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Record W4386757674 · doi:10.3917/rsi.153.0024

Mieux comprendre la relation entre les intervenants et les jeunes adultes vivant avec un trouble concomitant de santé mentale et lié à l’usage de substances : une revue intégrative des écrits

2023· review· fr· W4386757674 on OpenAlexaff
Sophie Sergerie‐Richard, France Dupuis, Christine Cassivi

Bibliographic record

VenueRecherche en soins infirmiers · 2023
Typereview
Languagefr
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophySociology

Abstract

fetched live from OpenAlex

INTRODUCTION: The importance of a quality relationship between young adults living with dual diagnosis and their health care providers is well documented. CONTEXT: Although this complex phenomenon was mostly studied from an individual perspective, the results indicated the systemic nature of this relationship. OBJECTIVE: This study aims to better understand the relationship between young adults living with dual diagnosis and their health care providers, with a systemic perspective. METHOD: Six data bases were consulted; manual research in gray literature and references screening enhanced the process. RESULTS: Of a total of 532 studies and reports identified, 44 were included in the review. Thematic data analysis was carried out, and two themes were identified: the health care system as a constraining environment; and the relationship at the heart of care. DISCUSSION: This study confirms the joint role played by the young adult in question and their health care provider in developing and maintaining the relationship, by acknowledging the importance of the care, of mutual confidence, and of a hierarchic relationship. CONCLUSION: This integrative review provides a basis for future nursing interventions that foreground the relationship and take a systemic approach.

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)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.334
GPT teacher head0.511
Teacher spread0.177 · 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 designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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