Adapting the alcohol and alcohol problems perception questionnaire and the drug and drug problems perception questionnaire: A psychometric analysis of a person-centred approach
Bibliographic record
Abstract
Background: The Alcohol and Alcohol Problems Perception Questionnaire and the Drug and Drug Problems Perception Questionnaires were developed decades ago to assess health care providers' attitudes toward patients who use substances. Although reliable, the language in these tools no longer aligns with contemporary societal and academic discourse on person-centred language. Therefore, this study aimed to evaluate whether modifying the language in the Alcohol and Alcohol Problems Perception Questionnaire and Drug and Drug Problems Perception Questionnaire to create the person-centered Alcohol and Alcohol Problems Perception Questionnaire and person-centered Drug and Drug Problems Perception Questionnaire would affect their reliability, internal consistency, and factor structures when used with registered nurses and registered practical nurses. Methods: In fall 2024, an electronic survey was distributed to 1400 RNs and RPNs at an acute care hospital in northwestern Ontario, with 412 responding (29.4 % response rate). Participants were randomly assigned to complete either the original Alcohol and Alcohol Problems Perception Questionnaire and Drug and Drug Problems Perception Questionnaire or the revised person-centred versions. Confirmatory factor analysis and exploratory factor analysis were conducted to assess the factor structures of both versions. Results: Confirmatory factor analysis revealed suboptimal model fits for both the Alcohol and Alcohol Problems Perception Questionnaire and the person-centred Alcohol and Alcohol Problems Perception Questionnaire. The best-fitting Alcohol and Alcohol Problems Perception Questionnaire was a seven-factor, 30-item model, and the person-centred Alcohol and Alcohol Problems Perception Questionnaire was a revised four-factor, 22-item model after exploratory factor analysis. Confirmatory factor analysis for the Drug and Drug Problems Perception Questionnaire indicated support for the original five-factor structure, but a four-factor, 16-item model emerged after exploratory factor analysis for the person-centred version. Conclusions: Although limited by a small sample size and data from a single setting, the findings of this study provide preliminary support that slightly modified versions of the PC- AAPPQ and PC-DDPPQ may hold promise for use with practising clinical nurses in similar contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".