Research Aimed at Improving Both Mood and Weight: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Research Aimed at Improving Both Mood and Weight (NCT02246413), a randomized na study. The primary outcome is Co-Primary Outcome: Body Mass Index (BMI).

2. Clinical Question

The registry describes RAINBOW as a randomized controlled trial evaluating a primary-care integrated multicondition intervention for mood and weight outcomes. Its co-primary outcome listing identifies BMI as the primary measure discussed in these results. The central statistical question is therefore about the average BMI in each assigned group and the estimated difference between those averages at the stated follow-up, rather than about individual responses or a guaranteed result for every participant.

3. Trial Design

The registry identifies NCT02246413 as a randomized, double-blind, parallel-group trial. It lists an enrollment of 409 and a completed status. The study start date is 2014-09-30, and the primary completion date is 2018-01-17. The phase is listed as NA. The sponsor is Palo Alto Medical Foundation.

Participants were assigned to the RAINBOW Intervention Program or usual care. The intervention is described as integrated support intended to help improve mood and weight in adults who may be at risk for diabetes and heart disease. The registry does not give a detailed account of the usual-care services, the allocation procedure, or how masking was maintained. It also does not report the original sample-size justification or the trial’s planned statistical analysis strategy.

The registry’s brief summary also describes ENGAGE, a mechanistic investigation added to the main trial. Beginning Jan 11, 2016, at least 100 newly enrolled participants were to be consented for additional assays evaluating neurobiological mechanisms of self-regulation. That description concerns an added investigation; the posted primary result is the 12-month BMI comparison. Results of the additional assays are not reported in the registry record.

For the primary outcome, the registry reports BMI means and standard deviations for each group, along with the number analyzed. Its description says that when study-measured weight was missing, the closest electronic health record weight within 3 months of the due date of a missed study visit was used; if no electronic health record weight was available, self-reported weight was used. The record notes that the number analyzed therefore does not match the Participant Flow module. It does not provide a full account of missingness or of how participants were handled in every analysis.

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.

12-months (Primary Outcome)

24-months (Secondary Outcome)

Analysis population for the primary outcome, as defined in the registry: In the case of missing study-measured weight, the closest EHR weight within 3 months of the due date of a missed study visit or self-reported weight (if no EHR weight) was used. So the number of participants analyzed is not consistent with the number in the Participant Flow module.

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 Co-Primary Outcome: Body Mass Index (BMI), measured over 12 months.

BMI is a measure relating weight to height, expressed in kg/m^2. It is used as a continuous outcome: each participant’s measured value contributes to a group average, and the primary comparison estimates the difference between those averages at 12 months. A continuous measure can retain information across the range of observed values, rather than reducing the outcome to a yes-or-no category. That makes the mean useful for describing the group-level distribution, although it does not show how much individual participants changed or how their values were distributed beyond the reported standard deviations.

The registry lists the primary outcome as a mean with standard deviation and gives the timeframe as 12 months. It describes the endpoint as integrated intervention treatment response, but the posted summary statistics are group BMI values rather than a separate responder count. The outcome is relevant to the study’s stated focus on weight, while the SCL-20 score provides a separate measure related to depressive symptoms.

The registry reports a mean BMI of 35.9 kg/m^2 for the RAINBOW Intervention Program group and 36.6 kg/m^2 for usual care. The posted unadjusted mean difference is -0.7 kg/m^2. A group mean difference describes the contrast between averages; it does not imply that each participant experienced that amount of change. The record’s use of electronic health record or self-reported weights when study-measured weight was missing is also part of how this endpoint was assembled and should be considered when interpreting it.

7. Results Posted in the Registry

• RAINBOW Intervention Program: mean 35.90 versus 36.60 on control; difference -0.70 (95% CI -2.05 to 0.65), standardized effect d = -0.11; z-test p = 0.308.

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.

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:
  • RAINBOW Intervention Program: mean 36.20 versus 36.20 on control; difference 0.00 (95% CI -1.43 to 1.43), standardized effect d = 0.00; z-test p = 1.000.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between RAINBOW Intervention Program and the control. The interval gives the range of effects that remain compatible with the data.

Depression Symptom Checklist 20 (SCL-20) Score

• 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:
  • RAINBOW Intervention Program: mean 1.30 versus 1.40 on control; difference -0.10 (95% CI -0.28 to 0.08), standardized effect d = -0.12; z-test p = 0.288.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between RAINBOW Intervention Program and the control. The interval gives the range of effects that remain compatible with the data.

