Evaluating Digital Micro-Interventions to Reduce Distress and Increase Wellbeing in Breast Cancer Survivors: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluating Digital Micro-Interventions to Reduce Distress and Increase Wellbeing in Breast Cancer Survivors (NCT07160439), a randomized na study. The primary outcome is Evaluation of Digital Micro-Intervention.

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group behavioral study with no masking. The registry lists an enrollment of 120 and a status of Completed. The study start date is 2025-08-12, and the primary completion date is 2026-03-31. Phase is recorded as NA. The study was sponsored by the University of Virginia.

Participants were assigned to Savoring, Gratitude, Challenging UnhelpfulThoughts, Psychoeducation, Behavioral Activation, or Acceptance. Each is described as a digital micro-intervention intended to be focused and deliverable in daily life. The registry descriptions specify different activities for the groups, but intervention frequency, duration, adherence, and delivery details beyond those descriptions are not reported in the registry record.

The primary measure was administered after participants had used their assigned intervention, at post 1 week. The registry explains that this measure could only be administered after intervention use and that participants could skip it. The number contributing to this outcome therefore varies across groups and is lower than the overall enrollment. The posted primary outcome summaries include 12 participants in Challenging UnhelpfulThoughts and 15 in Psychoeducation, as well as 16 in Gratitude and 18 in each of Savoring, Behavioral Activation, and Acceptance.

The registry’s stated project goals were to develop and pilot a variety of digital micro-interventions for breast cancer survivors. Details of the original statistical design, including a protocol-defined sample-size justification, are not reported in the registry record. Neither the method of randomization nor any stratification factors are 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.

Before assignment: No significant events occurred between the enrollment and assignment of participants.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Any differences between the numbers here and the numbers of participants assigned to the groups in the Participant Flow is due to participants choosing to skip this measure.

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: Differences between these numbers and the numbers of participants assigned to the groups in the Participant Flow are due to participants not completing baseline measures after enrolling in the study.

Only the first 6 of 7 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Evaluation of Digital Micro-Intervention, measured over Post 1 week.

The primary endpoint is a 12 item scale of satisfaction and acceptability, measured at post 1 week. Each item is scored on a 0-4 scale, and the total raw summed score ranges from 0-48. Higher scores indicate greater satisfaction and acceptability. The registry says this measure was administered after participants used the intervention assigned to them, because the questions depend on having experienced that intervention.

This endpoint is relevant to a pilot of digital micro-interventions because participants’ assessment of acceptability can describe how the intervention was received. It is distinct from a symptom or wellbeing outcome: a satisfaction score is not itself a measure of reduced distress, improved wellbeing, or a change from baseline. It can therefore address participants’ ratings of the intervention, but it cannot on its own answer whether the intervention changed mental health outcomes.

The primary outcome is reported as a mean and standard deviation for each group. The outcome counts vary because some participants chose to skip the measure. The registry record does not report a separate threshold for interpreting a score, nor does it report a minimum clinically important difference for this scale.

7. Results Posted in the Registry

• Gratitude: mean 33.60 versus 32.80 on control; difference 0.80 (95% CI -2.68 to 4.28), standardized effect d = 0.15; z-test p = 0.652.
• Challenging UnhelpfulThoughts: mean 31.60 versus 32.80 on control; difference -1.20 (95% CI -6.46 to 4.06), standardized effect d = -0.18; z-test p = 0.655.
• Psychoeducation: mean 35.30 versus 32.80 on control; difference 2.50 (95% CI -2.57 to 7.57), standardized effect d = 0.35; z-test p = 0.334.
• Behavioral Activation: mean 31.80 versus 32.80 on control; difference -1.00 (95% CI -6.07 to 4.07), standardized effect d = -0.13; z-test p = 0.699.

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.

Insomnia Severity 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:
  • Gratitude: mean 18.20 versus 16.40 on control; difference 1.80 (95% CI -2.72 to 6.32), standardized effect d = 0.27; z-test p = 0.435.
  • Challenging UnhelpfulThoughts: mean 17.80 versus 16.40 on control; difference 1.40 (95% CI -1.97 to 4.77), standardized effect d = 0.27; z-test p = 0.415.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Gratitude and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Challenging UnhelpfulThoughts and the control. The interval gives the range of effects that remain compatible with the data.

