Here is the design of a clinical trial:

Official Title: A Social Media Game to Increase Physical Activity Among Older Adult Women

Included conditions:
- Aging

Study Armgroups:
- {'label': 'Social media game', 'type': 'EXPERIMENTAL', 'description': 'Private Facebook group with weekly walking challenges, Fitbit wearable activity monitor, and brief counseling', 'interventionNames': ['Behavioral: Social media game']}
- {'label': 'Standard self-regulation', 'type': 'ACTIVE_COMPARATOR', 'description': 'Fitbit wearable activity monitor and brief counseling', 'interventionNames': ['Behavioral: Standard self-regulation']}

Interventions:
- {'type': 'BEHAVIORAL', 'name': 'Social media game', 'description': 'Participants will engage in weekly challenges that require them to take photographs of interesting things they discover during their walks. They will post and discuss these photographs with other participants on a private social media page. They will track their steps using a wearable activity monitor and receive brief standard self-regulatory counseling.', 'armGroupLabels': ['Social media game']}
- {'type': 'BEHAVIORAL', 'name': 'Standard self-regulation', 'description': 'Participants will track their steps using a wearable activity monitor and receive brief standard self-regulatory counseling.', 'armGroupLabels': ['Standard self-regulation']}

Primary Outcomes:
- {'measure': 'Walking physical activity as measured by daily steps at 12 months', 'description': 'Mean of daily steps taken from accelerometers worn for a 7 day period', 'timeFrame': 'Baseline to 12 months'}

Please estimate the sample size based on the assumption: 
80% power to detect the difference at 18 months. 99% power to detect the increase in autonomous regulation. 83% power to detect the mediator coefficient. 81% power to detect a mediated effect of 372. Significance level (α) = 0.05. Consideration for missing data.
Sample size and statistical power
        Because effect size estimates taken directly from pilot studies can produce biased power estimates when used alone [62, 63] and our pilot trials could not provide the range of outcomes needed (e.g., steps at 6, 12, and 18 months), we used several sources to estimate the range of possible intervention effects. We estimated steps per day increases of approximately 1500, 1000, and 500 at the three follow-up points. These numbers were based on similar mHealth walking studies [36], preliminary research [32], and the clinical significance of 500-step-per-day increase for older adults [64â66]. To achieve 80% power, a sample size of approximately 252 participants would be needed to detect this difference between groups at 18 months. Our most conservative estimates would require a sample size of 275. We will recruit 300 participants in case of any missing data that cannot be dealt with via imputation (e.g., extreme levels of missingness, or if there is reason to believe that data are missing not at random).
        Assuming at least 275 participants, we will have 99% power to detect that the intervention increases autonomous regulation by 0.6 units, as measured by the BREQ-3, when the standard deviation of BREQ-3 scores are 1 (as observed in our preliminary research). Furthermore, we will have 83% power to detect a mediator coefficient of 620, which was calculated assuming that the number of steps walked has a standard deviation of 3000 (as observed in our preliminary research), and adjusting for the confounding of intervention with BREQ-3 score. Therefore, we will have 81% power to detect a mediated effect of 372, which would explain 27.4% of the effect of the intervention through the indirect effect of autonomous regulation [67â69]. All testing will be 2-sided with Î±â=â0.05.