Adaptation of a Digital Weight Loss Intervention Promoting Self-regulation for Use in Type 2 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Adaptation of a Digital Weight Loss Intervention Promoting Self-regulation for Use in Type 2 Diabetes (NCT03650088), a na na study. The primary outcome is Change in Weight.

2. Clinical Question

3. Trial Design

This completed study evaluated a behavioral weight-loss program adapted for people with type 2 diabetes. Its stated aims were to adapt an existing weight-loss app to participants’ needs and perspectives, incorporate blood glucose monitoring and diet self-monitoring, develop data displays to support understanding and decision-making, and conduct a pilot and feasibility study of short-term impacts. The registry lists the study as a single-group behavioral intervention with enrollment of 18.

Because there was no randomized or other comparison arm, the design does not estimate a controlled treatment effect. The registry records allocation as NA and masking as NONE. With no comparison group, any reported change from baseline would be a within-group observation. Such a change could reflect the intervention experience, but the design alone cannot separate that experience from other influences over time. The record does not describe a protocol for addressing those influences.

The intervention combined digital self-monitoring tools with weekly consultation. The arm description names a smartphone app using a traffic-light approach for diet, a physical activity tracker, a smart scale, blood glucose monitoring, and consultation in person or by phone. The brief summary additionally describes integrating continuous glucose monitoring and developing displays of data. The record does not provide further detail on how often participants used each tool or on adherence to the program.

The registry lists the primary outcome as change in weight, measured on a digital scale, with baseline and Month 3 as the timeframe. It also names changes in BMI, HbA1c percent, diabetes self-control behaviors and efforts, and diabetes-related quality of life. Although the study status is completed, outcome analyses and numerical outcome results are not reported in the registry record. The record also does not report the protocol’s sample-size justification or a statistical analysis plan.

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.

Overall Study

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, Month 3.

The primary endpoint is change in weight in kilograms, with measurements scheduled at baseline and Month 3. The registry says weight will be measured on a digital scale and identifies the summary parameter as a mean, with standard deviation as the dispersion measure. Weight is a direct, continuous measurement relevant to a behavioral weight-loss program; examining it at two stated time points can describe how participants’ recorded weight changed during the study period.

A mean summarizes the average measurement for the group. A standard deviation describes how spread out individual measurements are around that mean. These summaries answer different questions: the mean describes the group’s central value, while the standard deviation conveys variation among participants. Neither one alone describes the precision of an estimated change. A confidence interval, if reported, would add information about the uncertainty around an estimate, but no weight estimate or confidence interval is reported in the registry record.

The endpoint is identified as a change, but the registry record does not state how that change was calculated, which analysis method was used, or how missing follow-up measurements were handled. Nor does the record provide the baseline and Month 3 values. The scheduled measurement makes the endpoint clear, but the absence of posted outcome results means the magnitude and precision of any change cannot be evaluated from the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry classifies the primary outcome as continuous and describes its parameter as a mean, with standard deviation as the measure of dispersion. These terms describe how an outcome is summarized; they do not identify a statistical test or establish that a particular analysis was performed. The record does not report outcome analyses.

What do mean and standard deviation convey?

For a continuous measurement such as weight, the mean gives the average for the observations included in a calculation. The standard deviation describes how far individual observations tend to vary around that average. A mean and standard deviation are descriptive summaries. By themselves, they do not show whether a change is statistically distinguishable from no change, nor do they show how precise an estimated change is. Precision is usually conveyed with an uncertainty measure such as a confidence interval, but no such estimate is reported for weight in the registry record.

The endpoint is described as change in weight between baseline and Month 3. In general, a change outcome can be represented as a difference between a participant’s measurements at two time points, then summarized across participants. When measurements come from the same participants, the two observations are related. An analysis of change should account for that relationship rather than treating the measurements as if they came from unrelated groups. This is a general statistical consideration, not a description of the study’s analysis. The registry record does not say whether the investigators analyzed individual changes, compared group means across time, or used another method.

Why does the study design shape the analysis?

This is recorded as a single-group study, with no comparator arm. A within-group analysis can describe change among participants, but cannot estimate a contrast between the intervention and a separate control condition. Even a precise estimate of change would not, by itself, show that the intervention caused that change. A comparative design supports a different question: whether outcomes differ between groups under the study conditions. That question is not answered by this single-group design.

The registry records allocation as NA and masking as NONE. It does not describe a randomization procedure, and none should be inferred. It also does not describe blinded outcome assessment. These design features matter because group assignment and knowledge of intervention can affect how a study is conducted or interpreted. The record does not state whether any additional procedures were used to reduce such influences.

What would an uncertainty interval add?

In general, a confidence interval gives a range of values compatible with the data and the method used to calculate the interval. Its width reflects statistical precision: wider intervals indicate more uncertainty about the estimated value than narrower intervals. An interval does not eliminate limitations in design or establish causation. For a single-group study, an interval around mean change would quantify uncertainty in that within-group estimate, not uncertainty in a controlled comparison. The registry record does not report a confidence interval for the primary outcome.

