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Record W3007070994 · doi:10.1002/cpp.2433

Assessment and treatment of sleep problems in bipolar disorder—A guide for psychologists and clinically focused review

2020· review· en· W3007070994 on OpenAlexaff
Emma Morton, Greg Murray

Bibliographic record

VenueClinical Psychology & Psychotherapy · 2020
Typereview
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMoodBipolar disorderPsychologyClinical psychologyIntervention (counseling)CognitionPsychiatryPopulationSleep (system call)Sleep disorderPsychotherapistMedicine

Abstract

fetched live from OpenAlex

Sleep problems are highly prevalent in bipolar disorder (BD) and constitute an important therapeutic focus in this population: They are highly impairing and distressing, are an area of subjective importance to consumers, and likely play a role in predicting/triggering mood episodes. The aim of this review is to orient psychologists and psychotherapists to current research relevant to their clinical practice with people with BD, including (a) the prevalence and presentation of sleep problems, (b) the impacts and correlates of impaired sleep, and (c) the relationship between sleep problems and mood symptoms (including the predictive/triggering role of sleep in BD mood relapses). Detailed recommendations for assessment and cognitive-behavioural intervention strategies for use in BD are described. It will be concluded that although some sleep problems and comorbidities require interdisciplinary collaboration, a range of evidence-informed strategies can be effectively and appropriately applied by clinical psychologists and psychotherapists.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.002

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 head0.202
GPT teacher head0.549
Teacher spread0.347 · 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 designNot applicable
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

Citations28
Published2020
Admission routes1
Has abstractyes

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