Mindfulness for Pain and Suicide: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Mindfulness for Pain and Suicide (NCT05286112), a randomized na study. The primary outcome is Treatment Acceptability.

2. Clinical Question

3. Trial Design

This was a randomized, single-masked, parallel-group pilot study sponsored by Canandaigua VA Medical Center. The registry lists the study as completed, with enrollment of 76. Its title is “Mindfulness for Pain and Suicide,” and its official title is “A Pilot Study on Mindfulness for Pain and Mental Health Outcomes.” The phase is recorded as NA.

Participants were assigned to Mindfulness-Based Cognitive Therapy (MBCT) or health education. Both were behavioral interventions, each described as 10 sessions of about 60 minutes. The registry summary says the study was intended to assess the feasibility and acceptability of a mindfulness-based intervention in relation to functional impairment from chronic pain and risk of suicide. Randomization describes how allocation was made; the record does not identify which parties were masked.

The primary outcome was treatment acceptability at 1-month post-treatment. The posted summary statistics include 21.0 participants in the MBCT group and 22.0 in the health education group for that outcome. The record specifically notes that more data were missing at the 1-month follow-up than at study completion. The secondary outcomes with posted results concern physical health-related quality of life, pain intensity, and mental health-related quality of life. They were assessed at follow-up timeframes described separately in the registry.

Although overall enrollment was 76, the number with a posted outcome value differs across measures. Those outcome-specific counts should be read as the available data for each measure, not as a replacement for overall enrollment. The registry record does not report the original sample-size justification, the details of masking, or further design assumptions for the trial.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: Potential participants were screened for eligibility, consented (if eligible and interested), and completed a baseline assessment.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Data collected at 1-month follow-up when there was more missing data than at study completion.

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 Treatment Acceptability, measured over 1-month post-treatment.

The primary endpoint is treatment acceptability at 1-month post-treatment, measured with the Abbreviated Acceptability Rating Profile. Participants respond to 8 statements about the intervention. Scores range from 1 to 6, and higher scores indicate greater acceptability. The registry reports a mean and standard deviation for each group: the MBCT group had a mean of 4.7 and a standard deviation of 1.4, while the health education group had a mean of 4.3 and a standard deviation of 1.6.

Acceptability is relevant to a pilot because it describes how participants rated the intervention, an aspect of whether an intervention is acceptable to those receiving it. It is distinct from clinical outcomes such as pain intensity, quality of life, or suicide-related outcomes. A favorable acceptability score cannot establish that an intervention improves those outcomes, and the score does not itself measure feasibility in every sense.

The endpoint's timing matters for interpretation. The registry identifies these data as coming from the 1-month follow-up and notes that this assessment had more missing data than the assessment at study completion. The group summaries therefore describe participants with recorded data at that follow-up; the record does not report an analysis that adjusts for missing responses.

7. Results Posted in the Registry

• Health Education: mean 4.30 versus 4.70 on control; difference -0.40 (95% CI -1.30 to 0.50), standardized effect d = -0.27; z-test p = 0.382.

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.

Physical Health-related Quality of Life

• 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:
  • Health Education: mean 28.70 versus 28.60 on control; difference 0.10 (95% CI -6.15 to 6.35), standardized effect d = 0.01; z-test p = 0.975.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Health Education and the control. The interval gives the range of effects that remain compatible with the data.

Pain Intensity

• 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:
  • Health Education: mean 5.80 versus 5.40 on control; difference 0.40 (95% CI -0.38 to 1.18), standardized effect d = 0.28; z-test p = 0.317.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Health Education and the control. The interval gives the range of effects that remain compatible with the data.

Mental Health-related Quality of Life

• 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:
  • Health Education: mean 30.70 versus 37.40 on control; difference -6.70 (95% CI -13.22 to -0.18), standardized effect d = -0.57; z-test p = 0.044.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Health Education than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Across the secondary outcomes, the estimates vary in direction and precision rather than pointing to a single consistent pattern. Physical health-related quality of life and pain intensity have intervals that include zero, while the mental health-related quality-of-life interval excludes zero in the unadjusted comparison. Taken together, this mix is best viewed as exploratory information about several domains, not as one coherent confirmatory finding.

