Within-person association of volitional factors and physical activity: Insights from an ecological momentary...

Current health behavior models of physical activity (PA) suggest that not all PA intentions are translated into actual PA behavior, resulting in a significant intention-behavior gap (IBG) of almost 50%. These models further suggest that higher self-efficacy and specific planning can aid in decreasing this gap. However, as most evidence stems from between-person (trait level), questionnaire-based research, it is unclear how large short-term IBGs are, how self-efficacy and planning covary within-persons across time and whether they similarly predict smaller IBGs. It is likely that day-to-day changes in circumstances and barriers affect these variables thus the applicability of theoretical models is uncertain. Here, within-person prospective analyses of ecological momentary assessment (EMA) data can provide insights.

35 healthy participants (aged 23-67) completed four EMA-based questionnaires every day for three weeks. Each prompt assessed PA (retrospectively, "since the last EMA prompt"); PA intentions, planning specificity, self-efficacy, and intrinsic motivation (prospectively, "until the next EMA prompt") and momentary affect. Generalized logistic mixed-effect modeling was used to test predictors of PA.

Across the 2341 answered EMA prompts, PA intentions were not enacted in 25% of the episodes (IBG). In episodes with given intentions, PA likelihood increased with higher levels of self-efficacy, planning specificity, and intrinsic motivation. The latter two also positively predicted PA duration and intensity.

Short-term intention behavior gaps seem to be smaller than what is known from more long-term studies, most likely as individuals can anticipate the actual circumstances of PA. Further, current health behavior models show validity in explaining within-person dynamics in IBGs across time. Knowing the relevance of planning specificity, self-efficacy and intrinsic motivation for day-to-day variations in PA enactment can inform respective real-time mHealth interventions for facilitating PA.