Mental health nurses’ attitudes, empathy and caring efficacy towards consumers with co-existing mental health and drug and alcohol problems : a mixed methods study
Bibliographic record
Abstract
Background: Dual diagnosis is a significant cause of disability worldwide and accounts for 13% of the disease burden in Australia. In 2014-15, more than half of emergency hospital admissions in Australia were due to psychological and behavioural problems associated with illegal substance use. Mental health nurses play a critical role in caring for consumers with dual diagnosis. However, there is a shortage of evidence about mental health nurses’ attitudes, empathy, and caring efficacy towards these consumers. Materials and Methods: This concurrent mixed methods study examined mental health nurses’ attitudes, empathy, and caring efficacy towards consumers with dual diagnosis in Australian mental health settings. Data were collected between December 2019 and November 2020. A total of 103 mental health nurses completed the Comorbidity Problems Perceptions Questionnaire, 96 completed the Toronto Empathy Questionnaire, and 84 completed the Caring Efficacy Scale. Seventeen mental health nurses participated in semi-structured interviews. The data were analysed using regression, themes and joint displays. Results: Mental health nurses displayed a positive attitude (M = 83.97, SD = 28.49), empathy (M = 47.71, SD = 8.28) and caring efficacy (M = 145.70, SD = 19.92) towards consumers with dual diagnosis. Factors identified as contributing to a positive attitude were a high level of work experience (
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".