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Record W4408080272 · doi:10.1101/2025.02.27.25323019

Anatomy of a Failure: A Retrospective Evaluation of a Cognitive Bias Modification Intervention to Promote Physical Activity in Cardiac Rehabilitation

2025· preprint· en· W4408080272 on OpenAlexaff
Layan Fessler, Silvio Malatgliati, Philippe Meyer, Axel Finckh, Stéphane Cullati, David Sander, Malte Friese, Reínout W. Wiers, Ata Farajzadeh, Christophe Luthy, Philippe Sarrazin, Boris Cheval

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of Ottawa
FundersUniversité de GenèveUniversité de LyonHôpitaux Universitaires de GenèveSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsRehabilitationIntervention (counseling)Physical medicine and rehabilitationCognitionPhysical therapyMedicineHeart failurePsychologyNeuroscienceCardiologyNursing

Abstract

fetched live from OpenAlex

Abstract Objectives Promoting regular physical activity (PA) is essential in cardiac rehabilitation; yet many patients exhibit low levels of PA. In January 2022, the Improving Physical Activity (IMPACT) trial, a randomised controlled trial at the University Hospital of Geneva, was launched to promote PA in cardiac patients by targeting automatic approach tendencies towards exercise-related stimuli through a cognitive bias modification (CBM) intervention. This article examines the limited acceptance of this intervention, identifies potential barriers, and proposes strategies to improve future implementations. Design Retrospective evaluation of a pre-registered clinical trial. Setting The intervention was conducted in a cardiac rehabilitation centre in Switzerland. Participants. Sixty-eight cardiac rehabilitation patients ( M age = 57.76, SD = 10.76 years, 87% male). Intervention Patients received 12 CBM sessions over 6 weeks, designed to target approach-avoidance tendencies to exercise-related stimuli and improve PA levels. Primary and secondary outcome measures Acceptance was assessed using behavioural (e.g., enrolment and engagement rates), cognitive (e.g., perceived effectiveness), and emotional (e.g., affective evaluation) indicators. The cognitive and emotional indicators were derived from verbal feedback documented by the research assistants based on patients’ reactions during the intervention period. These observations do not constitute qualitative research as defined by methodological standards; they were informal notes provided by RAs during intervention delivery and were not collected or analysed using qualitative research methods. Results Of the 352 patients initially required, only 68 (19%) were enrolled. Among these 68, 63% completed the minimum number of CBM sessions, and 25% completed accelerometer-based PA measures during the week following discharge. These behavioural indicators of low acceptance showed cognitive (e.g., scepticism about the task relevance and perceived effectiveness of the intervention) and emotional (e.g., feelings of boredom and disinterest) barriers. Conclusion The low engagement and acceptance observed in the IMPACT trial reveal highlight several key barriers, such as perceived task irrelevance, task monotony, and task boredom, that undermine the acceptance and feasibility of this digital CBM intervention in cardiac rehabilitation. These findings emphasise the importance of designing patient-centred interventions, ensuring their seamless integration into clinical contexts, and conducting qualitative research prior to implementation to anticipate potential barriers. Strengths and limitations of this study This study uses a multidimensional assessment of acceptance by examining behavioural, cognitive, and emotional indicators of a cognitive-bias modification intervention. Including informal verbal feedback from research assistants (RAs) offer valuable insights into patients’ experience and perception of the intervention in a real-world cardiac rehabilitation setting. Acceptance was assessed primarily through RAs’ verbal feedback collected during intervention delivery, rather than direct patients’ reports or standardised measures, which may introduce recall bias and limit the reliability of the findings.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.057
GPT teacher head0.439
Teacher spread0.382 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
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

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