Development and validation of measures of pharmacists’ acceptability and willingness to screen for perinatal depression
Bibliographic record
Abstract
BACKGROUND: While pharmacists' roles in mental healthcare are expanding, research exploring pharmacists' acceptability and willingness to provide mental health services is limited. This study developed and validated theory-driven measures of pharmacists' acceptability and willingness to screen for perinatal depression in community pharmacy settings. MATERIALS/METHODS: Items were developed using published literature and the Theoretical Framework of Acceptability (TFA), then content validated using consensus methods with experts who completed the content validity index (CVI). The revised items were disseminated to pharmacists in Australia. Responses were analysed descriptively. Exploratory factor analyses (EFA) were used to explore the factorial structure and generate scales. Multivariate regression analysis was conducted to explore predictors of willingness. RESULTS: A 58-item questionnaire was developed, encompassing the 7 domains of the TFA and an eighth domain (willingness). The average CVI was 0.92, domain range (0.88-0.96). The universal CVI was 56/58. Expert feedback informed item revision, creation and deletion. Pharmacists' responses (n = 157) to the final 42-item questionnaire indicated overall acceptance and willingness to conduct PND screening. However, perceived knowledge was lacking. The EFA resulted a two-factor solution (1 = acceptance; 2 = self-efficacy). The measurement scales created had good internal consistency. In multivariate regression analysis, 'Acceptance' (Beta = 0.949 (0.760-1.103)) and 'Self-Efficacy' (Beta = 0.107 (0.036-0.174)) were significant predictors of 'Willingness' and the model predicted 77 % of the variation in 'Willingness'. CONCLUSIONS: Psychometrically-sound measures of pharmacists' acceptability and willingness to screen for PND have been developed with stakeholder input. The questionnaire can be used for standardised measurement of these constructs across studies.
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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 | 0.034 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".