Patient Health Questionnaire-8

• 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:
  • Gratitude: mean 14.60 versus 13.20 on control; difference 1.40 (95% CI -2.16 to 4.96), standardized effect d = 0.27; z-test p = 0.440.
  • Challenging UnhelpfulThoughts: mean 13.40 versus 13.20 on control; difference 0.20 (95% CI -3.01 to 3.41), standardized effect d = 0.04; z-test p = 0.903.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Gratitude and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Challenging UnhelpfulThoughts and the control. The interval gives the range of effects that remain compatible with the data.

Generalized Anxiety Disorder-7

• 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:
  • Gratitude: mean 13.40 versus 11.40 on control; difference 2.00 (95% CI -0.91 to 4.91), standardized effect d = 0.47; z-test p = 0.177.
  • Challenging UnhelpfulThoughts: mean 11.40 versus 11.40 on control; difference 0.00 (95% CI -3.32 to 3.32), 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 Gratitude and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Challenging UnhelpfulThoughts and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary measures that cover symptoms, functioning, pain, emotion regulation, insomnia, and related domains. The outcome names include PROMIS-29 Profile, the PEG Scale, the Emotion Regulation Questionnaire, and Insomnia Severity Index; the posted secondary summaries also include the Patient Health Questionnaire-8 and Generalized Anxiety Disorder-7. The record reports 12 secondary outcomes, but the secondary summaries described in the record are baseline measurements. Baseline comparisons describe the groups before the post-intervention primary assessment; they do not demonstrate change over time.

Unadjusted recalculated comparisons are posted for selected baseline measures. Their intervals include zero, and the record does not report sponsor analyses for these outcomes. These baseline estimates are not a direct complement to the primary satisfaction outcome: they measure different constructs and are collected at a different time. In particular, baseline symptom scores cannot establish whether symptoms changed after participants received an intervention.

The broader pattern is that the record contains several different secondary outcome domains but does not report comparative follow-up analyses for them. As a result, the secondary results do not establish whether the interventions affected distress, wellbeing, sleep, pain, or other listed outcomes. The primary result concerns acceptability and satisfaction, so secondary baseline summaries cannot be used to turn that result into an estimate of clinical benefit.

Unadjusted secondary results carry less weight when many outcomes or comparisons are considered without a reported multiplicity plan. In general, testing more comparisons increases the opportunity for chance findings. This is a reason to interpret isolated unadjusted results cautiously, not a claim that any particular estimate is invalid. The registry record does not report a prespecified hierarchy, adjustment method, or complete analysis plan for the secondary outcomes.

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

• PROMIS-29 Profile
• PROMIS-29 Profile
• Pain, Enjoyment of Life and General Activity (PEG) Scale
• Pain, Enjoyment of Life and General Activity (PEG) Scale
• Emotion Regulation Questionnaire
• Emotion Regulation Questionnaire
• Insomnia Severity Index
• Insomnia Severity Index

9. Statistical Interpretation

10. Statistical Methods Explained

The statistical summaries use means and standard deviations because the primary measure is a continuous summed score. A mean describes the arithmetic average among participants with an observed score. A standard deviation describes how dispersed individual scores are around that group mean. These two quantities answer different questions: the mean locates the group average, while the standard deviation describes variability among participants.

What does a mean difference represent?

Each posted primary comparison is an unadjusted mean difference between one intervention group and Savoring. A positive estimate means the observed average score was higher in the named group than in Savoring; a negative estimate means it was lower. For example, the estimated difference for Psychoeducation is 2.5, whereas the estimated difference for Acceptance is -2.2. Because higher scores indicate greater satisfaction and acceptability, the direction of these estimates describes the direction of the observed score difference. It does not establish that a difference is reliable, important, or caused by the intervention.

The comparison estimates are recalculated, simple unadjusted comparisons from the posted group summaries. They are not a substitute for an analysis model specified by the study team. No adjusted primary analysis is reported in the registry record. The registry also does not report covariates, a prespecified contrast hierarchy, or a method for handling multiple comparisons.

How should standard deviations and uncertainty be understood?

