SMART 2.0: Social Mobile Approaches to Reducing weighT in Young Adults: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for SMART 2.0: Social Mobile Approaches to Reducing weighT in Young Adults (NCT03907462), a randomized na study. The primary outcome is Change in Weight.

2. Clinical Question

3. Trial Design

SMART 2.0 (NCT03907462) is a completed, randomized, double-masked, parallel-group behavioral trial sponsored by the University of California, San Diego. The registry reports enrollment of 638 and a study period from 2019-04-01 to primary completion on 2024-02-01. The listed phase is NA. The trial was designed to evaluate weight outcomes over 24 months among young adults with overweight or obesity in a university setting.

Three groups are described: SMART 2.0 with technology and personal health coaching, SMART 2.0 technology alone, and control. The two intervention descriptions include wearable and scale devices with a corresponding app and daily text messages; the first also specifies personal health coaching. The control group received a wearable and scale with an app for use at the participant’s discretion. Further details of the intervention components are not reported in the registry record.

The primary outcome is mean change in weight, measured in kilograms, from baseline to 24 months. The posted outcome counts are 187 for Treatment One, 186 for Treatment Two, and 180 for Control. The registry does not explain why these outcome counts differ from the overall enrollment, or describe the analysis population used for the primary outcome. The method used to generate the randomized allocation, the masking procedures, and the original sample-size justification are not reported in the registry record.

Although the design is randomized, the registry record does not include sponsor-reported comparative analyses for the primary outcome. The numerical comparisons discussed in the statistical interpretation are unadjusted recalculations from the posted group summaries. They should not be mistaken for a complete account of any analysis conducted outside the registry record.

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 eligibility and consent were confirmed and baseline measurements were completed, participants were stratified by sex and university/college and then randomized within each stratum at a ratio of 1:1:1 to one of three study arms.

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 Change in Weight, measured over Baseline, 24 months.

The primary endpoint is change in objectively measured weight in kilograms, comparing baseline with 24 months. The registry reports a mean and standard deviation for each group. A change score describes how the measured value differs over the stated follow-up period; a negative mean change indicates an average decrease from baseline, while a positive mean change indicates an average increase.

Weight is a direct, continuous measure, so reporting a group mean preserves information about the size and direction of changes across participants. The standard deviation describes variation among individual changes within a group; it is not the uncertainty around the group mean. The endpoint is relevant to the trial’s stated aim of evaluating weight outcomes, but the registry record does not report further details about measurement procedures, timing within the 24-month visit window, or handling of measurements that were unavailable.

The endpoint does not by itself describe the distribution of individual outcomes or establish why any group differences occurred. A group mean can coexist with substantial variation among participants, and a mean difference between groups is an estimate with uncertainty. Interpretation therefore depends on the comparison estimate, its confidence interval, and the analysis methods—not simply on whether a group mean is positive or negative.

7. Results Posted in the Registry

• Treatment One: mean -0.33 versus 1.20 on control; difference -1.53 (95% CI -3.04 to -0.03), standardized effect d = -0.21; z-test p = 0.046.
• Treatment Two: mean 0.74 versus 1.20 on control; difference -0.46 (95% CI -2.07 to 1.14), standardized effect d = -0.06; z-test p = 0.571.

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.

Change in Body Mass Index

• 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:
  • Treatment One: mean -0.21 versus 0.42 on control; difference -0.63 (95% CI -1.22 to -0.04), standardized effect d = -0.27; z-test p = 0.035.
  • Treatment Two: mean 0.01 versus 0.42 on control; difference -0.40 (95% CI -1.04 to 0.24), standardized effect d = -0.16; z-test p = 0.216.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Treatment One than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment Two and the control. The interval gives the range of effects that remain compatible with the data.

