Table 2 Application of Wilson and Cleary model

Ade-Oshifogun 2012 USA

Obesity/Chronic Pulmonary Disease (COPD)

Cross sectional

BP: BMI, FEV1, DLCO, Percent trunk fat (DEXA)

SS: Dyspnoea (CRQ), fatigue (CRQ), sleep apnoea (ESS)

FS: 6-min walk distance (6MWD)

GHP: Functional Performance Inventory (FPI)

76

69.7

(10.3)

35.5%

To test a theoretically and empirically supported model of the relationship among clinical variables, symptoms, function status and health status of elderly people with COPD

Path analysis

● Function status, symptoms and biological variable DLCO have direct causal effect on health status

● DLCO ad dyspnoea predict functioning

● The effect of clinical variables on health status is mediated by symptoms

● Symptoms, function status and clinical variable indirectly influence health status

● Model explained 29% of the variance

● Clinical variables explain 29.6% of symptoms

● Clinical variables explained 50.5% of function status

Arnold 2005

Netherlands

1. Chronic Obstructive Pulmonary Disease (COPD)

2. Chronic Heart Failure (CHF)

Cross sectional

BP: COPD: FEV₁

VHF: LVEF

SS: Dyspnoea measured by a questionnaire

FS: Physical Functioning subscale of SF-36

GHP: General health subscale of SF-36

HRQL: Perceived health competence scale

COPD:95

CHF 90

65 (9.3)

59 (10)

35.8%

24.4%

To investigate relationship between objective and subjective health in patients with COPD and CHF

Structural equation model (SEM)

● Biological/physiological variables in both diseases are not significantly related to symptoms but predict physical functioning for COPD (β = 0.20) and CHF (β = 0.17)

● Symptoms predict physical functioning in COPD (β = 0.63) and in CHF (β = 0.67).

● Physical functioning associate with general health perceptions in COPD (β = 0.39) and CHF 9 β = 0.32)

● Symptoms directly associate with general health perceptions only in COPD

● In COPD, symptoms, physical functioning explain general health perception

● Only physical functioning explains general health perceptions in CHF

● Global HRQL explained by symptoms and general health perceptions in both diseases.

Baker 2007

UK

Xerostomia

Longitudinal

BP: Salivary flow

Clinical signs

SS: Xerostomia Inventory (XI)

FS: (OHIP-14)

GHP: Global oral health rating (GOH)

HRQL: (HADS)

85

59.8 (11.5)

76.5%

To systematically test Wilson and Cleary conceptual model of the direct and mediated pathways between clinical and non-clinical variables in relation to the oral health-related quality of life (OHRQoL) of patients with xerostomia.

Structural Equation Modelling (SEM)

● More severe clinical signs were associated with worse patient-reported symptoms

● More symptoms predicted a greater impact on everyday oral functioning

● Worse functioning predicted lower global oral health perceptions

● Both biological indicators and functioning predicted subjective well-being

● Function accounted for 96.9% of total effects

● 88.2% of total effect on functioning was mediated by symptoms status

● Symptoms 9%

● Functioning 22%

● GOH 24%

● Well-being 21%

Brunault 2014

France

Obesity

Cohort

BP: BMI

Type of Surgery

SS: BDI

Bulimic Investigatory Test, Edinburg (BITE)

FS: Quality of Life, Obesity and Dietetics (QOLOD)

-Physical QoL

-Psychological QoL

-Social QoL

-Sexual QoL

-Comfort with food

126

40.2 (10)

79.4%

To put the Wilson Cleary model to test by determining the predictors of postoperative change in each QoL dimension 12 months after bariatric surgery

Linear mixed model

● Improvement in Psychosocial QoL was associated with lower preoperative depression severity, lower preoperative binge eating severity and higher weight loss

● Improvement in Sexual QoL was associated with lower preoperative depression severity, lower preoperative binge eating severity and younger age

● Improved comfort with food was associated with lower preoperative binge eating severity

● ?

