The objectives for this assignment are (1) to increase your familiarity with phenomena at the intersection of physical activity, motivation, and well-being, (2) to familiarize you with methods used to measure those phenomena, (3) to develop your skills in handling and interpreting data, and (4) to develop your professional/scientific writing skills.
As a class, we completed two 7-day measurement bursts about our daily experiences, one in September and another a month later in October. A deidentified dataset summarizing your weekly data is posted on Canvas as an Excel file. You will now use that class dataset to write a written report.
Evaluation. Completing daily reports counts for 10% of your final course grade. You had to complete at least 5 each week to earn full credit for the week and we averaged your score for each week to calculate your participation score). The written report will count for 20% of your course grade. Requirements for that report are detailed below.
Dataset. The dataset includes the following variables (.x at the end of each variable name represents whether the data are from week 1 or week 2):
• Physical activity scores for each week
o metmin_mean.x: Total physical activity volume (MET•min)
o ipaq_vig_mean.x: Average daily duration of vigorous intensity each week (minutes)
o ipaq_mod_mean.x: Average daily duration of moderate intensity each week (minutes)
o ipaq_walk_mean.x: Average daily duration of walking (light-intensity physical activity) each week (minutes)
• Sedentary behavior (sitting) scores for each week
o sit_total_mean.x: Average daily duration of total sedentary behavior (sitting time)
o sit_travel_mean.x: Average daily duration of total sedentary behavior (sitting time)
o sit_school_mean.x: Average daily duration of total sedentary behavior (sitting time)
o sit_tv_mean.x: Average daily duration of total sedentary behavior (sitting time)
o sit_computer_mean.x: Average daily duration of total sedentary behavior (sitting time)
o sit_leisure_mean.x: Average daily duration of total sedentary behavior (sitting time)
• Motivation
o intentions_mean.x: Average daily intentions to engage in guidelines-level of moderate-to-vigorous intensity physical activity rated on a scale ranging from 1 (strongly disagree) to 7 (strongly agree), higher scores represent stronger intentions to engage in a guidelines-based dose of physical activity
o schedeff_mean.x: Average daily scheduling efficacy (belief that you can accumulate a guidelines-level of moderate-to-vigorous intensity physical activity) rated on a scale ranging from 0 (not at all confident) to 100 (extremely confident), higher scores represent stronger scheduling efficacy beliefs
o barrierseff_mean.x: Average daily barriers efficacy (belief that you can overcome barriers to engaging in a guidelines-level of moderate-to-vigorous intensity physical activity) rated on a scale ranging from 0 (not at all confident) to 100 (extremely confident), higher scores represent stronger barriers efficacy beliefs
• Well-being scores for each week
o lifesat_mean.x: Average daily life satisfaction rating on a scale ranging from 1 (strongly agree that life is satisfying) to 7 (strongly disagree that life is not satisfying). We reversed this score so that higher values in the dataset represent greater life satisfaction.
o affect_valence_mean.x: Average daily affective valence rating on a scale ranging from 0 (unpleasant) to 100 (pleasant)
o affect_arousal_mean.x: Average daily affective arousal rating on a scale ranging from 0 (sleepy) to 100 (aroused/activated)
o anxiety_mean.x: Average daily anxiety rating on a scale ranging from 0 (not at all anxious) to 100 (extremely anxious), higher scores represent more intense anxiety
Written Report. You should prepare a written report that addresses the following three questions:
- How physically active and sedentary were you?
a. To answer this question, please focus on the overall physical activity and total sedentary time scores (metmin_mean.x and sit_total_mean.x). Calculate an average score for each across the two weeks (=AVERAGE(week1:week2)). Then estimate the percentile rank of your physical activity and sedentary scores in relation to the rest of the class (one percentile for your physical activity, one percentile for your sedentary behavior). 10 pts
b. Interpret the two percentile scores you calculated. What do the numbers mean? Do they match your sense of your behavior in relation to your peers? 10 pts
c. Note one strength and one weakness of daily self-reports for assessing physical activity and sedentary behavior. 10 pts - How did your physical activity and sedentary behavior change from the first week to the second week?
a. For this question, look at the individual scores for the three physical activity intensities (ipaq_vig_mean.x, ipaq_mod_mean.x, ipaq_walk_mean.x) and for the five domains of sedentary behavior (sit_travel_mean.x, sit_school_mean.x, sit_tv_mean.x, it_computer_mean.x, sit_leisure_mean.x) each week. Compare the average duration of each behavior in week 1 with the corresponding average duration in week 2. Make a bar chart summarizing changes in these behaviors from week 1 to week 2. 10 pts
b. Which behaviors were the most stable and which changed the most? 10 pts
c. What factors contributed to changes in those behaviors from week 1 to week 2? 10 pts - How was one of the activity variables associated with one motivation or well-being variables (your choice)?
a. Select one variable representing either physical activity (total or intensity-specific) or sedentary behavior (total or domain-specific). Select one variable representing either motivation (intentions, scheduling self-efficacy, barriers self-efficacy) or well-being (anxiety, affective valence, affective arousal, life satisfaction). Find a study in a peer-reviewed journal article that provides a basis for formulating a hypothesis about relations between the variables you selected. State your hypothesis about how you expect those two variables to be associated (positive, negative, null). For example: Variable X is hypothesized to have a [small/medium/large] [positive/negative] association with variable Y. With correlations, you can use the following rule of thumb for interpreting the size of associations: small r = .1, medium r = .3, large r ≥ .5. Explain why you made that hypothesis. Cite the study you used as background. 10 pts
b. Calculate correlations between the behavioral and psychological variables you selected for both week 1 and week 2 (=CORREL(variable1:variable2)). Report those correlations. 10 pts
c. Interpret the correlations. Were they both in the expected direction? Were they stronger or weaker than expected? What conclusion would these results lead you to draw about relations between the variables? 10 pts
d. What factors might have influenced these results? 10 pts
Formatting. All reports should be typed in 11-point Arial font and double-spaced with 1” margins. The page limit for this assignment is 2 pages (not including figures or references). Reports that exceed this limit will be penalized. Clearly labeled section headings are strongly encouraged to organize the three questions in your report. References should be made in APA style (see https://apastyle.apa.org/style-grammar-guidelines).
Please submit your report as a single file in .pdf or .docx format to the Canvas dropbox before the deadline (). Late papers will incur a 10 pt penalty for each day or part of a day after the deadline. Early submissions are welcome and encouraged.