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Record W3026385390 · doi:10.1093/schbul/sbaa029.784

T224. TESTING THE EFFECTIVENESS OF A BRIEF, PEER SUPPORT INTERVENTION TO FACILITATE TRANSITION FROM PSYCHIATRIC HOSPITALIZATION FOR A SCHIZOPHRENIA SPECTRUM POPULATION

2020· article· en· W3026385390 on OpenAlexaff
Sean A. Kidd, Larry Davidson, Dawn I. Velligan, Aristotle N. Voineskos

Bibliographic record

VenueSchizophrenia Bulletin · 2020
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
Fundersnot available
KeywordsIntervention (counseling)Psychological interventionRandomized controlled trialPopulationSchizophrenia (object-oriented programming)PsychiatryPsychologyPeer supportMedicineClinical psychologyEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Background The period immediately following discharge is highly stressful for many individuals with schizophrenia spectrum illnesses as they transition from protracted inpatient stays to community settings with minimal support. In this period the risk of hospital re-admission is at its highest, many do not engage with community supports and clinical resources, and the risk of suicide is greatest. The evidence base for brief, effective interventions to support such transitions is to date underdeveloped. Methods This randomized controlled trial examined the effectiveness of a Peer Support intervention that combines components of Cognitive Adaptation Training (CAT) and the Welcome Basket Program. CAT is an evidence-based intervention that provides environmental supports to help people with schizophrenia compensate for the cognitive impacts of the illness. The Welcome Basket Program is a peer intervention approach that helps bridge discharge through the provision of a small individualized ‘basket’ of staple supplies and comfort items along with the facilitation of engagement with community resources. The intervention involves peer supports engaging patients in the days preceding discharge to assess goals and needs followed by weekly visits post-discharge for 1 month providing Welcome Basket and CAT supports. The study also collected pilot data examining the outcomes of an abbreviated, two contact version of the intervention. Inpatients with a schizophrenia spectrum diagnosis were randomized with a 2:2:1 ratio to treatment as usual, the full intervention, and the abbreviated intervention. Along with feasibility assessments, outcome metrics included re-hospitalization, symptomatology, quality of life, and community functioning. Assessments at baseline, 1-month post-discharge, and 6 months post-discharge facilitated the examination of relative effectiveness and sustainment of gains. Results The trial was successfully implemented with data collected from 106 participants at baseline, 82 at post-intervention, and 74 at 6-month follow up. Overall, the interventions and the study design appeared feasibility with attrition primarily due to the high acuity nature of a population recruited largely through an early psychosis inpatient unit (mean age 34.6 years). Preliminary analysis suggests limited effects on community functioning though completed analyses of other metrics are pending and may provide insight into the possible mechanisms of action of this intervention should it prove to be effective. Discussion This study was designed to assess the development and dissemination of a cost-effective method for mitigating relapse risk and promoting community involvement and engagement in care. The effort to better support successful care transitions through approaches such as this is a priority area for service systems globally and contributes to the literature on peer support. While widely implemented, models of peer support have seldom been examined for effectiveness in clinical trials.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.036
GPT teacher head0.278
Teacher spread0.242 · 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 designNon-randomized trial
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

Citations1
Published2020
Admission routes1
Has abstractyes

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