Randomized Controlled Clinical Trial of Weight Loss Programs in Obese Persons: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Randomized Controlled Clinical Trial of Weight Loss Programs in Obese Persons (NCT00960414), a randomized na study. The primary outcome is Change in Weight From Baseline to 18 Months.

2. Clinical Question

This is a comparison of group summaries. It does not establish what happened to every participant, and it does not by itself explain why any observed difference arose. The results should be read as evidence about the specific program comparison and outcome definition recorded for SHINE.

3. Trial Design

SHINE was a completed, randomized, double-masked, parallel-group clinical trial sponsored by the University of California, San Francisco. The registry records the study start as 2009-08 and primary completion as 2013-08. Its condition was obesity, and its listed phase was NA. The registry describes the overall purpose as comparing two approaches to a diet and exercise-based weight-loss program.

Participants were assigned to SHINE A or SHINE B. SHINE A combined mindfulness training with diet-exercise education; SHINE B received diet-exercise education. The parallel design means the recorded comparison is between groups assigned to different approaches, rather than a comparison of the same participants receiving each approach in sequence. Random allocation can help make groups comparable on average, although it cannot ensure that every measured or unmeasured characteristic is balanced.

The record labels masking as double, but it does not say which people were masked or how masking was maintained. The randomization method, allocation concealment procedures, and any stratification factors are not reported in the registry record. The record also does not describe the original sample-size justification or detailed conduct of the intervention.

The enrollment figure is 194, while outcome-specific summaries use different arm counts. These counts should be understood in the context of the particular outcome rather than treated as interchangeable. For the primary weight outcome, the record notes pregnancy-related censoring of weight variables for two women in Arm B. The primary outcome description refers to attention-to-treat analyses of observed data. Further detail on how that analysis label was implemented is not reported in 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.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Two women in Arm B had weight-related variables censored at 18 months due to pregnancy.

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.

Population: We randomized 194 participants to two arms (100 to group A, 94 to group B).

6. Primary Endpoint

The registry lists the primary outcome as Change in Weight From Baseline to 18 Months, measured over 18 months.

The primary endpoint is change in body weight from baseline to 18 months, expressed in kilograms. A change score describes how the recorded weight at follow-up differs from baseline; a negative value in this record represents a decrease in weight. The registry frames the 18-month measurement as occurring approximately one year after intervention completion, so it reflects a follow-up outcome rather than only an immediate end-of-program measurement.

Weight change is used as a direct continuous measure of the outcome targeted by these diet-exercise programs. Reporting a mean summarizes the average change in each arm, while the standard deviation describes how spread out individual observed changes are around that arm's mean. A group mean is not a statement that every participant had the same change, and it does not reveal the full distribution of individual outcomes.

The registry describes the primary analysis as attention-to-treat using observed data. It also notes that two women in Arm B had weight-related variables censored at 18 months because of pregnancy. The record does not explain the broader handling of missing observations, the exact calculation of each participant's change, or whether additional adjustments were used in the sponsor's analysis. Those details matter when interpreting a mean change and the comparison between groups.

7. Results Posted in the Registry

• SHINE B: mean -3.20 versus -5.00 on control; difference 1.80 (95% CI 1.49 to 2.11), standardized effect d = 1.90; 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.

Fat Distribution

• 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:
  • SHINE B: mean -3.60 versus -4.80 on control; difference 1.20 (95% CI 0.89 to 1.51), standardized effect d = 1.27; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for SHINE B than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Insulin Sensitivity

• 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:
  • SHINE B: mean 0.50 versus -0.01 on control; difference 0.51 (95% CI -0.15 to 1.18), standardized effect d = 0.25; z-test p = 0.133.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SHINE B and the control. The interval gives the range of effects that remain compatible with the data.

Change in Perceived Stress From Baseline to 18 Months

• 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:
  • SHINE B: mean -0.11 versus -1.03 on control; difference 0.92 (95% CI -0.72 to 2.56), standardized effect d = 0.19; z-test p = 0.270.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SHINE B and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover a range of biological and psychological domains, including fat distribution, insulin sensitivity, perceived stress, stress hormones, autonomic nervous system function, adipocyte activity, and influenza vaccine response. The record lists eight secondary outcomes, but the numerical summaries represented in these results cover fat distribution, insulin sensitivity, and perceived stress. These outcomes provide context around the primary weight comparison rather than serving as interchangeable measures of the same effect.

