RELAX: A Mobile Application Suite Targeting Obesity and Stress: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for RELAX: A Mobile Application Suite Targeting Obesity and Stress (NCT02615171), a randomized na study. The primary outcome is Percentage of Days App Used Over 12 Weeks.

2. Clinical Question

The study is titled RELAX: A Mobile Application Suite Targeting Obesity and Stress. Its brief summary states that the research evaluates the feasibility and acceptability of a novel weight-loss mobile app designed to be less burdensome than traditional weight-loss apps. The primary endpoint therefore focuses on app engagement rather than a clinical measure of weight or stress. Weight change, perceived stress, and emotional eating are listed as secondary outcomes.

3. Trial Design

RELAX is registered as a randomized, parallel-group study with no masking. The registry lists phase as not applicable. The record reports enrollment of 64 and identifies two behavioral intervention arms: Comprehensive Dietary Self-Monitoring and Simple Dietary Self-Monitoring. The reported arm sizes for the primary outcome are 32 in each arm.

The comprehensive approach combined Facebook-delivered weight-loss counseling with MyFitnessPal, a comprehensive diet and exercise self-monitoring app. The simple approach combined Facebook-delivered counseling with Slip Buddy, an app created by the investigative team. Its described recording process asks users to register an instance of overeating with a single button and then indicate the overeating trigger and stress and hunger levels. The intervention descriptions are incomplete in the registry record, so additional details about what participants were encouraged to do cannot be established from the available text.

The study start date is 2019-07-08, the primary completion date is 2019-11-30, and the status is completed. The primary outcome timeframe is 12 weeks. Secondary outcomes are percent weight change from baseline to 12-week follow-up, change in perceived stress from baseline to 12-week follow-up, and change in emotional eating from baseline to 12-week follow-up.

Randomization and the parallel structure support a comparison between the assigned approaches, but the registry record does not report the randomization procedure, allocation concealment, or other operational details. Masking is recorded as none. The record does not report the original sample-size justification or the detailed statistical plan. It also does not provide further information about recruitment, participant characteristics, adherence support beyond the intervention descriptions, or how analyses handled departures from the assigned approach.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: After participants were initially screened, a telephone screening, webinar orientation and baseline survey was required prior to being randomized.

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Days App Used Over 12 Weeks, measured over 12 weeks.

The primary endpoint is the mean percentage of days an app was used over 12 weeks. It represents frequency of app engagement during the intervention period, not the amount of time spent in the app, the quality of entries, or a direct measure of weight or stress. The registry says that use was identified through Slip Buddy backend data in the simple self-monitoring arm and through MyFitnessPal entries indicating use over each 24-hour period in the comprehensive arm.

For the comprehensive arm, the posted mean was 57.5 percent of days, with a standard deviation of 28.4. For the simple arm, the mean was 53.8 percent, with a standard deviation of 31.3. The reported comparison is a mean difference of -3.7 for simple relative to comprehensive self-monitoring. Its interval extends from -18.34 to 10.94.

App use is relevant to a feasibility and acceptability question because a self-monitoring tool must be used for its intended recording process to be experienced. However, frequency alone does not establish whether participants found the app acceptable, whether recording was burdensome, or whether app use changed weight or stress. Those aspects require other measures, and acceptability details beyond the registry description are not reported in the registry record. The use endpoint is also operationalized differently across arms, so the recorded frequency reflects the respective app data sources and definitions of a day with use.

7. Results Posted in the Registry

• Simple Dietary Self-Monitoring: mean 53.80 versus 57.50 on control; difference -3.70 (95% CI -18.34 to 10.94), standardized effect d = -0.12; z-test p = 0.620.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Percent Weight Change From Baseline to 12-Week Follow-Up

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Simple Dietary Self-Monitoring: mean -3.00 versus -3.60 on control; difference 0.60 (95% CI -1.71 to 2.91), standardized effect d = 0.13; z-test p = 0.610.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Simple Dietary Self-Monitoring and the control. The interval gives the range of effects that remain compatible with the data.