In general, a standard deviation describes participant-to-participant spread; it is not the same as the standard error of a group mean. A standard error describes the sampling uncertainty in an estimate and is affected by both variability and the number of observations. With small group counts, estimates can be imprecise even when the group mean is straightforward to calculate.

In general, a confidence interval gives a range of values reasonably compatible with the estimate under the statistical method used. It is not a guarantee that the true difference falls within the interval, and it is not the probability that one treatment is better. For a difference in means, an interval containing zero includes no difference as one value compatible with the data. The posted primary intervals all include zero, and they also include values in both directions.

What do the p-values tell the reader?

In general, a p-value describes how unusual data at least as inconsistent with a specified null hypothesis would be if that hypothesis and the statistical model were correct. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of a group difference. The primary p-values are labeled unadjusted and are recalculated from posted summary statistics. The registry record does not report the study team’s own primary analysis or a prespecified decision rule for interpreting the p-values.

Unadjusted testing across several comparisons can make apparently noteworthy results more likely to arise by chance when the null hypotheses are all true. This is the general reason that multiplicity matters. It does not mean a particular observed result is false; it means the analysis strategy and the number of comparisons need to be considered when weighing evidence. No multiplicity procedure is reported in the registry record.

Why can over-dispersion matter?

In general, over-dispersion means that observed variability is greater than a statistical model expects. A model that underestimates variability can produce standard errors that are too small and confidence intervals that are too narrow. The primary measure is analyzed as a continuous score, and the posted summaries include standard deviations, so the reader can see participant variability. The registry record does not report a model diagnostic or an over-dispersion assessment. This concept is a general statistical consideration, not a reported finding about this trial.

The primary outcome was collected only after intervention use, and participants could skip the measure. The outcome counts therefore reflect people with an observed score, rather than necessarily everyone assigned. The registry attributes differences between these counts and participant flow to skipped measures. The statistical method used to handle missing data, the analysis population, and any sensitivity analysis are not reported in the registry record. This limits assessment of whether the observed summaries represent all randomized participants or only those who completed the scale.

Finally, the registry’s sample-size illustrations use observed effects and stated planning assumptions. They are useful for understanding how assumed effect size and target power relate to a required number of participants. They do not document the original design calculation, which is not reported in the registry record. The distinctions between descriptive summaries, recalculated unadjusted comparisons, and any original sponsor analysis are important when interpreting the results.

11. Confidence Intervals and Precision

Precision concerns how narrowly the data estimate a group difference. For the primary outcome, every posted comparison interval includes zero and extends to values on both sides of zero. The results therefore do not pinpoint a single direction or size of difference with much certainty. This does not prove that the groups are identical; it indicates that the estimates remain compatible with a range of possibilities.

The primary estimates come from group counts of 12 to 18 participants. The standard deviations also indicate variation in scores within groups. In general, smaller samples and greater variability tend to yield less precise estimates, reflected in wider confidence intervals. The intervals for these comparisons are accordingly important context: the point estimate should not be read in isolation as a stable estimate of a group difference.

A confidence interval is a measure of uncertainty under the calculation method, not a range containing most individual participants’ scores. Nor does it express the probability that a particular intervention is superior. The primary intervals are recalculated from posted summaries; the registry record does not report sponsor confidence intervals or a model-based adjusted estimate.

Precision is also distinct from practical importance. The registry record does not report a threshold for a meaningful difference on the satisfaction and acceptability scale. Without such a threshold, the score differences cannot be classified from this record as meaningfully large or small. The endpoint is a rating after intervention use, and the intervals describe uncertainty in the mean comparisons for participants who completed the measure.

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 participants per arm for 80% power and participants per arm for 90% power. They are not total sample sizes and are not total event counts. The figures use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. They take the observed effect as a starting point and calculate planning illustrations for detecting the stated fraction of that observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the illustrative number per arm under which the calculation would have an 80% chance of detecting the assumed effect if that effect and the planning assumptions were correct. The 90% power column uses a higher target chance of detecting that same assumed effect, and consequently calls for more participants per arm. These are planning concepts, not a description of what happened in the completed study.

The rows for 100%, 75%, and 50% of the observed effect show how the calculated requirement changes when the assumed effect is reduced. Smaller effects need more participants to distinguish them from sampling variation under the same assumptions. For example, the Gratitude comparison illustrates a requirement of 682 participants per arm for 80% power at 100% of the observed effect, and 2,727 participants per arm at 50% of the observed effect. These figures are illustrations derived from the observed estimate, not the trial’s enrollment target.

