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Lifestyle Factors and Health01:20

Lifestyle Factors and Health

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Related Experiment Video

Updated: Jun 27, 2026

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
05:59

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

Predictors of increased physical activity in the Active for Life program.

Sara Wilcox1, Marsha Dowda, Andrea Dunn

  • 1Department of Exercise Science, Arnold School of Public Health, 921 Assembly Street, PHRC, 3rd Floor, University of South Carolina, Columbia, SC 29208, USA. swilcox@sc.edu

Preventing Chronic Disease
|December 17, 2008
PubMed
Summary

Physical activity programs like Active for Life benefit those most in need, particularly younger and less active individuals. Older adults and those with low social support may require tailored interventions for better results.

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Last Updated: Jun 27, 2026

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05:59

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Area of Science:

  • Behavioral science
  • Public health
  • Gerontology

Background:

  • Identifying participants who benefit most and least from evidence-based programs is crucial for effective targeting.
  • The Active for Life program aimed to increase physical activity in community-dwelling adults.

Purpose of the Study:

  • To examine pretest predictors of increased physical activity among participants in the Active for Life program.
  • To understand how baseline characteristics influence response to different physical activity interventions.

Main Methods:

  • A total of 1,963 participants from 9 community organizations enrolled in either a 6-month telephone-based or a 20-week group-based physical activity program.
  • Pretest surveys were completed by all participants, with 1,335 returning posttest surveys.
  • Statistical analyses tested for interactions between baseline characteristics and intervention effects on physical activity increases.

Main Results:

  • In the telephone program, younger, less active, and higher social support participants showed greater improvements.
  • In the group program, younger, less active, female, Hispanic/Latino, heavier, and those with more health conditions/osteoporosis showed greater improvements.
  • The least active participants demonstrated the most significant improvements in physical activity across both program types.

Conclusions:

  • Participant response to physical activity interventions varies significantly based on age, baseline activity, and other demographic and health factors.
  • The Active for Life program appears particularly effective for individuals most in need, such as the least active.
  • Older adults (over 75) and those with low social support in the telephone program may require specialized or more intensive interventions.