MétaCan
Menu
Back to cohort
Record W4412078046 · doi:10.1080/17581869.2025.2529773

Evaluating patient satisfaction and perceived accuracy in questionnaires completed before vs. during a pain clinic visit

2025· article· en· W4412078046 on OpenAlexaff
Guy Feigin, Elad Dana, Victoria Bains, Anuj Bhatia

Bibliographic record

VenuePain Management · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicinePatient satisfactionPhysical therapyFamily medicineNursing

Abstract

fetched live from OpenAlex

Introduction Effective assessment is essential for planning treatment in chronic pain management. This study compared patient satisfaction and perceived data accuracy between completing pre-assessment questionnaires at home versus in the clinic prior to a neuromodulation consultation.Methods In this prospective, single-center study, adult patients referred for neuromodulation assessment were randomized to complete intake questionnaires either at home (“Home” group) or upon arrival at the clinic (“Clinic” group). Prior the appointment, all participants completed a satisfaction survey assessing perceived accuracy, time efficiency, and preference.Results Forty-two patients participated (Home: 17; Clinic: 25). Overall satisfaction was not significantly different between groups (88.2% vs. 64%, p = 0.202). However, perceived response accuracy (88.2% vs. 36%, p < 0.001) and time efficiency (82.4% vs. 28%, p = 0.002) were significantly higher in the Home group. More than half of Clinic group participants stated they would have preferred to complete the questionnaires at home (52% vs. 5.9%, p = 0.001).Conclusions Completing pre-assessment questionnaires at home resulted in higher perceived accuracy and time efficiency without compromising satisfaction. These findings support incorporating remote pre-visit assessments into chronic pain clinic workflows to optimize patient experience.Clinical trial registration www.clinicaltrials.gov identifier is NCT03852381.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.516

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 head0.016
GPT teacher head0.339
Teacher spread0.323 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuePain ManagementSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207