Behavioral Activation Intervention for Smoking Cessation in Smokers With Depressive Symptoms: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Behavioral Activation Intervention for Smoking Cessation in Smokers With Depressive Symptoms (NCT01199380), a randomized phase 2 study. The primary outcome is Number of Participants Smoking-Abstinent for 7 Days, 52 Weeks Post Quit Date.

2. Clinical Question

The comparison addresses abstinence at a specified follow-up point, rather than abstinence maintained continuously throughout the follow-up period. The registry identifies a randomized, parallel-group Phase 2 trial with single masking. It does not report the masking procedure, the eligibility criteria in detail, or which outcomes beyond the posted primary endpoint were analyzed.

3. Trial Design

The registry describes a randomized, parallel-group Phase 2 trial comparing Behavioral Activation for Smoking with Standard Treatment. The record lists single masking, but does not report who was masked or how masking was implemented. The study status is completed, and enrollment is listed as 184.

The trial summary described a proposed study of 200 adult smokers with elevated depressive symptoms. The registry’s enrollment figure is 184. The dates recorded for study start and primary completion are 2010-09 and 2016-05. These dates identify the registry milestones; they do not, on their own, establish the timing of individual participants’ follow-up.

Standard Treatment was described as group smoking cessation treatment based on a clinical practice guideline, delivered in 8 sessions of 60 minutes across an 8-week period. Behavioral Activation for Smoking included standard cessation strategies and activities relating to values, mood, and daily life. The registry lists transdermal nicotine patch among the interventions, but arm-specific details about its use are not clear in the posted descriptions.

The posted primary outcome is a count of participants with 7 days of smoking abstinence confirmed biochemically at 52 weeks post quit date. The record gives the number assessed in each arm and the number meeting this outcome. It does not report the randomization method, allocation concealment, a detailed protocol, the trial’s original sample-size justification, or the intended statistical analysis plan. The sponsor is University of Maryland, College Park.

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

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: Analysis population is not different from the assignment in Participant Flow.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Smoking-Abstinent for 7 Days, 52 Weeks Post Quit Date, measured over 52 weeks post quit date.

The primary endpoint counts participants who had 7 days of smoking abstinence, confirmed biochemically at 52 weeks post quit date. The registry describes this as a count of participants and specifies the follow-up time as 52 weeks post quit date. The posted arm counts are 26 of 88 participants for Standard Treatment and 19 of 96 for Behavioral Activation for Smoking.

This endpoint represents abstinence at the 52-week assessment, with a 7-day abstinence period. It does not establish that participants remained abstinent throughout the entire period after their quit date. The record does not specify the biochemical verification method or the handling of participants whose abstinence status could not be determined.

General: A biochemically confirmed measure can complement self-report by using an objective check of smoking status. A defined 7-day period also gives the outcome a consistent reference window at follow-up. Such an endpoint is useful for comparing the groups at a clinically relevant time point, while its interpretation remains tied to that particular window and assessment. It should not be read as a measure of continuous abstinence unless the record explicitly defines it that way.

7. Results Posted in the Registry

• Behavioral Activation for Smoking: 19.8% (19/96) versus 29.5% (26/88) on control; risk difference -9.8 percentage points (95% CI -22.2 to 2.7), risk ratio 0.67 (0.40–1.12); unadjusted two-proportion z-test p = 0.124.

8. Statistical Interpretation

9. Statistical Methods Explained

The posted result is a comparison of a binary outcome: each participant either met the defined abstinence endpoint or did not. The registry reports the count meeting the endpoint and the number of participants in each arm. Because the outcome is a count of participants with an event, the comparison can be expressed using group proportions, a risk difference, a risk ratio, or an odds ratio. The registry’s reported comparisons are unadjusted.

What does the risk difference describe?

The risk difference subtracts the event proportion in the comparator group from the event proportion in the intervention group. In this trial’s posted comparison, the direction is Behavioral Activation for Smoking minus Standard Treatment. A negative estimate therefore means the observed abstinence proportion was lower in the Behavioral Activation for Smoking group. The estimate is -0.098, with a confidence interval from -0.222 to 0.027. The interval spans zero, the value representing no difference on the risk-difference scale.

General: A risk difference expresses an absolute contrast between proportions. It is often straightforward to interpret because it uses the outcome’s original proportion scale. Its uncertainty depends on the data and the method used to form the interval. The registry record does not describe the interval method, so no more specific claim about its construction is warranted.

