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Exploring response patterns to motivational messages supporting physical activity: A latent class analysis
ABSTRACT
Background:
In mobile healthcare, text messages play an important role in improving physical activity. Recent studies have developed message banks based on theories, including the behaviour change technique (BCT) taxonomy. However, little evidence is available for individual differences (i.e. who responds to what BCTs recommended in messages), which are crucial for optimizing message delivery.
Objective:
We investigated how individuals perceive messages supporting physical activity and what clusters of individuals are identified by their responses.
Methods:
Japanese-speaking adults (N = 2859; mean age = 54.5, SD = 17.5; 1486 women) were presented with messages conveying different BCTs, and rated how motivational each message was. The motivation ratings were subjected to latent class analysis to identify clusters of individuals per motivation rating.
Results:
Seven clusters were identified through analysis. One cluster gave the highest ratings to any messages, and two others showed high ratings, but some preferences for specific BCTs (e.g. information about social and environmental consequences). Another cluster showed variable ratings across messages (with salience of consequences rated as the most motivational), and the remaining three gave overall low ratings and typically included inactive individuals in the pre-action stages.
Conclusions:
These results highlight individual differences in perceived motivations across BCTs, informing what BCTs should be prioritized in delivery. The practical implications for message tailoring are also discussed.
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