This is not observed power. It is a planning illustration based on the observed effect and stated assumptions, and it should not be used to determine whether the trial succeeded or failed. The registry record does not report a protocol-based sample-size calculation.

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 = 0.800; pooled standard deviation σ = 5.272.
2. n = 2 × (1.96 + 0.842)² × 5.272² / 0.800² = 681.7, rounded up to 682 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 <- 0.800000000000004                      # observed difference in means
sigma <- 5.27182961598722                     # 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(7160439)
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 = 682 (80% power), 913 (90% power)
 75% of observed effect: n per arm = 1,212 (80% power), 1,623 (90% power)
 50% of observed effect: n per arm = 2,727 (80% power), 3,651 (90% power)
power.t.test: 682.6 
Simulated power at n = 682 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 study compares several digital micro-interventions on the primary satisfaction and acceptability measure and lists multiple secondary outcome measures. When many outcomes or pairwise comparisons are considered, the chance of at least one apparently unusual result can increase if each is judged separately. In general, a multiplicity strategy can define which comparisons are primary or adjust the interpretation of multiple tests. No such strategy is reported in the registry record.

The primary comparative p-values are unadjusted recalculations from posted group summaries. They should not be treated as adjusted evidence across the full set of comparisons. The registry record does not report a sponsor-conducted primary analysis, a hierarchy among the intervention comparisons, or a prespecified approach to secondary testing. The absence of those details means the reader cannot determine how the study team intended to control or interpret multiplicity.

Missingness is relevant because the primary measure was administered only after participants had used their assigned intervention, and participants could choose to skip it. The record explicitly attributes differences between primary outcome counts and participant flow to skipped measures. Counts contributing to the primary group summaries range from 12 to 18. The registry does not report reasons for skipping beyond the stated choice, nor does it report an imputation method, a missing-data assumption, or sensitivity analyses.

The analysis population is not reported in the registry record. It is therefore not clear from the record whether the sponsor’s intended primary analysis was based on everyone randomized, those who used the intervention, those who completed the measure, or another defined group. The registry also does not report the method used for randomization, allocation concealment, interim analyses, or the original statistical analysis plan. These are unknown details, not evidence that a particular procedure was or was not used.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The adverse-event record lists serious events, other events, and deaths by intervention group. For each listed group, the number affected by serious adverse events is recorded as 0, the number affected by other adverse events is recorded as 0, and deaths are recorded as 0. The listed numbers at risk vary by group; the record reports 18 for Savoring, 17 for Gratitude, 16 for Challenging UnhelpfulThoughts, 16 for Psychoeducation, 19 for Behavioral Activation, and 20 for Acceptance.

These are registry counts over the reported safety record. They should be read as the counts recorded for the groups and categories, not as a statistical comparison between interventions. The registry does not provide event terms for serious adverse events, and no serious-event terms are listed. The record does not report an exposure-adjusted safety analysis, a formal between-group test, or additional details about how events were monitored. Zero recorded events in these categories does not by itself establish that no other safety outcomes occurred or that the groups have equivalent safety profiles.

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

The primary result answers a narrow but useful question: how participants who completed the measure rated the satisfaction and acceptability of their assigned digital micro-intervention at post 1 week. The group means and unadjusted comparisons describe those ratings. The estimates are uncertain, and their confidence intervals include zero. The posted results do not establish a clear difference in average satisfaction and acceptability between any comparison group and Savoring.

The result does not directly answer whether the interventions reduce distress or increase wellbeing. The study’s title and stated goals concern those broader aims, but the primary endpoint is an acceptability and satisfaction scale. The registry does not report comparative follow-up analyses of the listed symptom and wellbeing-related measures. The primary score should therefore not be interpreted as evidence of improvement in mental health outcomes.

The trial record describes randomized allocation, which is relevant to comparisons between assigned groups, but it also records no masking. The observed scale scores may reflect participants’ perceptions of the assigned activities, and the record does not provide information about masking participants or assessors. In general, self-reported acceptability ratings can capture the participant’s experience, while also being different from independently assessed clinical outcomes.

