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How Much Non-response Matters? Diagnosis Prevalence Estimates in Survey Participants Versus the Total Sample
Frerk T, Vogelgesang F, Thamm R, Julia T, Joachim S, Schumacher C, Marschall U, Grobe TG.. Research Square, 2026-08-25
Topic: Health services, long-term care and technology
Background Survey-based estimates of disease prevalence may be affected by non-response. To assess the extent to which incomplete participation may distort prevalence estimates, we compared diagnosis prevalences among survey participants with those in the total sample Methods A total of 26,000 insurees of the German statutory health insurance fund BARMER were selected and invited to participate in a health survey. After few exclusions, the analytic total sample comprised 25,977 individuals, of whom 7,087 participated. Raw and population standardized/weighted diagnosis prevalences were estimated for both survey participants and the total sample based on health claims data. Results Differences between survey participants and the total sample were observed across ICD chapters, ICD groups, and selected diagnoses. In most instances, prevalence estimates were higher among participants than in the total sample. Mental and behavioural disorders represented the main exception, with lower prevalence estimates among participants. After weighting for sex, age, and region of residence, differences were generally small at the aggregate level, although notable deviations remained for some mental disorders and for dementia. Conclusion In this setting, selective participation had only a limited effect on prevalence estimates after weighting. These findings suggest that, despite a modest response rate, survey-based prevalence estimates for many common diagnoses may be more robust than often assumed. At the same time, diagnosis-specific non-response bias remains relevant for some mental disorders and vulnerable subgroups.
Key findings
- Results Differences between survey participants and the total sample were observed across ICD chapters, ICD groups, and selected diagnoses.
- These findings suggest that, despite a modest response rate, survey-based prevalence estimates for many common diagnoses may be more robust than often assumed.
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Study details
- Participants25,977
- Evidence strengthLow
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 32 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, effect reported and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 20 of the 62 points we could judge it on, which is 32 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (Research Square) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 4 / 4 | 25,977 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 20 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 20 of the 62 points we could judge it on is 32 out of 100. |
| Total | 32 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 8 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Frerk, T., Vogelgesang, F., Thamm, R., Julia, T., Joachim, S., Schumacher, C., et al. (2026). How Much Non-response Matters? Diagnosis Prevalence Estimates in Survey Participants Versus the Total Sample. Research Square. https://doi.org/10.21203/rs.3.rs-10216874/v1
Vancouver
Frerk T, Vogelgesang F, Thamm R, Julia T, Joachim S, Schumacher C, et al. How Much Non-response Matters? Diagnosis Prevalence Estimates in Survey Participants Versus the Total Sample. Research Square. 2026. doi:10.21203/rs.3.rs-10216874/v1.
BibTeX
@article{frerk2026-033fcf76,
author = {Frerk, T. and Vogelgesang, F. and Thamm, R. and Julia, T. and Joachim, S. and Schumacher, C. and Marschall, U. and Grobe, T. G.},
title = {{How Much Non-response Matters? Diagnosis Prevalence Estimates in Survey Participants Versus the Total Sample}},
journal = {Research Square},
year = {2026},
doi = {10.21203/rs.3.rs-10216874/v1},
url = {https://doi.org/10.21203/rs.3.rs-10216874/v1}
}