At a broad level, the available secondary summaries do not all point to equally precise evidence of a group contrast. The fat-distribution comparison has an interval excluding zero, while the intervals for insulin sensitivity and perceived stress include zero. This mixed pattern does not negate the primary weight result, nor does it independently establish a broad effect across all measured domains. Different endpoints may have different variability, measurement properties, and relevance to the trial question.

Secondary outcomes generally carry less weight than a prespecified primary outcome because they are additional questions and may be assessed in greater number. If many comparisons are examined, some may appear noteworthy by chance even when there is no underlying difference. The registry does not report a multiplicity adjustment or a hierarchy for interpreting the secondary outcomes. Their unadjusted estimates and p-values should therefore be treated as exploratory or descriptive evidence rather than as confirmatory findings.

The record does not include numerical results for every listed secondary domain, so no conclusion about those unreported results is justified. Nor does the registry provide a joint analysis explaining whether changes in any secondary measure account for the weight comparison. The secondary outcomes can broaden the description of what the trial set out to measure, but they cannot establish a mechanism for the primary result on the information reported.

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

• Fat Distribution
• Insulin Sensitivity
• Change in Perceived Stress From Baseline to 18 Months
• Change in Positive Emotions Subscale of the Differential Emotions Scale
• Stress Hormones
• Autonomic Nervous System Function
• Adipocyte Activity
• Influenza Vaccine Response

9. Statistical Interpretation

10. Statistical Methods Explained

Statistical methods help distinguish the observed group summaries from uncertainty about the underlying comparison. The primary outcome is continuous: weight change can take a range of values, and the record reports a mean and standard deviation for each arm. The mean describes the center of the observed values. The standard deviation describes how much individual observations vary around that mean; it is not the uncertainty in the mean itself.

What does the mean difference represent?

The reported contrast is defined as the mean in SHINE B minus the mean in SHINE A. The posted means are -3.2 kg and -5.0 kg, respectively, and the simple unadjusted recalculation is 1.8 kg. Its positive sign means that the SHINE B mean is less negative. Since both means are changes from baseline, this is a difference between average changes, not a comparison of final weights alone. It is also not an estimate of an individual participant's likely change.

A mean difference is straightforward to interpret in the outcome's units, but it can conceal variation among participants. The arm standard deviations are 0.9 kg and 1.0 kg. A reader should not confuse these values with standard errors or confidence limits. Standard deviations describe observed spread; standard errors quantify sampling uncertainty in an estimate. The registry lists standard deviations for the primary outcome, while some secondary summaries report standard errors instead.

What does a confidence interval add?

A confidence interval expresses uncertainty around an estimated contrast. In general statistical terms, it gives a range of values compatible with the data and the method's assumptions. It does not mean that the true value has a particular probability of lying inside the calculated interval after the interval has been observed. The primary recalculated interval runs from 1.488 to 2.112 kg. Its location above zero indicates that the simple unadjusted calculation is inconsistent with a zero mean contrast at the corresponding conventional two-sided significance level. The interval's width also conveys precision: narrower intervals indicate less sampling uncertainty than wider intervals under the same approach.

The posted recalculation is explicitly unadjusted. It does not account for covariates, clustering, or other features unless those are incorporated in an analysis, and such details are not reported in the registry record. It should therefore be distinguished from any sponsor analysis that may have used a more detailed model. The record marks no discrepancy between the recalculated results and sponsor results, but does not give a complete account of the sponsor's analysis method.

How should a p-value be read?

The primary unadjusted p-value is < 0.001. In general, a p-value describes how incompatible the observed data, or more extreme data, would be with a specified null hypothesis under the statistical model. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of the difference. The estimate and confidence interval provide complementary information about direction, magnitude, and precision. A small p-value does not resolve concerns about missing observations, outcome selection, or model assumptions.

The secondary unadjusted p-values have to be read in their own outcome contexts. Insulin sensitivity and perceived stress have confidence intervals that include zero, whereas the fat-distribution comparison's interval excludes zero. An interval including zero indicates that the summary-based calculation does not rule out no mean difference at the corresponding level; it does not establish that the groups are identical. No multiplicity correction is reported, so the secondary p-values do not account for the fact that multiple outcomes are considered.

