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Record W2946450607 · doi:10.1016/j.schres.2019.05.012

Predictors of persisting psychotic like experiences in children and adolescents: A scoping review

2019· review· en· W2946450607 on OpenAlexfundno aff
János Kálmán, Michaeline Bresnahan, Thomas G. Schulze, Ezra Susser

Bibliographic record

VenueSchizophrenia Research · 2019
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
FundersBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftYork University
KeywordsPsychologyDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Subclinical psychotic experiences (PLEs) are among the frequently reported mental health problems in children/adolescents. PLEs identified in cross sectional studies of children/adolescents are associated with current and future mental health problems. These associations are stronger for PLEs that persist over time. Hence, it could be useful to examine which children/adolescents with PLEs at a first assessment (baseline) are more likely to have PLEs at subsequent assessments. METHODS: We conducted a scoping review of studies that examined whether characteristics of children/adolescents (≤18 years) with PLEs at baseline predict whether PLEs are likely to be persistent or remittent at subsequent assessments. We included studies published between January 2002 and December 2017, conducted on general child/adolescent populations of ≥300 individuals, that provided data on PLEs for at least 2 time points, had available follow-up data for ≥50% of those assessed for PLEs at baseline and targeted for follow-up examination, and reported the differences between individuals with PLEs that persisted or remitted during the study period. RESULTS: Six studies met our criteria. Each of them investigated a wide range of baseline characteristics but no predictor of persistence was replicated. CONCLUSIONS: Our knowledge about which children/adolescents with PLEs at an initial assessment are likely to have persistent PLEs at subsequent assessments is sparse. A handful of predictors of persistent PLEs have been investigated so far, and none replicated. A better understanding of these predictors would be an important complement to investigations examining the evolution of PLEs and of mental health problems in children/adolescents.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.633
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.106
GPT teacher head0.433
Teacher spread0.327 · 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

Citations47
Published2019
Admission routes1
Has abstractyes

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