The needs of carers who support people living with schizophrenia and a substance use disorder: a multiperspective evaluation
Bibliographic record
Abstract
Purpose Those who care for people with schizophrenia and substance use disorders (PLS-SUD) are faced with the complex demands of a long journey to recovery. For the carers, this translates into specific needs related to various areas of their lives. However, few studies have contributed to the understanding of these carers’ needs. The purpose of this qualitative evaluative study is to identify, understand and prioritize the needs of PLS-SUD carers in the context of intervention design from the viewpoint of carers themselves (n= 9), those they were accompanying (n= 5) and other key actors involved (n= 10). Design/methodology/approach A design of action research was employed. Data analysis was done in three phases: concept map analysis, thematic analysis and transversal analysis of the results from two focus groups, 28 interview transcriptions and a logbook. Findings Over 60 needs were identified. After review, 39 of those were selected for prioritization. For needs related to the carers’ role as clients of the health-care system, the committee prioritized the needs for support, sharing with other carers and improving their own well-being. For the role of supporter, knowledge about substance use disorders and their interactions with psychotic disorders as well as skills such as communication and problem resolution were considered priorities. Needs to be prioritized relating to the role of partner were fewer. Research limitations/implications The results of this study highlight the diversity and complexity of the needs experienced by carers. Originality/value This is among the first needs surveys carried out by stakeholders to describe the needs of PLS-SUD carers.
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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 | 0.037 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".