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Personalized multicomponent exercise programs using smartphone technology among older people: protocol for a

Yael Netz1, Esther Argov2, Ziv Yekutieli3

  • 1The Academic College at Wingate, 4209200, Netanya, Israel. neyael@wincol.ac.il.

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Summary
This summary is machine-generated.

This study tests a personalized exercise program for older adults, delivered via smartphone, against standard guidelines. It aims to improve fitness by tailoring workouts to individual needs.

Keywords:
Artificial intelligenceExercise prescriptionIndividualized programMotor fitnessRemote assessment

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Area of Science:

  • Gerontology
  • Exercise Physiology
  • Digital Health

Background:

  • Updated World Health Organization (WHO) exercise guidelines for older adults require personalized adjustments for age-related fitness variability.
  • A novel, validated tool was developed for remote assessment of motor fitness components (balance, strength, flexibility) and personalized exercise prescription via smartphone.
  • A prospective randomized controlled trial is designed to compare this remote, personalized program against WHO guidelines and no intervention.

Purpose of the Study:

  • To evaluate the effectiveness of a remotely delivered, personalized multicomponent exercise program for older adults.
  • To compare the personalized program's impact on motor fitness against standard WHO exercise recommendations and a control group.
  • To assess the value of individualized motor fitness assessment in generating tailored exercise interventions for community-dwelling older adults.

Main Methods:

  • A prospective randomized controlled trial involving 300 healthy, independent older adults (≥65 years).
  • Participants are assigned to an 8-week personalized multicomponent exercise program, WHO guideline-based counseling, or no intervention.
  • Primary outcome is participant fitness level, measured by 42 digital markers from 10 motor fitness tests at baseline, 4, 8, and 12 weeks.

Main Results:

  • The study is designed with 99% power to detect moderate to high effect sizes (Cohen's f=0.25, 0.40).
  • Data collection includes baseline, mid-trial, trial-end, and follow-up measurements of motor fitness.
  • The primary outcome operationalized as 42 digital markers from 10 motor fitness measures.

Conclusions:

  • The study will elucidate the benefits of individualized motor fitness assessment for older adults.
  • It will determine the efficacy of remotely delivered, personalized multicomponent exercise programs.
  • Findings will inform the optimal application of exercise guidelines for aging populations.