Registry-based analysis of participator representativeness: a source of concern for sickness absence research?

Abstract

ObjectivesSelective participation can bias results in epidemiological surveys. The importance of health status is often suggested as a possible explanation for non-participation but few empirical studies exist. In a population-based study, explicitly focused on sickness absence, health and work, we examined whether a history of high levels of sickness absence was associated with non-participation.DesignThe study is based on data from official sickness absence registers from participants, non-participants and the total target population of the baseline survey of the Health Assets Project (HAP).SettingHAP is a population-based cohort study in the Västra Götaland region in South Western Sweden.ParticipantsHAP included a random population cohort (n=7984) and 2 cohorts with recent sickness absence (employees (n=6140) and non-employees (n=990)), extracted from the same overall general working-age population.Primary outcome measuresWe examined differences in participation rates between cohorts (2008), and differences in previous sickness absence (2001–2008) between participants (individual-level data) and non-participants or the target population (group-level data) within cohorts.ResultsParticipants had statistically significant less registered sickness absence in the past than non-participants and the target population for some, but not all, of the years analysed. Yet these differences were not of substantial size. Other factors than sickness absence were more important in explaining differences in participation, whereby participants were more likely to be women, older, born in Nordic countries, married and have higher incomes than non-participants.ConclusionsAlthough specifically addressing sickness absence, having such experience did not add any substantial layer to selective participation in the present survey. Detailed measures are needed to gain a better understanding for health selection in health-related surveys such as those addressing sickness absence, for instance in order to discriminate between selection due to ability or motivation for participation.

Differences in Sickness Allowance Receipt between Swedish Speakers and Finnish Speakers in Finland

“…An obvious strength of this study is consequently the population-based data we have used, which imply nonselective participation and medically screened cases. Surveys, in contrast, may offer some additional useful information related to health behaviours, health literacy and lifestyles, but they often suffer from problems with non-participation and selective response (Knapstad et al 2016). Sickness allowance receipt may nevertheless be considered a more complex health measure than disability pension.…”

Unmet Need for Mental Healthcare in a Population Sample in Sweden: A Cross-Sectional Study of Inequalities Based on Gender, Education, and Country of Birth

“…Two postal reminders followed up questionnaire distribution resulting in a final general participation rate of 50% ( n = 4027). Persons born outside Nordic countries had the lowest participation rate (34%), followed by those with the lowest incomes (39%), those in the youngest age group (19–30 years, 41%), men (44%), and those who were unmarried (46%) (Knapstad et al 2016 ). Full details of HAP and an extensive non-response analysis are presented elsewhere (Hensing et al 2011 ; Knapstad et al 2016 ).…”

Refraining from Seeking Mental Healthcare and Poorer Mental Well-Being: A Longitudinal Population-Based study on Men in Sweden

“…The T1 questionnaire comprised questions on mental healthcare-seeking at any time in life, mental and physical persistent illness, sociodemographic factors, and an index on mental well-being. A previous analysis of non-participation showed that those born outside the Nordic countries, those with low income, young persons, men, and those who were single were less likely to participate at T1 (31). Previously, several studies have been published based on the T1 questionnaire and the population-based sample, e.g., a recently published study showing gender and education-based differences in unmet need for mental healthcare (24).…”