The secondary measures complement the primary acceptability endpoint but answer different questions. Acceptability concerns participants’ ratings of the intervention; quality-of-life and pain measures concern reported health outcomes at their specified follow-up times. A difference in acceptability cannot be assumed to imply a difference in pain or quality of life, and a secondary outcome result does not establish acceptability or feasibility.

The secondary comparisons carry less weight as confirmatory evidence because the registry lists multiple outcome measures, posts three secondary outcomes, and does not report a multiplicity strategy or detailed analysis plan. The unadjusted p-values do not account for the number of outcomes examined. Moreover, the outcome counts vary, and the registry notes missing data at the primary follow-up. These considerations make estimates useful for generating hypotheses and informing future study planning, while limiting strong conclusions from any single secondary result.

The registry record does not report thresholds for clinically important differences on the secondary scales. Statistical evidence and practical importance are distinct: an estimated difference can be statistically distinguishable from zero without being known to matter to participants, while an imprecise estimate can leave meaningful effects unresolved. The secondary results should therefore be considered alongside their uncertainty, scale interpretation, follow-up timing, and the absence of a reported multiplicity plan.

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

• Physical Health-related Quality of Life
• Pain Intensity
• Mental Health-related Quality of Life

9. Statistical Interpretation

10. Statistical Methods Explained

These outcomes are continuous measures summarized using group means and standard deviations. A mean gives the average recorded score among participants with available outcome data. A standard deviation describes how spread out individual scores are around that average. It is not the same quantity as the uncertainty in the estimated group mean: uncertainty also depends on how many participants contributed data.

What does a mean difference represent?

A mean difference subtracts one group’s mean from the other group’s mean. The direction depends on which group is placed first in the comparison. For the comparisons reported in the registry, the displayed estimates are health education relative to MBCT. Thus, the primary estimate of -0.4 corresponds to the health education mean of 4.3 compared with the MBCT mean of 4.7. On the mental health-related quality-of-life outcome, the estimate of -6.7 corresponds to the health education mean of 30.7 compared with the MBCT mean of 37.4. A negative estimate does not automatically mean a worse outcome: the meaning depends on the scale and its scoring direction. The acceptability scale explicitly says higher scores mean higher acceptability; scoring interpretation for the secondary scales is not further detailed in the record.

How should a confidence interval be read?

A confidence interval expresses uncertainty around an estimated difference. It gives a range of values compatible with the data and the method used to calculate the interval. A narrow interval indicates greater precision than a wide interval, all else equal. When an interval for a mean difference includes zero, the data do not clearly distinguish the estimate from no difference under that interval procedure. An interval that excludes zero indicates a nominal statistical distinction under that procedure, but does not address multiplicity, missing data, bias, or whether the difference is important to participants.

What does an unadjusted p-value say?

A p-value describes how unusual results at least as discrepant as those observed would be under a specified null model. It is not the probability that the null hypothesis is true, nor does it measure the size or importance of a difference. The reported p-values are unadjusted. With several outcomes, a collection of unadjusted tests increases the chance that at least one result appears notable by chance. The registry record does not report whether a correction or prespecified hierarchy was used.

Why do sample counts vary by outcome?

The counts attached to each mean identify how many participants contributed to that outcome summary. The primary endpoint includes 21.0 participants in the MBCT group and 22.0 in the health education group. Secondary outcome counts differ: physical and mental health-related quality of life have 26.0 and 24.0, while pain intensity has 25.0 in each group. Different follow-up timing and missing observations can result in different available counts. The record notes more missing data at the primary 1-month follow-up than at study completion, but does not report reasons for missingness or a missing-data analysis.

Why can over-dispersion matter?

