Effects of an evidence service on health-system policy makers' use of research evidence: A protocol for a randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Health-system policy makers need timely access to synthesised research evidence to inform the policy-making process. No efforts to address this need have been evaluated using an experimental quantitative design. We developed an evidence service that draws inputs from Health Systems Evidence, which is a database of policy-relevant systematic reviews. The reviews have been (a) categorised by topic and type of review; (b) coded by the last year searches for studies were conducted and by the countries in which included studies were conducted; (c) rated for quality; and (d) linked to available user-friendly summaries, scientific abstracts, and full-text reports. Our goal is to evaluate whether a "full-serve" evidence service increases the use of synthesized research evidence by policy analysts and advisors in the Ontario Ministry of Health and Long-Term Care (MOHLTC) as compared to a "self-serve" evidence service. METHODS/DESIGN: We will conduct a two-arm randomized controlled trial (RCT), along with a follow-up qualitative process study in order to explore the findings in greater depth. For the RCT, all policy analysts and policy advisors (n = 168) in a single division of the MOHLTC will be invited to participate. Using a stratified randomized design, participants will be randomized to receive either the "full-serve" evidence service (database access, monthly e-mail alerts, and full-text article availability) or the "self-serve" evidence service (database access only). The trial duration will be ten months (two-month baseline period, six-month intervention period, and two month cross-over period). The primary outcome will be the mean number of site visits/month/user between baseline and the end of the intervention period. The secondary outcome will be participants' intention to use research evidence. For the qualitative study, 15 participants from each trial arm (n = 30) will be purposively sampled. One-on-one semi-structured interviews will be conducted by telephone on their views about and their experiences with the evidence service they received, how helpful it was in their work, why it was helpful (or not helpful), what aspects were most and least helpful and why, and recommendations for next steps. DISCUSSION: To our knowledge, this will be the first RCT to evaluate the effects of an evidence service specifically designed to support health-system policy makers in finding and using research evidence. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01307228.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
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 | 0.265 | 0.266 |
| Meta-epidemiology (narrow) | 0.008 | 0.006 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.019 | 0.018 |
| Insufficient payload (model declined to judge) | 0.109 | 0.030 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".