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Record W1985265451 · doi:10.1080/16506073.2011.632434

Can We Modify Maladaptive Attributions for Fatigue?

2012· article· en· W1985265451 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCognitive Behaviour Therapy · 2012
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAttributionAnxietyIntervention (counseling)PsychologyInsomniaSleep (system call)Clinical psychologySleep disorderPsychiatrySocial psychologyComputer science

Abstract

fetched live from OpenAlex

Research has shown that those with insomnia focus primarily on their sleep as a cause of daytime fatigue rather than the multitude of other possible causes of fatigue. This can create sleep-related anxiety and further perpetuate the sleep disturbance. In order to lessen the increased focus on sleep, the present study investigated whether people could learn to consider other attributions for fatigue via an information-based manipulation. Undergraduate students (N = 88) were randomized to two information groups: They either received information about common factors that could explain daytime fatigue (the fatigue information condition) or received generic sleep-related information (the control condition). Each group was tested pre- and post-intervention. Fatigue information participants were significantly more likely to consider non-sleep-related attributions for fatigue at post-intervention, relative to control participants. These results demonstrate that attributions for fatigue may be amenable to change via an information-based intervention; thus, this research explores a preliminary step toward investigating refinements to insomnia treatments.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.109
GPT teacher head0.371
Teacher spread0.262 · 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