General statistical explanation: over-dispersion occurs when variability in observed data exceeds what a chosen statistical model assumes. If a model understates variability, standard errors may be too small and confidence intervals too narrow, which can make evidence appear more precise than it is. The posted endpoints are continuous group summaries with standard deviations; the registry does not report a model assessment or an over-dispersion analysis. That concept should not be mistaken for a finding about this trial.

What do the reported comparisons represent?

The comparisons are unadjusted mean differences based on the posted group summaries. They do not incorporate covariate adjustment or a reported repeated-measures model. The registry lists no reported secondary analyses. The posted summaries can still describe observed group values, but they do not reveal how an analysis might have handled baseline measurements, repeated observations, or incomplete follow-up. Those details are not reported in the registry record.

General statistical explanation: randomization is intended to make treatment groups comparable in expectation, but in a small pilot, chance imbalances can remain. Adjustment for baseline variables can sometimes improve precision, depending on the design and analysis plan. Whether the sponsor used such an approach, and what prespecified model was planned, are not reported in the registry record. Therefore, the unadjusted comparisons should be interpreted as straightforward descriptions of the posted summaries rather than as a complete account of any trial analysis plan.

11. Confidence Intervals and Precision

The primary mean difference is -0.4, with a confidence interval that extends across zero. This interval indicates that the estimate is not precise enough to establish a clear direction of difference in acceptability between groups. It allows values on both sides of no difference. The p-value of 0.382 is consistent with that uncertainty, but the interval is more informative about the range of differences compatible with the data.

The physical health-related quality-of-life and pain-intensity intervals also include zero. For physical health-related quality of life, the estimate is 0.1; for pain intensity, it is 0.4. Both intervals span values that would correspond to differences in either direction. The mental health-related quality-of-life estimate is -6.7, and its interval lies on the negative side of zero. That estimate is more distinct from zero under the unadjusted comparison, but it remains one of several secondary findings and is not adjusted for multiple testing.

Precision depends on both the variability of scores and the available sample size. The standard deviations are substantial relative to the group mean differences for several outcomes, while outcome-specific counts are modest. Wide intervals reflect that the observed data do not tightly locate the underlying group difference. A confidence interval does not guarantee that the true difference lies within its endpoints; it summarizes uncertainty under the statistical procedure and assumptions used.

These intervals should not be treated as proof of equivalence when they include zero. Demonstrating that differences are small enough to be unimportant requires a prespecified margin and an analysis designed for that purpose; neither is reported in the registry record. Likewise, an interval excluding zero does not by itself establish clinical importance. No threshold for a meaningful difference is reported for these outcomes.

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 figures are illustrations based on the observed effect sizes, not the trial’s original design justification. The registry record does not report the assumptions used to choose the original enrollment target. 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. Each scenario uses the stated fraction of the observed effect as the effect to detect.

Rows for 100% of the observed effect use the full observed difference as the planning target. Rows for 75% or 50% of the observed effect plan around a smaller difference. Under the same assumptions, smaller effects require more participants to distinguish them from no difference reliably. The figures are shown for targets of 80% and 90% power. In plain terms, 80% power is the planned probability of detecting an effect of the specified size under the assumed model if that effect is present; 90% power sets a higher detection probability and generally requires a larger sample.

These calculations are sensitive to the observed effect, which can be unstable in a small pilot. In particular, a very small observed difference can produce extremely large planning estimates when treated as the target effect. The illustrations should therefore be read as conditional planning scenarios, not as a recommendation or a guarantee about a future study. The figures are not observed power: they do not describe the probability that this completed study detected an effect after the results were known. The original sample-size assumptions and any sponsor-planned power calculation are not reported in the registry record.

