Computer-Based Weight Maintenance in Primary Care: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Computer-Based Weight Maintenance in Primary Care (NCT01946191), a randomized na study. The primary outcome is Body Weight.

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group behavioral trial with no masking. The registry lists an enrollment of 194 and a completed status. The recorded start date is 2013-10-01, and the primary completion date is 2017-03-02. The phase is listed as not applicable. The University of Pittsburgh is identified as the sponsor.

The intervention contrast was between a multicomponent EHR-based program and online self-monitoring alone. The Coaching Group received personalized portal coaching, scheduled contacts, online self-monitoring, and real-time updates to primary care physicians. The Tracking Group received online self-monitoring. The registry summary frames the study hypothesis as an incremental benefit from personalized coaching and primary-care support for patients seeking to maintain recent intentional weight loss of at least 5%.

The primary outcome summaries report 80.0 participants in the Coaching Group and 77.0 in the Tracking Group. Those outcome counts are distinct from the registry’s overall enrollment figure. The record does not explain the relationship between enrollment and the numbers contributing to this outcome, including whether any participants lacked outcome data or were excluded from a particular analysis.

Randomization supports a between-group comparison by assigning participants to intervention groups, but the record does not report the sequence-generation procedure, allocation concealment, or detailed analysis population. Because masking is listed as none, the trial was unmasked. The record does not describe steps, if any, taken to limit the influence of that design feature on outcome measurement or study conduct.

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.

Allocation

Reasons for not completing this period:

Follow-Up, 24-mo Endpoint

Reasons for not completing this period:

Primary Outcome Analysis

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 Body Weight, measured over Baseline to 24 months.

The primary endpoint is body weight in kilograms, expressed as change from baseline to 24 months. The registry describes the outcome as an estimate with a standard error and a 95% confidence interval for the change. A change score focuses on how weight at follow-up differs from the participant’s baseline rather than treating a single weight measurement as the outcome.

Using a continuous measure preserves information about the size and direction of weight change across participants. The group mean summarizes the average change, while the between-group mean difference compares those averages. A positive mean change indicates an increase relative to baseline; in these results, the group estimates are positive. The primary comparison therefore concerns whether the average increase differed between the randomized groups over the stated follow-up interval.

The endpoint is relevant to the trial’s stated purpose because the intervention was designed to support maintenance of recent intentional weight loss. Still, a group mean does not indicate how many individuals maintained a particular amount of weight loss. The registry lists maintenance of 5% weight loss as a secondary outcome, which addresses a threshold-based question separately. Details of the measurement procedures, timing windows, and handling of repeated or missing weight measurements are not reported in the registry record.

7. Results Posted in the Registry

• Tracking Group: mean 4.93 versus 2.07 on control; difference 2.86 (95% CI 1.13 to 4.59), standardized effect d = 0.52; z-test p = 0.001.

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.

BMI

• 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 errors.
• Result:
  • Tracking Group: mean 1.80 versus 0.80 on control; difference 1.00 (95% CI 0.38 to 1.62), standardized effect d = 0.50; z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Tracking Group than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Waist Circumference (cm)

• 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 errors.
• Result:
  • Tracking Group: mean 3.83 versus 1.34 on control; difference 2.49 (95% CI 0.45 to 4.53), standardized effect d = 0.38; z-test p = 0.017.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Tracking Group than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Maintenance of 5% Weight Loss

• 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:
  • Tracking Group: 94.8% (73/77) versus 98.8% (79/80) on control; risk difference -3.9 percentage points (95% CI -9.5 to 1.6), risk ratio 0.96 (0.91–1.02); unadjusted two-proportion z-test p = 0.159.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tracking Group and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary outcomes spanning body size, maintenance of a weight-loss threshold, physical activity, health-status measures, function, and systolic blood pressure. The posted numeric results include BMI, waist circumference, and maintenance of 5% weight loss. The registry lists additional secondary outcomes, but corresponding results are not included in the posted outcome summaries described in this record.

The continuous body-size outcomes have group patterns that point in the same broad direction as the primary body-weight comparison: average changes are larger in the Tracking Group than in the Coaching Group. The threshold-based maintenance outcome has a different statistical profile: the posted unadjusted comparison does not provide the same degree of evidence for a group difference as the primary continuous outcome. This contrast illustrates that a continuous measure and a thresholded count answer different questions. Categorizing an outcome at a cutoff can discard information about the amount of change.

These secondary findings can add context to the primary result, but they do not replace it. BMI and waist circumference concern related aspects of body size, while maintaining a 5% loss asks whether a participant met a particular threshold. Agreement or disagreement across these outcomes does not establish a mechanism, and related measures are not independent pieces of evidence simply because they have different names.

