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Record W2035121790 · doi:10.3109/09638288.2012.748835

A case of mistaken identity? The role of injury representations in chronic musculoskeletal pain

2013· article· en· W2035121790 on OpenAlexafffund
Fergal O’Hagan, Marie‐France Coutu, Raymond Baril

Bibliographic record

VenueDisability and Rehabilitation · 2013
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailUniversité de SherbrookeTrent University
FundersCanadian Institutes of Health Research
KeywordsMusculoskeletal painChronic painIdentity (music)Physical therapyPhysical medicine and rehabilitationPsychologyRehabilitationMedicineAesthetics

Abstract

fetched live from OpenAlex

PURPOSE: To explore how patients construe bodily injury, examine how injury representations change over the course of a rehabilitation program and how injury representations influence adaptation and recovery trajectories. METHODS: A case study method was used with qualitative interviews as the primary data source. Qualitative semi-structured interviews were conducted three times over the course of a 12-week intensive interdisciplinary occupational rehabilitation program with one interview 1 month following discharge. To capture changes in rehabilitation trajectories, data analysis employed a narrative approach informed by Bury (progression, regression, and stability) and Frank's (chaos, restitution, and quest) approaches. RESULTS: Sixteen patients (10 men and 6 women) were disabled as a result of persistent pain and impairment from a variety of work injuries participated. Progression/restitution narratives were characterized by the transformation of bone and nerve problems to include soft tissue elements. These participants expanded their scope of injury representations and appraisal to include neurobiological aspects of chronic pain and dimensions of psychosocial well-being, and linked diagnostic representations to self-management strategies in a functional manner. CONCLUSION: Body representations of injury morphology and pain mechanisms are important objects of fear and acceptance for injury recovery. Active strategies that encourage a "hands on" understanding of diagnosis may prove most effective in treating persistent pain. IMPLICATIONS FOR REHABILITATION: Patient representations of pain and body injury are windows into the personal experience of individuals with chronic musculoskeletal pain. When patients enter programs, practitioners need to assess what the patient believes is wrong with their body and what will be helpful in rectifying the problem. Based on their initial assessment, practitioners need to direct education and activity toward shifting patient beliefs to include elements of soft tissue and a broader scope of pain sensitization and psychological impact. Activity-based intervention is essential for creating coherence between injury and pain representations and coping action. During rehabilitation, practitioners need to monitor patient beliefs about their injury. Shifting beliefs are signs that the patient is adopting a more adaptive cognitive stance toward their injury. Lack of movement indicates that the message is not getting through and the approach needs to be modified. When working with patients to transform beliefs, a collaborative approach might be best to increase trust and reduce reactance.

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)0.010
metaresearch head score (Gemma)0.035
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.035
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0080.026
Scholarly communication0.0070.010
Open science0.0010.009
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.298
Teacher spread0.291 · 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

Citations10
Published2013
Admission routes2
Has abstractyes

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