Change in Perceived Stress From Baseline to 12-Week Follow-Up

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Simple Dietary Self-Monitoring: mean 2.50 versus 2.80 on control; difference -0.30 (95% CI -4.34 to 3.74), standardized effect d = -0.04; z-test p = 0.884.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Simple Dietary Self-Monitoring and the control. The interval gives the range of effects that remain compatible with the data.

Change in Emotional Eating From Baseline to 12-Week Follow-Up

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Simple Dietary Self-Monitoring: mean -9.90 versus -1.10 on control; difference -8.80 (95% CI -21.50 to 3.90), standardized effect d = -0.35; z-test p = 0.174.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Simple Dietary Self-Monitoring and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the focus from app engagement to weight change, perceived stress, and emotional eating. Their overall pattern is mixed in direction: the posted mean changes indicate reductions for weight and emotional eating, while perceived stress changes are positive in both arms. Across these outcomes, the comparisons do not yield a consistent pattern of clear separation between the approaches. The posted intervals include zero, leaving uncertainty about the direction and size of the comparative effects.

This pattern is relevant alongside the primary result, which concerns frequency of app use. Engagement is not interchangeable with weight or stress change: more frequent recording does not necessarily imply a larger change in a clinical or behavioral measure. The secondary summaries do not establish that app-use frequency explains the other outcomes, and the registry record does not report a mediation analysis or other analysis linking engagement to those changes.

The secondary comparisons are described as unadjusted. In general, when several outcomes are tested, the chance of at least one apparently notable result can increase unless the analysis accounts for the multiplicity or clearly defines which comparisons are confirmatory. The registry record does not report a multiplicity strategy. This means the secondary findings warrant more caution than a single prespecified primary comparison would, particularly if emphasis is placed on any isolated result. Their value is chiefly descriptive in this record: they provide context about the range of measured outcomes without resolving comparative effects.

The registry lists seven outcome measures overall and three posted secondary outcomes. The other measures and their results are not characterized in the information available for this account. The secondary arm counts also differ from the primary endpoint counts, and the reasons are not reported in the registry record. These limitations reinforce the need to treat the secondary pattern as incomplete rather than as a comprehensive account of all outcomes or all participants.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Percent Weight Change From Baseline to 12-Week Follow-Up
• Change in Perceived Stress From Baseline to 12-Week Follow-Up
• Change in Emotional Eating From Baseline to 12-Week Follow-Up

9. Statistical Interpretation

10. Statistical Methods Explained

The primary and secondary outcomes are continuous measures, and the registry reports arm means and standard deviations. A mean describes the average outcome within an arm; a standard deviation describes how spread out individual observations are around that average. A mean difference compares the two arm averages in the units of the outcome. For the primary endpoint, the comparison is stated for simple relative to comprehensive self-monitoring, and the reported estimate is -3.7.

What does the interval communicate?

In general, a confidence interval gives a range of estimates compatible with the observed data under the method used to construct it. A narrower interval indicates greater precision than a wider interval, while the interval’s location indicates which values remain plausible. The primary interval runs from -18.34 to 10.94 and includes zero. That means the registry result does not pin down a difference in one direction: the data are compatible with a negative difference, no difference, or a positive difference. The interval should be considered alongside the estimate rather than replaced by a yes-or-no reading of the p-value.

The registry reports unadjusted p-values for the displayed comparisons. In general, a p-value evaluates how unusual data at least as discrepant as those observed would be under a specified null model. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of a difference. The primary p-value is 0.62. The registry record does not report the sponsor’s detailed inferential method or a fuller statistical analysis plan, so the displayed p-values should not be attributed to a particular model or adjustment procedure beyond their stated unadjusted status.

Why does measurement matter?

App use was not recorded through the same named source in both arms: Slip Buddy use was assessed with backend data, whereas MyFitnessPal use was assessed by reviewing entries indicating use over each 24-hour period. In general, measurement definitions matter because a comparison is most interpretable when both groups’ outcomes are captured in comparable ways. The record supplies these measurement descriptions but does not report a validation study or further detail about how the two sources were aligned. A difference in recorded use could reflect engagement, measurement conventions, or both; the posted summaries do not separate these possibilities.