Why does over-dispersion matter?

For a continuous mean outcome, variation around the mean affects the standard error and therefore the precision of the estimated contrast. More variability generally makes a mean less precise when other features are held fixed. In other settings, such as counts, over-dispersion means that the observed variability exceeds what a simple model assumes; ignoring it can make uncertainty appear too small. That general concern illustrates why the statistical model should match the outcome and its variability. The registry does not report an over-dispersion assessment for SHINE, and the primary endpoint is recorded as a continuous mean rather than a count outcome.

For secondary insulin sensitivity and perceived stress, the registry reports standard errors rather than standard deviations. A standard error is a measure of uncertainty in the reported mean, not the spread of participant-level values. Those secondary summaries should not be read as if their spread values were directly comparable to the primary outcome standard deviations. The fat-distribution outcome is reported with standard deviations.

What can be inferred from the posted analysis?

The comparisons in the statistical summaries are simple, unadjusted recalculations from posted group summaries. They are not evidence that a specific covariate-adjusted model was used. The registry record does not report the sponsor's full model specification, handling of all missing values, or a detailed analysis population definition. The primary description says attention-to-treat analyses of observed data; that phrase does not, by itself, specify how missing outcomes were treated or whether all randomized participants contributed to each estimate.

Random allocation supports a group comparison by reducing systematic differences on average, but observed-data analyses can still be affected by missingness, measurement, adherence, and chance imbalance. A statistical result is therefore strongest when interpreted together with trial conduct and analysis details. For SHINE, the registry supports a description of the recorded arm means and their simple unadjusted contrast, while leaving important details of the full analysis strategy unreported.

11. Confidence Intervals and Precision

The primary mean difference is 1.8 kg for SHINE B compared with SHINE A. Its 95% confidence interval extends from 1.488 to 2.112 kg. The interval excludes zero and is centered around the posted contrast, indicating that the summary-based unadjusted estimate is relatively concentrated on a positive difference rather than spanning both directions. The interval nevertheless allows a range of possible contrast magnitudes; it should not be reduced to a claim that the exact difference is known.

Precision concerns the uncertainty of the estimated group contrast, not whether the result is important or whether the intervention caused it. A confidence interval is affected by variability, the number of observed outcomes, and the method used to estimate uncertainty. The primary arm summaries report standard deviations of 0.9 kg and 1.0 kg, with outcome counts of 81 and 65. The record also notes pregnancy-related censoring of weight variables for two women in Arm B. These features are relevant context when judging the estimate's precision and the population represented by the observed data.

The secondary results illustrate that precision varies by endpoint. The fat-distribution interval excludes zero, while the insulin-sensitivity and perceived-stress intervals include zero. The latter intervals consequently leave room for a range of contrasts that includes no mean difference under the recalculated method. This does not prove the absence of a difference; it indicates that the estimates are less decisive about direction relative to zero. The outcome scales and uncertainty measures differ, so the intervals should not be compared as if they measured the same quantity.

These intervals are simple unadjusted recalculations from posted summaries, not substitutes for a full sponsor model. The registry does not report all analysis details needed to assess whether the interval method accounts for every feature of the trial. Precision is therefore best described as precision of the posted-summary comparison, conditional on its assumptions.

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 own original design calculation. For these continuous outcomes, the figures are participants per arm, not total participants or total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row represents planning for a stated fraction of the observed effect. The primary-outcome illustrations give participants per arm for 80% power and participants per arm for 90% power at 100%, 75%, and 50% of the observed effect.

The 80% power column means that, under the stated planning assumptions and effect size, the design would have an 80% chance of producing a statistically significant result if that assumed effect were the true effect. The 90% column expresses the same idea at a higher probability of detection. Neither column is a probability that the observed result is correct. The primary illustrations list 5 and 6 participants per arm for planning for 100% of the observed effect, 8 and 11 for 75%, and 18 and 24 for 50%, at 80% and 90% power respectively.

Smaller effects require more participants to distinguish them from random variation with the same planned power and significance level. Thus, the planning figures increase as the assumed fraction of the observed effect gets smaller. These calculations are not observed power: they are hypothetical design illustrations using the observed effect as an input, not a retrospective measure of how likely the completed trial was to detect its result.

