Mental health nurses' empathy towards consumers with dual diagnosis: A descriptive study
Bibliographic record
Abstract
AIM: This study aimed to assess mental health nurses' empathy towards consumers with dual diagnosis in Australian mental health settings. The research question was What is mental health nurses' empathy towards consumers with co-existing mental health and drug and alcohol problems? DESIGN AND METHODS: A cross-sectional survey was carried out to understand mental health nurses' empathy. The convenience sample included 96 mental health nurses from various mental health settings with experience working with consumers with dual diagnosis. We assessed empathy using the Toronto Empathy Questionnaire. We utilised SPSS™ software to analyse both the descriptive data and multiple-regression. RESULTS: The mean empathy score was 47.71 (SD 8.28). The analysis of the association between demographic variables and individual subscales showed an association between the clinical setting and empathy (p = .031) and sympathetic physiological arousal (p = .049). The work sector was associated with sympathetic physiological arousal (p = .045) and conspecific altruism (p = .008). Emotional contagion (β = .98, p < .001), emotional comprehension (β = 1.02, p < .001), sympathetic physiological arousal (β = 1.01, p < .001) and conspecific altruism (β = 10.23, p < .001) predicted mental health nurses' empathy. CONCLUSIONS: This study found that most mental health nurses showed empathy towards consumers with dual diagnosis. Mental health nurses who are more empathetic towards their consumers experience emotional contagion. They understand emotions better, show sympathetic physiological responses and exhibit kind behaviour towards consumers. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Further research is required to understand how mental health nurses adapt to consumers' emotional states in different mental health settings. This information can help clinicians make better decisions about care quality for consumers with dual diagnosis. IMPACT: This study addressed mental health nurses' empathy towards consumers with dual diagnosis. Mental health nurses showed increased empathy towards consumers with dual diagnosis. The empathy levels vary based on age, clinical setting, work sector and work experience. Mental health nurses' empathy levels were predicted by emotional contagion, emotion comprehension, sympathetic physiological arousal and conspecific altruism. Empathy enhancement among mental health nurses, particularly towards consumers with dual diagnosis, is crucial and should be regarded as a top priority by healthcare leaders and educators. REPORTING METHOD: Outlined by the Consensus-Based Checklist for Reporting of Survey Studies (CROSS). PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".