Understanding Helpful Nursing Care From the Perspective of Mental Health Inpatients With a Dual Diagnosis: A Qualitative Descriptive Study
Bibliographic record
Abstract
BACKGROUND: An estimated 30% to 50% of people with a mental illness also have a substance use problem. Referred to as having a dual diagnosis, these patients experience high levels of unmet needs, poor health outcomes, and require specialized care during psychiatric hospitalization. Research on nursing inpatients with a dual diagnosis is limited and patient perceptions of helpful care during hospitalization are unknown. AIMS: What nursing interventions, attitudes, actions, and/or behaviors are perceived as helpful by patients with a dual diagnosis during psychiatric hospitalization? METHODS: A qualitative-descriptive design was used. Twelve adult inpatients with a dual diagnosis were recruited using purposive sampling. Individual, semistructured interviews were conducted, and interview data were analyzed using content analysis. RESULTS: Helpful nursing occurred across three themes: (1) promoting health in everyday living, (2) managing substance use in tandem with mental illness, and (3) building therapeutic relationships. CONCLUSIONS: Specific examples of helpful interventions and their reported outcomes reinforce the critical role that nurses play in the health and recovery of inpatients with a dual diagnosis. The importance of collaborative, strengths-based approaches is highlighted, and expanding the nurse’s role to include evidence-based responses to substance use is recommended.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".