Referee report. For: An international, Delphi consensus study to identify priorities for methodological research in behavioural trials: A study protocol [version 2; referees: 2 approved]
Bibliographic record
Abstract
Background: Effective behaviour change interventions are needed to impact important health outcomes, including morbidity and mortality. However, the uptake and impact of behavioural interventions have been limited by methodological challenges. The International Behavioural Trials Network (IBTN) was established in 2013 to facilitate global improvement in methodological quality of behavioural trials. There has been no formal process, within the network or in the broader literature, to define the most important research priorities to achieve this aim. In this project, we will conduct an international, Delphi consensus study to identify and achieve consensus on priorities for methodological research in behavioural trials among IBTN members. Methods: Fifteen core members of IBTN, who are experts in the field of behavioural intervention research, will be invited to generate a list of all items they consider priority areas for methodological research in trials of behavioural interventions. The IBTN Research Prioritisation team (the authors) will review all items generated, removing duplicates and merging similar topics, and generate a ‘long-list’ of items. This long-list will be sent to the 15 IBTN core members for approval. We will then administer two online Delphi surveys to all IBTN members. In the first survey, respondents will be asked to rate the importance of each item on a nine-point scale and rank their top five priorities. In the second survey, respondents will receive feedback on others’ responses and a reminder of their own responses in survey 1, and will be asked to re-rate items and re-select their ‘top five’. Discussion: Findings from the project will be used to inform the research agenda of the IBTN and to make recommendations for future 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.089 | 0.536 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.174 | 0.058 |
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 source (direct Gemma or distilled Codex), 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".