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Record W2317472596 · doi:10.1155/2016/6838596

Incorporating Family Function into Chronic Pain Disability: The Role of Catastrophizing

2016· article· en· W2317472596 on OpenAlexfundno aff
Fatemeh Akbari, Mohsen Dehghani, Ali Khatibi, Tine Vervoort

Bibliographic record

VenuePain Research and Management · 2016
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersShahid Beheshti University of Medical SciencesMcMaster University
KeywordsPain catastrophizingContext (archaeology)PsychologyChronic painDepression (economics)Clinical psychologyCognitionPhysical therapyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Background. Observers' responses to pain are recently investigated to more comprehensively explain chronic pain (CP) and disability. However, the role of family context, defined as interference in roles, communication, and problem-solving, and how (i.e., through which mechanisms) these variables contribute to CP related disability have yet to be examined. Objectives. The aim of the present study is to examine family context in relationship to pain catastrophizing, fear of movement, and depression and its role in understanding CP disability. Three different models were examined. Methods. A total sample of 142 patients with musculoskeletal chronic pain was recruited to examine the role of fear of movement, pain intensity, pain catastrophizing, and depression in relationship to family functioning as predictors of disability. Results. Findings indicated that two models showed acceptable fit, but one of them revealed superior fit indices. Results of the model with superior fit indices indicated that family dysfunction may contribute to catastrophic thinking, which, in turn, contributes to patients' disability through increasing fear of movement and depression. Discussion. The current study provides further support for the notion that the impact of emotional and cognitive variables upon CP-related disability can be better understood when we consider the social context of pain patients and family function in particular.

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)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.312
Teacher spread0.290 · 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 designOther design
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

Citations34
Published2016
Admission routes1
Has abstractyes

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