The registry record lists no reported analyses for the secondary outcomes. The comparisons are unadjusted recalculations from posted summaries, and the record does not report a plan for controlling the chance of false-positive findings across multiple outcomes. For that reason, secondary p-values carry less weight than a clearly prespecified primary analysis would. The absence of a reported result for other listed outcomes should not be interpreted as evidence of no effect; the corresponding analyses are not reported in the registry record.

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

• BMI
• Waist Circumference (cm)
• Maintenance of 5% Weight Loss
• Pedometer Steps Per Day
• Physical Component Score (SF-36)
• Mental Component Score (SF-36)
• WOMAC Function Score
• Systolic Blood Pressure

9. Statistical Interpretation

10. Statistical Methods Explained

For the primary outcome, the posted group summaries are means of a continuous measure: change in body weight from baseline to 24 months. A mean is the arithmetic average of the observations contributing to the summary. The reported standard error describes the statistical uncertainty in estimating a group mean; it is not the spread of individual participants’ weight changes. Because the record does not give standard deviations for the primary endpoint, those should not be inferred from the standard errors without additional assumptions.

What does a mean difference represent?

The comparison is Tracking Group minus Coaching Group. A mean difference is the difference between the two group averages, expressed in the same unit as the outcome, kilograms. A positive value in this direction means the Tracking Group’s average change is larger. The posted estimate is 2.86 kg. This contrast is useful because it expresses the group separation directly, while the separate group means show the direction of change relative to baseline in each arm.

In general, a difference in means is a measure of location, not a description of the full outcome distributions. Two groups can have the same mean while differing in variability or in how observations are distributed. The registry summaries do not provide the individual-level distributions, so the averages cannot show whether changes were similar across participants or concentrated among a subset.

What do the standard error and confidence interval add?

In general, a standard error quantifies the sampling uncertainty of an estimated quantity under the calculation’s assumptions. It is different from a standard deviation, which describes variability among observations. A confidence interval gives a range of estimates compatible with the observed data under a specified method. For the primary difference, the posted 95% confidence interval is 1.128 to 4.592 kg. Its interpretation depends on the method and assumptions used; the registry record does not identify the original inferential procedure.

The primary comparison is a recalculated, unadjusted comparison from posted summary statistics. “Unadjusted” means the calculation does not account for covariates or other model terms. This is not a substitute for an investigator analysis that might have been prespecified or otherwise appropriate to the trial. No reported analyses are listed in the registry record, and the detailed statistical plan is not reported in the registry record.

How should the p-value be read?

In general, a p-value measures how unusual data at least as extreme as those observed would be under a specified null model. It does not give the probability that the null hypothesis is true, and it does not measure the clinical importance of an estimate. The primary unadjusted p-value is 0.001. It should be interpreted alongside the estimated difference and its confidence interval, not as a stand-alone measure of evidence.

The posted summary does not identify whether the investigators planned one primary comparison, how they handled multiple outcomes, or whether any interim analyses were conducted. Those details are not reported in the registry record. The unadjusted label matters because no multiplicity correction is reflected in the recalculated p-value.

Why do the planning illustrations depend on effect size?

In general, a sample-size calculation relates a target effect to variability, a significance threshold, a desired probability of detecting that effect, and design choices such as allocation. For a fixed set of assumptions, smaller effects are harder to distinguish from random variation and generally require more participants. The registry’s planning illustration uses the observed effect and fractions of it; it is not evidence about the trial’s original planning rationale. The original sample-size justification is not reported in the registry record.

These methods describe statistical summaries and general concepts. They do not establish that the assumptions behind the calculations match the trial’s actual conduct. The registry record does not report the outcome-level missing-data procedure, the primary analysis population, or whether the reported means incorporate any model-based adjustments.

11. Confidence Intervals and Precision

The primary mean difference is 2.86 kg, with a 95% confidence interval from 1.128 to 4.592 kg. The interval is entirely positive, which aligns with the direction of the point estimate: the Tracking Group had the larger average increase in weight relative to baseline. The interval also shows that the exact size of the group difference is not pinned down by the estimate alone.

In general, a confidence interval communicates uncertainty in an estimated population quantity under the assumptions of its calculation. It is not a guarantee that the true value lies in the interval, nor is it a range for individual participants’ outcomes. The confidence interval’s width reflects sampling uncertainty as represented by the calculation, but it does not capture every potential source of uncertainty, including bias from missing data or limitations in measurement and analysis that cannot be assessed from the registry record.

The posted standard errors for the group means are 0.62 for the Coaching Group and 0.63 for the Tracking Group. The registry does not provide separate confidence intervals for those arm means. The between-group interval is more directly relevant to the comparative question than interpreting the two mean estimates in isolation.

