Effectiveness of fitness-boosting strategies may be linked to
personality traits
Approach could help identify subgroups likely to benefit from
competitive, collaborative or supportive activities

Date:
October 14, 2020
Source:
PLOS
Summary:
In a randomized clinical trial, the effectiveness of different
strategies for boosting physical activity varied according
to participants' demographic, psychological, and behavioral
characteristics.



FULL STORY ==========================================================================
In a randomized clinical trial, the effectiveness of different strategies
for boosting physical activity varied according to participants'
demographic, psychological, and behavioral characteristics. Xisui Shirley
Chen formerly of the University of Pennyslvania Perelman School of
Medicine (currently at the Mount Sinai Health System in New York City)
and colleagues present these findings in the open-access journal PLOS
ONE on October 14.


========================================================================== Strategies to alter people's health behaviors -- such as increasing
their physical activity -- vary in effectiveness, likely due in part to personality and psychological traits. However, it is unclear how best
to determine which subgroups benefit most from which strategies.

Chen and colleagues addressed this issue by revisiting data from
a randomized clinical trial that showed that a competition-based
strategy to boost activity among 602 American adults with overweight or
obesity worked better than strategies based on collaboration or social
support. The researchers wondered whether these findings would hold true
for subgroups of the participants.

Using a statistical approach called latent class analysis, the scientists identified three major subgroups based on the trial participants'
demographic, psychological, and behavioral characteristics: extroverted
and motivated, less active and less social, or less motivated and
at-risk. Each participant was assigned to one of the three categories.

By reanalyzing the trial data, the researchers found that the
competition-based strategy was effective in boosting physical activity
for extroverted and motivated participants, but these participants
were less likely to stay active after the program ended. Competition-, collaboration-, and social support-based strategies were all effective
for less active and less social participants, who all stayed active
afterwards. None of the strategies were effective for less motivated
and at-risk participants.

These findings suggest that latent class analysis could aid efforts to
target behavior-changing strategies to the people most likely to benefit
from them.

Future research could help validate latent class analysis and other
statistical approaches to identify key sub-groups, as well as formally
test different strategies within identified sub-groups.

The authors add: "We demonstrated that we can identify groups
of people who have different behavioral phenotypes and that they
responded differently to a physical activity program using social
incentives. Clearly, one size does not fit all so constructing behavioral phenotypes is a promising approach to designing and targeting behavioral interventions based on meaningful individual differences."

========================================================================== Story Source: Materials provided by PLOS. Note: Content may be edited
for style and length.


========================================================================== Journal Reference:
1. Xisui Shirley Chen, Sujatha Changolkar, Amol S. Navathe, Kristin
A. Linn,
Gregory Reh, Gregory Szwartz, David Steier, Sarah Godby, Mohan
Balachandran, Joseph D. Harrison, Charles A. L. Rareshide, Mitesh S.

Patel. Association between behavioral phenotypes and response to
a physical activity intervention using gamification and social
incentives: Secondary analysis of the STEP UP randomized
clinical trial. PLOS ONE, 2020; 15 (10): e0239288 DOI:
10.1371/journal.pone.0239288 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/10/201014141111.htm

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