Percent Weight Change

• 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:
  • Treatment One: mean -0.27 versus 1.44 on control; difference -1.70 (95% CI -3.56 to 0.16), standardized effect d = -0.21; z-test p = 0.073.
  • Treatment Two: mean 0.95 versus 1.44 on control; difference -0.48 (95% CI -2.47 to 1.51), standardized effect d = -0.06; z-test p = 0.635.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment One and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment Two and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants Who Lost at Least 5% of Their Weight From Baseline

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Treatment One: 22.9% (35/153) versus 18.8% (27/144) on control; risk difference 4.1 percentage points (95% CI -5.1 to 13.3), risk ratio 1.22 (0.78–1.91); unadjusted two-proportion z-test p = 0.382.
  • Treatment Two: 18.3% (28/153) versus 18.8% (27/144) on control; risk difference -0.4 percentage points (95% CI -9.3 to 8.4), risk ratio 0.98 (0.61–1.57); unadjusted two-proportion z-test p = 0.921.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment One and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment Two and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists several secondary outcomes, including body mass index, percent weight change, weight-loss thresholds, waist measures, body composition, and bone mineral density. The posted secondary results cover a subset of those measures. Taken together, the continuous outcomes generally point in a direction similar to the primary mean-weight contrast for Treatment One, while the technology-alone estimates are closer to no difference. The threshold outcome does not give a clear separation between either intervention and control. This broad pattern is compatible with the primary comparison’s more favorable direction for the coaching group and the greater uncertainty around the technology-alone comparison, but it is not an independent confirmation of the primary finding.

The secondary measures differ in scale and meaning. A continuous change measure retains information about the magnitude of observed changes, whereas a threshold outcome divides participants according to whether they crossed a specified cutoff. Such dichotomization can discard information about how far participants were from the cutoff and can leave estimates sensitive to the number of observations on either side. These outcomes should therefore be interpreted according to their measure and uncertainty rather than treated as interchangeable versions of the primary endpoint.

The posted secondary comparisons are unadjusted recalculations, and the registry lists no sponsor-reported analyses for them. When many outcomes and comparisons are examined, the chance of obtaining at least one apparently unusual result increases. Without a reported multiplicity strategy, isolated nominal p-values deserve less weight than a prespecified, jointly interpreted analysis. The registry record does not report which secondary outcomes were designated as confirmatory, how their order was set, or whether any adjustment was planned.

Secondary outcomes can add context by showing whether related measures move in a broadly coherent direction, but they do not replace the primary endpoint. In this record, their overall pattern is mixed in precision and does not remove the uncertainty in the primary comparison. The record also does not report detailed methods for handling missing values across these outcomes, so differences in contributing outcome counts further limit direct comparisons across measures.

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

• Change in Body Mass Index
• Percent Weight Change
• Percentage of Participants Who Lost at Least 3% of Their Weight From Baseline
• Percentage of Participants Who Lost at Least 5% of Their Weight From Baseline
• Change in Waist Circumference
• Change in Waist-to-hip Ratio
• Change in Body Composition
• Change in Bone Mineral Density

9. Statistical Interpretation

10. Statistical Methods Explained

For the primary outcome, the posted values are group means and standard deviations of change in weight. The comparisons are unadjusted differences between each intervention group mean and the control group mean, recalculated from the posted summaries. A negative difference means the intervention group’s average change was lower than the control group’s average change. It does not, by itself, describe how every participant changed.

What does a confidence interval express?

General statistical explanation: A confidence interval describes the range of estimates reasonably compatible with the observed data under the statistical procedure used. A narrower interval indicates greater precision; a wider one indicates more uncertainty. An interval that includes zero is compatible with no mean difference under that procedure, as well as with values on either side of zero. An interval entirely below zero is compatible with a lower mean change in the intervention group than in control, although it does not establish the cause of the difference or its importance to every participant.

The confidence intervals discussed for the primary outcome are recalculated from summary data. The registry record does not report the sponsor’s inferential model, covariate adjustments, or a prespecified statistical analysis plan. This means the recalculated intervals and p-values should be distinguished from a sponsor-reported trial analysis. The record lists no reported analyses for the posted outcomes.

How should the p-values be read?

General statistical explanation: A p-value measures how unusual data at least as incompatible with a specified null hypothesis would be under the assumptions of a statistical test. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of an effect. The values discussed for the primary comparisons are unadjusted. No multiplicity adjustment is reported, so they do not account for the fact that the trial includes multiple outcome measures and comparisons.

The posted group standard deviations describe variation in individual weight changes. They are not confidence limits for the mean and do not indicate how precisely the group mean is estimated. A large spread among participants can coexist with a modest average difference between groups. The recalculated comparisons also report pooled standard deviations and standardized effect-size estimates; these express differences relative to variation in the groups, but do not replace the original kilogram-scale estimate or its confidence interval.

