MétaCan
Menu
Back to cohort
Record W4387433027 · doi:10.1002/pri.2053

Establishing the prognostic profile of patients with work‐related musculoskeletal disorders: Development and acceptability of the MAPS questionnaire

2023· article· en· W4387433027 on OpenAlexafffund
Yannick Tousignant‐Laflamme, Catherine Houle, Christian Longtin, Nathalie Desmarais, Thomas Gérard, Kadija Perreault, Émilie Lagueux, Pascal Tétreault, Marc‐André Blanchette, Hélène Beaudry, Simon Décary

Bibliographic record

VenuePhysiotherapy Research International · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité du Québec à Trois-RivièresCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleUniversité LavalCentre for Interdisciplinary Research in RehabilitationOntario Stroke NetworkCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersRéseau Provincial de Recherche en Adaptation-RéadaptationInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsRehabilitationMedicineCoping (psychology)Work-related musculoskeletal disordersPersonalizationPhysical therapyHealth careComputer-assisted web interviewingMEDLINELow back painPsychologyClinical psychologyAlternative medicineHuman factors and ergonomicsMedical emergencyComputer science

Abstract

fetched live from OpenAlex

PURPOSE: Work-related musculoskeletal disorders (WRMD) are the most common causes of disability worldwide and are associated with significant use of healthcare. One way to optimize the clinical outcomes of injured workers receiving rehabilitation is to identify and address individual prognostic factors (PF), which can facilitate the personalization of the treatment plan. As there is no pragmatic and systematic method to collect prognostic-related data, the purpose of the study was to develop and assess the acceptability of a set of questionnaires to establish the "prognostic profile" of workers with WRMD. METHODS: We utilized a multistep process to inform the acceptability of the Measures Associated to PrognoStic (MAPS) questionnaire. During STEP-1, a preliminary version of the was developed through a literature search followed by an expert consensus including a patient-advisor. During STEP-2, future users (rehabilitation professionals, healthcare administrators and compensation officers) were consulted through an online survey and were asked to rate the relevance of each content item; items that obtained ≥80% of "totally agree" answers were included. They were also asked to prioritize PF according to their usefulness for clinical decision-making, as well as perceived efficacy to enhance the treatment plan. RESULTS: The questionnaire was developed with three categories: the outcome predicted, the unique PF, and prognostic tools. Personal PF (i.e.: coping strategies, fear-avoidance beliefs), pain related PF (i.e.: pain intensity/severity, duration of pain), and work-related PF (i.e.: work physical demands, work accommodations) were identified to be totally relevant and included in the questionnaire. 84% of the respondents agreed that their patients could complete the MAPS questionnaire in their clinical setting, while 75% totally agreed that the questionnaire is useful to personalize rehabilitation interventions. CONCLUSION: The MAPS questionnaire was deemed acceptable to establish the "prognostic profile" of injured workers and help the clinicians in the treatment decision-making process.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.341
Teacher spread0.327 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuePhysiotherapy Research InternationalSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207