177a x0.186b

% variance explained 5.1% 5.2% 7.0% 7.9% 4.0% 3.9% 4.3% 2.3% 3.2% 9.3% 7.6% 3.4% 4.0%

Clinical variables at BLGAF score 0.193a 0.192b 0.185a x0.105c 0.256a 0.119c 0.180a

BPRS mean score x0.142b x0.088c x0.069c x0.025c

DAS mean score x0.032c x0.108c

% variance explained 3.9% 2.8% 6.0% 3.9% 2.3% 2.9% 3.8% 3.0% 1.8% 10.9% 7.6% 5.8% 5.4%

Service utilization at BLAdmissions x0.150b

Out-patient contacts x0.188a x0.214b

Day-care contacts x0.078c x0.201a x0.231b x0.122c

Community care x0.173b x0.218b x0.227a x0.219b

% variance explained 1.8% 3.2% 3.7% 2.3% 2.9% 4.0% 7.1% 3.0% 4.5% 1.6% 2.4%

Met needs at BLCAN met basic x0.138b — x0.145b x0.154b 0.224b

CAN met service x0.181a — x0.142b — x0.169a

% variance explained 3.4% 4.9% 1.7% 2.4% 4.1% 2.2% 3.1%

Unmet needs at BLCAN unmet health x0.213a — — x0.227b x0.189a x0.276a x0.218a x0.267a x0.254a x0.247a x0.341a x0.234a x0.261a

CAN unmet social x0.273a — x0.258a — x0.327a x0.206b x0.188a

CAN unmet basic x0.287a x0.219b

% variance explained 7.1% 4.0% 6.1% 3.0% 3.0% 7.1% 5.9% 4.2% 6.5% 5.4% 10.5% 3.4% 5.6% 7.9% 12.7% 8.0%

% total varianceexplained

19.5% 8.0% 11.0% 7.9% 18.8% 6.9% 14.2% 6.6% 17.2% 13.2% 6.5% 7.0% 14.6% 15.7% 25.0% 15.5% 18.1% 15.5% 27.4% 17.4%

BL, Baseline ; FU, follow-up; GAF, Global Assessment of Functioning; BPRS, Brief Psychiatric Rating Scale ; DAS, Disability Assessment Schedule ; CAN, Camberwell Assessment ofNeeds.

a p<0.01; b p<0.05; c N.S.

Need

sandquality

oflife

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various life dimensions. Unmet needs in healthand social domains showed a relevant impact onall life dimensions, particularly on global well-being, leisure, living situation, social relationsand total QoL.

The models including staff-rated needs weredifferent with respect to the models which in-cluded self-rated needs, with unmet needs ratherthan met needs as predictors and percentagesof variance explained generally lower (rangingfrom 3.0% to 7.9%). With regard to the effecton the various life dimensions, higher levels ofstaff-rated unmet needs predicted poorer QoL inliving situation, family relations, health andtotal QoL, while higher levels of staff-rated metneeds in basic domain predicted higher lifesatisfaction for legal/safety.

Changes of needs as predictors of changes insubjective QoL

The effect of changes of needs for care onchanges in QoL over a 4-year period constitutesthe main focus of this paper.

We first assessed whether, and to what extent,needs and QoL showed any changes over thefollow-up period. Changes in the number ofstaff-rated and self-rated needs were assessed atthe cohort level by comparing, respectively,CAN-P and CAN-S mean values in the variousneed domains at T0 and T1 (Wilcoxon test,p<0.05). Changes in staff-rated and self-ratedneeds at the individual patient level were assessedby exploring the percentage of baseline needswhich changed their status (i.e. ‘absent ’, ‘met ’,‘unmet’) at follow-up. Table 3 (upper part)shows the changes in patient-rated needs(n=188) over the follow-up period in each CANdomain.