How do the relative measures differ?

The risk ratio compares the event proportion in one group with the event proportion in the other. The odds ratio instead compares the odds of the event. The posted risk ratio is 0.670, with a confidence interval from 0.400 to 1.122. The posted odds ratio is 0.588, with a confidence interval from 0.298 to 1.161. For both measures, the null value represents no group contrast, and the posted intervals include that value. A relative measure and an absolute measure can give different numerical impressions because they use different scales; they are not interchangeable quantities.

The posted unadjusted p-value is 0.124. A p-value describes how compatible the observed data are with a specified statistical null model, under the assumptions of the test. The record does not identify the test used or report a prespecified significance threshold for the primary analysis. A p-value is not the probability that the null hypothesis is true, nor does it measure the size or practical importance of a difference. It should be considered alongside the effect estimate, interval, outcome definition, and design.

What does the confidence interval add?

General: A confidence interval is a range of estimates compatible with the data under a particular statistical procedure. Its width conveys precision: a wider interval leaves more uncertainty about the magnitude and direction of the underlying contrast. The interval does not assign a probability to the true value after observing the data. For this risk difference, the interval includes zero and extends to estimates on either side of zero. The registry does not report the confidence level or calculation method, so those details are not inferred.

What can be said about adjustment and analysis populations?

The comparison is labeled unadjusted. No adjusted estimate, covariate list, model specification, or analysis population is reported in the registry record. Random allocation is a design feature intended to make groups comparable on average, but it does not make information about the analysis method unnecessary. The registry also does not report whether the analysis followed an intention-to-treat approach, used a per-protocol population, or applied another rule for inclusion.

Missing outcomes can affect a binary endpoint if participants’ abstinence status is unavailable. The record does not report the number of missing outcomes, the method for handling them, or whether participants lost to follow-up were classified in any particular way. Without those details, the posted counts can be described, but the exact relationship between the counts and all randomized participants cannot be fully assessed.

What do the planning illustrations mean?

The planning calculations use the observed effect as a reference and show participant counts per arm under specified assumptions. They are separate from the trial’s own original design justification, which is not reported in the registry record. The assumptions for the illustrations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at a stated fraction of the observed effect. These calculations are prospective planning illustrations, not a reconstruction of the trial’s analysis.

General: Statistical methods do not replace attention to the outcome definition, enrollment, follow-up, and uncertainty. A single unadjusted estimate is one part of the evidence; it cannot by itself establish why the groups differed, whether the difference is clinically important, or how the result would generalize beyond the enrolled population. The registry record does not post analysis entries for the outcome, so further details about the analysis procedure are not reported in the registry record.

10. Confidence Intervals and Precision

The risk-difference estimate is -0.098, with a confidence interval from -0.222 to 0.027. This interval includes zero, the value corresponding to no difference on the risk-difference scale. It therefore does not rule out a null contrast, and it also includes values on either side of zero. The estimate’s direction is not precise enough to exclude plausible differences in the opposite direction.

General: Confidence intervals communicate uncertainty around an estimated effect. A narrower interval would indicate greater precision, while a wider one would leave a broader range of plausible values. Precision is not the same as whether a result crosses a conventional significance threshold, and an interval does not tell whether an effect is important to patients or clinicians. The confidence level and interval calculation method are not reported in the registry record.

The relative measures tell a similar uncertainty story on their own scales. The risk ratio is 0.670, with a confidence interval from 0.400 to 1.122; the odds ratio is 0.588, with a confidence interval from 0.298 to 1.161. Each interval includes its null value. The posted unadjusted p-value is 0.124, but it does not replace the effect estimate or interval and should not be interpreted as the probability that one treatment is better.

The group counts are 26 of 88 and 19 of 96. These counts provide the basis for the posted comparison, but do not resolve uncertainties about missing outcomes or the analysis population. The registry does not report those details. Overall, the result is an uncertain estimate of a group contrast, rather than a precise determination of the direction or magnitude of an underlying effect.

11. 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, not total events. They are illustrations based on the observed effect and use a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. The trial’s original sample-size assumptions and justification are not reported in the registry record.

The 80% power column describes the number of participants per arm in a hypothetical study that, under the stated assumptions and if the target effect were true, would have an 80% chance of detecting that effect by the specified statistical procedure. The 90% power column gives the corresponding planning target for a 90% chance. These are design calculations, not measures of what happened in this completed trial.

