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Record W2921440017 · doi:10.1080/24740527.2019.1591823

The Development of a Novel Interdisciplinary Chronic Pelvic Pain Program

2019· article· en· W2921440017 on OpenAlexaff
Laura Katz, Adria Fransson, Ramesh Zacharias

Bibliographic record

VenueCanadian Journal of Pain · 2019
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsPelvic painChronic painMedicinePhysical therapySurgery

Abstract

fetched live from OpenAlex

Introduction: Chronic pelvic pain (CPP) is a significant issue for women, with approximately 14% of women experiencing CPP at least once in their life. CPP is chronic and debilitating associated with significant costs and morbidity, and its etiology is multifactorial often complicating medical treatment and symptom management. Best practice guidelines recommend an interdisciplinary and biopsychosocial approach to treatment. The aim of this poster is to describe the ongoing development and evaluation of a novel Interdisciplinary CPP Program at the Michael G. DeGroote Pain Clinic. Methods: Female patients were referred to the Program from community gynecologists and urologists, and were scheduled for an orientation to learn about the Program. Patients were then scheduled for an interdisciplinary assessment (psychology, physiotherapy, internal pelvic examination), and if appropriate were scheduled for the Program. The Program occurs once a week for 8 weeks, and each day consists of physiotherapy, psycho-education, goal setting, and mindfulness. Preliminary Results & Discussion: Ninety-four referrals have been received since January 2018. Eight out of nine patients completed the first Program, and assessments and programs are ongoing. In terms of the demographics of the first sample of patients, the mean age was 33.3 ± 6.2, they last worked 2.8 ± 2.2 years ago, their pain started 10.1 ± 7.5 years ago, with predominantly an underlying diagnosis of endometriosis (77.8%). Ninety percent reported a history of anxiety/panic and depression. Upon discharge, all outcomes measures showed improvements. As the Program develops, future research will evaluate the statistical changes in outcomes, and will continue to support women coping with CPP.

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)0.005
metaresearch head score (Gemma)0.000
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 score0.939
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
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)0.0000.000

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 head0.011
GPT teacher head0.286
Teacher spread0.275 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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