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 = -0.400; pooled standard deviation σ = 1.506.
2. n = 2 × (1.96 + 0.842)² × 1.506² / -0.400² = 222.4, rounded up to 223 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 <- -0.4                      # observed difference in means
sigma <- 1.50576129355577                     # 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(5286112)
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 = 223 (80% power), 298 (90% power)
 75% of observed effect: n per arm = 396 (80% power), 530 (90% power)
 50% of observed effect: n per arm = 890 (80% power), 1,192 (90% power)
power.t.test: 223.4 
Simulated power at n = 223 per arm: 0.797 (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 12 outcome measures and posts results for three secondary outcomes in addition to the primary acceptability outcome. Examining several outcomes creates a multiplicity issue: when many comparisons are made, the chance of at least one apparently notable result can increase even if there are no true effects. The registry record does not report a correction for multiple testing, a prespecified hierarchy among outcomes, or another strategy for controlling that risk. The unadjusted secondary p-values should consequently be read as exploratory.

The record reports no analyses under the secondary outcomes. It also does not describe a statistical analysis plan, including whether baseline values or repeated measurements were modeled, which analysis population was intended, or how missing observations were handled. Those choices can affect estimates and uncertainty. They should not be inferred from the posted means and standard deviations.

Missingness is particularly relevant to the primary endpoint: the registry states that the 1-month follow-up had more missing data than the assessment at study completion. The outcome summaries include 21.0 MBCT participants and 22.0 health education participants. The record does not report reasons for missingness, the characteristics of participants without data, imputation, or sensitivity analyses. If availability of a score is related to treatment experience or outcome, summaries of participants with recorded data may not fully represent the randomized groups.

The sample-size assumptions for the trial’s original design, any interim analyses, and the planned analysis populations are not reported in the registry record. The planning illustrations based on observed effects are separate from these unknown design details. These reporting gaps do not invalidate the descriptive summaries, but they limit assessment of whether the posted analyses follow a prespecified confirmatory plan and how robust conclusions would be to missing data or multiplicity.

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: cardiac related hospitalization (7.9%), hospitalization associated with significant psychiatric distress (5.3%), hospitalization related to metabolism disorder (5.3%), hospitalization related to respiratory system (2.6%), hospitalization associated with digestive system (2.6%).

The registry reports serious adverse events among 38 participants at risk in each group. Serious adverse events affected 7 participants in the MBCT group and 6 in the health education group. Other adverse events affected 13 and 19 participants, respectively. The posted death count is 0 in each group. These are counts of participants affected, not a measure of whether an event was caused by an intervention.

The record lists cardiac related hospitalization at 7.9%, hospitalization associated with significant psychiatric distress at 5.3%, hospitalization related to metabolism disorder at 5.3%, hospitalization related to respiratory system at 2.6%, hospitalization associated with digestive system at 2.6%, and hospitalization from an injury at 2.6% among the top serious terms. These terms describe reported event categories; the record does not establish from these figures alone whether events were related to treatment, nor does it provide a basis for comparing the clinical significance of categories.

Safety counts should be interpreted in light of the study’s size and the registry’s reporting. They describe events recorded for the trial, not a complete estimate of risk in other populations or settings. No causal conclusion about the interventions follows from these counts alone.

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

The posted primary results describe acceptability ratings among participants with 1-month follow-up data. The average score was 4.7 for MBCT and 4.3 for health education on a scale where higher values indicate higher acceptability. The estimated difference is uncertain: its confidence interval includes zero, and its unadjusted p-value is 0.382. The result does not establish a clear between-group difference, nor does it demonstrate that the groups are equivalent.

The secondary results offer additional, but exploratory, information about physical health-related quality of life, pain intensity, and mental health-related quality of life. Their estimates differ in direction and precision. The mental health-related quality-of-life comparison is nominally distinct from zero, but it is one of several unadjusted secondary results. Without a reported multiplicity plan, that result should not be isolated as definitive evidence.

These findings do not show that an intervention works or does not work. A pilot with outcome-specific counts and uncertainty can help describe observed scores and identify questions for further study, but the registry record does not report the design assumptions, complete analysis plan, or missing-data methods needed to make stronger claims. The primary endpoint is acceptability, not a direct measure of suicide risk, suicide attempts, pain-related functional impairment, or treatment benefit.