For planning at 100% of the observed effect, the figures are 306 participants per arm for 80% power and 409 participants per arm for 90% power. At 75% of the observed effect, the figures are 562 and 752 participants per arm. At 50% of the observed effect, they are 1,303 and 1,744 participants per arm. The pattern reflects a general statistical principle: smaller effects are harder to distinguish from random variation and therefore require more participants to detect under otherwise similar assumptions.

General: A planning curve illustrates how the required sample size changes as the effect targeted for detection changes. It should be read as a set of hypothetical design scenarios rather than as evidence about the treatment result. These figures are not observed power.

12. 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.295; treatment proportion p₁ = 0.198; average p̄ = 0.247.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6096 = 1.1949.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6057 = 0.5098.
4. n = (1.1949 + 0.5098)² / (-0.0975)² = 305.4, rounded up to 306 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
p0 <- 0.295454545454545                          # control proportion
p1 <- 0.197916666666667                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1199380)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 306 (80% power), 409 (90% power)
 75% of observed effect: n per arm = 562 (80% power), 752 (90% power)
 50% of observed effect: n per arm = 1,303 (80% power), 1,744 (90% power)
power.prop.test: 305.4 
Simulated power at n = 306 per arm: 0.800 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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.

13. Multiplicity, Missing Data and Analysis Populations

The registry posts one primary outcome: the number of participants with 7 days of smoking abstinence confirmed biochemically at 52 weeks post quit date. It reports no secondary outcomes. The record also lists zero analysis entries. This means that the registry record does not provide a collection of posted outcome analyses from which to assess the complete set of statistical tests.

Multiplicity arises when several outcomes, time points, or comparisons are tested. Repeated testing can increase the chance of obtaining a small p-value by chance, so trial analysis plans sometimes specify how to manage multiple comparisons. The registry does not report whether multiplicity was considered, whether any adjustment was planned, or whether other outcomes were analyzed outside the posted record. It would be inappropriate to infer a multiplicity strategy from the single posted primary result.

The registry gives group counts and unadjusted estimates, but does not report the analysis population, missing-outcome handling, participant flow, or a detailed statistical analysis plan. It is therefore not possible to determine from the record whether the comparison included all randomized participants, how unavailable abstinence assessments were treated, or whether any exclusions occurred after randomization. These details matter because a binary outcome may be affected by how participants without a recorded status are handled.

The record also does not report a prespecified hierarchy of outcomes or whether the primary endpoint definition changed during the trial. The number of outcomes posted does not establish how many outcomes were collected or analyzed. Consequently, the result can be described as the posted unadjusted primary comparison, while the broader analysis context and any adjustments for missing data or multiplicity are not reported in the registry record.

14. 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

Serious events with the highest arm-level rate: hospitalization (1.1%), seizure (1.1%), throat cancer (1.0%).

The registry reports serious adverse events in 2 participants in Standard Treatment and 1 participant in Behavioral Activation for Smoking. The numbers at risk were 88 and 96, respectively. Deaths are listed for 2 participants in Standard Treatment and 0 in Behavioral Activation for Smoking. Other adverse events are listed as 0 in each group.

The listed serious-event terms include hospitalization at 1.1%, seizure at 1.1%, and throat cancer at 1.0%. The registry does not give enough detail to assign these terms to a particular arm or to establish their timing, duration, severity criteria, or relationship to the study interventions. The term percentages are reported as listed and should not be treated as arm-specific rates.

General: Serious adverse event counts describe events meeting a seriousness definition; they do not by themselves show that an intervention caused an event. Death counts are reported separately and should not be added to the serious-event figures without knowing how the registry categorized them. Small event counts are especially limited as a basis for comparing safety. The posted figures are a record of reported events, not a complete safety assessment.

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

The posted result describes 7-day biochemically confirmed abstinence at 52 weeks post quit date in a randomized comparison. The registry reports 26 participants meeting the endpoint among 88 in Standard Treatment and 19 among 96 in Behavioral Activation for Smoking. The unadjusted risk difference is -0.098, with a confidence interval from -0.222 to 0.027; the unadjusted p-value is 0.124.

These estimates do not establish a clear direction for the underlying difference. The risk-difference interval includes zero and values on both sides of zero, while the relative-measure intervals also include their respective null values. The data are compatible with a range of possible contrasts, which limits how precisely the result can be interpreted. The registry does not report an adjusted analysis or details of missing-outcome handling that could add context.