The registry record does not report the trial's own original sample-size assumptions or justification. The planning values should not be treated as evidence that the trial was designed around the observed contrast, nor as proof that the original design was adequate or inadequate.

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 = 1.800; pooled standard deviation σ = 0.946.
2. n = 2 × (1.96 + 0.842)² × 0.946² / 1.800² = 4.3, rounded up to 5 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 <- 1.8                      # observed difference in means
sigma <- 0.945750730607407                     # 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(960414)
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 = 5 (80% power), 6 (90% power)
 75% of observed effect: n per arm = 8 (80% power), 11 (90% power)
 50% of observed effect: n per arm = 18 (80% power), 24 (90% power)
power.t.test: 5.5 
Simulated power at n = 5 per arm: 0.748 (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 trial has a primary weight-change outcome and several listed secondary outcomes. Testing multiple outcomes creates a multiplicity issue: when many hypotheses are assessed, the chance of at least one apparently unusual result can rise even if all null hypotheses are true. Statistical approaches can address this, for example by adjusting significance thresholds or defining an ordered testing strategy, but the registry record does not report such a plan or any multiplicity adjustment.

This matters especially for the secondary comparisons. Their unadjusted p-values describe individual comparisons without accounting for the broader set of outcomes. A secondary result with a small unadjusted p-value should not automatically be read as confirmatory evidence. The primary result is more central to the stated trial question, but the registry record does not include enough information to verify the full prespecified outcome hierarchy or analysis plan.

Missing-data handling is another limitation. The primary description says attention-to-treat analyses of observed data and identifies two women in Arm B whose weight-related variables were censored at 18 months due to pregnancy. The record does not explain how other missing observations were handled, whether imputation was used, or whether sensitivity analyses assessed alternative missing-data assumptions. It also does not report whether the reason for missingness was examined beyond the pregnancy note. Results based on observed values can be affected if the availability of measurements is related to outcomes or group assignment.

Analysis populations are not fully defined. The outcome-specific arm counts differ, and the record does not provide a detailed participant flow or explain precisely which participants were included for each analysis. The phrase attention-to-treat does not fully specify the population or missing-data procedure. It is therefore not possible from the registry record to establish whether every randomized participant was included in the primary comparison according to a particular intention-to-treat definition.

The registry also does not report a detailed statistical analysis plan, original sample-size justification, interim analyses, covariate adjustment, or sensitivity analyses. Those items are not assumptions to be filled in by interpretation. Their absence limits assessment of prespecification, robustness, and the relationship between the posted summaries and any fuller sponsor 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 5% reporting threshold.

The serious adverse event figures are reported separately from the weight and secondary outcome summaries. For SHINE A, the registry lists 100 participants at risk for serious adverse events and 0 affected; for SHINE B, it lists 94 at risk and 0 affected. The reported death count is 0 in each arm. The other adverse event tally likewise lists 0 affected in each group, with the same at-risk counts recorded for that category. No top serious event terms are listed.

These figures describe what the registry reports for the stated categories and at-risk groups. A recorded zero means no affected cases are listed in that category; it is not proof that no adverse experiences occurred or that the programs are free of risk. Interpretation depends on event definitions, follow-up, reporting completeness, and how events were collected. Those details are not reported in the registry record. The at-risk counts also differ from the primary outcome counts, so they should not be substituted for the outcome-specific analysis populations.

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

The posted results describe mean weight decreases in both randomized arms over the baseline-to-18-month period. The SHINE A mean was -5.0 kg and the SHINE B mean was -3.2 kg. The simple unadjusted contrast is 1.8 kg for SHINE B compared with SHINE A, with a 95% confidence interval from 1.488 to 2.112 kg and p < 0.001. In direction, the recorded mean decrease was greater in SHINE A than in SHINE B.

This result is a comparison of the two program approaches as recorded: mindfulness training added to diet-exercise education versus diet-exercise education. It does not isolate the effect of mindfulness training from the rest of the program, establish the mechanism behind the contrast, or describe the experience of every participant. The mean difference is a group-level summary, and the registry does not report a threshold for deciding whether a particular difference is clinically meaningful.

The result also does not mean that every participant experienced a decrease, or that the observed comparison would necessarily be the same in a different population or setting. The primary outcome uses observed data, and the record notes pregnancy-related censoring for two women in Arm B. Further missing-data procedures and the complete analysis population are not reported. These details constrain how broadly and confidently the result can be interpreted.