Carlson 2014

USA

Heart Failure

Cross-sectional

BP: Number of chronic illness

Comorbidity burden (CCI)as in index of severity of illness

Diagnosis of diabetes

Diagnosis of chronic atrial fibrillation

SS: Depression measure with PHQ-9

Physical symptoms measured with KCCQ

FS: Physical and social functioning measured with KCCQ

GHP: First item in the SF-36(v2)

265

62

35.8%

To determine the key predictors of overall perceived health (OPH)

Hierarchical multiple regression

● Age, gender and race/ethnicity were predictors of OPH

● Perceived sufficiency of income, social functioning, comorbid burden, symptom stability, black compared to white race were independent predictors of OPH

● Physical and social functioning mediated the effect of SOB and fatigue on OPH as well as the effect of symptom on OPH

● 39.2%

Cosby

2000

USA

HIV/AIDS

BP: CD4 counts

SS: Health distress, mental health, energy/fatigue and pain of Health Status Questionnaire (HSQ), SSC-HIV

FS: Physical, role, social and cognitive functioning of HSQ

GHP: QAM, General health perception of HSQ

HRQL: Overall quality of life of HSQ

146

To determine the relationships among haematological complications associated with AIDS, characteristics of the individual and the five dimensions of Wilson and Cleary model

Logistic regression

● All five dimensions of Wilson and Cleary model significantly predicted anaemia.

Eilayyan 2015

Canada

Asthma

Longitudinal

SS: Physical symptoms (MAQLQ-symptoms)

Emotional symptoms (MAQLQ-emotion)

Self-efficacy (KASE-AQ)

FS: Physical function (MAQLQ-activity)

299

62.1 (14.4)

69%

To identify direct and indirect predictors of perceived asthma control among primary care population.

Path model

● Symptom was affected by self-efficacy

● Emotional status was affected by symptom and self-efficacy

● Physical activity was affected through symptom, emotional status and self-efficacy

● Perceived asthma control at baseline was affected by asthma symptom, physical activity, self-efficacy and smoking

● Perceived asthma control at follow-up was predicted by asthma symptom, physical activity, self-efficacy and baseline perceived asthma control.

● Perceived asthma control was indirectly predicted by emotion status through self-efficacy and physical activity

Halvorsrud

2010 Norway

Chronic Disease

Cross- sectional

SS: Geriatric Depression Score (GDS-15)

FS: SF-12 subscale of physical function

GHP: Health satisfaction: global item measure from WHOQoL-Bref

HRQL: WHOQoL-Old

89

78.6

73%

To explore the predictors of QOL among community-dwelling older adults receiving community health care

Path analysis: Structural equation Modelling (SEM)

● Environment has direct effects on QOL and indirect effects on QOL with depressive symptoms and health satisfaction (GHP) as mediators

● Depressive symptoms had an indirect, negative effects on QOL with physical functions and general health perceptions as mediators

● Health satisfaction was a mediator between physical function and QOL

● The predictor variables accounted for 37% of the variance in depressive symptoms, 29% in physical function, 44% in general health perceptions and 66% of the variance in QOL (the overall model)

Heo 2005

USA

Heart failure

Baseline data

BP: Patient interview

Medical records,

CCI

SS: Patients perception of Presence and severity of dyspnoea and fatigue measured by Dyspnoea-Fatigue Index

Questionnaire

FS: NYHA

GHP: SF-36

HRQL: MLHFQ

293

73 (11)

53%

To determine the bivariate relationships between HRQL and other variables proposed by Wilson and Cleary

To determine best multivariate model based on these variables

To test specific components of the Wilson and Cleary model of HRQL

Multiple regression

● Health perception, symptom status and age predict HRQL

● Health perception mediates the effect of symptoms on HRQL

● Functional status does not mediate the effect of symptom status on health perception

● Final model explains 29% of the variance

Hofer 2005

Austria

Coronary Artery Disease (CAD)

Longitudinal

BP: Severity of CAD (no of diseased vessel

No. of risk factors

SS: Canadian Cardiovascular Society classification of angina pectoris

FS: SF-36 physical function score

GHP: SF-36 general health score

HRQL: Scores on the three scales (physical, social and emotional) of MacNew Heart Disease Quality of Life Questionnaire

432

61.8 (10.2)

24.1%

To apply Wilson and Cleary model a priori to patients with CAD in a prospective longitudinal design and to find out whether it is applicable to CAD patients and is stable over time.

Structural Equation Modelling (SEM)

● Physical functioning, anxiety symptoms have effect on overall HRQL

● Anxiety predicts poorer HRQL

● Depression affects physical functioning and general health perception.

