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Record W3026644075 · doi:10.3390/mti4020021

Gender Preference and Difference in Behavior Modeling in Fitness Applications: A Mixed-Method Approach

2020· article· en· W3026644075 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMultimodal Technologies and Interaction · 2020
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSquatPsychologySquatting positionCrunchPreferenceApplied psychologySocial psychologyPhysical therapyMedicineMathematicsStatistics

Abstract

fetched live from OpenAlex

In recent years, the employment of behavior models to motivate behavior change has become a global trend in fitness application design. However, there is hardly any large-scale study of these applications to understand users’ exercise-type preferences, their drivers and barriers, and the potential of employing them for gender-based tailoring. To bridge this gap, we conducted a mixed-method study among 669 participants to investigate users’ exercise-type preferences (their drivers and barriers) and how they and gender can impact users’ social-cognitive beliefs and projected performance of bodyweight exercises. Firstly, we presented to the study participants a behavior model performing push-up or squat bodyweight exercise in a fitness application and asked them to rate their perceived self-efficacy, self-regulation, outcome expectation, and projected (exercise) performance level as observers of the behavior model. Secondly, we presented the study participants with a preselected list of commonly employed exercise types in fitness applications and requested them to identify their most/least preferred, and the reasons behind their choices. Our results showed that there were differences between both genders in their exercise-type preferences, perceived self-efficacy and projected exercise performance level. Males prefer push-up, squat, crunch, plank, and chair dip the most, with effectiveness being the most important driver, followed by ease of performance and improvement of the physique, look, and appearance. On the other hand, females prefer squat, crunch, jumping jack, step up, and plank the most, with ease of performance being the most important driver, followed by improvement of the physique, look, appearance, and effectiveness. Moreover, males prefer running in place the least, while females prefer push-up the least, with perceived difficulty being the greatest barrier for both genders. Moreover, our analysis of variance supported the female’s least preference for a push-up. Females have a lower perceived self-efficacy and projected performance level for push-up than males. We discussed the implications of our findings and provided guidelines for tailoring fitness applications on the market to users’ preferences and gender.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.121
GPT teacher head0.328
Teacher spread0.207 · 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