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Record W1966204039 · doi:10.1186/s12913-014-0557-6

Evaluation of the implementation of the Montreal at home/chez soi project

2014· article· en· W1966204039 on OpenAlexaffabout
Marie‐Josée Fleury, Guy Grenier, Catherine Vallée

Bibliographic record

VenueBMC Health Services Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversité LavalDouglas CollegeMcGill UniversityDouglas Mental Health University Institute
FundersMental Health Commission
KeywordsConstruct (python library)Focus groupContext (archaeology)Psychological interventionPublic relationsProject teamProcess managementMedicineSociologyNursingKnowledge managementPolitical scienceBusinessMarketingComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Homelessness and mental disorders constitute a major problem in Canada. The purpose of the At Home/Chez Soi pilot project was to house and provide supports to marginalised groups. Policymakers are in a better position to nurture new, complex interventions if they know which key factors hinder or enable their implementation. This paper evaluates the implementation process for the Montreal site of this project. METHODS: We collected data from 62 individuals, through individual interviews, focus groups, questionnaires, observations and documentation. The implementation process was analysed using a conceptual framework with five constructs: Intervention Characteristics (IC), Context of Implementation (CI), Implementation Process (IP), Organizational Characteristics (OC) and Strategies of Implementation (SI). RESULTS: The most serious obstacle to the project came from the CI construct, i.e., lack of support from provincial authorities and key local resources in the homelessness field. The second was within the OC construct. The chief hindrances were numerous structures, divergent values among stakeholders, frequent turnover of personnel and team leaders; lacking staff supervision and miscommunication. The third is related to IC: the complex, unyielding nature of the project undermined its chances of success. The greatest challenges from IP were the pressure to perform, along with stress caused by planning, deadlines and tension between teams. Conversely, SI construct conditions (e.g., effective governing structures, comprehensive training initiatives and toolkits) were generally very positive even with problems in power sharing and local leadership. For the four other constructs, the following proved useful: evidence of the project's scope and quality, great needs of services consolidation, generous financing and status as a research pilot project, enthusiasm and commitment toward the project, substantially improved services, and overall user satisfaction. CONCLUSION: This study demonstrated the difficulty of implementing a complex project in the healthcare system. While the project faced many barriers, minimal conditions were also achieved. At the end of the study period, major tensions between organizations and teams were significantly reduced, supporting its full implementation. However, in late 2013, the project was unsustainable, calling into question the relevance of achieving a significant number of positive conditions in each area of the framework.

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)0.033
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.649

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0040.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.407
GPT teacher head0.594
Teacher spread0.187 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2014
Admission routes2
Has abstractyes

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