What can randomization and masking tell us?

General statistical explanation: Random assignment is intended to make comparison groups similar, on average, with respect to measured and unmeasured characteristics at the start of a trial. Double masking is intended to limit the influence of knowledge of assignment on participants or study personnel, according to the study’s masking designation. The registry record does not specify the allocation procedure, who was masked, or how masking was maintained. A randomized design supports a comparative interpretation, but it does not resolve uncertainty arising from missing outcomes, incomplete reporting, or analyses that are not documented in the record.

The registry reports standard deviations and outcome counts for the primary measure, but does not report how missing measurements were treated, whether the analysis followed an intention-to-treat approach, or whether the estimates were adjusted for baseline values. It also does not report an analysis plan, handling of protocol deviations, or procedures for any interim analyses. These details should not be inferred from the randomized and double-masked design labels.

In general, over-dispersion is a concern when data vary more than a model’s assumptions allow; estimates of uncertainty may then be too small if the model does not account for that extra variation. The primary outcome is summarized with standard deviations, but the registry record does not describe a model-based analysis or report a check for over-dispersion. There is no basis in the posted record for concluding that over-dispersion occurred or that a particular adjustment was used.

The recalculated results are useful for reading the posted group summaries on a common comparative scale. Their limits are equally important: they do not recover unreported trial procedures, establish the originally planned estimand, or account for unreported adjustments. General statistical concepts can clarify how estimates and uncertainty work, but the registry record does not supply the detail needed to verify a complete analysis.

11. Confidence Intervals and Precision

The primary Treatment One comparison has an estimated mean difference of -1.535 kg. Its confidence interval extends from -3.039 kg to an upper limit just below zero. The interval is therefore consistent with a range of negative differences, from a more noticeable separation to one close to no difference. The unadjusted p-value of 0.046 is close to the conventional 0.05 reference point, but should be read alongside the interval and the fact that the registry does not report a multiplicity adjustment or sponsor analysis.

For Treatment Two, the estimated mean difference is -0.465 kg and the confidence interval runs from -2.072 kg to 1.142 kg. Because this interval includes zero and values on both sides, it conveys substantial uncertainty about the direction and size of the difference. The unadjusted p-value is 0.571. That value does not prove the groups are equivalent; an equivalence conclusion would require an appropriate design and prespecified margin, neither of which is reported in the registry record.

General statistical explanation: Confidence intervals are more informative than a binary significant-or-not label because they show both an estimate’s direction and the range of values compatible with the data under the method used. Precision depends on the amount of outcome information and its variability, among other factors. The primary outcome counts are 187, 186, and 180 across the three groups, and the reported standard deviations indicate variation in weight change. The registry record does not explain why the outcome counts differ or how absent outcomes were handled.

These intervals are recalculated from posted summary statistics and are not sponsor-reported confidence intervals. Their precision should be understood as conditional on that recalculation, not as confirmation of the trial’s unreported analytic choices.

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 sample-size illustrations describe hypothetical planning requirements based on the observed effect sizes; they are not the trial’s original design calculations. For these continuous outcomes, the figures are participants per arm. The planning assumptions listed in the registry material are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm for a design with an 80% chance of detecting the specified effect under those assumptions, if that effect and the assumptions were correct. The 90% column gives the corresponding number for a 90% chance. These are prospective planning quantities, not evidence about whether the completed trial had adequate power for its actual results.

Rows for planning at 100% of the observed effect use the full observed estimate as the hypothetical effect to detect. Rows for planning at 75% or 50% use smaller effects, and smaller effects require more participants to detect with the same target power. For example, for the Treatment One primary comparison, the illustrative requirement for 80% power is 358 participants per arm at 100% of the observed effect, 636 at 75%, and 1,430 at 50%. The corresponding 90% figures are 479, 851, and 1,914 participants per arm. These values illustrate how planning requirements change with the chosen effect and target power.

This is not observed power. The illustrations use observed effects as planning inputs and cannot tell whether the trial’s results were reliable, whether its initial design was adequate, or what probability the trial had of detecting an unknown true effect.