● The higher the level of anxiety, the more severe the symptoms reported

● Final model explains 49% at baseline, 62% one month after and 66% 3 months after intervention of the variance of overall HRQL

Kanters 2012

Netherlands

Pompe disease

Cross-sectional

BP: Enzyme activity (fibroblasts) Skeletal muscle strength assessed by MRC, respiratory function assessed by FVC

SS: shortness of breath,

Fatigue assessed by Fatigue Severity Scale (FSS)

FS: Rotterdam Handicap Scale (RHS)

GHP: EQ-5D Visual Analogue Scale (EQ-5D-VAS)

HRQL: MCS and PCS of SF-36

Utility derived from EQ-5D

103

49.3

50.6%

To develop a conceptual model for Pompe disease in adults and statistically test it in untreated patients

Random effects linear regression

● MRC and FSS were negatively associated with disease duration

● FVC was affected by female gender

● RHS was affected by FSS, MRC, FVC and Age

● EQ-5D Vas was associated with RHS and disease duration

● MCS was associated with EQ-5D VAS

● PCS was associated with EQ-5D VAS

● Utility was associated with EQ-5D Vas

Krethong 2008

Thailand

Heart Failure

Cross- sectional

BP: Medical records-LVEF

SS: Cardiac Symptoms Survey (CSS)

FS: NYHA functional classification

GHP: 100 mm horizontal visual analogue scale

HRQL: MLFHQ

422

58.47

Ns

To develop and test a hypothesized causa model of HRQL in Thai heart-failure patients

Structural equation modelling (SEM)

● Biological/physiological affected functional status (β = −0.34, p < 0.05).

● Symptom affected functional status (β = 0.45, p < 0.05); GHP (β = −0.27, p < 0.05) and HRQL (β = −0.48, p < 0.05)

● Functional status had impact on GHP (β = −0.28, p < 0.05); HRQL (β = −0.25, p < 0.05)

● Social support had impact on symptom (β = −0.25, p < 0.05); GHP (β = 0.19, p < 0.05) and HRQL (β = −0.17, p < 0.05)

● The effect of biological/physiological on symptom was not significant.

Model explained 58% of the variance in overall HRQL

Mathisen 2007

Norway

Heart Surgery

Longitudinal

GHP: General Health subscale of SF-36

HRQL: Global Quality of Life (gQoL)

Norwegian version of the Quality of Life Survey (QoLS-N)

108

64.2

19%

To investigate the existence of a reciprocal relationship between patients’ assessment of quality of life and their appraisal of health.

Structural equation modelling (SEM)

● Baseline overall QoL has a cross lagged effect on three months assessment of general health

● The path from general health at six months to QoL at 12 months was significant

● The simultaneous effects model demonstrated a bidirectional causal paths at each point observed after baseline

Mayo 2015

Canada

Stroke

Cross-sectional

BP: Side of lesion

Stroke severity measured with CNS, CCI

SS: SIS

Pain: SF-36 (body pain)

Vitality: SF-36 (vitality)

Emotional well-being: SF-36 (mental health)

FS: Physical Functioning:

SF-36 (PF)

SIS (mobility)

Health Utility Inventory(HUI):

HUI (ambulation)

HUI (dexterity)

Social Functioning:

SF-36 (SF)

SIS 8b

Role:

Worst of SF-36 RE & RP

Cognitive: Mini mental State Education (MMSE)

GHP: EQ-5D VAS

SF-36 (General health)

678

67.3 (14.8)

45%

To empirically test a biopsychosocial conceptual model of HRQL for people recovering from stroke

Structural equation modelling (SEM)

● Less comorbidity, less pain, better memory and more vitality associated with better health perception.

Nokes 2011

USA

HIV/AIDS

Cross sectional

SS: Centre for Epidemiological Depression Scaled (CES-D)

Revised SSC-HIV

Body Change Distress Scale

HRQL: HAT-QOL

1217

41.7 (9.1)

31.5%

To determine if there were age-related differences in symptoms status and HRQL for HIV-positive persons aged 50 years and older compared with younger (aged 49 years and younger).

Stepwise regression

● Age was a predictor for sexual function and provider trust

● Less depressive symptoms and less body change distress were related to increase in sexual functioning

Phaladze 2005 Sub-Saharan Africa

HIV/AIDS

Cross sectional

BP: Has been given AIDS diagnosis

Has Comorbidities

SS: Revised SSC-HIV

FS: Overall functioning

GHP: Health worries

HRQL: HAT-QOL.

743

34.1 (9.6)

61.2%

To increase understanding of the meaning of quality of life for people living with HIV/AIDS in four countries in Sub-Saharan Africa: Botswana, Lesotho, South Africa and Swaziland.

