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Talk about life: subjective experience in early psychosis

2002· article· en· W1564315622 on OpenAlexaff
Julie Brown, R. Stadnyk, D. Whitehorn, Lili C. Kopala, Elisabeth Townsend

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2002
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsCapital District Health AuthorityDalhousie University
Fundersnot available
KeywordsPsychosisPsychologyFeelingEveryday lifePhenomenology (philosophy)Qualitative researchCompetence (human resources)Lived experienceDevelopmental psychologyPsychotherapistPsychiatrySocial psychologySociology

Abstract

fetched live from OpenAlex

Objective To explore the complex ways that early psychosis affects young people, and the things they do to look after themselves, enjoy life, and be productive, and the influence of the environmental factors. Methods An occupational life history approach, based on phenomenology, guided interviews with five participants. Results Data analysis identified eight common themes, that coalesced into the following: (1) There was no ‘life before psychosis’, (2) Life becomes increasingly narrow with the onset of symptoms after treatment, life expands again through an active learning process, which involves taking action with limited awareness about what one can actually do, (3) Maintaining productive roles limits the impact of psychosis however, few were enjoying life, had a boyfriend or girlfriend, or lived independently, (4) People with early psychosis maintain a feeling of competence, make their own decisions, and use meaningful occupations to rebuild their identities. Conclusions Qualitative research is useful in gaining an understanding into what young people with early psychosis experience in trying to recover in everyday life.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.010
Scholarly communication0.0050.004
Open science0.0010.009
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 head0.096
GPT teacher head0.450
Teacher spread0.354 · 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 designQualitative
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".

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Citations0
Published2002
Admission routes1
Has abstractyes

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