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Record W4415438959 · doi:10.1302/1358-992x.2025.10.136

A DIGITAL EXERCISE PROGRAMME IMPROVED PATIENT ENGAGEMENT DURING REHABILITATION FOLLOWING ANTERIOR CRUCIATE LIGAMENT RECONSTRUCTION

2025· article· en· W4415438959 on OpenAlexaff
Jürgen Fritz, S. Mark Heard, Greg Buchko, Laurie A. Hiemstra, Michaela Kopka, Sarah Kerslake

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsBanff Centre
Fundersnot available
KeywordsRehabilitationAnterior cruciate ligament reconstructionAttendanceExercise prescriptionAnterior cruciate ligamentMedical prescriptionPatient satisfaction

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate patient engagement with, and acceptability of, a digital exercise program for primary anterior cruciate ligament (ACL) reconstruction during the first 6-months post-operative. A secondary purpose was to determine if engagement with the digital exercise program also improved overall patient involvement in rehabilitation. Patients that underwent primary ACL reconstructive (ACLR) surgery between 2019 and 2021 were enrolled in PhysioAid and received an email-delivered digital ACL rehabilitation exercise program. The customised ACLR PhysioAid program was provided in addition to the standard rehabilitation protocol. The digital program delivered 12 phases of exercise prescription videos every 2 & 3 weeks for 35 weeks post-operative. Patient engagement with PhysioAid was measured by the number of exercise prescriptions opened. Patient acceptability of PhysioAid was evaluated via an online questionnaire. Overall patient engagement was measured by number of email queries related to rehabilitation, completion of 6-month post-operative ACL-QOL questionnaire, and attendance at the 6-month post-operative functional testing clinic. Data was descriptively analysed using means, SD and qualitative measures. Four hundred and fifty patients were enrolled in the PhysioAid program. Two hundred and eighty-nine patients (64%) accessed at least one exercise prescription, with 49% accessing 6 or more of the 12 prescriptions. Overall, 242 patients (54%) responded to the online survey, with 221 (49%) returning completed questionnaires. Of the patients that accessed PhysioAid, 62% responded to the online questionnaire, compared with 39% that did not access any exercise prescriptions. Of those respondents, 80% responded they followed the PhysioAid exercise prescriptions. In addition, 75% of respondents indicated that they found the prescriptions helpful in someway, with 86% responding they accessed the prescriptions over the 6-month period with a frequency of about 30% or greater. Most respondents (61%) also agreed that the PhysioAid exercise prescriptions were an essential part of their rehabilitation program due to COVID-19 restrictions. Patients that accessed PhysioAid exercise prescriptions were more likely to send email queries regarding their rehabilitation compared to those that didn't access the program (24.2% versus 14.9%), were more likely to complete their 6-month post-operative ACL-QOL questionnaire (40.8% versus 28.0%), and attend their scheduled 6-month functional testing clinic (49.8% versus 39.1%). The addition of a digital rehabilitation program to the standard-of-care protocol increased patient engagement with their rehabilitation. Patients who accessed the exercise prescriptions were more likely to attend the 6-month post-operative appointment and complete the ACL-QOL. Further research is needed to determine if the incorporation of a digital exercise program during ACLR rehabilitation improves patient outcomes.

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 score0.917
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.005
GPT teacher head0.239
Teacher spread0.234 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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