Applying behaviour change models to policy-making: development and validation of the Policymakers’ Information Use Questionnaire (POLIQ)
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to develop and validate the Policymakers' Information Use Questionnaire (POLIQ) to capture the intention of individuals in decision-making positions, such as health policy-makers, to act on research-based evidence in order to inform theory and the application of behaviour change models to decision-making spheres. METHODS: The development and validation comprised three steps: item generation, qualitative face validation with cognitive debriefing and factorial construct validation. Confirmatory factor analysis was applied to estimate item-domain correlations for five predefined constructs relating to content, beliefs, behaviour, control and intent. Cronbach's alpha coefficient was calculated to assess the overall consistency of questionnaire items with the predefined constructs. Participants in the item generation and face validation were health and policy researchers and two former decision-makers (former assistant deputy ministers) from the Canadian provincial level. Participants in the construct validation were 39 Canadian decision-makers at various positions of municipal, provincial and federal jurisdiction who participated in a series of policy dialogues focused on childhood disability. RESULTS: Cognitive debriefing allowed for small adjustments in language for clarity, including simultaneous validation of the English and French questionnaires. Participants found that the questions were clear and addressed the domains being targeted. Internal consistency of items belonging to the respective questionnaire domains was moderate to high, with estimated Cronbach's alpha values ranging from 0.67 to 0.84. Estimated item-domain correlations indicated moderate to high measurement performance for the domains norm, control and beliefs, whereas weak to moderate correlations resulted for the constructs content and intent. Estimated imprecision of factor loadings (95% confidence interval widths) was considerable for the questionnaire domains content and intent. CONCLUSION: Measuring decision-makers' behaviour in relation to research evidence use is challenging. We provide initial evidence on face validity and appropriate measurement properties of the POLIQ based on a convenience sample of decision-makers in social and health policy. Larger validation studies and further psychometric property testing will support further utility of the POLIQ.
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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 | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | 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 | 0.074 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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, 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".