Hierarchical multiple regression

● Daily functioning predicts overall HRQL

● Higher level of education associates with lower HRQL

● Higher symptom intensity associates with lower HRQL

● A close correlation between symptom intensity and functional status

● Overall model explains 53.2% of the variance

Portillo 2005

USA

HIV/AIDS

Cross sectional

BP: Has been given AIDS diagnosis

Has Comorbidities

SS: Revised SSC-HIV

FS: Overall functioning

GHP: Health worries

(HAT-QOL)

920

41 (8.7)

32.6%

To test the Wilson and Cleary model in a sample of ethnic minority persons living with HIV/AIDS

Hierarchical regression

Association between physiologic factors, symptoms, functioning, general health perception and life satisfaction

● Overall model explains 22.9%

Saengsiri 2014

Thailand

Coronary Artery Disease (CAD)

BP: LVEF

Rose Questionnaire for angina

Rose Dyspnea Scale (RDS)

SS: Centre for Epidemiologic Studies Depression Scale (CES-D)

Cardiac Self Efficacy Scale (C-SES)

FS: Functional Performance Inventory Short-Form (FPI-SF)

SF-36 Vitality subscale

HRQL: Quality of Life Index-Cardiac Version

303

61.2 (10.9)

26.4%

To explain relationship between cardiac self-efficacy, social support, biological and physiological (LVEF) symptoms of angina, dyspnoea, depression, vital exhaustion, functional performance and quality of life in post-PCI CAD patients

Pearson Correlation Path analysis

● Social support (β = 0.31), depression(β = 0.24), vital exhaustion (β = 0.23) and cardiac self-efficacy(β = 0.21) had the most powerful direct effect on quality of life of post-PCI CAD patients

● Self-efficacy had indirect effect on quality of life (β = 0.21, p < 0.001)

Santos 2015

Brazil

Oral health

Cross sectional

BP: Edentulism (dentate = 0, edentulous = 1) assessed by clinical examination

SS: Assessed using the question, “are you satisfied with the appearance of your prostheses?”

FS: Assessed with the question, “have you decreased or changed the type of food because of problems with your teeth or dental prostheses?”

GHP: Assessed using the question, “compared with others your age, how would you rate the health of your mouth overall?”

HRQL: OHIP-14

578

68 (6.3)

67.3%

To test the Wilson and Cleary model of the direct and mediated pathways between clinical and non-clinical variables in relation to oral health-related quality of life

Structural Equation Modelling (SEM)

● Dissatisfaction with symptom status are associated with worse functional status

● Worse functioning predicts poor oral health perception

● Poor oral health perception associates with higher worse oral health quality of life

● Final model shows negative significant direct effect between biological variable and symptom status

● Age, gender and geographical location have direct paths to biological variable (edentulism)

● Age and gender directly impact oral health-related quality of life

● The comparative fit index is 0.98 indicating adequate fit.

Schulz 2012

Netherlands

Kidney Transplant

Cross-sectional

BP: Number of active comorbidities reported by patients

FS: European Quality of Life −5 dimension (EQ-5D)

GHP: EQ-5D Visual Analogue Scale (EQ-5D-VAS)

HRQL: General Health Questionnaire (GHQ-12)

609

53.7 (12.3)

43.9%

To identify pathways through which objective health affects psychological distress and to clarify how personal characteristics are shaped by objective health and determine psychological distress

Structural equation modelling (SEM)

● Impact of objective health and functional status on psychological distress was fully mediated by subjective health and personal characteristics

● Influence of objective health was mediated by successively by functional status and personal characteristics; successively by functional status and subjective health; exclusively by personal characteristics and; exclusively by subjective health

The model explained 32% of variance of psychological distress

Shiu 2014

Hong Kong

Diabetes

Cross sectional

BP: Time since diagnosis

Age of onset and type of diabetes

HbA1c level, blood pressure and lipid profile

SS: Self-reported comorbidity characteristics and presence of comorbidity and no of comorbidities

FS: Physical functioning subscale of SF-36

Older American Resources and Services Multidimensional Functional Assessment Questionnaire

GHP: SF-36: general health

Self-developed ratings

6 HRQL: subscales of the SF-36: role-physical, role-emotional, mental health, social functioning, bodily pain and vitality

452

71.8 (7.3)

59.1%

To apply the Wilson and Cleary model of HRQL to understand the relationship among clinical and psychological outcomes in community-dwelling older Hong Kong Chinese people with diabetes.