Precision and statistical evidence are related but distinct. A small unadjusted p-value accompanies this interval, yet neither the p-value nor the interval determines whether a difference is important to patients or meaningful in practice. The registry record does not identify a threshold for an important difference in weight change. Therefore, the statistical interval can describe uncertainty in the estimated contrast, but it cannot on its own establish the practical importance of that contrast.

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 illustrations use participants per arm for the continuous outcomes, including the primary body-weight outcome. They are not total-event counts. The assumptions listed for these calculations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is specified as a fraction of the observed effect. For the primary outcome, the illustrations give participants per arm for both 80% power and 90% power at 100%, 75%, and 50% of the observed effect.

In plain language, the 80% power column describes the estimated number of participants per arm needed for an 80% chance of detecting the stated effect under the calculation assumptions, if that effect is real. The 90% power column expresses the corresponding planning target for a 90% chance. These are prospective planning concepts, not descriptions of what happened in the completed trial. Smaller effects require more participants under otherwise unchanged assumptions, which is why the illustrations increase as the assumed fraction of the observed effect becomes smaller.

The calculations are planning illustrations based on the observed effect, not the trial’s original design calculations. The original sample-size justification and its assumptions are not reported in the registry record. This is not observed power: it does not measure the probability that the completed trial detected an effect after looking at its results. The values should be read as conditional illustrations that depend on the stated assumptions, rather than as a recommendation for a future study or proof that a particular design is adequate.

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 = 2.860; pooled standard deviation σ = 5.537.
2. n = 2 × (1.96 + 0.842)² × 5.537² / 2.860² = 58.8, rounded up to 59 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 <- 2.86                      # observed difference in means
sigma <- 5.53701142168507                     # 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(1946191)
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 = 59 (80% power), 79 (90% power)
 75% of observed effect: n per arm = 105 (80% power), 141 (90% power)
 50% of observed effect: n per arm = 236 (80% power), 316 (90% power)
power.t.test: 59.8 
Simulated power at n = 59 per arm: 0.794 (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

Multiplicity arises when several outcomes, comparisons, time points, or analytic choices are examined. In general, the more statistical tests conducted, the greater the chance that at least one result may appear unusual by chance if all null hypotheses are true. A prespecified testing strategy or an adjustment can address this issue, but the registry record does not report whether either was used.

The record identifies one primary outcome and lists multiple secondary outcomes. It does not report how the primary and secondary tests were ordered, whether secondary findings were intended to be confirmatory or exploratory, or whether multiplicity adjustments were planned. The posted secondary comparisons are unadjusted recalculations. Their p-values should therefore be read as individual, unadjusted results, not as conclusions that account for the full set of outcomes.

Missing-data handling is also not reported in the registry record. The overall enrollment is 194, while the primary endpoint summaries list 80.0 participants in the Coaching Group and 77.0 in the Tracking Group. The record does not explain how these numbers relate to all enrolled participants, why some participants may not appear in the outcome summaries, or whether the reported endpoint values come from a complete-case, intention-to-treat, or other analysis population. No missing-data method, imputation procedure, or sensitivity analysis is described.

These omissions matter because the interpretation of a randomized comparison can depend on which participants are included and how unavailable outcomes are handled. Random assignment alone does not resolve uncertainty arising after randomization. The record also does not report interim analyses, stopping rules, or the full statistical analysis plan. Their absence from the registry record should be understood as unavailable documentation, not as proof that such procedures were or were not used.

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 serious adverse event summaries list 0 affected participants in the Continued Group among 98 at risk and 0 in the Tracking Group among 96 at risk. Deaths are listed as 0 in both groups. For other adverse events, the record lists 48 affected participants among 98 at risk in the Continued Group and 67 among 96 at risk in the Tracking Group.

These are counts of participants recorded as affected, not counts of distinct event episodes. The registry record does not define the adverse-event categories, describe how events were collected, or provide event-level details. It also gives no serious-event terms in the listed serious-event summary. The label “Continued Group” is used in this safety record; the record does not explain its relationship to the intervention labels used for the primary outcome.

Counts alone do not establish whether an intervention caused an event or whether groups differed in risk. Interpretation depends on definitions, follow-up, ascertainment, and participant-level context. The reported zeros mean that no affected participants or deaths are listed in those serious-event fields; they do not establish that no other health events occurred.

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

The posted primary results describe a difference in average body-weight change from baseline to 24 months between two randomized groups. The Coaching Group’s mean change was 2.07 kg and the Tracking Group’s mean change was 4.93 kg. The mean difference for Tracking Group relative to Coaching Group was 2.86 kg, with a 95% confidence interval of 1.128 to 4.592 and an unadjusted p-value of 0.001. These figures describe the posted comparison and its statistical uncertainty.

