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Generative AI in Education: Insights from Rehabilitation Sciences Students
Erin Pletcher, Travis Pollen, Robert Dekerlegand, Malachy Clancy, and Alison Bell
Background
- Generative artificial intelligence (GenAI) creates original, contextually relevant outputs that mimic human-like creativity and reasoning.
- GenAI promises to reshape health care from student and clinician education to comprehensive patient management in rehabilitation sciences.
- Insight into students’ perceptions and use of GenAI in education can help guide instructional strategies to facilitate its responsible implementation.
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Harmful or Helpful? A Content Analysis of Online ‘Yoga for Low Back Pain’ Videos
Travis Pollen, Jenni Rawlings, Lindsey Burns, Dylan Lloyd, Natalie Pifer, and Sheri Silfies
INTRODUCTION
- Low back pain (LBP) is one of the most prevalent musculoskeletal conditions worldwide (Walker, 2000).
- To self-manage LBP, yoga is often used.
- One convenient and common way to access yoga practices specifically dedicated to LBP is through the internet.
- However, the informational quality of online yoga for LBP videos has not been investigated.
PURPOSE
- To determine the prevalence and nature of potentially problematic narratives in popular online yoga for LBP videos.
METHODS
- A deductive content analysis was conducted on the 30 most-viewed yoga for LBP videos on a popular online video platform.
- The themes of interest were the purported causes of LBP, intended effects of yoga on LBP, and guidance for managing LBP through yoga and movement.
- Investigators extracted potentially problematic passages pertaining to the themes of interest from video transcripts then conducted thematic analysis to identify sub-themes.
- Two independent investigators performed each step of the analysis, with disputes resolved by a third investigator and/or discussion.
RESULTS
- Of the 30 videos analyzed, 24 videos (80.0%) contained a total of 79 potentially problematic passages.
- In terms of subthemes, the most common purported causes of LBP were tightness (10 videos, 33.3%), tension (9 videos, 30.0%), posture/alignment (6 videos, 20.0%), and sitting (5 videos, 16.7%).
- The most common intended effects of yoga were relief of LBP through stretching (13 videos, 43.3%); increasing range of motion, flexibility, or mobility (8 videos, 26.7%); and strengthening (7 videos, 23.3%).
- The most commonly implicated anatomical structures for causing or relieving LBP were the hamstrings (6 videos, 20.0%), gluteal muscles (6 videos, 20.0%), hips (4 videos, 13.3%), and hip flexors/psoas (4 videos, 13.3%).
- Guidance for managing LBP often featured kinesiophobic warnings, most commonly pertaining to forward folding (i.e., spinal flexion) (3 videos, 10.0%).
CONCLUSION
- The majority of popular online yoga for LBP videos promote outdated, reductionist biomechanical explanations and solutions for LBP.
- This bias comes at the expense of an up-to-date, evidence-based biopsychosocial depiction of LBP.
SIGNIFICANCE/NOVELTY
- This is the first content analysis of online yoga for LBP videos.
- The potentially problematic narratives in the videos, some of which have millions of views, could inadvertently elicit nocebo effects, possibly perpetuating viewers’ LBP.
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In Season Heart Rate and Session Rate of Perceived Exertion in Collegiate Softball Athletes
Erin R. Pletcher, PhD, ATC, CSCS
Introduction
- Monitoring of workload is vital to minimize risk of overuse musculoskeletal injuries in athletes while optimizing performance
- Heart rate (HR) and session rate of perceived exertion (sRPE) have been shown to be reliable measures of training intensity in steady state and interval exercise
- Relationship between training load and injury in running-based team sports has been established
- Limited studies have investigated internal load in throwing-dominant athletes despite rigorous competition season
