Trial reportScientific reports2021
Artificial intelligence application versus physical therapist for squat evaluation: a randomized controlled trial.
Trial report in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Artificial Intelligence (AI) Mobile Application Versus Health Care Provider (HCP) for Bodyweight Squats: A Randomized, Blinded, Controlled Clinical Trial
Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training In Healthy And Post COVID19 Subjects
Crossover Randomized Controlled Trial to Evaluate the Efficacy and Usability of Artificial Intelligence (ChatGPT) for Health Sciences Students (AIHSS)
Who cites it
5 citing papers in PubMed.
- Artificial Intelligence in Physical Therapy: A Narrative Review of Artificial Intelligence Applications Across the Patient and Client Management Model.Health science reports · 2026Article
- The impact of AI precision feedback on college students' thinking shaping ability: mediating effect of intrinsic value identification and moderating role of critical consciousness transformation.Frontiers in psychology · 2026Article
- Usability and Efficacy of Artificial Intelligence Chatbots (ChatGPT) for Health Sciences Students: Protocol for a Crossover Randomized Controlled Trial.JMIR research protocols · 2023Article
- Effects of left thigh blood flow restriction exercise on muscle strength and golf performance in amateur golfers.Journal of exercise rehabilitation · 2023Article
- Digital therapeutics from bench to bedside.NPJ digital medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Artificial intelligence technology is becoming more prevalent in health care as a tool to improve practice patterns and patient outcomes. This study assessed ability of a commercialized artificial intelligence (AI) mobile application to identify and improve bodyweight squat form in adult participants when compared to a physical therapist (PT). Participants randomized to AI group (n = 15) performed 3 squat sets: 10 unassisted control squats, 10 squats with performance feedback from AI, and 10 additional unassisted test squats. Participants randomized to PT group (n = 15) also performed 3 identical sets, but instead received performance feedback from PT. AI group intervention did not differ from PT group (log ratio of two odds ratios = - 0.462, 95% confidence interval (CI) (- 1.394, 0.471), p = 0.332). AI ability to identify a correct squat generated sensitivity 0.840 (95% CI (0.753, 0.901)), specificity 0.276 (95% CI (0.191, 0.382)), PPV 0.549 (95% CI (0.423, 0.669)), NPV 0.623 (95% CI (0.436, 0.780)), and accuracy 0.565 95% CI (0.477, 0.649)). There was no statistically significant association between group allocation and improved squat performance. Current AI had satisfactory ability to identify correct squat form and limited ability to identify incorrect squat form, which reduced diagnostic capabilities.Trial Registration NCT04624594, 12/11/2020, retrospectively registered.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.