The group counts for the primary measure are smaller than the overall enrollment because some participants skipped it. The record does not report how missing scores were handled in a sponsor analysis or whether those who completed the scale differed from those who did not. Thus, the estimates apply directly to the observed responses and their generalizability to all randomized participants is uncertain.

These results are best read as descriptive, pilot-stage information about participant ratings, alongside substantial uncertainty in between-group estimates. They do not establish that any intervention is effective or ineffective, and they do not provide a basis for treatment decisions. Further interpretation of clinical outcomes would require reported follow-up analyses and a clear account of the statistical plan and missing-data approach.

17. Why This Trial Matters Statistically

This trial is statistically notable because its primary outcome is acceptability rather than a direct symptom or wellbeing measure. In a pilot of digital interventions, a measure of whether participants find an activity acceptable can inform the assessment of the intervention experience. At the same time, the distinction between acceptability and clinical outcome is essential: a favorable rating would not itself show reduced distress, and the posted results do not show that relationship.

The design places several distinct behavioral activities in parallel groups and reports each against Savoring. That makes the size and precision of each contrast important. The primary estimates are based on relatively small numbers of completed ratings, and their confidence intervals are broad enough to include differences in either direction. The figures illustrate why a point estimate or an unadjusted p-value should not be treated as a definitive ranking.

The registry also makes a useful distinction between the trial’s enrollment and the number contributing to the post-intervention satisfaction measure. Because the outcome was only available after use and could be skipped, outcome-specific counts matter when assessing precision and missingness. The record attributes the difference to skipped measures but does not report a missing-data analysis.

Finally, planning illustrations based on observed effects can help readers understand how sample-size requirements depend on the assumed effect and target power. They are not evidence of the original design rationale and do not turn this pilot into a confirmatory test. For readers evaluating digital behavioral interventions, the case highlights the value of separating feasibility and acceptability questions from clinical outcome questions and of reporting a prespecified analysis plan for both.

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 primary outcome is a satisfaction and acceptability score collected only at post 1 week. It is not a baseline-to-follow-up measure of distress or wellbeing, and the registry does not report a threshold for a meaningful score difference. The record also does not report comparative follow-up analyses for the secondary measures. These features limit what can be concluded about clinical outcomes from the posted results.

The number of completed primary ratings varies by group, from 12 to 18. Participants could skip the measure, but the registry does not report a missing-data method, sensitivity analysis, or comparison of completers and non-completers. The resulting group summaries may not represent all participants assigned to each intervention.

There was no masking. The registry record does not report the allocation sequence method, concealment procedures, intervention adherence, or detailed delivery and exposure information. It also does not report the statistical analysis plan, analysis population, sample-size justification, or any multiplicity method. These unknowns limit assessment of possible sources of bias and the intended interpretation of the comparisons.

The trial enrolled 120 participants across multiple intervention groups, while the primary outcome summaries include smaller group counts. That combination produces limited precision for individual comparisons. The confidence intervals reflect substantial uncertainty, and unadjusted comparisons across several groups and outcomes need cautious interpretation. Further population characteristics and eligibility criteria are not reported in the registry record, limiting assessment of how closely these results may apply to other groups of breast cancer survivors.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Evaluating Digital Micro-Interventions to Reduce Distress and Increase Wellbeing in Breast Cancer Survivors — NCT07160439.
• Registry record last updated 2026-08-13; status last verified 2026-08.
• Results first posted 2026-08-13.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry describes a completed randomized, unmasked, parallel behavioral trial sponsored by the University of Virginia, with enrollment of 120. It evaluated Savoring, Gratitude, Challenging UnhelpfulThoughts, Psychoeducation, Behavioral Activation, and Acceptance for breast cancer survivors.

The primary outcome was a 12 item satisfaction and acceptability scale collected at post 1 week. Group means were between 30.6 and 35.3 in the posted summaries. Recalculated unadjusted comparisons with Savoring have confidence intervals that include zero. Outcome counts vary because participants could skip the measure.

The record lists secondary measures but does not report comparative follow-up analyses for them. It records zero affected by serious adverse events, zero affected by other adverse events, and zero deaths in each listed group. The original statistical plan, sample-size justification, analysis population, missing-data method, and multiplicity approach are not reported in the registry record.