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Biased interpretations of ambiguous bodily threat information in adolescents with chronic pain

2017· article· en· W2571247728 on OpenAlexfundno aff
Lauren C. Heathcote, Sally Jacobs, Christopher Eccleston, Elaine Fox, Jennifer Y. F. Lau

Bibliographic record

VenuePain · 2017
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchAction Medical Research
KeywordsChronic painPain catastrophizingPsychologyCognitionClinical psychologyInterpretation (philosophy)MedicinePsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

Adult patients with chronic pain are consistently shown to interpret ambiguous health and bodily information in a pain-related and threatening way. This interpretation bias may play a role in the development and maintenance of pain and disability. However, no studies have yet investigated the role of interpretation bias in adolescent patients with pain, despite that pain often first becomes chronic in youth. We administered the Adolescent Interpretations of Bodily Threat (AIBT) task to adolescents with chronic pain (N = 66) and adolescents without chronic pain (N = 74). Adolescents were 10 to 18 years old and completed the study procedures either at the clinic (patient group) or at school (control group). We found that adolescents with chronic pain were less likely to endorse benign interpretations of ambiguous pain and bodily threat information than adolescents without chronic pain, particularly when reporting on the strength of belief in those interpretations being true. These differences between patients and controls were not evident for ambiguous social situations, and they could not be explained by differences in anxious or depressive symptoms. Furthermore, this interpretation pattern was associated with increased levels of disability among adolescent patients, even after controlling for severity of chronic pain and pain catastrophizing. The current findings extend our understanding of the role and nature of cognition in adolescent pain, and provide justification for using the AIBT task in longitudinal and training studies to further investigate causal associations between interpretation bias and chronic pain.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.434
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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)0.0000.000

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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.

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

Citations39
Published2017
Admission routes1
Has abstractyes

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