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Record W2588269300 · doi:10.4088/jcp.15m09815

The Relationship Between Stressful Life Events and Axis I Diagnoses Among Adolescent Offspring of Probands With Bipolar and Non-Bipolar Psychiatric Disorders and Healthy Controls

2017· article· en· W2588269300 on OpenAlexaff
Lisa Pan, Tina R. Goldstein, Brian Rooks, Mary Beth Hickey, Jie Fan, John Merranko, Kelly Monk, Rasim Somer Diler, Dara Sakolsky, Satish Iyengar, Benjamin I. Goldstein, David J. Kupfer, David Axelson, David A. Brent, Boris Birmaher

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2017
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Institute of Mental Health
KeywordsOffspringProbandBipolar disorderPsychologyMoodMood disordersPsychiatryMedicinePregnancyBiologyAnxietyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Previous studies have explored the role of stressful life events in the development of mood disorders. We examined the frequency and nature of stressful life events as measured by the Stressful Life Events Schedule (SLES) among 3 groups of adolescent offspring of probands with bipolar (BD), with non-BD psychiatric disorders, and healthy controls. Furthermore, we examined the relationship between stressful life events and the presence of DSM-IV Axis I disorders in these offspring. Stressful life events were characterized as dependent, independent, or uncertain (neither dependent nor independent) and positive, negative, or neutral (neither positive nor negative). METHODS: Offspring of probands with BD aged 13-18 years (n = 269), demographically matched offspring of probands with non-BD Axis I disorders (n = 88), and offspring of healthy controls (n = 81) from the Pittsburgh Bipolar Offspring Study were assessed from 2002 to 2007 with standardized instruments at intake. Probands completed the SLES for their offspring for life events within the prior year. Life events were evaluated with regard to current Axis I diagnoses in offspring after adjusting for confounds. RESULTS: After adjusting for demographic and clinical between-group differences (in probands and offspring), offspring of probands with BD had greater independent (χ² = 11.96, P < .04) and neutral (χ² = 17.99, P < .003) life events compared with offspring of healthy controls and greater number of more severe stressful life events than offspring of healthy controls, but not offspring of probands with non-BD. Offspring of BD probands with comorbid substance use disorder reported more independent stressful life events compared to those without comorbid substance use disorder (P = .024). Greater frequency and severity of stressful life events were associated with current Axis I disorder in offspring of both probands with BD and probands with other Axis I disorders regardless of dependency or valence. Greater frequency and severity of stressful life events were associated with greater current Axis I disorder in all offspring. CONCLUSIONS: Offspring of probands with BD have greater exposure to independent and neutral life events than offspring of healthy controls. Greater frequency and severity of stressful life events were associated with Axis I disorder in offspring of both BD and non-BD affected probands.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.362
Teacher spread0.322 · 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 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

Citations25
Published2017
Admission routes1
Has abstractyes

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