Evidence map›Paper›PMID 27798012›Full record

ArticleBMJ open2016

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

Marit Knapstad, Jesper Löve, Kristina Holmgren, Gunnel Hensing, Simon Øverland

Abstract read
In one paragraph

Article in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Marit KnapstadDepartment of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway.
Jesper LöveDepartment of Public Health and Community Medicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Kristina HolmgrenDepartment of Public Health and Community Medicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Gunnel HensingDepartment of Public Health and Community Medicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Simon ØverlandDepartment of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 MEASURES: We 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.

Indexed as

AbsenteeismEmploymentHealth StatusHealth SurveysRegistriesResearch DesignSick LeaveAdultBiasCohort StudiesFemaleHumansMaleMiddle AgedResearch SubjectsSocioeconomic FactorsEPIDEMIOLOGYparticipation rateSelection biasSickness absencesurvey

Identifiers

PMID27798012
PMCPMC5093686

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.