In general, standard deviations describe variation among observations, whereas standard errors describe the uncertainty of an estimated mean. These are not interchangeable. The registry record includes standard deviations for the arm summaries and also gives standard errors in the comparison calculations. The standard errors help characterize uncertainty in the estimated means, while the interval around the mean difference addresses uncertainty in the contrast. The standard deviation is not itself an interval for the mean difference.

What does over-dispersion mean in general?

Over-dispersion occurs when variability in observed data is greater than a statistical model assumes. In general, this can make model-based standard errors too small if the extra variation is ignored, leading to intervals that are too narrow and tests that overstate precision. The posted primary outcome is summarized as a continuous mean with a standard deviation; the registry does not report a count model or a formal assessment of over-dispersion. This concept is therefore useful background, not a claim that over-dispersion was present in this trial.

The record reports three secondary outcomes and three posted secondary comparisons. Their unadjusted p-values do not account for the possibility of multiple testing, according to the available information. A multiplicity adjustment can be used in general when several hypotheses are tested, to control the chance of false-positive findings across a family of comparisons. Whether a family of outcomes was defined in advance, and whether an adjustment was planned or performed, are not reported in the registry record.

The planning illustrations are based on a normal approximation, equal allocation between arms, and a two-sided significance level of 0.05, as stated in the record. In general, such illustrations use an assumed effect and variability to show how participant requirements change under those assumptions. They are not the same as the trial’s original design calculation. The record does not report the assumptions used for the original trial design or a sample-size justification.

The reported comparison estimates are not accompanied by a sponsor-reported analysis description in the registry record. The registry’s reported analyses field is empty for the secondary outcomes, and the detailed handling of covariates, missing observations, analysis populations, and deviations from assigned intervention is not reported in the registry record. Those omissions limit how fully the posted summary results can be audited or connected to a prespecified analysis plan.

11. Confidence Intervals and Precision

The primary mean difference is -3.7, with an interval from -18.34 to 10.94. The interval includes zero and extends in both directions. This indicates uncertainty about whether the average recorded use was higher in the comprehensive arm or the simple arm, and about the size of any difference. The estimate alone suggests a small difference in favor of the comprehensive arm, but the interval allows substantially different estimates, including differences in the opposite direction. The data therefore do not support a precise estimate of the comparative app-use frequency.

Precision is distinct from the point estimate and from the p-value. A point estimate is the single value calculated from the observed summaries; an interval indicates the range of values that remain compatible with the data under the calculation method. The unadjusted p-value of 0.62 is consistent with the interval’s inclusion of zero, but it does not show that the arms are identical. The registry record does not report an equivalence margin or a precision target for the primary comparison.

The standard deviations for the primary measure are 28.4 in the comprehensive arm and 31.3 in the simple arm. These describe the spread of individual app-use percentages within each arm, not the uncertainty of the mean difference itself. The registry reports 32 participants in each primary-outcome arm. The secondary outcome counts vary, and their precision also depends on the observed variability and the number of observations available for each outcome. Their reported intervals likewise span zero, so the posted summaries do not establish a clear between-arm difference on those measures.

An interval is informative about statistical precision, but it does not address every source of uncertainty. It does not by itself account for differences in how app use was measured, unreported missing-data handling, or the limited detail about the analysis plan. The interval should therefore be interpreted as uncertainty around the reported comparison, not as a complete description of every limitation in the evidence.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm for 80% power and participants per arm for 90% power. They are not total events: the outcome measures are continuous, and the record specifies that non-time-to-event planning values are per arm. In plain terms, 80% power describes a design that would have an 80% chance of detecting the stated effect under the planning assumptions if that effect were the true one; 90% power describes a higher chance under the same kind of assumptions. Neither column is a guarantee that a future study will detect a difference.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The rows therefore illustrate planning for the full observed effect, planning for 75% of the observed effect, and planning for 50% of the observed effect. A smaller effect is harder to distinguish from random variation, so it requires more participants per arm to achieve the same target power under the same assumptions.