At the cohort level, the majority of needs didnot change over time; only the mean number ofunmet health and met social needs decreasedsignificantly. At the individual patient level,when needs were absent at baseline they tend toremain absent at follow-up; when they werepresent at baseline (whether met or unmet), aclear general trend towards improvement wasdetected at follow-up suggesting that treatmentaiming to enhance patients’ autonomy had beenprovided in the interim (in fact, the highestproportions of baseline needs – either met orunmet – showed the tendency to become ‘noneed’ at follow-up).

The lower part of Table 3 reports the changesin staff-rated needs (n=110) over the follow-upperiod, showing at the cohort level only a sig-nificant reduction in the mean number of metneeds in the health domain. At the individualpatient level, a trend towards improvement inneed status at follow-up was detected, sincemost needs present at baseline were met orabsent at follow-up.

Changes in subjective QoL were assessed bycomparing the mean scores reported in LQoLPdomains at T0 and T1 (Wilcoxon test, p<0.05).An overall improvement in subjective QoL wasdetected over time, reaching statistical signifi-cance in the total mean score [4.6 (S.D.=1.1) v.4.7 (S.D.=0.8) ; p<0.052] and some specific lifedomains, such as global well-being [4.1(S.D.=1.4) v. 4.5 (S.D.=1.2)], work [4.1 (S.D.=1.7) v. 4.4 (S.D.=1.5)] and health [4.6 (S.D.=1.1)v. 4.7 (S.D.=0.9)].

In order to investigate the relationship be-tween changes in patient-rated met and unmetneeds and changes in subjective QoL during thefollow-up period, a series of block-stratifiedregression models with residual change scores insubjective QoL as dependent variables, and re-sidual change scores in met and unmet needs asperceived by patients among the independentvariables, were performed. The confounderswere sociodemographic and illness-relatedvariables at baseline, residual change scoresof clinical variables and service utilizationindicators (Table 4).

Accounting for the effect of confounders,changes in self-rated unmet needs gave a furthersignificant contribution to the variance ex-plained by the various models : in fact, a greaterimprovement in QoL was predicted by a greaterreduction in patient-rated unmet needs, withfractions of variance explained ranging from2.1% to 6.2%, whereas the global effect of metneeds on changes in QoL was negligible. Withregard to the specific effect of need domains onthe various life dimensions, social needs playeda major role, having a significant impact ongeneral well-being, leisure activities, family andsocial relations and total QoL, with basicneeds showing an impact on work and leisureactivities, and health needs on satisfaction withhealth. A reduction in met social needs pre-dicted an amelioration in satisfaction withhealth, with 2.2% of variance explained.

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Among the confounders, being psychoticpredicted a lower increase in overall QoL and insome life domains, such as global well-being,finance, social relations and health; improve-ments in global functioning and psychopatho-logy predicted an increase in QoL in all lifedomains and were the strongest predictors, withfractions of variance explained ranging from3.8% (family relations) to 13% (health).

The percentage of variance explained by thetotal models ranged from 6.2% to 24.8%.

If the reduction in self-rated needs was foundto be a predictor of improvement in QoL over 4

years, by applying the same procedure (multipleblock-stratified regressions analyses) we couldnot find any significant effect of changes in staff-rated needs on changes in QoL due to a lack ofsignificant correlations (Pearson coefficient,p<0.05) between changes in QoL domains andchanges in met and unmet needs for care asperceived by staff.

DISCUSSION

This study aimed to determine whether, andto what extent, provision of mental heath care

Table 3. Changes in needs for care over the 4-year follow-up period according to patients (n=188 ;upper part) and staff perception (n=110 ; lower part). Significant differences between means at baselineand follow-up are reported in bold (Wilcoxon test ; p<0.05)

Health Basic Social Service Functioning

Patient-rated needsMet needsMean (S.D.) BL 0.83 (0.85) 0.33 (0.64) 0.31 (0.63) 0.19 (0.45) 0.35 (0.62)Mean (S.D.) FU 0.85 (0.85) 0.32 (0.65) 0.19 (0.46) 0.22 (0.47) 0.38 (0.77)