The trial’s stated question concerns whether coaching and primary-care support add benefit to online self-monitoring for maintaining recent intentional weight loss. The primary outcome pattern is consistent with a smaller average increase in the Coaching Group than in the Tracking Group. It does not establish that each participant in the Coaching Group maintained weight loss, or that every participant in the Tracking Group gained weight. A group average cannot describe the range of individual outcomes.

The result does not by itself show that the intervention caused the observed difference. Randomization is an important design feature, but interpretation also depends on how outcomes were measured, who contributed data, and the analysis procedure. The registry record does not report enough detail to evaluate missing-data methods, the analysis population, or the full statistical plan. Those limitations qualify how precisely the causal contrast can be assessed from the registry results alone.

The result also does not establish clinical importance. The registry record does not state a threshold for a meaningful difference in weight change, and statistical evidence is not the same as practical significance. Nor does the result establish effects on health outcomes beyond those specifically measured and reported. The record lists several secondary outcomes, but does not report analyses for all of them.

In short, the posted primary summaries show a positive between-group difference in average weight change, with uncertainty quantified by the stated interval. They do not answer every question about individual response, long-term outcomes, or the mechanisms underlying the contrast.

17. Why This Trial Matters Statistically

This trial is statistically informative because it separates the effect of a multicomponent support program from the effect of online self-monitoring alone. The intervention contrast is aligned with the registry’s stated hypothesis about the incremental contribution of personalized coaching and primary-care support. That framing is more specific than a comparison of a program with no support, and helps define what the primary estimate can address.

The primary outcome is continuous, and its comparison is expressed in the original unit of kilograms. This gives a direct estimate of the difference in average change, with a confidence interval describing uncertainty. The posted secondary outcomes also illustrate why outcome type matters: a continuous measure of change and a count of participants meeting a weight-loss threshold convey different information and may produce different statistical patterns.

The record also illustrates the distinction between statistical evidence and evidentiary completeness. A numerical estimate, confidence interval, and unadjusted p-value can be recalculated from posted summaries, but they do not reveal the original analysis plan, missing-data strategy, or multiplicity approach. Readers need those details to understand how closely a summary-statistic comparison corresponds to the investigators’ intended analysis.

Finally, planning calculations based on an observed effect should not be confused with the original design rationale or with observed power. Their value is illustrative: they show how planning requirements change when the target effect changes under stated assumptions. The trial therefore offers a useful example of how to interpret an effect estimate while keeping design, analysis, precision, and reporting limitations distinct.

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 trial-specific details needed for a fuller assessment are not reported in the registry record. These include the eligibility criteria beyond the summary description, participant characteristics, randomization and allocation-concealment procedures, and the detailed intervention delivery and adherence. The record describes scheduled coaching contacts and portal-based components, but does not report how much of the intervention participants received or whether use of online self-monitoring differed between groups.

The registry reports overall enrollment of 194, while the primary endpoint summaries include 80.0 participants in the Coaching Group and 77.0 in the Tracking Group. It does not explain the difference between the enrollment figure and endpoint counts. Without participant flow, reasons for unavailable outcomes, or a reported analysis population, it is not possible to determine from this record whether missing observations could have affected the comparison.

The record does not report measurement procedures for body weight, the timing window around the 24-month assessment, or an analysis plan. It also does not give a clinical threshold for an important difference. The recalculated primary comparison is unadjusted, and the record lists no reported analyses. Consequently, it should not be assumed to reproduce an investigator-specified model or account for covariates, repeated observations, or other design features.

There is also a naming inconsistency: the BMI summary uses “Continued Group,” while the primary outcome and intervention descriptions use “Coaching Group.” The safety summary also uses “Continued Group.” The registry record does not clarify whether these labels refer to the same group. These reporting limitations do not change the numerical entries, but they constrain how confidently the group labels and analytic details can be reconciled across outcomes.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Computer-Based Weight Maintenance in Primary Care — NCT01946191.
• Registry record last updated 2020-11-02; status last verified 2020-10.
• Results first posted 2020-11-02.
• 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

The registry record describes a completed randomized, parallel-group behavioral trial sponsored by the University of Pittsburgh. It enrolled 194 participants and compared an EHR-based program of personalized coaching, online self-monitoring, and real-time physician updates with online self-monitoring alone. The stated purpose was to support maintenance of recent intentional weight loss of at least 5%.

The primary outcome was body-weight change from baseline to 24 months. The posted summaries show a mean difference of 2.86 kg for Tracking Group relative to Coaching Group, with a 95% confidence interval of 1.128 to 4.592 and an unadjusted p-value of 0.001. The record lists secondary outcomes and adverse-event counts, but does not report the full statistical plan, missing-data methods, or analyses for all listed outcomes. The findings are best read as registry-level summaries whose precision and interpretation depend on those reporting limitations.