Evidence map›Paper›PMID 35094681›Full record

ArticleBMC medical research methodology2022

Health and study dropout: health aspects differentially predict attrition.

Johannes Beller, Siegfried Geyer, Jelena Epping

Open access · goldAbstract read
In one paragraph

Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
10.9field-weighted citation impact, top 1% of its field
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

41 citing papers in PubMed, 64 citations in OpenAlex.

  1. Trial
  2. Depression trends in Europe: sociodemographic differences.European journal of public health · 2026
    Article
  3. The Aarhus bereavement study (TABstudy).European journal of epidemiology · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

3 authors at 1 institution in 1 country.

Johannes BellerHannover Medical School, Medical Sociology, Carl-Neuberg-Straße 1, 30625, Hannover, Germany. beller.johannes@mh-hannover.de.ORCID 0000-0002-3041-9895
Siegfried GeyerHannover Medical School, Medical Sociology, Carl-Neuberg-Straße 1, 30625, Hannover, Germany.
Jelena EppingHannover Medical School, Medical Sociology, Carl-Neuberg-Straße 1, 30625, Hannover, Germany.
Medizinische Hochschule Hannover · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParticipant dropout poses significant problems in longitudinal survey studies. Although it is often assumed that a participant's health predicts future study dropout, only a few studies have examined this topic, with conflicting findings. This study aims to contribute to the literature by clarifying the relationship between different aspects of health and study dropout.

methodsThe 2008 baseline sample of the German Aging Survey was used to predict study dropout (N = 4442). Indicators of health included physical health using the number of chronic conditions, physical functioning using the SF-36 Physical Functioning subscale, cognitive functioning using the digit symbol substitution test, and depression using the CESD-15.

resultsIt was found that different aspects of health had differential associations with survey dropout: Worse physical functioning and in part worse cognitive functioning predicted increased dropout rates; contrarily, worse physical health predicted decreased dropout when controlling for other health aspects and covariates. Depression was not significantly related to study dropout.

conclusionsTherefore, participants with chronic conditions, but minimal physical and cognitive disability were most likely to participate in the future. These findings suggest that health has a complex relationship with survey dropout and must be accounted for in longitudinal studies. Neglecting this systematic attrition due to health problems bears the risk of severely under- or overestimating health-related effects and trends.

Indexed as

AgingCognitionChronic DiseaseHumansLongitudinal StudiesPatient DropoutsSurveys and QuestionnairesAttritionChronic diseaseDropoutHealthLongitudinal

Identifiers

PMID35094681
PMCPMC8802529
OpenAlexW4210766278

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.