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Record W2052912498 · doi:10.4102/hsag.v19i1.799

Interventions to promote psychiatric patients’ compliance to mental health treatment: A systematic review

2014· review· en· W2052912498 on OpenAlexaff
Mosidi B. Serobatse, Emmerentia du Plessis, Magdalena P. Koen

Bibliographic record

VenueHealth SA Gesondheid · 2014
Typereview
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsScience North
FundersNorth-West University
KeywordsPsychological interventionMental healthSystematic reviewCompliance (psychology)Motivational interviewingMedicineGrading (engineering)PsychologyPsychiatryNursingMEDLINE

Abstract

fetched live from OpenAlex

Background: Non-compliance to treatment remains one of the greatest challenges in mental healthcare services, and how to improve this remains a problem.Aim: The aim of this study was to critically synthesise the best available evidence from literature regarding interventions to promote psychiatric patients’ compliance to mental health treatment. The interventions can be made available for mental health professionals to use in clinical practice.Method: A systematic review was chosen as a design to identify primary studies that answered the following research question: What is the current evidence on interventions to promote psychiatric patients’ compliance to mental health treatment? Selected electronic databases were thoroughly searched. Studies were critically appraised and identifid as answeringthe research questions. Evidence extraction, analysis and synthesis were then conducted by means of evidence class rating and grading of strength prescribed in the American Dietetic Association’s manual.Results: The systematic review identifid several interventions that can improve patients’ compliance in mental health treatment, for example adherence therapy and motivational interviewing techniques during in-hospital stay.Conclusions: Conclusions were drawn and recommendations formulated for nursing practice, education and research.Agtergrond: Geen-samewerking met behandeling bly steeds een van die grootste uitdagings in geestesgesondheidsorgdienste, en genoegsame kennis oor hoe om dit te verbeter, is steeds ’n probleem.Doelwit: Die doel van hierdie studie was om die beskikbare bewyse vanuit literatuur aangaande intervensies ter bevordering van psigiatriese pasiënte se samewerking met geestesgesondheidsbehandeling krities te sintetiseer. Hierdie intervensies kan aan professionele gesondheidsorgpersoneel beskikbaar gestel word ter bevordering van psigiatriese pasiënte se samewerking met geestesgesondheidsbehandeling.Metode: ’n Sistematiese literatuuroorsig is gekies as die ontwerp om primêre studieste identifieer wat die volgende navorsingsvraag beantwoord: Wat is die huidige kennis ten opsigte van intervensies wat psigiatriese pasiënte se samewerking met geestesgesondheidsbehandeling bevorder?Resultate: Studies is ingesluit vir kritiese gehalte-beoordeling ten opsigte van metodologie, en is uiteindelik geïdentifieer as bronne van bewyse wat die literatuuroorsigvraag toepaslik beantwoord. Bewysonttrekking, -analise en -sintese is gedoen deur middel van die beoordeling van bewysklas en -gradering van bewyssterkte, soos voorgeskryf in die American Dietetic Association se handleiding. Die sistemiese literatuuroorsig het aangedui datdaar heelparty intervensies is wat psigiatriese pasiënte se samewerking met behandeling kan verbeter, byvoorbeeld samewerkingsterapie en motiveringsonderhoudstegnieke.Gevolgtrekking: Gevolgtrekkings is gemaak en aanbevelings is geformuleer vir die verpleegpraktyk, verpleegonderrig en navorsing in verpleging.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.062
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.009
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.164
GPT teacher head0.508
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2014
Admission routes1
Has abstractyes

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