Evidence map›Paper›PMID 30948596›Full record

ArticleBMJ open2019

Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper.

Megan A McMinn, Pekka Martikainen, Emma Gorman, Harri Rissanen, Tommi Härkänen, Hanna Tolonen, Alastair H Leyland, Linsay Gray

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Observational
  2. 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

8 authors.

Megan A McMinnMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.ORCID 0000-0001-8398-2633
Pekka MartikainenPopulation Research Unit, Faculty of Social Science, University of Helsinki, Helsinki, Finland.
Emma GormanDepartment of Economics, Lancaster University, Lancaster, UK.
Harri RissanenDepartment of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland.
Tommi HärkänenDepartment of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland.
Hanna TolonenDepartment of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland.
Alastair H LeylandMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
Linsay GrayMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.

Funding

Chief Scientist Office SPHSU13Medical Research Council MC_EX_MR/J013498/1Medical Research Council MC_EX_UU_MR/J013498/1Medical Research Council MC_UU_12017/13Medical Research Council MRC_MC_UU_12017/13Medical Research Council MR/J013498/1
6 · The paper itself

Abstract

introductionDecreasing participation levels in health surveys pose a threat to the validity of estimates intended to be representative of their target population. If participants and non-participants differ systematically, the results may be biased. The application of traditional non-response adjustment methods, such as weighting, can fail to correct for such biases, as estimates are typically based on the sociodemographic information available. Therefore, a dedicated methodology to infer on non-participants offers advancement by employing survey data linked to administrative health records, with reference to data on the general population. We aim to validate such a methodology in a register-based setting, where individual-level data on participants and non-participants are available, taking alcohol consumption estimation as the exemplar focus. METHODS AND ANALYSIS: We made use of the selected sample of the Health 2000 survey conducted in Finland and a separate register-based sample of the contemporaneous population, with follow-up until 2012. Finland has nationally representative administrative and health registers available for individual-level record linkage to the Health 2000 survey participants and invited non-participants, and the population sample. By comparing the population sample and the participants, synthetic observations representing the non-participants may be generated, as per the developed methodology. We can compare the distribution of the synthetic non-participants with the true distribution from the register data. Multiple imputation was then used to estimate alcohol consumption based on both the actual and synthetic data for non-participants, and the estimates can be compared to evaluate the methodology's performance. ETHICS AND DISSEMINATION: Ethical approval and access to the Health 2000 survey data and data from administrative and health registers have been given by the Health 2000 Scientific Advisory Board, Statistics Finland and the National Institute for Health and Welfare. The outputs will include two publications in public health and statistical methodology journals and conference presentations.

Indexed as

Health SurveysModels, StatisticalRegistriesAdolescentAdultAgedFemaleFinlandHumansMaleMedical Records Systems, ComputerizedMiddle AgedPatient ParticipationRetrospective StudiesYoung Adultpublic health

Identifiers

PMID30948596
PMCPMC6500270

What OpenQuestion holds

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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.