The endpoint reflects abstinence during a 7-day window at the 52-week assessment. It does not show that participants were abstinent throughout the period after their quit date. Nor does the registry result identify why the observed group counts differed. Randomization supports a comparative design, but the posted result alone does not demonstrate that the intervention caused the observed difference.

The result also does not establish that either approach works or does not work. It is a finding from a particular trial population, outcome definition, and follow-up point. Eligibility details, the analysis population, and important elements of the statistical plan are not reported in the registry record. Those omissions limit conclusions about the robustness of the comparison and its applicability to other populations or settings.

The safety counts are similarly descriptive. Serious events and deaths are reported, but the record does not establish whether they were related to either intervention. Taken together, the posted statistics describe the outcomes recorded in this trial and their uncertainty; they do not settle broader clinical questions or substitute for evidence across studies.

16. Why This Trial Matters Statistically

This trial raises statistical questions that are common in behavioral intervention research: how to define a meaningful follow-up outcome, how to compare event proportions, and how to communicate uncertainty when group counts are limited. The primary endpoint is a specific 7-day abstinence measure at 52 weeks post quit date, with biochemical confirmation. Keeping the time window explicit helps prevent a point-in-time assessment from being mistaken for continuous abstinence over the full follow-up.

The comparison also illustrates why an effect estimate should be read with its confidence interval. The risk difference is -0.098, but its interval extends from -0.222 to 0.027. The unadjusted p-value is 0.124. Neither a single estimate nor a p-value conveys the full range of uncertainty; the interval shows that the data remain compatible with contrasts in either direction.

Planning calculations are useful for understanding how assumptions about the effect size influence future study size. The registry’s illustrations use the observed effect as a reference and show larger participant requirements when planning to detect a smaller fraction of that effect. Those illustrations are distinct from the trial’s original design assumptions, which are not reported in the registry record. They should be understood as planning scenarios rather than evidence of trial power or outcome.

Finally, the record demonstrates the importance of transparent reporting beyond the main estimate. Information on participant flow, missing outcomes, analysis populations, multiplicity, and the statistical analysis plan would help readers evaluate the comparison more fully. Their absence does not change the posted counts, but it limits how much can be concluded about the analysis behind them.

17. 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 does not report detailed eligibility criteria, so the precise characteristics of the enrolled population and the criteria used to identify elevated depressive symptoms cannot be assessed. The summary describes adult smokers with elevated depressive symptoms, but the record does not provide the thresholds or further population details. Generalizability beyond this population is therefore uncertain.

The primary endpoint is a 7-day abstinence measure at 52 weeks post quit date, not a measure of continuous abstinence across the full follow-up. The biochemical verification method is not specified. Participant flow, missing abstinence assessments, and the treatment of missing outcomes are also not reported. These gaps limit interpretation of how the endpoint counts relate to all participants enrolled.

The record reports an unadjusted comparison but does not give the statistical test, confidence-interval method, covariate adjustments, or analysis population. It does not report the original sample-size rationale, prespecified analysis plan, or multiplicity approach. The summary described a proposed sample of 200, while registry enrollment is 184; the original design assumptions are not reported, so the implications of that difference cannot be established from the record.

Details of treatment delivery are incomplete in the posted descriptions, including the arm-specific use of the listed transdermal nicotine patch. The masking procedure is also unspecified. Safety reporting provides counts and selected terms, but not arm-specific attribution for the listed terms or details about relatedness and timing. These limitations call for a cautious reading of the posted result and do not imply that unreported procedures or analyses did not occur.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Behavioral Activation Intervention for Smoking Cessation in Smokers With Depressive Symptoms — NCT01199380.
• Registry record last updated 2022-05-18; status last verified 2022-05.
• Results first posted 2020-09-16.
• 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.

21. Record Summary

The registry describes a completed, randomized, single-masked, parallel-group Phase 2 trial sponsored by University of Maryland, College Park. Enrollment was 184. The study compared Standard Treatment with Behavioral Activation for Smoking among smokers with depressive symptoms. The recorded study start is 2010-09, and primary completion is 2016-05.

The primary outcome was the count of participants with 7 days of biochemically confirmed smoking abstinence at 52 weeks post quit date. The registry reports 26 of 88 participants meeting this outcome in Standard Treatment and 19 of 96 in Behavioral Activation for Smoking. The unadjusted risk difference is -0.098, with a confidence interval from -0.222 to 0.027 and an unadjusted p-value of 0.124. The record does not report secondary outcomes or analysis entries.