Unmet needsMean (S.D.) BL 0.51 (0.95) 0.13 (0.46) 0.43 (0.84) 0.16 (0.45) 0.10 (0.43)Mean (S.D.) FU 0.36 (0.66) 0.14 (0.39) 0.44 (0.73) 0.20 (0.44) 0.11 (0.39)

Needs absent at BL (%)Still absent at FU 78.2 89.5 82.2 91.9 92.1Met at FU 7.6 7.4 4.6 4.0 5.8Unmet at FU 2.4 3.2 8.9 3.8 1.7

Needs met at BL (%)Absent at FU 51.3 56.4 56.7 76.9 54.5Still met at FU 32.1 30.6 15.0 12.8 37.9Unmet at FU 16.0 12.9 28.3 10.3 7.6

Needs unmet at BL (%)Absent at FU 55.9 64.0 48.1 45.2 61.9Met at FU 30.1 24.0 9.1 29.0 23.8Still unmet at FU 14.0 12.0 36.4 25.8 14.3

Staff-rated needsMet needsMean (S.D.) BL 1.53 (0.96) 0.43 (0.72) 0.42 (0.66) 0.22 (0.54) 0.49 (0.87)Mean (S.D.) FU 1.25 (1.01) 0.55 (0.94) 0.46 (0.79) 0.25 (0.53) 0.63 (0.93)

Unmet needsMean (S.D.) BL 0.25 (0.53) 0.21 (0.54) 0.49 (0.88) 0.05 (0.25) 0.07 (0.29)Mean (S.D.) FU 0.33 (0.67) 0.13 (0.36) 0.38 (0.74) 0.11 (0.39) 0.13 (0.41)

Needs absent at BL (%)Still absent at FU 90.2 86.2 73.1 91.1 86.4Met at FU 6.6 10.0 10.5 6.0 9.2Unmet at FU 2.4 3.5 7.0 2.7 3.2

Needs met at BL (%)Absent at FU 37.9 51.1 12.7 87.5 50.9Still met at FU 50.0 44.7 13.6 12.5 47.4Unmet at FU 11.4 4.3 6.8 0.0 0.0

Needs unmet at BL (%)Absent at FU 36.7 30.4 35.3 66.7 50.0Met at FU 53.3 56.5 27.5 0.0 37.5Still unmet at FU 10.0 13.0 31.4 33.3 12.5

BL, Baseline ; FU, follow-up.

Needs and quality of life 7

Table 4. Predictors of changes in subjective QoL over the 4-year follow-up period, with changes in patient-rated needs among independentvariables (n=188). Multiple block-stratified regression models : estimated b coefficients and adjusted R squares are reported. Only vari-ables with significant coefficients are reported ; non-significant values indicate that those variables significantly improve the adjusted Rsquare of the previous blocks, but lost their significance when variables from the further blocks were added

D quality of life during FU period

Globalwell-being Work Leisure Finance

Livingsituation Legal/safety

Familyrelations

Socialrelations Health Total QoL

Sociodemographics at BLBeing female x0.176a (1.7%)Being married x0.190a (2.5%)Being unemployed x0.205a (3.1%) x0.203a (4.1%)

Illness-related variables at BLBeing psychotic x0.142b (2.8%) x0.190a (4.4%) x0.177a (4.0%) x0.239a (6.7%) x0.203a (4.8%)

Changes in clinical variablesduring FU periodDGAF score +0.191a (4.5%) +0.081c (1.8%) +0.154b (4.3%) +0.263a (6.3%)DBPRS mean score x0.311a (7.0%) x0.493a (10.4%) x0.188a (3.8%) x0.294a (9.4%) x0.318a (13.0%) x0.365a (12.3%)DDAS mean score +0.293a (5.6%)

Changes in service utilizationduring FU periodDDay-care contacts +0.175b (2.4%) +0.148b (1.7%)

Changes in patient-ratedmet needsduring FU periodDCAN met social x0.179a (2.2%)

