Incorporate Exogenous Ketones Drink Mix into your morning routine as part of your marathon training for 90 days.

Complete the PROMIS Sleep Disturbance Scale and the Depression, Anxiety, and Stress Scales (DASS-21) at designated times.

The "Boost Your Marathon Training: Ketone Supplement Challenge" is designed as a single-arm observational trial where participants act as their own control, commonly referred to at Efforia as a "Signal Phase" study. The study seeks to explore the effects of incorporating an Exogenous Ketones Drink Mix into the daily training routines of marathon runners. Over a structured 90-day marathon preparation program, the primary aim is to assess the impact of the ketone supplement on various aspects of running performance, including speed, distance, and recovery. By focusing on these metrics, the study endeavors to provide preliminary signals regarding the efficacy of exogenous ketones, which could potentially lead to enhanced athletic performance.

Participants in this study will integrate the Exogenous Ketones Drink Mix into their morning routine, consuming it before their daily runs. This regimen will be closely monitored, with data collection focusing on several key performance indicators and health metrics. The structured protocol includes linking digital tools like Google Calendar and Todoist to ensure participants maintain an organized training schedule and remain updated on study-related communications. Participants are encouraged to prioritize communications from Efforia to effectively track their progress and remain engaged. This comprehensive approach aims to generate insights into the influence of ketones on performance while ensuring the privacy and confidentiality of participant data.

In terms of study experience, participants will follow a personalized protocol schedule that includes data collection through various means such as the Strava Data Collection, PROMIS Sleep Disturbance Scale, and Depression, Anxiety, and Stress Scales (DASS-21). These measures will provide a holistic view of the participants' physical and mental health throughout the study period. The collected data will not only assess performance metrics but also offer more robust safety data that is currently lacking. If the study indicates a positive signal, suggesting that the ketone supplement impacts running performance favorably, it may pave the way for more comprehensive study designs to further explore these initial findings. For more detailed information, please refer to the "Minimal Risk Umbrella protocol."

To determine the minimum sample size required to detect a statistically significant effect in Efforia's sub-studies, I'll conduct a power analysis based on the provided assumptions and constraints. The primary statistical methods considered are paired t-tests and ANOVA, as the study involves single-arm observational trials and stratified analysis.

Minimum Sample Size Estimate (No Stratification)

Assumptions:

• Effect Size (Cohen’s d): 0.1
• Significance Level (α): 0.05
• Power (1 - β): 0.80
• Dropout Rate: 60%

Calculation:

Using the formula for determining sample size for a paired t-test (or single-group pre-post design) with a small effect size: [ n = \left( \frac{(Z_{\alpha/2} + Z_{\beta})^2 \times (2\sigma^2)}{\Delta^2} \right) ]

Where:

• ( Z_{\alpha/2} ) = 1.96 (for α = 0.05)
• ( Z_{\beta} ) = 0.84 (for power = 0.80)
• ( \Delta ) = Cohen's d * standard deviation = 0.1 * assumed SD
• Adjust for dropout: ( n_{\text{adjusted}} = \frac{n}{1 - \text{dropout rate}} )

Assuming a standard deviation (SD) of 1 for simplicity (can be adjusted based on pilot data or literature): [ n \approx \left( \frac{(1.96 + 0.84)^2 \times 2}{0.1^2} \right) \approx 313 ]

Adjusting for dropout: [ n_{\text{adjusted}} = \frac{313}{0.4} \approx 783 ]

Minimum sample size required (no stratification): 783 participants

Middle Sample Size Estimate (Stratified by Treatment Expectancy)

Assumptions:

• Assume equal distribution among high and low expectancy groups.
• Stratification may increase variability, necessitating a larger sample size.

Calculation follows the same logic as above but considers two groups: [ n_{\text{per group}} = 783 ] (derived without stratification)

Total after stratifying by treatment expectancy: [ n_{\text{total}} = 783 \times 2 = 1566 ]

Middle sample size required (stratified by treatment expectancy): 1566 participants

Maximum Sample Size Estimate (Stratified by Health and Fitness Measures)

Assumptions:

• Stratification by additional factors (sex, physical activity, self-reported disease states, etc.) can increase group complexity.
• Assume up to 5 additional stratification factors with potential interactions.

Assuming similar group sizes and stratification increases complexity: [ n_{\text{per group}} = 783 ]

Maximize stratification with 5 health measures: [ n_{\text{total}} = 783 \times 6 = 4698 ]

Maximum sample size required (stratified by multiple measures): 4698 participants

Justification:

1. Minimum Estimate (783 participants): Provides a baseline for detecting a small effect size without considering variability introduced by stratification. Useful for an initial exploratory analysis where resource constraints are significant.

2. Middle Estimate (1566 participants): Stratification by treatment expectancy allows control for expectancy bias, providing more nuanced insights into efficacy while still being resource-manageable.

3. Maximum Estimate (4698 participants): Comprehensive stratification accounts for various health and fitness measures, offering a highly detailed and robust analysis. However, this requires substantial resources and participant recruitment.

This tiered approach to sample size estimation allows for flexibility depending on available resources and the depth of analysis desired.

This single-arm observational trial aims to explore the impact of exogenous ketones on marathon training performance, focusing on enhancements in speed, endurance, and recovery. As with any single-arm design, a key limitation is the absence of a control group, which inherently raises concerns about the introduction of bias, particularly regarding participant expectations. In order to mitigate this, the study incorporates an expectations questionnaire, which serves to quantify and account for any potential biases stemming from participants' preconceived notions about the benefits of ketones. This methodological approach is crucial for distinguishing between actual physiological effects and those merely perceived due to participant bias.

Additionally, the study faces challenges related to sample size and demographic diversity, which are common limitations in single-arm trials. To address these, the trial's statistical methodology includes potential stratification by participant demographics, allowing for a more nuanced analysis of the data. By carefully designing the sample size and statistical approach, the study aims to ensure that the findings are as representative and reliable as possible, given the constraints of the study design. Furthermore, the trial is structured as a signal detection study. This means that if a positive signal is observed, it will pave the way for more robust, controlled trials to replicate and validate these findings, thereby strengthening their scientific credibility.

The overarching objective of this study is in line with Efforia's mission under the Minimal Risk Citizen Science Umbrella Protocol: to democratize clinical research by addressing neglected research questions and supporting researchers who might otherwise be overlooked. By focusing on an area of high interest but limited empirical evidence—namely, the use of exogenous ketones in marathon training—this study seeks to bridge the gap between anecdotal claims and scientific validation. Participants and interested parties are encouraged to review the Minimal Risk Umbrella Protocol for a comprehensive understanding of the study's framework and safety measures, as well as its commitment to empowering diverse research endeavors.