Weight

• 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:
  • RAINBOW Intervention Program: mean 100.80 versus 103.40 on control; difference -2.60 (95% CI -7.08 to 1.88), standardized effect d = -0.12; z-test p = 0.255.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between RAINBOW Intervention Program and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary results span weight-related outcomes and depressive symptom scores, with measures at 12 and 24 months. The broad pattern is not a consistent set of clearly separated intervention-versus-usual-care estimates: the recalculated intervals for the continuous secondary comparisons include zero. This does not establish that all outcomes are identical between groups; it indicates that these posted comparisons retain uncertainty about the size and direction of their differences.

The secondary measures relate to the primary BMI result but answer distinct questions. BMI and body weight both describe weight-related outcomes, though on different scales. The SCL-20 score addresses depressive symptoms, so it adds a mood-related perspective rather than serving as another measure of BMI. Remission and treatment response are also listed as outcomes, but the registry’s secondary outcome list does not include posted numerical results for every listed measure in the record.

Secondary outcomes can help describe whether the pattern of results extends across related domains and follow-up times. However, they do not automatically confirm or overturn the primary result. Outcomes may differ in measurement, analyzed participants, completeness, and statistical precision. Any comparison across follow-up times should also recognize that a result at one time point does not establish persistence or change over time without an analysis designed to compare those time points.

Unadjusted secondary results carry less weight as confirmatory evidence when many outcomes are examined. The more comparisons considered, the greater the chance that at least one may appear unusual by chance. A prespecified hierarchy or multiplicity adjustment can help control that issue, but such procedures are not reported in the registry record. The secondary results are therefore most useful as descriptive context and as a record of the outcomes measured, rather than as a collection of independent definitive tests.

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

• Body Mass Index
• Depression Symptom Checklist 20 (SCL-20) Score
• Weight
• Weight
• Depression Remission (Number of Participants With SCL-20 Scores <0.5)
• Depression Remission (Number of Participants With SCL-20 Score <0.5)
• Depression Treatment Response (Number of Participants With ≥50% Decrease in SCL-20 Scores From Baseline)
• Depression Treatment Response (Number of Participants With ≥50% Decrease in SCL-20 Scores From Baseline)

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference describe?

For a continuous outcome such as BMI, the mean is the arithmetic average of the observed values in a group. The standard deviation describes how spread out those values are around the group mean. It is not the uncertainty of the mean itself. The primary results report a mean of 35.9 kg/m^2 and standard deviation of 7.1 for the RAINBOW Intervention Program group, and a mean of 36.6 kg/m^2 and standard deviation of 6.0 for usual care. The mean difference is reported as -0.7 kg/m^2, with the intervention group subtracted from the comparator in the direction used for the posted estimate.

A mean difference summarizes a contrast in averages, not a contrast in every participant’s outcome. It does not show whether most participants changed in the same direction, whether a small number of observations influenced the mean, or how the distributions overlap. Those questions require information beyond the group means and standard deviations.

What do the interval and p-value add?

An interval around an estimate communicates its precision: a narrower interval indicates less statistical uncertainty in the range of values compatible with the analysis, while a wider interval indicates more. The primary interval crosses zero, meaning values below and above zero are both compatible with the reported interval. The record does not state the confidence level for the interval in the information available, so the interpretation should focus on its endpoints and its inclusion of zero rather than assuming a particular level.

The unadjusted p-value is 0.308. In general, a p-value measures how unusual data at least as incompatible with a specified null model would be if that model and the calculation’s assumptions held. It is not the probability that the null hypothesis is true, nor is it a measure of the size or importance of the difference. A p-value should be read with the estimated effect and its interval, not in isolation.

What does “unadjusted” mean in these results?

The comparisons are simple unadjusted recalculations from the posted summary statistics. They do not incorporate covariate adjustment or a model-based correction that is not reported in the registry record. Randomization supports a comparison of assigned groups, but the specific planned analysis, treatment of repeated measures, and any adjustment strategy are not reported in the registry record. The recalculated values should therefore be understood as descriptive inferential summaries of the posted group data, not as a reconstruction of every step in the trial’s original analysis.

The posted primary means and standard deviations are paired with analyzed group counts of 183 and 184. These analyzed counts are not necessarily interchangeable with participant-flow counts: the registry explicitly notes that endpoint counts differ from the Participant Flow module because alternative weight sources could be used when a study measurement was missing. The full missing-data pattern and the analysis population definition are not reported in the registry record.

