A critical synthesis of interventions to reduce stigma attached to mental illness
Bibliographic record
Abstract
Background: Interventions have been developed and implemented to reduce the stigma attached to mental illness. However, mental healthcare users are still stigmatised.Objective: The objective of this study was to critically synthesise the best available evidence regarding interventions to reduce stigma attached to mental illness.Method: An exploratory and descriptive research design was followed to identify primary studies; systematic review identifid primary studies answering this research question: What best evidence is available regarding interventions to reduce the stigma attached to mental illness? A search was done on selected electronic databases. Seventeen studies (n = 17) were identifid as providing evidence that answered the research question. The following instruments were used: Critical Appraisal Skills Programme, John Hopkins Nursing Evidence-Based Practice research evidence appraisal tool and the Academy of Nutrition and Dietetics Evidence Analysis Manual. The study was submitted to the Post-graduate Education and Research Committee of the School of Nursing Science at Potchefstroom Campus of North-West University for approval.Results: Results indicated some interventions that reduce the stigma attached to mental illness, such as web-based approaches, printed educational materials, documentary and antistigma fims, as well as live and video performances.Conclusions: Humanising interventions seems to have a positive effect on reducing stigma attached to mental illness. From the results and conclusions recommendations were formulated for nursing practice, nursing education and research.Agtergrond: Ingrypings is ontwikkel en geïmplementeer om die stigma verbonde aan geestesongesteldhede te verminder. Die persone wat aan geestesongesteldhede ly, ondervind egter steeds dat daar 'n stigma aan hulle kleef.Doelstellings: Die doel van die studie was om die beste beskikbare voorbeelde van intervensies om stigmatisering van geestesongesteldhede te verminder, krities saam te vat.Metode: ’n Verkennende en beskrywende navorsingsontwerp is gevolg om primêre studies te identifieer. ’n Sistematiese oorsig is gekies as metode om primêre studies te identifieer om die volgende navorsingsvraag te beantwoord: Wat is die beste beskikbare voorbeelde vaningrypings om die stigma verbonde aan geestesongesteldhede te verminder? ’n Ondersoek is gedoen op ’n uitgesoekte elektroniese databasis.Resultate: Tydens die keuring van studies is 17 studies geïdentifieer (n = 17) as bewyslewering en wat die navorsingsvraag beantwoord. Die volgende instrumente is gebruik: ‘Critical Appraisal Skills Programme’, ‘John Hopkins Nursing Evidence-Based Practice’, ‘Research Evidence Appraisal Tool and Evidence Analysis Manual’, en ‘Academy of Nutrition and Dietetics’.Gevolgtrekking: Die studie is aan die Nagraadse Onderrig- en Navorsingskomitee van die Skool van Verpleegkunde van die Potchefstroomkampus, Noordwes-Universiteit, voorgelê vir goedkeuring. Aanbevelings is geformuleer vir die verpleegpraktyk, verpleegonderrig ennavorsing.
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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 | 0.000 |
| 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".