Changes in patient-ratedunmet needs during FU periodDCAN unmet health x0.184a (2.9%)DCAN unmet basic x0.269a (6.2%) x0.159b (1.8%)DCAN unmet social x0.256a (6.1%) x0.167b (3.4%) x0.172b (2.4%) x0.162b (2.1%) x0.189a (3.2%)

% total variance explained 15.1% 11.1% 9.5% 10.7% 9.4% 18.5% 6.2% 19.6% 24.8% 22.0%

D, Residual change scores ; BL, baseline ; FU, follow-up; GAF, Global Assessment of Functioning; BPRS, Brief Psychiatric Rating Scale ; DAS, Disability Assessment Schedule ; CAN,Camberwell Assessment of Needs.

a p<0.01, b p<0.05, c N.S.

8A.Lasalvia

etal.

targeted at meeting specific needs in a sample ofpatients with the full spectrum of mental dis-orders would change their levels of perceivedQoL over 4 years. The research also explored therelative weight of patient-rated and staff-ratedneeds in predicting changes in subjective QoL.

This research has several advantages overprevious studies: (1) the longitudinal design; (2)the long time period considered; (3) the needsassessment performed according to the views ofboth staff and patients ; (4) the use of routineoutcome data, (5) a series of specific hypothesesset a priori based on the analysis of the existingliterature.

This research has also some limitations: (1)the study was conducted with a naturalisticdesign, and it was not possible to disentanglewhich specific components of care provided hadmore weight in reducing needs: with this regard,the present research should be considered ahypothesis-generating study for future testingthrough specific intervention studies; (2) havingneeds for care and QoL assessed at the sametime intervals, the study could not establish acausal relation between their mutual change; (3)this is a prevalence cohort composed of bothlong-term patients and patients at their initialcontact with the service, receiving differing typesof intervention according to the specific phase oftheir illness.

Nevertheless, the present study is the firstattempt to clarify, through the provision of a‘dynamic’ picture, the complex relationshipsbetween needs for care and QoL in patients withthe full spectrum of mental disorders occurringin a routine clinical service. In this respect, theSouth-Verona CMHS, due to its general organ-ization and principles of intervention, seems tobe a particularly suitable setting for testing thestudy hypotheses : in fact, (1) the service aims toprovide prompt, adequate and coherent re-sponses to patients’ needs, practical as well aspsychological and social, while trying to alleviateand control their symptoms, (2) over the years,the service has acquired considerable resourcesand facilities to meet such needs, and (3) theevaluation of users’ needs is routinely performed.

Subjective QoL life at 4 years is predicted bythe baseline number of self-rated unmet needs

Based on the previous literature (Slade et al.1999; Wiersma & van Busschbach, 2001; Ochoa

et al. 2003), we hypothesized that levels of sub-jective QoL in psychiatric patients receivingcommunity care are predicted by the number ofself-rated unmet needs measured at baseline.Results of our multivariate analyses confirmedthis hypothesis, since poor subjective QoL at 4years is predicted by a higher number of patient-rated unmet needs at baseline; the impact ofpatient-rated needs appears to be more robustthan staff-rated needs, which only explained alimited fraction of the total variance. The needdomains showing the more significant effect onglobal QoL and on the various life domainswere related to health and social relations.

The finding that self-rated needs have asignificant impact on subjective QoL has beeninterpreted by some authors by the hypothesisthey may reflect the same underlying ‘subjec-tive appraisal ’ construct (Priebe et al. 1998;Fakhoury et al. 2002). They certainly have, as acommon basis, the subjective perspective ofeither the user or the staff. However, it shouldbe noted that correlation coefficients betweenneeds and QoL domains are low and thatmultivariate analyses conducted in our studyfound that patient-rated needs explain, bothcross-sectionally and longitudinally, differingpercentages of QoL variance depending on thesubdomains.