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 = -1.535; pooled standard deviation σ = 7.323.
2. n = 2 × (1.96 + 0.842)² × 7.323² / -1.535² = 357.3, rounded up to 358 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 <- -1.535                      # observed difference in means
sigma <- 7.32277717902837                     # 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(3907462)
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 = 358 (80% power), 479 (90% power)
 75% of observed effect: n per arm = 636 (80% power), 851 (90% power)
 50% of observed effect: n per arm = 1,430 (80% power), 1,914 (90% power)
power.t.test: 358.2 
Simulated power at n = 358 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 reports no analyses for the posted outcomes and does not describe a statistical analysis plan. It therefore does not report whether the primary contrast, secondary contrasts, or outcome time points were selected in advance for formal testing. A multiplicity adjustment or a hierarchical testing strategy is also not reported. Since multiple outcomes and comparisons are listed, unadjusted p-values should not be interpreted as if they were protected from the increased chance of chance findings across a family of tests.

Missing-data handling is not reported in the registry record. For the primary outcome, the contributing counts are 187 for Treatment One, 186 for Treatment Two, and 180 for Control, while overall enrollment is 638. The record does not explain the difference between the enrollment and these outcome counts, give reasons for absent measurements, or state whether missing values were imputed, excluded, or addressed using a model. It also does not provide enough information to assess whether outcome availability differed by group or was related to weight change.

The analysis population is not reported in the registry record. The record does not say whether the primary results followed an intention-to-treat principle, included only participants with observed follow-up, or used another definition. It does not describe treatment of participants who discontinued, did not follow the intervention, or had measurements outside a visit window. These omissions limit assessment of how closely the posted summaries represent all randomized participants.

The registry also does not report interim analyses, stopping rules, baseline-adjusted models, or procedures for protocol deviations. These items cannot be inferred from the completed status or from the randomized, double-masked design. In their absence, the available results support a descriptive reading of posted group summaries and unadjusted recalculations, rather than verification of a prespecified confirmatory analysis.

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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: serious mental health episode (0.5%), stroke (0.5%), muscle/bone injury (0.5%), appendectomy (0.5%), covid-19 (0.5%).

The registry reports serious adverse events for 2 of 214 participants at risk in Treatment One, 4 of 212 in Treatment Two, and 2 of 212 in Control. It reports zero deaths in each group. These figures describe the serious adverse-event counts and at-risk denominators recorded for the safety reporting; they are not the same denominators as those contributing to the primary weight outcome.

The listed serious-event terms include serious mental health episode, stroke, muscle/bone injury, appendectomy, COVID-19, and asthma attack, each recorded at 0.5%. The registry’s event information should be read as descriptive reporting. It does not establish that an event was caused by an intervention, nor does it provide enough information to compare event risk with adjustment for follow-up duration or participant characteristics.

Other adverse events are reported for 73 of 214 participants in Treatment One, 53 of 212 in Treatment Two, and 40 of 212 in Control. The registry record does not provide additional detail in the registry record presented about event severity, timing, recurrence, or the method used to assess relatedness. Counts across groups alone therefore should not be used to make causal conclusions about safety.

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

The posted primary results describe average change in objectively measured weight from baseline to 24 months. Treatment One had a lower mean change than Control, and its recalculated confidence interval lies just below zero at the upper end. Treatment Two also had a lower point estimate than Control, but its confidence interval includes zero and extends in both directions. These estimates express uncertainty as well as direction; neither should be reduced to a simple claim that an intervention did or did not work.

The registry’s study summary records the investigators’ hypothesis that both interventions would improve weight compared with control and that coaching would yield the greatest improvement. The observed point estimates are more favorable for Treatment One than Treatment Two, but the record does not report a direct comparison between the two intervention groups. The separate comparisons against control do not, on their own, test whether coaching adds benefit over technology alone.

These results also do not establish what happened to every participant. Group averages and standard deviations summarize distributions; they do not show individual trajectories or explain why measurements were unavailable for some participants. The registry record does not report details of missing-data handling, the analysis population, or the sponsor’s inferential model. It is therefore important to distinguish what the posted summaries show from a full trial-level conclusion.