These figures are planning illustrations computed from observed effects, not the trial’s own original design assumptions. The original sample-size justification and assumptions are not reported in the registry record. This is not observed power: the calculations do not measure the probability that the completed trial had to find its result, and they should not be used to reinterpret the observed p-value. The figures describe hypothetical future planning under specified assumptions, rather than outcomes or design details about the completed study.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -3.700; pooled standard deviation σ = 29.885.
2. n = 2 × (1.96 + 0.842)² × 29.885² / -3.700² = 1,024.1, rounded up to 1,025 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -3.7                      # observed difference in means
sigma <- 29.8851970045372                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(2615171)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 1,025 (80% power), 1,371 (90% power)
 75% of observed effect: n per arm = 1,821 (80% power), 2,438 (90% power)
 50% of observed effect: n per arm = 4,097 (80% power), 5,484 (90% power)
power.t.test: 1025.1 
Simulated power at n = 1,025 per arm: 0.801 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry record lists a primary endpoint and several secondary outcomes, while the posted results include unadjusted comparisons for the primary endpoint and three secondary endpoints. When multiple outcomes or comparisons are examined, multiplicity is a concern because the chance of at least one apparently unusual result can rise across the set of tests. Statistical approaches can address this in different ways, but the choice depends on which outcomes were intended to be confirmatory and how the analysis plan defined the testing family.

Whether any adjustment for multiplicity was planned or applied is not reported in the registry record. The record also does not report whether the secondary outcomes were exploratory, whether a hierarchy of hypotheses was specified, or whether outcomes were selected for reporting after analysis. The unadjusted secondary p-values should therefore not be treated as if they necessarily control the chance of false-positive findings across all measured outcomes.

The posted arm counts are 32 in each group for the primary outcome. For perceived stress and emotional eating, the reported arm counts are 30 and 31. The record does not report the reasons for these differences, the amount or pattern of missing data, or the method used to handle missing observations. It is therefore not possible to determine from the registry record whether the analyses used complete cases, an imputation method, or another approach.

The analysis populations are not described in detail. In particular, the registry record does not report whether analyses followed the randomized assignment regardless of app use, or whether participants were excluded for nonadherence or other reasons. The handling of protocol deviations, adjustment for baseline characteristics, and any interim analyses are also not reported in the registry record. These omissions do not negate the posted summaries, but they limit assessment of how closely the reported results represent the randomized comparison and how robust they are to missing outcomes or analytic choices.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports zero serious adverse events in each arm and zero deaths in each arm. For the other adverse event category, it reports 5 events in each arm. Each arm lists 32 participants at risk for serious adverse events and 32 at risk for other adverse events.

These figures describe the safety entries posted to the registry; they do not establish that no unrecorded events occurred or that the interventions have no risks. The record does not provide serious adverse event terms, and no top serious-event terms are listed. It also does not provide further detail about event types, severity, timing, relatedness to the intervention, or the method of collecting adverse events. The category labeled other adverse events should be read separately from the serious adverse event and death figures, rather than treated as a description of the clinical importance of those events.

Because the registry gives counts without additional event descriptions, the safety information is limited. It offers a report of the numbers entered for the two arms but does not permit a detailed comparison of event profiles or attribution of events to the app, counseling, or another cause.

16. What the Result Does, and Does Not, Mean

The posted primary results describe average app use during the 12-week intervention period. The observed arm means are close in the sense that the reported comparison estimate is -3.7, but the interval from -18.34 to 10.94 is wide and includes zero. The record therefore does not establish a clear difference in recorded app use between the two approaches. It also does not establish that the approaches are equivalent, because no equivalence margin or equivalence analysis is reported.

The study summary frames the research around feasibility and acceptability of a mobile weight-loss app designed to be less burdensome than traditional apps. App-use frequency is one relevant engagement measure, but it does not fully measure acceptability or burden. The registry record does not report enough detail to determine whether users considered one app more acceptable, whether they found the recording process burdensome, or why use varied across days.

The secondary outcomes provide information on weight, perceived stress, and emotional eating over 12 weeks. Their comparative estimates remain uncertain, and the posted results do not show that one approach caused better outcomes than the other. Because the trial compares bundles that include counseling and different apps, the results cannot isolate the effect of an app component from the full intervention approach described in each arm.