Why does variability matter?

Standard deviations help describe how much individual values vary within each group. When variation is large relative to the difference between means, the group averages may be estimated less precisely, unless supported by a large amount of information. This is one reason that a point estimate alone is insufficient. The standard deviations also provide context for the spread of the observed BMI values, but they do not show the distribution’s shape, outliers, or subgroup patterns.

More generally, over-dispersion means that data vary more than a statistical model expects. If a model fails to account for that extra variability, its uncertainty estimates can be too small and its evidence can appear stronger than warranted. The registry record does not report an over-dispersion assessment or a model for the primary continuous endpoint; this general concept should not be mistaken for a finding about this trial.

How should secondary tests be read?

The registry lists multiple outcomes, including BMI, weight, and SCL-20 depression symptom scores at different follow-up times, along with remission and response measures. Repeatedly testing outcomes creates a multiplicity issue: even when no real effects exist, a larger collection of tests makes it more likely that at least one result may appear notable by chance. An adjustment strategy can address this, but none is reported in the registry record. The posted recalculated comparisons are unadjusted and should not be treated as a definitive set of confirmatory tests.

The secondary outcomes also differ in measurement and analysis scale. BMI and weight are continuous measures summarized by means and standard deviations. The SCL-20 score is also continuous, while remission and treatment response are categorical outcomes in the registry listing. The posted numerical summaries described in the record do not cover every listed secondary measure, and formal reported analyses are absent. General statistical interpretation should respect those differences rather than treating every outcome as equivalent.

11. Confidence Intervals and Precision

The primary mean difference is -0.7 kg/m^2. Its interval extends to values on both sides of zero, so the estimate is not precise enough to exclude no difference under the reported interval. It also allows for effects in either direction. The interval is an important complement to the point estimate: the point estimate is a single summary of the group contrast, while the interval communicates the uncertainty around that summary.

Precision is not the same as clinical importance. A narrow interval can estimate a small contrast precisely, and a broad interval can leave substantial uncertainty even when the point estimate appears notable. Assessing practical importance would require an agreed threshold for meaningful change and context about the participants and outcome. Such a threshold is not reported in the registry record.

The group standard deviations are 7.1 and 6.0 kg/m^2, indicating substantial spread of BMI values around their respective means. These standard deviations describe participant-level variability; they are not confidence intervals and do not directly state the precision of the difference. The interval for the mean difference is the more direct summary of precision for the primary contrast.

The interval’s inclusion of zero should not be interpreted as proof of equivalence. Equivalence requires a prespecified range of differences considered acceptably small and an analysis designed to test whether the interval lies within that range. An equivalence margin and such an analysis are not reported in the registry record. Likewise, the unadjusted p-value of 0.308 does not quantify the probability that there is no effect or establish that the groups are the same.

The registry’s weight-substitution procedure is relevant to precision and interpretation because endpoint values could come from study measurement, an electronic health record, or self-report when study measurement was missing. The record does not report how often each source was used or how source choice affected variability. This limits assessment of measurement uncertainty beyond the statistical interval.

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 figures are planning illustrations based on the observed effect, not the trial’s original design assumptions. For these continuous outcomes, the figures are participants per arm, not total events. 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 the stated fraction of the observed effect. The trial’s own original sample-size assumptions are not reported in the registry record.

The 80% power column gives the estimated number of participants per arm that would be needed under those assumptions for an 80% chance of detecting the specified effect if that effect were the true one. The 90% power column uses the same interpretation with a higher target chance of detection. These are planning quantities, not observed outcomes of the completed trial. They describe hypothetical future designs built around the posted effect estimate and assumptions, rather than the probability that this completed trial succeeded.

The rows for planning at 100%, 75%, and 50% of the observed effect illustrate how the target effect size changes the required sample size. A smaller effect is harder to distinguish from random variation, so it generally requires more participants per arm to reach the same target power. The posted illustrations show this increasing requirement as the fraction of the observed effect becomes smaller.

These calculations are sensitive to their assumptions. Equal allocation, the normal approximation, the chosen significance level, and the effect estimate all shape the resulting planning numbers. A future study’s actual requirements could differ if its design, analysis, outcome variability, or target effect differed. The figures are not a substitute for a design-specific sample-size justification.

This is not observed power. Observed power calculated from the effect estimated in the same study adds little information beyond the estimate and its uncertainty. The planning figures are best read as illustrations of how much sample size may be needed for specified targets under the stated assumptions.

