Responsiveness of Device-Based and Self-Report Measures of Physical Activity to Detect Behavior Change in Men Taking Part in the Football Fans in Training (FFIT) Program

Responsiveness of Patient-Reported and Device-Based Physical Activity Measures: Secondary Analysis of Four Randomized Trials

PURPOSE

This study aimed to compare the responsiveness of patient-reported and device-based instruments within four physical activity trials.

METHODS

This was a secondary analysis of four randomized trials that used both a patient-reported outcome measure (the Incidental and Planned Exercise Questionnaire (IPEQ)) and a device-based instrument (ActiGraph or ActivPAL) to measure physical activity. The four trials included were (i) Activity and MObility UsiNg Technology (AMOUNT), digitally enabled exercises in those undertaking aged care and neurological rehabilitation; (ii) Balance Exercise Strength Training at Home, home-based balance and strength exercises in community-dwelling people 65 yr or older; (iii) Coaching for Healthy Ageing (CHAnGE), physical activity coaching and fall prevention intervention in community-dwelling people 60 yr or older; and (iv) Fitbit trial, fall prevention and physical activity promotion with health coaching and activity monitor in community-dwelling people 60 yr or older. We estimated treatment effects for all variables within each physical activity instrument using regression analyses and expressed results as effect sizes (ES).

RESULTS

Overall, device-based instruments were more responsive among healthy older adults (ES range, 0.01 to 0.32), whereas the IPEQ was more responsive among adults requiring rehabilitation (ES range, -0.06 to 0.35). Both the IPEQ and device-based instruments were more responsive in trials that promoted walking via coaching participants to increase their daily steps (AMOUNT (ES range, -0.06 to 0.35), CHAnGE (ES range, -0.24 to 0.22), and Fitbit trial (ES range, -0.23 to 0.32)). Individual variables within the IPEQ and device-based instruments varied in their responsiveness (ES range, -0.13 to 0.20).

CONCLUSIONS

Both the IPEQ and device-based instruments are able to detect small changes in physical activity levels. However, responsiveness varies across different interventions and populations. Our findings provide guidance for researchers and clinicians in selecting an appropriate instrument to measure changes in physical activity.

Primary Care and Physical Literacy: A Non-Randomized Controlled Pilot Study to Combat the High Prevalence of Physically Inactive Adults in Austria

The multidimensional concept of physical literacy is fundamental for lifelong physical activity engagement. However, physical literacy-based interventions are in their infancy, especially among adults. Therefore, the purpose of this pilot study was to assess the association of a physical literacy-based intervention with changes in self-reported physical literacy among inactive adults. A non-randomized controlled study (2 × 2 design) was conducted, comparing pre- vs. postintervention. Twenty-eight inactive healthy participants in the intervention group (89% female, 53 ± 10 years) entered a physical literacy-based intervention once weekly for 14 weeks. The non-treated control group consisted of 22 inactive adults (96% female, 50 ± 11 years). Physical literacy was evaluated with a questionnaire encompassing five domains: physical activity behavior, attitude/understanding, motivation, knowledge, and self-efficacy/confidence. ANOVA models were applied to evaluate changes by time and condition. Following the intervention, significant improvements were seen for overall physical literacy and in four out of five physical literacy domains, including physical activity behavior, attitude/understanding, knowledge, and self-efficacy/confidence (all p < 0.01, Cohen's d = 0.38-0.83). No changes by time x condition were found for motivation. The physical literacy-based intervention applied in this study may be a promising approach to help inactive adults to adopt an active lifestyle.