The findings should not be extended automatically to other populations, apps, counseling formats, or follow-up periods. Participant eligibility and characteristics are not reported in the registry record, and the registered timeframe is 12 weeks. Details about longer-term outcomes are not reported in the registry record. Overall, the posted information offers a limited account of recorded engagement and several short-term outcomes; it does not resolve questions about broader effectiveness, sustained use, or acceptability beyond what was measured and reported.

17. Why This Trial Matters Statistically

This trial is statistically informative because its primary outcome is engagement with a digital self-monitoring tool, rather than a clinical endpoint alone. Engagement is often part of the pathway through which an app-based intervention is intended to operate, but it must be interpreted as its own measured outcome. The RELAX record makes that distinction visible by identifying app-use frequency as primary and weight, stress, and emotional eating as secondary outcomes.

The design also illustrates a practical measurement issue in app studies. Use was assessed from backend data for Slip Buddy and from entries indicating use over each 24-hour period for MyFitnessPal. Different measurement sources can affect what counts as use, and the comparison is therefore best understood as a contrast in recorded app engagement under the two specified approaches. The registry does not report additional work aligning or validating those measures.

The interval around the primary comparison emphasizes why the estimate and its precision matter together. A single mean difference does not capture the range of uncertainty, and an unadjusted p-value does not establish equivalence or practical importance. The planning illustrations further show, under their stated assumptions, how sample-size requirements depend on the effect one aims to detect. They are distinct from the trial’s own design rationale, which is not reported in the registry record.

Finally, the record demonstrates why interpretation depends on more than the primary result. Missing details about the analysis plan, multiplicity, and outcome handling constrain conclusions from the secondary measures. For clinical researchers and biostatisticians, these are not merely documentation issues: they determine how precisely a randomized comparison can be understood and how far its conclusions can reasonably be extended.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several limitations are specific to the reported RELAX record. The intervention descriptions are truncated, so the full content and delivery of each approach cannot be reconstructed from the registry text. Although both arm descriptions include Facebook-delivered counseling, the record does not supply enough detail to assess how counseling was delivered or whether it was identical across arms. The comparison is between intervention packages, not an isolated test of one app feature.

The primary outcome is measured using different sources in the two arms: backend data for Slip Buddy and reviewed entries for MyFitnessPal. The record does not report whether those sources were validated against one another or how a day with use was defined in each system. That limits interpretation of a between-arm difference as a pure difference in engagement.

The study enrolled 64, and the posted sample sizes for some secondary outcomes are smaller than the primary arm sizes. Reasons for these differences and missing-data handling are not reported in the registry record. The record also does not give participant characteristics or eligibility details, limiting assessment of how broadly the results may apply.

Masking is recorded as none. Details about the original sample-size rationale, statistical analysis plan, multiplicity handling, analysis populations, and interim analyses are not reported in the registry record. The primary interval is broad, and the secondary comparisons are unadjusted. These features constrain precision and interpretation, especially for the secondary outcomes. Follow-up described for the primary and secondary outcomes is 12 weeks; longer-term results are not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: RELAX: A Mobile Application Suite Targeting Obesity and Stress — NCT02615171.
• Registry record last updated 2021-04-13; status last verified 2021-03.
• Results first posted 2021-03-11.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

RELAX is a completed randomized, unmasked, parallel-group study registered as NCT02615171. It compared comprehensive dietary self-monitoring using MyFitnessPal with simple dietary self-monitoring using Slip Buddy, within interventions described as including Facebook-delivered counseling. The primary endpoint was mean percentage of days the app was used over 12 weeks.

The primary arm means were 57.5 percent and 53.8 percent, with a reported mean difference of -3.7 and an interval from -18.34 to 10.94. Secondary outcomes addressed weight change, perceived stress, and emotional eating. The record reports zero serious adverse events and zero deaths in each arm, and 5 other adverse events in each arm.

The registry describes feasibility and acceptability as the research focus. Detailed analysis plans, missing-data handling, multiplicity methods, participant characteristics, and the original sample-size rationale are not reported in the registry record.