Sample study protocol for adapting and translating the 5C scale to assess the psychological antecedents of vaccination
Bibliographic record
Abstract
INTRODUCTION: Published in 2018, the 5C scale is psychometrically validated to assess five psychological antecedents of vaccination (confidence, complacency, constraints, calculation and collective responsibility). The original version offers a validated English and German scale to assess these determinants with a short 5-item scale (1 item per antecedent) and a long 15-item scale (3 items per antecedent). This sample study protocol provides a step-by-step guidance for the process of adapting the 5C scale to another country, language or cultural context. Data obtained from the 5C scale can support developing, implementing and evaluating an intervention and monitoring of general vaccine acceptance and demand. METHODS AND ANALYSIS: Phase 1 comprises the adaptation of the 5C scale including the translation and back translation of the antecedents, an expert evaluation of the antecedents and the identification of new antecedents as well as a pretest. Phase 2 involves the validation of the translated and potentially expanded scale including the assessment of reliability, construct and concurrent validity of all items of the scale. Code for data analysis is provided. ETHICS AND DISSEMINATION: The University of Erfurt's institutional review board provided ethical clearance (EV-201900416.2). The authors suggest and encourage publicly sharing all data obtained from the translated 5C scale (eg, on publication). The materials and the code for data analysis to support the process described in this protocol are available in https://osf.io/2agxe/. Sharing data on vaccine acceptance and demand is in the public and the scientific interest and will facilitate gaining a global overview of its current state and development over time. The authors of the original 5C scale are currently working on an online platform to facilitate publishing the data and to visualise the psychological antecedents across different countries.
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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 | 0.025 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.159 | 0.049 |
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".