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 = -0.700; pooled standard deviation σ = 6.572.
2. n = 2 × (1.96 + 0.842)² × 6.572² / -0.700² = 1,383.5, rounded up to 1,384 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 <- -0.700000000000003                      # observed difference in means
sigma <- 6.57154930545093                     # 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(2246413)
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 = 1,384 (80% power), 1,853 (90% power)
 75% of observed effect: n per arm = 2,460 (80% power), 3,293 (90% power)
 50% of observed effect: n per arm = 5,534 (80% power), 7,409 (90% power)
power.t.test: 1384.5 
Simulated power at n = 1,384 per arm: 0.803 (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 lists 43 outcome measures and posts 41 secondary outcomes. This breadth raises a multiplicity question: repeated statistical testing across numerous outcomes can increase the chance of obtaining an apparently notable result even when the underlying differences are small or absent. The registry record does not report a multiplicity adjustment, a hierarchy of outcomes, or which outcomes were designated confirmatory before the results were examined. The posted secondary comparisons are unadjusted recalculations and should be interpreted with that limitation in mind.

The registry record also does not report a detailed statistical analysis plan, including a model specification, covariate adjustment strategy, or rules for handling all analysis populations. Although the trial is described as randomized and double-blind, those design labels do not supply the missing details of the analysis plan. The record lists zero reported analyses for the posted set, so a sponsor-reported inferential analysis is not available in the registry record.

Missing data are particularly relevant for the primary BMI outcome. The record states that when study-measured weight was unavailable, the closest electronic health record weight within 3 months of the missed visit’s due date was used; if no electronic health record weight was available, self-reported weight was used. It also states that the number analyzed does not match the Participant Flow module. This explains a discrepancy in counts but does not show how often each type of replacement measurement occurred, why study measurements were missing, or whether missingness differed between groups.

The analyzed numbers vary across outcomes, but the registry record does not give a full account of the reasons for those differences or define a common analysis population for all measures. It does not report a sensitivity analysis comparing alternative missing-data assumptions. As a result, the available information is insufficient to assess whether missingness could have affected the estimates or their precision. These omissions do not invalidate the posted summaries, but they limit how fully their robustness can be evaluated.

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: musculoskeletal problems (4.4%), cardiac problems (2.0%), digestive system problem (2.0%), psychiatric problems (1.0%), lymphoma diagnosis (1.0%).

The registry reports serious adverse events affecting 17 participants at risk in the RAINBOW Intervention Program group and 19 participants at risk in the usual-care group. The listed numbers at risk are 204 and 205, respectively. The record reports zero deaths in each group. Other adverse events affected 42 participants at risk in the RAINBOW group and 47 participants at risk in usual care.

The registry lists musculoskeletal problems at 4.4% among the serious adverse event terms, cardiac problems at 2.0%, digestive system problem at 2.0%, psychiatric problems at 1.0%, lymphoma diagnosis at 1.0%, and reproductive system problems at 1.0%. These are term-level figures as reported; they should not be read as evidence that the intervention caused those events. The record does not provide enough detail to determine event timing, severity beyond the serious-event classification, relatedness to treatment, or whether a participant could contribute more than one event term.

Counts of participants with events are descriptive safety information, not a randomized comparison adjusted for follow-up or other factors. The figures do not establish that one group was safer, and zero reported deaths does not address other aspects of risk. A complete safety interpretation would require the event definitions, ascertainment procedures, exposure and follow-up context, and attribution information, which are not reported in the registry record.

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

The primary result gives a group-level estimate for BMI at 12 months: the RAINBOW Intervention Program mean was 35.9 kg/m^2 and the usual-care mean was 36.6 kg/m^2, with an unadjusted mean difference of -0.7 kg/m^2. The interval includes zero, and the unadjusted p-value is 0.308. These results describe the posted data and the uncertainty around the estimated contrast; they do not establish a definitive difference or prove that no difference exists.

The estimate also does not describe the experience of every participant. Group averages can conceal variation in individual outcomes and in the distributions within each group. The posted means and standard deviations do not show which participants changed, how consistently outcomes changed, or whether different subgroups followed different patterns. The registry record does not report those details in the primary result.

The secondary measures provide related but separate information about weight and depressive symptoms. Their unadjusted estimates can help describe the range of outcomes recorded, but multiple outcomes and follow-up times make isolated findings less conclusive when no multiplicity strategy is reported. The secondary measures should not be treated as independent confirmation of the primary result.