The secondary outcomes offer additional but incomplete context. The available numerical summaries do not show uniform precision across outcomes, and no multiplicity adjustment is reported. They do not establish that the primary comparison occurred through a particular biological or psychological pathway. Numerical results for all listed secondary domains are not reported in the registry record.

Overall, the record supports a descriptive statement about the observed mean changes and a simple unadjusted comparison. It does not, on its own, provide the full analysis detail needed to resolve every question about missing data, model choice, multiplicity, or clinical importance. The distinction between a statistical contrast and a practical or clinical conclusion is essential when reading these results.

17. Why This Trial Matters Statistically

SHINE illustrates why trial results should be read through more than a single p-value. The primary outcome combines a clear direction in the observed arm means with an unadjusted confidence interval that excludes zero. The interval helps communicate the range of contrasts compatible with the summary-based analysis, while the p-value addresses a different question about compatibility with a null comparison. Neither statistic answers whether the difference matters to participants or explains how it arose.

The example also highlights the importance of defining the contrast. SHINE A and SHINE B differ by the addition of mindfulness training to diet-exercise education. The recorded comparison is between those program packages, not an isolated test of mindfulness. Correctly describing the comparison prevents an overstatement of what random assignment can identify.

Outcome-specific counts and pregnancy-related censoring show why analysis populations and missingness matter even when the main summary appears straightforward. A reported mean and standard deviation can be interpreted only with attention to which observations contributed and what happened to unavailable measurements. The registry provides some relevant information, but not a complete account of missing-data handling or the detailed analysis plan.

Finally, the secondary outcomes demonstrate the need to distinguish prespecified primary evidence from multiple additional comparisons. Unadjusted secondary results may be informative, but without a reported multiplicity strategy their evidential weight is more limited. Together, these features make SHINE a useful example of interpreting effect estimates, uncertainty, outcome hierarchy, and record completeness as parts of the same statistical assessment.

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.

The registry record leaves several trial-specific limitations unresolved. The primary endpoint is described as an attention-to-treat analysis of observed data, but the precise analysis population and handling of missing measurements are not reported. The note about pregnancy-related censoring in Arm B identifies one reason weight variables were unavailable, but it does not explain the treatment of other missing observations or whether conclusions were tested under alternative assumptions.

The posted arm counts vary by outcome, and the registry does not provide a detailed participant flow explaining all differences. Overall enrollment is recorded as 194, but that figure should not be taken as the number contributing to each outcome analysis. The record also does not describe adherence, intervention exposure, or whether the masking was successful; it says only that the trial was double masked.

The comparisons presented as simple recalculations are unadjusted. The registry does not give a complete sponsor model, adjustment variables, or a detailed statistical analysis plan. It also does not report the original sample-size justification or whether interim analyses were planned or performed. The planning illustrations based on observed effects are not evidence about the trial's original design.

For secondary outcomes, numerical summaries are available for only some of the listed domains in these results. The record does not report a multiplicity adjustment, and it does not set out how secondary findings should be prioritized. Finally, no threshold for a clinically meaningful difference in weight change is reported. These limitations do not erase the posted summaries, but they restrict how far the summaries can support claims about robustness, mechanism, or practical importance.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Randomized Controlled Clinical Trial of Weight Loss Programs in Obese Persons — NCT00960414.
• Registry record last updated 2024-07-24; status last verified 2024-07.
• Results first posted 2024-02-14.
• 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

NCT00960414 is the completed SHINE randomized, double-masked, parallel-group trial sponsored by the University of California, San Francisco. It compared mindfulness training added to diet-exercise education with diet-exercise education alone among people with obesity. The recorded enrollment was 194.

The primary outcome was mean weight change from baseline to 18 months. The posted means were -5.0 kg for SHINE A and -3.2 kg for SHINE B. The simple unadjusted recalculation for SHINE B compared with SHINE A was 1.8 kg, with a 95% confidence interval from 1.488 to 2.112 kg and p < 0.001. The registry notes pregnancy-related censoring of weight variables for two women in Arm B.

The record lists multiple secondary outcomes, but the numerical summaries considered include fat distribution, insulin sensitivity, and perceived stress. Detailed analysis methods, the original sample-size justification, multiplicity handling, and broader missing-data procedures are not reported in the registry record.