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Record W3134996486 · doi:10.2196/25717

Perception of Purposeful and Recreational Smartphone Use in Physiotherapy: Randomized Controlled Trial

2021· article· en· W3134996486 on OpenAlexvenueno aff
Martina Bientzle, Anne Restle, Joachim Kimmerle

Bibliographic record

VenueJMIR mhealth and uhealth · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialCompetence (human resources)Physical therapyRecreationPerceptionPhoneSmartphone applicationMedicineSession (web analytics)PsychologyApplied psychologyMultimediaSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Many people constantly use their smartphones in all kinds of situations. Often smartphones are used in a meaningful and targeted way, but frequently they are used as a pastime without any purpose. This also applies to patients and therapists in treatment situations. OBJECTIVE: The aim of this study was to investigate how purposeful smartphone use compared with recreational smartphone use (by a physiotherapist or by a patient) influenced the perception of a physiotherapeutic treatment situation. We examined the impact of smartphone use during a physiotherapy session on the perception of the physiotherapist, evaluation of attentiveness, and evaluation of smartphone use in physiotherapy in general. METHODS: Members of various music and sports clubs were invited to participate in an online randomized controlled trial. Participants were randomly assigned to one of four conditions. They watched a video in which a physiotherapeutic treatment was shown and in which a smartphone was used or not used in the following four different ways: (1) therapeutically purposeful use, (2) recreational use by the physiotherapist (looking at the phone from time to time with no therapeutic purpose), (3) recreational use by the patient, and (4) no smartphone use (control condition). After watching the video, the participants indicated their perception of the physiotherapist's professional competence, social competence, and empathetic behavior. They also rated the physiotherapist's and patient's attentiveness and evaluated the usage of smartphones generally in physiotherapy. RESULTS: The analysis included 118 participants (63 women and 55 men). When the physiotherapist used the smartphone in a purposeful way, the physiotherapist was perceived as more professionally competent (P=.007), socially competent (P=.03), and empathetic (P=.04) than if the physiotherapist used it with no therapeutic purpose. These effects occurred because recreational smartphone use by the physiotherapist was evaluated more negatively than the behavior in the control condition (professional competence: P=.001; social competence: P=.03; empathy: P=.04). Moreover, when the physiotherapist used the smartphone in a recreational way, the physiotherapist was perceived as being less attentive (P<.001). Likewise, when the patient used the smartphone in a recreational way, the patient was perceived as being less attentive (P<.001). Finally, smartphone use in physiotherapy was rated as more positive in general when the smartphone was used in a purposeful way compared with the conditions in which the physiotherapist or patient looked at the smartphone with no therapeutic purpose (P<.001). This positive evaluation occurred because purposeful use led to a more positive rating than no smartphone use (P<.001, R=0.42). CONCLUSIONS: Smartphones are only appropriate for therapists and patients if they are used directly for a therapeutic purpose. Otherwise, it is better not to use smartphones during treatment. TRIAL REGISTRATION: AsPredicted (aspredicted.org) #24740; https://aspredicted.org/blind.php?x=vv532i.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.062
GPT teacher head0.454
Teacher spread0.392 · 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 designRandomized trial
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

Citations6
Published2021
Admission routes1
Has abstractyes

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