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Record W4410861758 · doi:10.1093/ptj/pzaf077

Using a Discrete Choice Experiment to Elicit Patient Preferences for Physical Therapist Services After Surgery for Breast Cancer

2025· article· en· W4410861758 on OpenAlexaffabout
Helen McTaggart‐Cowan, Kendra Zadravec, Bolette Skjødt Rafn, Adam Raymakers, Dean A. Regier, Kristin L. Campbell

Bibliographic record

VenuePhysical Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of British ColumbiaWomen's Health Research InstituteSimon Fraser University
Fundersnot available
KeywordsBreast cancerCancerMedicinePhysical therapistPhysical therapyGeneral surgeryPsychologyInternal medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: Patients often experience challenges accessing physical therapy for breast cancer-related impairments. Eliciting patient preferences for physical therapy can inform design of patient-centered, breast cancer-focused physical therapy programming. OBJECTIVE: A discrete choice experiment (DCE) was used to elicit patient preferences for physical therapy after breast cancer surgery. DESIGN: Sequential mixed methods identified 7 attributes of physical therapy: education timing; referral method; first appointment timing; physical therapist expertise level; treatment format; treatment frequency; and annual out-of-pocket cost. Respondents chose between 2 physical therapy programs and an opt-out option. SETTINGS: The DCE was administered online. PARTICIPANTS: Participants were adults with breast cancer in Canada. MAIN OUTCOMES AND MEASURES: Responses were analyzed using a mixed logit model. Willingness-to-pay estimates were calculated as the marginal rate of substitution between each attribute level with respect to cost. RESULTS: The DCE was completed by 148 respondents (completion rate: 77.5%). Most were within 3 years post-diagnosis (54.1%), had completed post-secondary education (70.9%), and had annual family incomes over $40,000 (76.5%). Nearly half were referred to physical therapy (48.5%). Respondents preferred to be seen by a physical therapist with expertise in breast cancer (β = .368, SD = 0.091) and to receive more frequent appointments (β = -.011, SD = 0.025). CONCLUSION: The DCE was capable of eliciting patient preferences for physical therapy after breast cancer surgery. Respondents exhibited preferences for physical therapist expertise level and treatment frequency. Findings from this study will be the first step in informing development of accessible physical therapy programming that is responsive to the needs and preferences of patients with breast cancer. RELEVANCE: This work can inform design of accessible, patient-centered physical therapist services for patients with breast cancer. Receiving timely physical therapy can improve patients' physical function, quality of life, and ability to engage in life roles and activities.

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)0.000
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 score0.744
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.043
GPT teacher head0.373
Teacher spread0.331 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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