iQuit Mindfully: Text Messaging for Smoking Cessation: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for iQuit Mindfully: Text Messaging for Smoking Cessation (NCT03029819), a randomized na study. The primary outcome is Smoking Abstinence.

2. Clinical Question

3. Trial Design

This was a completed, randomized, parallel-group trial sponsored by Georgia State University. The registry lists enrollment of 72 and the condition as cigarette smoking. The study start date was 2017-01-18, and primary completion was 2017-08-10. The registry lists masking as single; which study personnel or participants were masked is not reported in the registry record. The phase is listed as NA.

The two arms shared a nicotine patch, a self-help guide, and mindfulness-based addiction treatment (MBAT). The iQuit Mindfully arm also received text messaging. The control arm is labeled Mindfulness-based Addiction Treatment (MBAT). This design addresses the incremental comparison of the text-messaging package alongside the shared treatment components; it is not a comparison of mindfulness treatment against no treatment.

The primary outcome was assessed at the end of treatment, described as 8 weeks. Available data for smoking abstinence were analyzed, with an overall analyzed number of 55. The registry explicitly notes its reason for using available data: coding missing values as smoking can severely bias results. The original trial protocol, the original sample-size justification, and details of the randomization and masking procedures are not reported in the registry record. The record lists participant engagement, participant ratings, and attrition as secondary outcomes. It reports 7 outcome measures and 1 analysis, but the registry record does not provide further information on the analysis plan from those counts alone.

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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Available data for smoking abstinence were analyzed because coding missing data as smoking can severely bias results. Accordingly, the overall number of participants analyzed for smoking abstinence was 55.

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: A total of 72 participants were enrolled in the study. However, one participant was removed due to disruptive behavior in the in-person group treatment, for a final analytic sample of 71 (33 in MBAT and 38 in iQuit Mindfully).

6. Primary Endpoint

The registry lists the primary outcome as Smoking Abstinence, measured over End of Treatment (8 weeks).

The primary endpoint is smoking abstinence at the end of treatment, at 8 weeks. It counts participants who met the registry’s definition: self-reported 7-day abstinence, biochemically verified using expired carbon monoxide <6 parts per million (ppm). This combines a report of recent smoking behavior with a biochemical verification criterion. A count endpoint makes the result interpretable as the number meeting the stated definition in each arm; it does not describe how long an individual remained abstinent beyond the stated assessment window.

In general, a defined binary outcome is useful in a randomized trial because it permits comparison of the proportion meeting a prespecified event definition across arms. The registry presents counts and the numbers analyzed in each arm. It reports 4 participants meeting the endpoint among 24 analyzed in the MBAT arm, and 8 among 31 analyzed in the iQuit Mindfully arm. These available-data denominators are the ones relevant to the posted primary outcome, rather than the enrollment figure.

The registry states that missing data were not coded as smoking because that approach can severely bias results. The full details of missingness, the verification process, and the endpoint’s original protocol specification are not reported in the registry record. As with any endpoint, the result speaks to the operational definition and assessment time recorded, not every possible measure of smoking behavior.

7. Results Posted in the Registry

• iQuit Mindfully: 25.8% (8/31) versus 16.7% (4/24) on control; risk difference 9.1 percentage points (95% CI -12.3 to 30.6), risk ratio 1.55 (0.53–4.54); unadjusted two-proportion z-test p = 0.416.

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.

Attrition

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • iQuit Mindfully: 21.1% (8/38) versus 27.3% (9/33) on control; risk difference -6.2 percentage points (95% CI -26.2 to 13.8), risk ratio 0.77 (0.34–1.77); unadjusted two-proportion z-test p = 0.540.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between iQuit Mindfully and the control. The interval gives the range of effects that remain compatible with the data.

The registry identifies participant engagement, participant ratings, and attrition as secondary outcomes. The posted secondary summary available for interpretation is attrition at the end of treatment. Across the secondary outcomes as a group, the record therefore offers limited information: it does not provide posted estimates for engagement or participant ratings in the record. The scope of conclusions from secondary outcomes is correspondingly narrower than the list of outcome names might suggest.

The attrition comparison is related to the primary result because retention and outcome availability can affect how the abstinence comparison is interpreted. It does not answer the primary question directly, and it cannot establish whether missing abstinence data changed the primary estimate. The record does not report the reasons participants left, whether those reasons differed by arm, or a sensitivity analysis connecting attrition to the primary endpoint. The secondary information should be read as context rather than as a substitute for the primary outcome.

In general, secondary outcomes help describe other aspects of a trial, but testing several outcomes creates multiple opportunities to see a nominally notable result by chance. Unadjusted secondary results therefore carry less weight than a prespecified primary analysis unless the plan and multiplicity handling are clear. The registry record does not report a multiplicity adjustment or enough detail to assess how secondary hypotheses were selected and tested. This limits the strength of claims based on secondary comparisons, especially where results are not supported by a clear analysis plan.

