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Record W6884639193 · doi:10.11575/prism/25715

Discharge Transition and Self-Regulation of Youth Between 15 and 24 Years of Age with Mental Illness

2014· other· en· W6884639193 on OpenAlexfundno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersAlberta Children's Hospital FoundationAlberta Children's Hospital Research InstituteChildren's Hospital FoundationAlberta Health Services
KeywordsMental illnessCoping (psychology)Context (archaeology)CognitionMental healthPsychological interventionWindow of opportunityPerspective (graphical)Social environmentSocial support

Abstract

fetched live from OpenAlex

The consequences for youth with mental illness are particularly acute and many experience crises that precipitate admission to hospital. When these youth are discharged, continuity of care is a key factor in a positive transition experience. Following discharge, youth require a form of social scaffolding to help them transfer their adaptive coping and self-regulation skills from the cool cognition of the hospital to the potentially hot cognition of their community. Recent research on the brain has demonstrated the importance of neuroplasticity during the period between the onset of puberty and adulthood. This period may be viewed as a window of both risk and opportunity. Risk, because the young person’s ability to make rational decisions is often adversely affected by his or her intense emotions. Opportunity, because the rapid growth of the brain during adolescence is strongly affected by the youth’s social environment, and this growth does not wane until after young adulthood. Thus, an understanding of the process of self-regulation of youth with mental illness in the context of discharge is essential for a successful discharge transition program. And yet, literature on the process of self-regulation in the context of discharge from the perspective of youth with mental illness is lacking. Using a grounded theory approach, this research study revealed the challenges and strengths experienced by youth in this process. Potential implications for practice included identifying and implementing strategies for addressing gaps in current programs, and directions for future research were discussed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.807
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.174
Teacher spread0.167 · 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 teacher head, 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

Citations0
Published2014
Admission routes1
Has abstractyes

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