More generally, a confidence interval crossing zero does not prove equivalence, and a confidence interval narrowly on one side of zero does not prove a meaningful effect for each participant. Clinical importance requires context and prespecified criteria, neither of which is reported for interpreting the size of the weight difference. No medical advice follows from these registry summaries.

The most defensible reading is that the posted primary summaries show a modestly negative recalculated mean difference for Treatment One versus Control, with an interval close to zero at its upper end, and a more uncertain estimate for Treatment Two versus Control. The registry record’s limited analysis reporting, unadjusted comparisons, and unreported missing-data procedures constrain stronger conclusions.

17. Why This Trial Matters Statistically

This trial raises several statistical questions that are common in behavioral intervention studies. Its primary outcome is continuous and directly measured, yet the interpretation still depends on the difference between group means, the spread of individual changes, and the uncertainty around each comparison. Reporting all three helps avoid treating a point estimate as if it were exact or representative of every participant.

The three-arm structure also makes the comparison question important. The two intervention groups are each compared with control in the posted recalculations, but the registry does not report a direct coaching-versus-technology-alone contrast. A pattern in which one intervention estimate appears more favorable than another is not itself evidence that the interventions differ from one another. That distinction is especially relevant because the study summary hypothesizes a greater improvement with coaching.

The record illustrates why transparent analysis reporting matters. Randomization and masking are important design features, but they do not reveal which participants contributed to each outcome, how missing measurements were handled, whether baseline adjustment was used, or how multiple outcomes were treated. Without those details and sponsor-reported analyses, recalculated summaries are informative but cannot answer every question about the trial’s planned inference.

Finally, the secondary outcomes broaden the picture beyond mean weight change, while also increasing the need for a stated multiplicity strategy and clear hierarchy of outcomes. The posted results support careful comparison of estimates and their precision, rather than a single conclusion based on one p-value. This is a useful example of how effect estimates, uncertainty, analysis transparency, and outcome selection jointly shape interpretation.

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 registry information available for SMART 2.0. Although the study is marked completed, the record does not report sponsor-conducted analyses for the posted outcomes. The comparisons discussed are unadjusted recalculations from group summaries, so they cannot account for any model choices, covariates, or analysis procedures not described in the record.

Outcome counts are lower than the total enrollment, but reasons for this and the missing-data approach are not reported. The record does not define the analysis population or say whether participants without a 24-month outcome were included through an imputation or modeling procedure. This limits assessment of attrition and the extent to which the observed summaries represent all randomized participants.

The registry record does not give the original sample-size justification, a statistical analysis plan, the randomization procedure, or details of who was masked. Its sample-size illustrations use observed effect sizes and stated planning assumptions, rather than documenting the trial’s original design rationale. The record also does not report a multiplicity strategy despite the range of secondary outcomes.

Descriptions of the intervention components are incomplete in the available record. This restricts reproducibility and makes it difficult to judge which elements were delivered, how consistently they were used, or whether exposure differed across participants. Detailed weight-measurement procedures, timing of follow-up assessments, and information about adherence are not reported in the registry record.

Finally, the posted outcome information does not provide a direct comparison between the two intervention groups, nor does it report enough detail to establish the clinical importance of the estimated differences. These limitations do not invalidate the posted summaries, but they narrow what can be concluded from them.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: SMART 2.0: Social Mobile Approaches to Reducing weighT in Young Adults — NCT03907462.
• Registry record last updated 2025-04-15; status last verified 2025-03.
• Results first posted 2025-04-15.
• 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

SMART 2.0 is a completed, randomized, double-masked, parallel-group behavioral trial sponsored by the University of California, San Diego. It enrolled 638 young adults with overweight or obesity in a university setting and evaluated weight change from baseline to 24 months.

The primary outcome summaries show mean changes of -0.333 kg for technology with coaching, 0.737 kg for technology alone, and 1.202 kg for control. Unadjusted recalculated comparisons estimate a lower mean change for each intervention group versus control, with greater uncertainty for the technology-alone contrast. The registry record does not report sponsor-conducted analyses or explain missing outcome data.

Secondary outcomes and adverse events provide additional descriptive information, but their analysis methods and multiplicity handling are not reported. The results should be interpreted as registry summaries and unadjusted recalculations, not as a substitute for a full statistical analysis report.