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Record W2403996066 · doi:10.1111/eip.12349

Post‐traumatic growth following a first episode of psychosis: a scoping review

2016· review· en· W2403996066 on OpenAlexafffund
Gerald Jordan, Megan A. Pope, Angella Lambrou, Ashok Malla, Srividya N. Iyer

Bibliographic record

VenueEarly Intervention in Psychiatry · 2016
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsPsychologyReligiosityClinical psychologyPsychosisPerceptionSet (abstract data type)PsychotherapistPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

AIM: A first-episode psychosis (FEP) is a traumatic experience that can often result in great suffering. However, in addition to suffering, persons affected by FEP may also experience post-traumatic growth (PTG) or the perception that good has followed psychosis. Although much is known concerning the negative outcomes following FEP, little attention has been given to the state of scientific knowledge on PTG following FEP. The aim of this study is to determine the state of knowledge concerning PTG following FEP to help set the stage for a full systematic review. METHODS: A scoping review was conducted following six steps: identifying the research question and relevant studies, selecting studies, charting the data, coding and summarizing results and consulting with relevant stakeholders regarding the findings. RESULTS: Post-traumatic growth following FEP was described mostly as following the process of recovery and primarily, in qualitative articles. Themes related to PTG included developing positive character traits, making positive lifestyle changes, developing stronger connections with others, integrating the FEP with the self, experiencing greater religiosity and appreciating life more. CONCLUSIONS: In addition to the negative aftermath of FEP, PTG may also occur. Evidence of PTG following FEP will be examined in a systematic review focused on the recovery and qualitative literature.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.399
Teacher spread0.359 · 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 designSystematic review
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

Citations27
Published2016
Admission routes2
Has abstractyes

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