Nor do the findings establish how results would generalize beyond the participants and follow-up assessments represented in the registry. The posted data are bounded by the reported measures, timing, and available observations. A statistically notable secondary estimate does not settle whether a difference is meaningful to participants, and an interval including zero does not rule out potentially important differences. The record does not report thresholds for meaningful differences on these scales.

17. Why This Trial Matters Statistically

This trial illustrates an important distinction in pilot research: acceptability and clinical outcomes are related questions but are not interchangeable. The primary endpoint captures participants’ ratings of an intervention, while the secondary endpoints capture quality-of-life and pain scores. Interpreting each measure according to its purpose avoids treating an acceptability result as proof of clinical benefit.

The results also show why estimates need to be read together with uncertainty. The group means alone can suggest a direction, but confidence intervals indicate how much the data leave unresolved. In this study, the primary comparison and two secondary comparisons have intervals that include zero, while one secondary interval does not. The number of outcome measures and the absence of a reported multiplicity plan matter when judging that isolated secondary signal.

Outcome-specific sample counts and the note about missingness at the primary follow-up are also statistically important. Overall enrollment does not mean every participant contributed to every endpoint. Differences in available data affect precision and can complicate comparisons if missingness is related to participants’ experiences. The registry does not report analyses that address this issue.

Finally, planning estimates based on observed effects can be highly dependent on the size of a pilot estimate. They are conditional illustrations rather than evidence that a future sample size is sufficient or that the completed study had a particular probability of success. Clear reporting of prespecified hypotheses, analysis methods, missing-data handling, and multiplicity would help readers distinguish exploratory patterns from confirmatory evidence.

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 main limitation visible in the registry record is the small, outcome-specific number of observations relative to overall enrollment. The primary acceptability summaries include 21.0 participants in MBCT and 22.0 in health education, while secondary counts vary by measure. The record notes that the primary 1-month follow-up had more missing data than the assessment at study completion, but does not explain why data were missing or how this was handled analytically.

There are also reporting limitations. The original sample-size justification, trial statistical analysis plan, analysis populations, and interim analysis details are not reported in the registry record. The record does not describe whether secondary comparisons were prespecified or whether any adjustment for multiple outcomes was intended. Consequently, the secondary results are difficult to classify as confirmatory and should be treated cautiously.

The registry reports group means, standard deviations, and unadjusted comparisons, but does not report model-based secondary analyses. It does not explain whether baseline scores were incorporated into the comparisons or whether repeated measurements were modeled. The follow-up timeframes vary across outcomes, which means the measures do not represent the same assessment point.

Interpretation of practical importance is limited because meaningful-difference thresholds for the scales are not reported. The primary acceptability scale’s range and direction are described, but the registry does not provide comparable interpretive thresholds for the secondary scales. Finally, a pilot study’s estimates can be unstable; planning illustrations derived from observed effects are particularly sensitive to that uncertainty. These limitations constrain conclusions from the posted results without erasing their descriptive value.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Mindfulness for Pain and Suicide — NCT05286112.
• Registry record last updated 2026-08-25; status last verified 2026-08.
• Results first posted 2026-08-25.
• 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, single-masked, parallel pilot study sponsored by Canandaigua VA Medical Center, with enrollment of 76. Participants were assigned to MBCT or health education, each delivered in 10 sessions of about 60 minutes. The primary outcome was acceptability at 1-month post-treatment, assessed with the Abbreviated Acceptability Rating Profile. The posted means were 4.7 for MBCT and 4.3 for health education, with an imprecise unadjusted comparison.

Three secondary outcomes have posted results: physical health-related quality of life, pain intensity, and mental health-related quality of life. Their estimates vary, and the unadjusted secondary findings should be viewed as exploratory in the absence of a reported multiplicity strategy. The record notes greater missingness at the primary follow-up than at study completion. Original design assumptions, detailed analysis methods, and missing-data procedures are not reported in the registry record.