A hypothesis test, if used, would address a specified statistical question under stated assumptions. A p-value alone would not give the magnitude of change or its practical meaning, and it would not correct for the absence of a comparator. No test, p-value, or prespecified testing approach is reported in the registry record. The record also does not identify a statistical analysis plan or interim analyses.

How should variation and assumptions be considered?

Standard deviation describes variation among observed measurements. In general, when outcome data have greater variability than an analysis assumes, standard errors and significance tests based on that assumption may be unreliable. Over-dispersion is one example: the observed variability exceeds what a specified model expects. Appropriate modeling depends on the outcome’s distribution and study design. The primary outcome is continuous weight, but the registry does not give its distribution or identify a model, so no claim about over-dispersion or model adequacy can be made.

The registry’s sample-size justification is not reported. Its record describes a pilot and feasibility purpose, but does not state a planned minimum effect, power target, or calculation supporting enrollment. In general, a sample-size calculation is a planning exercise based on assumptions; it is not evidence that a study had a particular probability of detecting an effect after the data are observed. No conclusion about observed power or the adequacy of the planned enrollment is supported by the registry record.

The same caution applies to any planning illustration based on an observed effect: such an illustration depends on the estimate and assumptions used and is not an observed trial result. Since the registry record does not report outcome estimates or a statistical analysis, it does not permit an assessment of the precision of the primary endpoint or the assumptions underlying an analysis.

10. Confidence Intervals for Each Arm

No two-arm comparison is shown for this trial, but each arm's mean can be given with a t-based 95% confidence interval computed from the posted mean, spread and number of participants.

R code and output

arm <- c("Weight Loss Intervention")
n   <- c(17)
m   <- c(-4.54)
sp  <- c(1.01)
sd  <- sp      # posted standard deviations
for (i in seq_along(n)) {
  se <- sd[i] / sqrt(n[i]); h <- qt(0.975, n[i] - 1) * se
  cat(sprintf("CARM|%s|%d|%.3f|%.3f|%.3f|%.3f\n", arm[i], n[i], m[i], sd[i], m[i] - h, m[i] + h))
}

CARM  Weight Loss Intervention  17  -4.540  1.010  -5.059  -4.021

11. Multiplicity, Missing Data and Analysis Populations

The registry names secondary outcomes involving BMI, HbA1c percent, diabetes self-control behavior and effort, and diabetes-related quality of life. It lists five outcome measures overall. The record does not identify an additional outcome beyond the named measures, nor does it report which outcomes were analyzed or their results.

When a study examines multiple outcomes or performs multiple statistical tests, the chance of at least one apparently notable result can increase. A prespecified approach to multiplicity can help readers understand how results were selected and interpreted. The registry record does not report a multiplicity plan, a hierarchy among outcomes, or whether any adjustment was used. It is therefore not possible to determine from the record how the investigators would distinguish primary from exploratory findings in their statistical interpretation.

The record does not report missing-data counts, reasons for missingness, or methods for handling incomplete measurements. This matters for the baseline and Month 3 weight endpoint because a change estimate depends on the available measurements and the analysis population. The record also does not define an intention-to-treat, per-protocol, or other analysis population. Enrollment of 18 should not be assumed to mean that all enrolled participants contributed data to every outcome.

These omissions do not establish that data were missing or that multiplicity adjustments were not made; they mean those details are not reported in the registry record. Without analysis populations, missing-data methods, and a multiplicity strategy, readers cannot assess how those choices may affect precision or the interpretation of any outcome estimates.

12. 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.

The adverse-event record lists the Weight Loss Intervention group. It reports 0 serious adverse events among 18 participants at risk, 0 other adverse events among 18 participants at risk, and 0 deaths. These are the counts recorded in the registry for the listed group.

Such figures describe reported events within the registry’s recording framework. A zero count does not establish that no symptoms or unwanted experiences occurred; it indicates that the record lists no events in those categories. The adverse-event information does not include a list of serious-event terms. The registry also does not report the period over which participants were considered at risk, event definitions, how events were collected, or whether participants were systematically asked about events.

Because the study has no comparator group, these figures cannot be used to compare event frequency with another intervention or with no intervention. They also do not, by themselves, establish a general safety profile. They should be read narrowly as the adverse-event counts posted for this single-group study, alongside the limitations in event detail and follow-up reporting.

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

The registry record establishes that the study was completed and describes a digital behavioral weight-loss intervention adapted for adults with type 2 diabetes. It identifies weight change from baseline to Month 3 as the primary endpoint and reports enrollment of 18. It also lists outcomes concerning BMI, HbA1c percent, diabetes self-control behavior and effort, and diabetes-related quality of life. These details clarify what the study set out to evaluate.

