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Record W4412657830 · doi:10.1016/j.dadr.2025.100366

Adapting the alcohol and alcohol problems perception questionnaire and the drug and drug problems perception questionnaire: A psychometric analysis of a person-centred approach

2025· article· en· W4412657830 on OpenAlex
Andrea Raynak, Michel Bédard, Brianne Wood, Christopher J. Mushquash

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDrug and Alcohol Dependence Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsThunder Bay Regional Research InstituteCentre for Addiction and Mental HealthNOSM UniversitySt. Joseph's Care GroupLakehead UniversityThunder Bay Regional Health Sciences Centre
FundersCanadian Institutes of Health Research
KeywordsExploratory factor analysisConfirmatory factor analysisPerceptionQuestionnairePsychologyAlcoholClinical psychologyPsychometricsMedicineStructural equation modelingComputer science

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.279
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it