A primary care based cross-sectional study will be conducted to investigate HRQoL in adult patients with chronic diseases in Flanders (Belgium).

To achieve the research aims, multiple linear regression models will be conducted assessing several key predictors associated to HRQoL as primary outcome. The regression models should allow for controlling the effect of main confounders (e.g., sex, age, educational attainment), and for including interaction terms with psychosocial variables. A sample size calculation showed that the minimum required sample for a multiple regression study including 10 predictors with a medium anticipated effect size was 118, given a desired statistical power level of 80% and a probability level of 5%. The sample size was increased with 50% to allow for testing interaction effects. This study has three clusters of disease groups (cardiovascular disorders, mental disorders, and musculoskeletal disorders), therefore stratified analyses require a triple sample size. Hence, an a priori sample size of minimum 531 participants is targeted. This sample size will also widely cover analyzing clinically relevant differences between a number of chronic disease subgroups. Based on the conclusions of a systematic review by Norman et al. (2003), the clinically relevant difference will be set at a half standard deviation which appears to be the threshold of discrimination for changes in HRQoL for NCDs. Using a statistical power level of 80% and a probability level of 5%, information on 76 patients per disease cluster is needed 1) to assess the HRQoL (based on SF-36) in each patients group with a 5% precision and 2) to allow for comparisons across groups.

Patient recruitment will be organized through general practitioners (GP) and community health centers across Flanders (Belgium). First, a number of GP practices located across urban and rural regions willing to participate in this study will be identified through a convenience sample based on their contact with a LOK group (Local Quality Group). This is a group of colleagues, doctors or pharmacists-biologists, who share and critically assess their medical practices (peer review) in order to improve the quality of care. GPs willingness to cooperate in the study will be asked at the LOK group meeting. In this meeting, the researchers will briefly present the study. Afterwards, interested GPs will be visited by the researchers at their practice with more detailed information about the study and they will receive the paper questionnaires. GPs will be asked to identify patients within their practice after validation of the eligibility criteria. GPs will explain briefly the purposes of the study to the patients and invite them to participate through voluntary response sample.

A paper-based questionnaire, including informed consent, will be distributed to the participant by the GP at consultation. The questionnaire will be filled in by the patient at home. Afterwards, the patient can return the questionnaire to the researchers for free via a prepaid envelope or the questionnaire can be given back to the GP at later consultation. The questionnaire will take 30 minutes to gather patient information and research outcomes. The GPs will receive in advance detailed information by the researcher to ensure the aim of the study and the data collection process are understood. Due to practical restrictions, home visits for fulfilling the questionnaires was not achievable in this study.

Descriptive statistics will be reported in order to describe the sample of the study participants. Means, standard deviations, median, and percentages for the continuous variables and frequency tables for categorical variables will be displayed. Socio-demographic differences between study participants will be tested with the appropriate test.

Exploratory data analysis will be performed both for the continuous variables as well as the categorical variables. T-tests and one-way analysis of variance will be reported to compare groups when normal distribution is applicable. Non-parametric tests will be used when variables are not normally distributed. A p-value of 0.05 will be considered as statistically significant. Furthermore, multiple linear regression models will be conducted assessing several main determinants, such as multimorbidity and SES, associated to HRQoL as main outcome parameter. Furthermore, the study results will be validated against the HRQoL data collected in the Health Interview Survey with the aim to predict future HRQoL burden.