The trial’s randomized design is relevant to the intended comparison, but the registry record does not report the full protocol or analysis plan needed to assess every analytic decision. In particular, the primary BMI endpoint could use electronic health record or self-reported weight when study-measured weight was missing, and the record notes that analyzed counts differ from participant flow. The available data do not reveal the frequency of these substitutions or the influence they may have had.

Accordingly, the result is best understood as an uncertain estimate from the posted registry summaries, not as a recommendation or a complete account of the trial’s clinical implications. It does not establish whether the intervention should be used, whether it changed outcomes for an individual, or whether any observed contrast was caused by the program. Those broader conclusions require context and evidence beyond this registry result.

17. Why This Trial Matters Statistically

This trial illustrates why a point estimate, its precision, and the analysis context need to be read together. The primary comparison has a negative estimated mean difference, but its interval crosses zero and its unadjusted p-value is 0.308. Focusing only on the direction of the point estimate would overstate what the data establish; focusing only on whether a p-value crosses a threshold would discard information about the estimate’s size and uncertainty.

It also illustrates how outcome construction matters. The primary result is based on BMI, with a registry-described fallback to electronic health record weight or self-reported weight when study-measured weight was missing. That approach affects what the endpoint represents and makes transparent reporting of measurement sources and missingness important for interpretation. The registry notes a difference between analyzed counts and the Participant Flow module but does not provide the detail needed to examine the consequences fully.

Finally, the record includes multiple outcomes spanning weight and mood, as well as a mechanistic investigation described as an addition to the main trial. Distinguishing the primary question from secondary and mechanistic questions helps prevent a large collection of measures from being read as a set of equivalent confirmatory tests. The lack of reported multiplicity procedures and formal analyses limits the strength of conclusions that can be drawn from the secondary results.

These statistical considerations matter because registry results are often the main accessible summary of a trial. Clear estimates, uncertainty intervals, outcome definitions, analysis populations, and missing-data procedures allow readers to judge what the evidence supports and where uncertainty remains. In this record, the primary group comparison is interpretable at a descriptive level, while important details about the planned analysis and the completeness of outcome measurement remain unreported.

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 that would help assess interpretation are not reported in the registry record. The intervention is described as an integrated program, but its components, intensity, adherence, and delivery are not detailed. Usual care is named as the comparator without a description of its services. The record therefore does not support a detailed account of what participants received in each group or how closely the program was implemented as intended.

The primary outcome may draw on different measurement sources. The registry says electronic health record weights or self-reported weights were used when a study-measured weight was missing, but does not report how often each source was used or how those values compared with study measurements. The number analyzed is explicitly noted as inconsistent with the Participant Flow module. The reasons for missing study measurements and the potential effect of the substitution procedure are not reported.

The registry record does not report the original sample-size justification, a detailed statistical analysis plan, formal sponsor analyses, or a multiplicity strategy. It also does not provide a full account of analysis populations or sensitivity analyses for missing data. Consequently, the posted unadjusted recalculations cannot answer questions that depend on those details.

The trial included a secondary mechanistic investigation, with at least 100 newly enrolled participants to be consented for additional assays beginning Jan 11, 2016. The summary describes the planned assays but does not report their results. Likewise, although the brief summary mentions clinical and cost effectiveness and implementation potential, those outcomes are not available in the posted results. The registry result therefore gives a limited view of the broader questions stated in the study description.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Research Aimed at Improving Both Mood and Weight — NCT02246413.
• Registry record last updated 2024-04-26; status last verified 2024-04.
• Results first posted 2020-06-11.
• 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

NCT02246413 is a completed randomized, double-blind, parallel-group trial sponsored by Palo Alto Medical Foundation, with enrollment listed as 409. It compared the RAINBOW Intervention Program with usual care in a primary-care study focused on adults with obesity and clinically significant depressive symptoms.

The primary result is mean BMI at 12 months. The reported means were 35.9 kg/m^2 for the intervention group and 36.6 kg/m^2 for usual care; the unadjusted mean difference was -0.7 kg/m^2, with an interval spanning zero and an unadjusted p-value of 0.308. The registry describes substitution of electronic health record or self-reported weight when study-measured weight was missing and notes that analyzed counts differ from participant flow.

Posted secondary results cover BMI, weight, and depressive symptom scores at additional time points. Interpretation is limited by unadjusted comparisons, multiple outcomes, and the absence of a reported analysis plan, multiplicity strategy, and detailed missing-data assessment. The statistical summaries describe estimates and uncertainty; they do not establish a definitive intervention effect.