Engaging knowledge users in development of the CONSORT-Equity 2017 reporting guideline: a qualitative study using in-depth interviews
Bibliographic record
Abstract
BACKGROUND: Randomized controlled trials ("randomized trials") can provide evidence to assess the equity impact of an intervention. Decision makers need to know about equity impacts of healthcare interventions so that people get healthcare that is best for them. To better understand the equity impacts of healthcare interventions, a range of people who were potentially the ultimate users of research results were involved in a six-phase project to extend the CONsolidated Standards Of Reporting Trials Statement for health equity ("CONSORT-Equity 2017"). We identified these "knowledge users" as: patients and healthcare researchers, decision makers and providers. This paper reports on one project phase: specifically, a qualitative study designed to integrate the expertise of knowledge users. The experiences and perspectives of knowledge users provided many insights about the reporting of health equity issues in randomized trials. This paper describes key informant interviews with knowledge users that contribute to a better understanding of the effects of an intervention on health equity. Additionally, the paper shows how these insights were used to develop CONSORT-Equity 2017. METHODS: A qualitative study that used the framework analysis method was conducted in collaboration with an international study executive and advisory board team. In-depth semi-structured interviews were conducted with a purposive sample of key informants who: consider the research ethics of, fund, conduct, participate in, publish, or use research evidence generated in randomized trials. Transcripts were coded and analyzed using the seven-stage framework analysis method, and data reported to reflect knowledge user suggestions to develop CONSORT-Equity 2017. RESULTS: Thirteen key informants, of which three were patients, chose to participate in interviews. Seven themes emerged: "Differentiate the type of trial", "Prompts for health equity", "Ethics matter", "Describe unique research strategies", "Clarity of reporting", "Implications of equity for sampling and analysis", "Think beyond the immediate trial". The interviews provided direction for the extension of 16 CONSORT-Equity 2017 items. CONCLUSIONS: Key informant interviews were used to identify new concepts that were not generated in our other studies and to develop CONSORT-Equity 2017. We encourage the use of key informant interviews in guideline development to obtain and include the real-life expertise of knowledge users.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.085 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".