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Record W4283738281 · doi:10.1176/appi.ps.202000641

Young Adults’ Perspectives on Factors Related to Relapse After First-Episode Psychosis: Qualitative Focus Group Study

2022· article· en· W4283738281 on OpenAlexaffabout
Shalini Lal, Anna Czesak, Philip G. Tibbo, Ridha Joober, Richard Williams, Ranjith Chandrasena, Nicola Otter, Ashok Malla

Bibliographic record

VenuePsychiatric Services · 2022
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsWorryPsychological interventionPsychologyFocus groupSocial supportClinical psychologyIntervention (counseling)Coping (psychology)PsychiatryPsychosisManiaMedicineAnxietyBipolar disorderPsychotherapistMood

Abstract

fetched live from OpenAlex

Relapse after first-episode psychosis (FEP) is a major clinical challenge for specialized early intervention services. Understanding patient perspectives on factors contributing to relapse can inform the development of risk assessments and preventive interventions. The objective of this study was to identify factors that may contribute to and prevent relapse from the perspectives of patients receiving services for FEP. Data from 25 participants across four focus groups in Canada were analyzed with a descriptive content analysis approach. Twelve factors were identified, of which four (social environment, technology use, medication, and lifestyle behaviors) had both contributory and preventive roles. In descending order of frequency, risk factors for relapse included substance use; unsupportive social environment; technology use; taking and not taking medication; lack of sleep; work, career, or school stress; significant life events; symptoms of depression or mania; generalized worry; and financial stress. Preventive factors consisted of having a supportive social environment, using technology, taking medication, using coping strategies, and engaging in healthy lifestyle behaviors and meaningful activities. These findings extend the literature on relapse vulnerability and protective factors. Importantly, the factors identified in this study are modifiable, and thereby provide insights for the development and optimization of relapse risk assessments and preventive interventions.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.320
Teacher spread0.307 · 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.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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