Improvement in QoL over 4 years is predictedby a reduction in the number of self-rated unmetneeds over the same period

The main hypothesis of the study – i.e. a re-duction in the number of self-rated unmet needswould predict a higher subjective QoL over4 years – has been confirmed by our findings.Patient-rated, rather than staff-rated needs,seem to play a major role in predicting subjec-tive QoL: in fact, improvement in QoL wasdetermined by a reduction of self-rated needs,whereas staff-rated needs showed no impact.This supports the view that if a goal of mentalhealth care is to improve the QoL of patients,then a policy of actively assessing and address-ing patient-rated needs should be considered: inother words, the patients’ assessment of theirneeds should have more influence in informingthe planning and provision of mental healthcare (Thornicroft & Tansella, 2005). This is amajor challenge for mental health services, sincethe traditional paternalistic approach to making

Needs and quality of life 9

decisions about treatment has been questionedby doctors, patients, medical ethicists andresearchers (Coulter, 1999; Charles et al. 1999;Tarrier & Barrowclough, 2003), who advocate amore modern and effective ‘shared model ’ or‘partnership model ’ between health profes-sionals and service users, based on mutualrespect for each others’ skills and competenciesand recognition of the advantages of combiningthese resources to achieve beneficial outcomes.

Predictors of subjective QoL in people withmental disorders, however, are complex, as hasbeen found in other specific research conductedby our group (Ruggeri et al. 2001, 2002, 2003).In the present study, multivariate analysesshowed that the reduction of self-rated needsexplained a limited fraction of total variance,suggesting that a change in needs gives only apartial contribution to the prediction of changesin QoL over 4 years. In fact, clinical variablesseem to play an important role in predictingQoL over time: reduction in symptom severityand amelioration of global functioning have thegreatest effects on the QoL of psychiatricpatients ; in addition, other clinical variablessuch as diagnosis, may also be relevant, since theQoL of people with non-psychotic disordersshows a greater tendency towards improvementover time than for patients with psychosis.

Reduction of unmet needs in the social domainplays a major role in improving QoL

Based on previous literature (UK700, 1999;Bengtsson-Tops & Hansson, 1999; Wiersma &van Busschbach, 2001; Hansson et al. 2003), wehypothesized that meeting needs in the socialdomain would specifically impact on changes inQoL over time. Our findings support this hypo-thesis, since a reduction in self-rated unmetsocial needs predicted an increase of overallQoL and life satisfaction in some specific lifedomains, such as general-well being, leisureactivities, family and social relations. However,the reduction in basic needs also had a specificimpact on some life domains such as work andleisure activities, and a reduction in unmethealth needs predicted an increase of satisfactionwith life in the health domain.

This suggests that particular attention shouldbe paid by mental health services in meetingneeds in the social (i.e. by providing interven-tions aiming to broaden patients’ social network

and improve sexual and emotional relationshipswith partners) and basic domains (i.e. by pro-viding interventions related to every-day life,such as supported housing, meal provision andday-time activities).

CONCLUSION

Improving the QoL of people with mental dis-orders is considered, besides symptoms control,a priority for mental health care; in this contexta policy of addressing patients’ self-perceivedneeds and actively involving service users in theprocess of care and should be considered andimplemented. This would contribute to improvecommunication between staff and patients andconstitute the first step of a process leading to abetter reciprocal understanding and to the im-plementation of a ‘partnership model ’ betweenhealth professionals and service users. However,the complex relationship between needs for careand subjective QoL in persons receiving com-munity mental health care warrants furtherinvestigation through randomized clinical trialswhich test the effect of treatments strategiesspecifically designed to meet patients’ self-ratedneeds.

ACKNOWLEDGEMENTS

We are grateful to the patients who participatedin the follow-up study and to the staff of theSouth-Verona Community Psychiatric Servicefor their kind collaboration in the project. Wethank Liliana Allevi, Rosa Dall’Agnola,Antonella Miletti, Paola Ognibene andBenedetta Stefani for their contribution in thedata collection. We also thank Dr Julia Jonesfor helping to revise earlier versions of themanuscript. This study was supported by a grantof Ministero dell’Istruzione, dell’Universita edella Ricerca Scientifica (MIUR), Roma (fondi60%) to Professor Mirella Ruggeri.

DECLARATION OF INTEREST

None.

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