Structural Equation Modelling (SEM)

● Four determinants: general health perception, psychological distress, adequacy of income and social support have direct effect on HRQL

● Three determinants: symptom status, physical functional status and psychological status have indirect effects on HRQL through general health perception

● Four determinants: symptom status, age, gender and physical activity have indirect effect on HRQL through physical function status

● The model explains between 64% and 72% of variance

Sousa 1999

USA

HIV/

AIDS

Cross- sectional

BP: APACHE III

SS: HIV-problem checklist

FS: HIV Quality Audit marker (QAM)

GHP: MOS-30 (single item for GHP)

HRQL: MOS-30 (single item for overall quality of life

142

38 (8.7)

20%

Multiple regression

● Symptoms correlated negatively with GHP (r = −0.48) and overall HRQL (r = −0.37). Functional status positively associated with GHP (r = 0.22) and overall HRQL (r = 0.29) Biological/physiological variables do not have significant associations either directly or indirectly on any of the variables.

●

Sousa 2006

USA

HIV/

AIDS

Cross- sectional

BP: CD4 Count

SS: SSC-HIV

FS: The Health Assessment Questionnaire-Disability Index (HAQ-DI)

GHP: 100 mm visual analogue scale

Ordinal scale

HRQL: Derived from general health status scales

917

30.4 (8.13)

43%

To estimate the primary pathways of the Wilson and Cleary HRQL conceptual model using structural equation modelling (SEM)

Structural equation modelling (SEM)

● A significant relationship between status and functional health (r = 0.56)

● There is significant relationship between symptoms status and general health perceptions (r = −0.33) and functional health and general health perceptions (r = −0.42)

● There is significant relationship between symptoms status and overall quality of life (r = −0.20) and between GHP and overall quality of life (r = 0.26)

CD4 count had a negative relationship with symptom status (r = − 0.20, p < 0.05)

● Symptoms explain 49% of functional health

● Both symptoms status and functional heath accounted for 62.5% of the variance of general health.

● Both symptoms status and general heath perceptions accounted for 38,2% of the variance in overall quality of life.

Ulvik 2008

Norway

Coronary Artery Disease (CAD)

Cross- sectional

BP: Myocardial disease

LVEF

SS: Angina (AFS, CCS)

Dyspnoea (NYHA)

Anxiety (HADS)

Depression (HADS)

FS: Physical function

Social function

GHP: General health (SF-36)

HRQL: Overall QoL: measured with a single question

753

61.7 (10.2)

26%

To analyse relationship between disease severity and both mental and physical dimensions of HRQL.

Linear and ordinal logistic regression

● Biological variables associate with symptoms

● Depression associates positively with LVEF

● Symptoms affect physical function

● Social function is low in patients with more symptoms of anxiety.

● General health is negatively related to anxiety and depression but positively related to physical and social functions

● Better overall QOL is associated with less symptoms and depression but related negatively to social function

● The model explains 43% of the variance of overall quality of life.

Wettergren

2004 Sweden

Hodgkin’s Lymphoma

Cross sectional

BP: Disease stage (I-IV)

Treatment modality (irradiation, chemotherapy or combined modality treatment

Time since diagnosis

SS: (SEQoL-DW)

HADS

FS: Measured as part of general health perceptions

GHP: PCS of Short Form 12 (SF-12),

MCS of SF-12

HRQL: QoL index of (SEQoL-DW)

121

45 (median)

45%

To evaluate HRQL in long-term survivors of |Hodgkin’s lymphoma (HL) and to identify determinants of HRQL using Wilson and Cleary’s conceptual model with the potential goal of improving care and rehabilitation.

Partial Correlations

● Disease stage correlated with Disease index (SEQoL-DW)

● Lower SOC was related to a worse HRQL

● Poorer physical health was associated with worse overall quality of life.

Wyrwich 2011 USA

General Anxiety Disorder (GAD)

Longitudinal

BP: CGI-S

SS: HAM-A

FS: PSQI

GHP: Q-LES-Q(SF) (items 1–14)

HRQL: Q-LES-Q(SF)) (Item 16)

1692

40.3 (11.8)

65.1%

To test the application of the Wilson-Cleary model to patient population with generalised anxiety disorder (GAD) using longitudinal clinical trial data.

Path Model

● CGI-S had a strong relationship with HAM-A

● HAM-A at week 8 had strong path (β = 0.5) to PSQI and moderate effect (β = −0.40) on Q-LES-Q(SF)

● Q-LES-Q(SF) had a strong relationship with overall quality of life (β = 0.66)

● Model explained 56% at baseline and 69% at week 8