Analytical Approach
The mean within-participant changes in AAM, health and well-being outcomes, and affective and behavioral processes from the baseline period to the treatment period were calculated. First, for each participant separately, all baseline measurements of a particular variable were averaged, all treatment measurements were averaged, and the resulting averages were subtracted (treatment average – baseline average) to obtain the within-participant change score. Second, within-participant change scores were averaged per condition, and 95% CIs were calculated.In addition, a multilevel longitudinal analysis was conducted to examine changes in average levels of each variable from the baseline period to the treatment period. For each variable, 2 models were fitted. Model 1 examined changes within the accurate step count condition from the baseline period to the treatment period and compared changes in the accurate step count condition (reference group) with changes in the deflated and inflated step count conditions. Model 2 compared changes from the baseline period to the treatment period in the accurate step count condition (reference group) with the meta-mindset intervention condition. This 2-model approach was chosen to account for the slight differences in what counted as baseline period for the different interventions. The step count manipulations started on day 8, the day after the first weekly survey, so that this survey was part of the baseline period. However, the meta-mindset intervention started on day 7 as part of the first weekly survey so that this survey was already part of the treatment period. AAM and affective and behavioral processes were theorized as mechanisms explaining changes in health. Thus, only their weekly (not onboarding or offboarding) measurements were used in model 1. However, because of the timing of the meta-mindset intervention, model 2 included onboarding (the only baseline measurements of AAM, affect, diet, smoking, and alcohol consumption), weekly, and offboarding measurements for these variables.To account for the within-subject design, we included by-participant random intercepts and random slopes for the period. For models predicting changes in health and well-being outcomes, which were measured only twice, no random slopes were included because of a lack of 