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Record W2050025843 · doi:10.1371/journal.pmed.1001069

Reporting Guidelines for Survey Research: An Analysis of Published Guidance and Reporting Practices

2011· article· en· W2050025843 on OpenAlexafffund
Carol Bennett, Sara D. Khangura, Ian D. Graham, David Moher, Beth K. Potter, Jeremy Grimshaw

Bibliographic record

VenuePLoS Medicine · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsCanadian Institutes of Health ResearchUniversity of OttawaOttawa Hospital
FundersCanadian Institutes of Health Research
KeywordsRepresentativeness heuristicMedicineGuidelineSystematic reviewMEDLINEMedical educationSurvey methodologyResearch designFamily medicinePsychologyPathologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Research needs to be reported transparently so readers can critically assess the strengths and weaknesses of the design, conduct, and analysis of studies. Reporting guidelines have been developed to inform reporting for a variety of study designs. The objective of this study was to identify whether there is a need to develop a reporting guideline for survey research. METHODS AND FINDINGS: We conducted a three-part project: (1) a systematic review of the literature (including "Instructions to Authors" from the top five journals of 33 medical specialties and top 15 general and internal medicine journals) to identify guidance for reporting survey research; (2) a systematic review of evidence on the quality of reporting of surveys; and (3) a review of reporting of key quality criteria for survey research in 117 recently published reports of self-administered surveys. Fewer than 7% of medical journals (n = 165) provided guidance to authors on survey research despite a majority having published survey-based studies in recent years. We identified four published checklists for conducting or reporting survey research, none of which were validated. We identified eight previous reviews of survey reporting quality, which focused on issues of non-response and accessibility of questionnaires. Our own review of 117 published survey studies revealed that many items were poorly reported: few studies provided the survey or core questions (35%), reported the validity or reliability of the instrument (19%), defined the response rate (25%), discussed the representativeness of the sample (11%), or identified how missing data were handled (11%). CONCLUSIONS: There is limited guidance and no consensus regarding the optimal reporting of survey research. The majority of key reporting criteria are poorly reported in peer-reviewed survey research articles. Our findings highlight the need for clear and consistent reporting guidelines specific to survey research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.668
metaresearch head score (Gemma)0.868
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.332
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6680.868
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0080.012
Bibliometrics0.0680.096
Science and technology studies0.0050.007
Scholarly communication0.0170.017
Open science0.0130.014
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0080.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.950
GPT teacher head0.672
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainReporting
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations407
Published2011
Admission routes2
Has abstractyes

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