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Record W4416321925 · doi:10.2196/73818

Effect of Intolerance of Uncertainty and Resource Consumption on Therapeutic Strategies Chosen by Physiotherapists: Virtual Patient Study

2025· article· en· W4416321925 on OpenAlexaffvenue
Clémence Brun, Alexis Akinyemi, Laurène Houtin, Philippe Meidinger, Jimmy Antunes, Richard Monvoisin, Nicolas Pinsault, Oulmann Zerhouni

Bibliographic record

VenueJMIR Rehabilitation and Assistive Technologies · 2025
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsConsumption (sociology)Resource (disambiguation)Resource consumptionQuality (philosophy)Patient careQuality of life (healthcare)Resource use

Abstract

fetched live from OpenAlex

Background There is a growing interest in the influence of variables that may negatively influence the reasoning of health care professionals, namely intolerance of uncertainty, defined as health care professionals’ difficulty tolerating ambiguous situations that often trigger discomfort, overtesting, and suboptimal treatment choices, and resource consumption, defined as the ordering of unnecessary diagnostic tests that can waste resources and compromise decision‐making. Objective Our purpose was to assess the influence of intolerance of uncertainty and resource consumption on the chosen therapeutic strategy. Methods A total of 127 physiotherapists were challenged to play a simulation game and choose a therapeutic strategy for 3 cases of low back pain of increasing difficulty (easy, medium, and difficult). Their intolerance of uncertainty level and their resource consumption were measured (ie, requests for test results for each case). Results Results showed that 87.4% (111/127) of participants chose the most appropriate strategy (ie, the one in line with the strategy recommended by experts) for the easy case, 46.5% (59/127) for the medium, and 29.1% (37/127) for the difficult. For the easy case, intolerance of uncertainty and resource consumption had a negative influence on the chosen therapeutic strategy, which was less appropriate (β=–4.03, t121=–3.92, P<.001). Moreover, resource consumption among highly intolerant individuals had a more adverse influence on the chosen strategy (β=–3.42, t121=–5.09, P<.001). Such results were not found for the medium and difficult cases. Conclusions Resource consumption may have a negative influence in some cases on the treatment strategies chosen by the physiotherapists who are most intolerant of uncertainty. Future research avenues are suggested to ensure the quality of patient care concerning physiotherapists’ level of intolerance of uncertainty.

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)0.008
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.346
Teacher spread0.337 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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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