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Record W4392822814 · doi:10.2196/51779

How a National Organization Works in Partnership With People Who Have Lived Experience in Mental Health Improvement Programs: Protocol for an Exploratory Case Study

2024· article· en· W4392822814 on OpenAlexvenueno aff
C. F. Robertson, Carina Hibberd, Ashley Shepherd, Gordon Johnston

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
FundersUniversity of Stirling
KeywordsGeneral partnershipMental healthExploratory researchProtocol (science)PsychologyApplied psychologyMedical educationGerontologyMedicineNursingSociologyPsychiatryPolitical scienceAlternative medicineSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: This is a research proposal for a case study to explore how a national organization works in partnership with people with lived experience in national mental health improvement programs. Quality improvement is considered a key solution to addressing challenges within health care, and in Scotland, there are significant efforts to use quality improvement as a means of improving health and social care delivery. In 2016, Healthcare Improvement Scotland (HIS) established the improvement hub, whose purpose is to lead national improvement programs that use a range of approaches to support teams and services. Working in partnership with people with lived experience is recognized as a key component of such improvement work. There is, however, little understanding of how this is manifested in practice in national organizations. To address gaps in evidence and strengthen a consistent approach, a greater understanding is required to improve partnership working. OBJECTIVE: The aim of this study is to better understand how a national organization works in partnership with people who have lived experience with improvement programs in mental health services, exploring people's experiences of partnership working in a national organization. An exploratory case study approach will be used to address the research questions in relation to the Personality Disorder (PD) Improvement Programme: (1) How is partnership working described in the PD Improvement Programme? (2) How is partnership working manifested in practice in the PD Improvement Programme? and (3) What factors influence partnership working in the PD Improvement Programme? METHODS: An exploratory case study approach will be used in relation to the PD Improvement Programme, led by HIS. This research will explore how partnership working with people with lived experience is described and manifested in practice, outlining factors influencing partnership working. Data will be gathered from various qualitative sources, and analysis will deepen an understanding of partnership working. RESULTS: This study is part of a clinical doctorate program at the University of Stirling and is unfunded. Data collection was completed in October 2023; analysis is expected to be completed and results will be published in January 2025. CONCLUSIONS: This study will produce new knowledge on ways of working with people with lived experience and will have practical implications for all improvement-focused interventions. Although the main focus of the study is on national improvement programs, it is anticipated that this study will contribute to the understanding of how all national public service organizations work in partnership with people with lived experience of mental health care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51779.

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)0.078
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.078
Threshold uncertainty score0.415

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.070
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0050.004
Science and technology studies0.0110.006
Scholarly communication0.0070.008
Open science0.0070.008
Research integrity0.0100.011
Insufficient payload (model declined to judge)0.0630.014

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 head0.749
GPT teacher head0.664
Teacher spread0.084 · 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 designQualitative
Domainnot available
GenreProtocol

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

Citations0
Published2024
Admission routes1
Has abstractyes

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