Instruments that measure psychosocial factors related to vaccination: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: As vaccine-preventable disease outbreaks increase, there is growing international interest in monitoring public attitudes towards vaccination and implementing and evaluating vaccine promotion interventions. Outcome selection and measurement are central to intervention evaluation. Measuring uptake rates alone cannot determine which elements in a multicomponent vaccine-promotion intervention are most effective, why specific populations are undervaccinated or when confidence in vaccines is wavering. To develop targeted and cost-effective interventions and policies, it is necessary to measure vaccination-related psychosocial factors such as knowledge, attitudes and aspects of decision-making. This scoping review aims to identify, compare and summarise the properties and validation of instruments for measuring vaccination-related psychosocial factors and identify gaps where no instruments exist. METHODS AND ANALYSIS: We will search Medline OVID, Embase OVID, CINAHL and PsycINFO with no date restriction, using a pilot-tested search strategy of terms related to vaccination: knowledge, attitudes, trust, acceptance and decision-making and measurement, psychometric testing or validation. This search will be supplemented with manual search and expert consultation. We will include studies that describe instrument development, adaptation or testing and include evaluation of at least two measurement properties (eg, content, criterion, or construct validity; test-retest reliability; internal consistency; sensitivity; responsiveness). Instruments measuring a vaccination-related psychosocial factor in any population will be included. All studies will be screened by one reviewer, with a sample double-screened to confirm accuracy. Disagreements will be resolved with a third reviewer. Data will be synthesised narratively and through summary tables to chart and compare instrument characteristics such as factors measured, date and/or location of development or validation, measurement properties evaluated and population. ETHICS AND DISSEMINATION: This scoping review aims to provide an overview of existing instruments and ascertain measurement gaps where no measurement instruments currently exist. The identified instruments will form the basis of an open-access online repository of instruments.
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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 | 0.103 | 0.101 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.017 | 0.013 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.082 | 0.016 |
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".