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Participants' average non-exercise activity was 36.3 milli-g/participant/minute (range = [14.3�C58.6]; SD = 9.8) across the 7 assessment days. For the sake of comparison, sedentary behavior (e.g., sitting) is associated with approximately 7 mg, walking (3.1 mph gait speed) with approximately 367 mg, and jogging (6.5 mph gait speed) with approximately 1103 mg (Anastasopoulou et al., 2014). The mean mood scores of the whole sample were 71.2 (SD = [https://en.wikipedia.org/wiki/Sitaxentan Sitaxentan] 10.5) for valence, 57.9 (SD = 10.6) for energetic arousal, and 67.7 (SD = 11.5) for calmness. The within-subject correlations between the mood components calculated applying Fisher's Z-transformation indicated that valence and energetic arousal were moderately associated (r = 0.36) across the study week. Moreover, valence and calmness were highly synchronized (r = 0.66) whereas energetic arousal and calmness were scarcely correlated (r = 0.08) within persons. Non-exercise activity was defined as the mean physical activity occurring in the 10-min intervals directly following [http://www.selleckchem.com/products/forskolin.html selleck chemical] the e-diary assessments. The intra-class correlation coefficient (��I = 0.068) revealed that 93.2% of the variance was explained by within-subject variation in non-exercise activity. A total of 49 participants (52.7%) engaged in exercise, with an average exercise duration of 186.2 min/participant/week (SD = 137.8). Predicting non-exercise activity Table ?Table11 shows the influences of various within-person (level 1) and between-person (level 2) predictors on non-exercise activity. Non-exercise activity was parameterized into 10-min intervals of physical activity following [http://www.selleckchem.com/products/cx-5461.html learn more] each e-diary prompt. Descriptively, seven of twelve predictors showed significance, namely time (p