The record does not report outcome values, estimates of change, confidence intervals, or statistical tests. It therefore does not establish whether weight or any listed secondary outcome increased, decreased, or remained similar. No claim about the size, precision, statistical significance, or clinical importance of an outcome can be drawn from the information reported in the registry.

Even if within-group changes were available, the single-group design would describe change during participants’ involvement rather than isolate the intervention’s effect from other influences. There is no control group with which to compare the participants’ course. A pre-post change can be useful descriptively, particularly in a pilot, but it is not equivalent to a randomized treatment contrast.

The study’s stated purpose includes adapting the intervention and assessing short-term impacts in preparation for a future R01 submission. That purpose is consistent with an early-stage pilot and feasibility effort, but the registry record does not report feasibility findings, participant engagement, adherence, or reasons for any discontinuation. Completion status alone does not supply those results.

Accordingly, the strongest interpretation supported by the record is about study intent and design: a digital program combining self-monitoring tools and behavioral consultation was evaluated in a single group, with weight scheduled for assessment at baseline and Month 3. The record does not provide the outcome evidence needed to judge the observed changes or to make causal claims.

14. Why This Trial Matters Statistically

This study is statistically instructive because its purpose and design should guide the claims made from its data. The registry describes a pilot and feasibility study of a digital intervention adapted for people with type 2 diabetes, not a randomized comparison. Its primary endpoint is a continuous measure of weight at baseline and Month 3. That setup invites a description of within-participant change, but it does not support an intervention-versus-control estimate.

The distinction matters because statistical precision and causal interpretation are separate issues. A mean change could be estimated with greater or lesser precision, and an uncertainty interval could quantify that precision. Yet even a precise within-group estimate would not resolve whether changes were due to the intervention rather than other factors occurring over time. A stronger causal comparison requires a design capable of distinguishing those explanations.

The record also illustrates why a completed status should not be confused with a posted analysis. Enrollment, intervention details, and an endpoint schedule describe the study’s conduct and intentions; they do not supply the observed weight values or estimates. Without results, there is no basis for interpreting the direction or magnitude of change, nor for examining how missing data, outcome selection, or statistical methods affected the findings.

Finally, the program combines multiple components: an app, dietary and activity monitoring, a smart scale, blood glucose monitoring, and consultation. The registry describes a combined intervention rather than a design that isolates the contribution of each tool. For statistical interpretation, that means the study question concerns the program as a whole, and the record does not support separate estimates for individual components.

15. 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.

The main limitation for interpreting this registry entry is that outcome analyses and numerical results are not reported. Although the primary endpoint and its assessment times are stated, baseline and Month 3 weight values, the estimated change, and its uncertainty are absent. The registry record therefore does not support conclusions about the observed primary outcome or the listed secondary outcomes.

The single-group design limits causal interpretation. Without a comparator arm, changes over time cannot be distinguished from other influences. The record also identifies no allocation method beyond NA and lists masking as NONE. It does not report additional procedures that might address bias in outcome measurement or analysis.

Details needed to evaluate the analysis are not reported in the registry record. These include the analysis population, missing-data counts and methods, the statistical method for estimating change, the multiplicity approach for multiple outcomes, and the sample-size justification. The record does not describe participant adherence, engagement with digital tools, or intervention fidelity. Those omissions limit assessment of both outcome estimates and feasibility.

The adverse-event entry gives counts for the intervention group but does not report event definitions, ascertainment procedures, or the risk period. The absence of listed events should therefore be interpreted only as the counts recorded, not as a complete account of all possible unwanted experiences.

These limitations are specific to what the registry record reports and do not establish that relevant information was absent from study conduct or other records. They do, however, constrain what can be concluded from this entry alone.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Adaptation of a Digital Weight Loss Intervention Promoting Self-regulation for Use in Type 2 Diabetes — NCT03650088.
• Registry record last updated 2023-01-13; status last verified 2021-12.
• Results first posted 2023-01-13.
• 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.

19. Record Summary

The registry identifies NCT03650088 as a completed, single-group behavioral intervention study sponsored by the University of North Carolina, Chapel Hill. Enrollment was 18. The study adapted a digital weight-loss program for adults with type 2 diabetes, with an app, dietary self-monitoring, physical activity tracking, a smart scale, blood glucose monitoring, and weekly consultation with an interventionist.

The primary outcome was change in weight in kilograms, measured by digital scale at baseline and Month 3. Listed secondary outcomes concern BMI, HbA1c percent, diabetes self-control behavior and effort, and diabetes-related quality of life. The adverse-event record lists 0 serious adverse events, 0 other adverse events, and 0 deaths in the intervention group.

Although the study status is completed, outcome analyses and numerical results are not reported in the registry record. The record also does not report a statistical analysis plan, missing-data methods, analysis populations, or a multiplicity plan. Its findings therefore cannot be evaluated from this entry.