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EFFECTS OF AN EIGHT-WEEK AI-GENERATED RESISTANCE TRAINING PROGRAM ON ANXIETY AND PHYSICAL FITNESS: A CASE STUDY

Abstract

Anxiety disorders are highly prevalent worldwide, with women disproportionately affected, and regular physical activity has been identified as a promising non-pharmacological intervention for symptom reduction. This case study examined the effects of an eight-week, twice-weekly resistance- and mobility-based exercise program on physical fitness and anxiety symptoms in a 49-year-old woman diagnosed with generalized anxiety disorder (GAD). Baseline and post-intervention assessments included anxiety severity using the GAD-7 scale, body composition, cardiovascular fitness, muscular fitness, flexibility, balance, and. Anxiety severity decreased substantially across the intervention, supporting evidence that exercise can reduce GAD symptoms through both physiological and psychological pathways. Over the eight-week period, pre-exercise anxiety scores averaged a score 5, with a range of 2-11; post-workout anxiety scores were consistently reported to be 0 or 1. The participant also demonstrated meaningful improvements in muscular endurance (push-ups increased from 13 to 24; sit-ups from 18 to 26), handgrip strength, aerobic capacity (+1 mL·kg⁻¹·min⁻¹ VO₂max), balance, and multiple flexibility measures. Although total body mass increased by 1.4 kg, reductions in skinfold-estimated body fat (−1.1%), waist circumference (−1.1 in), and hip circumference (−1.6 in) indicated improved body composition. AI-generated programming (ChatGPT) was integrated to design progressive weekly workouts, with human oversight required to ensure the selected exercises were appropriate for the individual’s skill level. Overall, findings suggest that structured resistance training may serve as an effective adjunct to psychiatric care for individuals with GAD, producing clinically relevant improvements in fitness and anxiety within a short timeframe. Further research is needed to evaluate long-term adherence, generalizability, and the role of AI-assisted exercise prescription in clinical populations.

Acknowledgements

GGC Seed Grant; Dept of EXSC

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