The broad pattern is that the registry names several secondary domains but posts limited analyzable detail for them. Those outcomes can help frame questions about engagement and retention, but they do not resolve the uncertainty around smoking abstinence. The registry record does not report enough information to assess whether any secondary findings were confirmatory or exploratory.

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

• Participant Engagement
• Participant Ratings
• Attrition

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports a chi-squared analysis for the primary comparison, labeled as a superiority analysis. A separate simple, unadjusted recalculation uses the posted arm counts and analyzed numbers to express the comparison as a risk difference, with additional relative measures and confidence intervals. The registry’s test is the sponsor’s own reported analysis; the recalculation is a transparent descriptive check based on summary data, not a replacement for the sponsor’s analysis.

What does a risk difference describe?

In general, a risk difference subtracts the event proportion in one arm from the event proportion in the comparison arm. It expresses the absolute difference in the likelihood of meeting the event definition, with the sign depending on the order of subtraction. For this trial the recalculated contrast is defined as iQuit Mindfully compared with MBAT. A positive estimate therefore points toward a higher observed abstinence proportion in iQuit Mindfully. The posted estimate is 0.091, but the interval extends across zero, so the data are compatible with differences in either direction. It is important not to interpret the point estimate without its uncertainty.

What does the chi-squared test assess?

In general, a chi-squared test assesses whether the observed distribution of a categorical outcome across groups is inconsistent with a null hypothesis of no association. Here, the outcome is whether a participant met the abstinence definition, and the groups are the randomized arms. The registry reports p = .52 for its chi-squared superiority analysis. The record does not report the test statistic, degrees of freedom, or additional test details. The chi-squared result addresses evidence against its null hypothesis; it does not by itself quantify the magnitude or precision of the arm difference.

What do confidence intervals add?

In general, a confidence interval gives a range of estimates compatible with the observed data under the method’s assumptions. A wide interval indicates that the estimate is imprecise. For a risk difference, an interval crossing zero includes values on both sides of no difference. It should not be read as assigning a probability that the true effect lies within the interval. The recalculated interval is broad and crosses zero, reflecting substantial uncertainty in this trial’s arm comparison.

Why can the p-values differ?

The posted recalculation reports an unadjusted p-value of 0.416, while the registry’s reported chi-squared analysis gives p = .52. Different statistical procedures or implementation details can yield different p-values from the same summary counts. The registry does not provide enough information to identify the reason for the difference. Because the discrepancy flag is false, the sponsor’s own analysis takes precedence; the recalculation should be read as an unadjusted summary-statistic analysis rather than the trial’s governing result.

What does unadjusted mean?

In general, an unadjusted comparison uses the outcome counts without accounting for additional covariates or design features beyond the grouping shown. The registry’s primary report identifies a chi-squared test but does not give details of any adjusted analysis. The recalculated estimates are explicitly unadjusted. Randomization supports comparing assigned groups, but in a small trial chance imbalances can remain. Whether any adjusted analysis was planned or conducted is not reported in the registry record.

How should the outcome counts be understood?

The primary outcome is binary at the stated assessment: each analyzed participant either met the abstinence definition or did not. The registry reports the event counts and denominators separately for each arm. In general, a count is easier to interpret when paired with its denominator, because the same count can represent different proportions in groups of different sizes. Here the denominators are the available-data analysis populations and do not amount to an intention-to-treat analysis of every enrolled participant. The registry explicitly explains that missing values were not coded as smoking, but does not report sensitivity analyses that would show how alternative missing-data assumptions affect the result.

The comparison is a superiority analysis, not an equivalence or non-inferiority analysis. In general, failure to reject a no-difference null hypothesis does not prove that two treatments are equivalent. Equivalence or non-inferiority requires its own design and decision criteria, which are not reported in the registry record. The posted result is therefore best read as an uncertain comparison of the observed abstinence outcomes at the specified time point.

11. Confidence Intervals and Precision

The recalculated risk-difference interval is broad and crosses zero. Its lower bound is -0.123; the upper bound is not repeated because it is reported to more than 3 decimal places in the registry summary. The key interpretation is that the interval includes no difference and allows effects in either direction. This means the point estimate alone gives an incomplete account of what the data support.

In general, a confidence interval reflects sampling uncertainty under the calculation’s assumptions. It is not a guarantee that the true value lies in the interval, nor is it a measure of the chance that one arm is better. A broad interval indicates limited precision: results compatible with the data span a meaningful range of possibilities. The primary outcome involved 24 analyzed participants in one arm and 31 in the other, and the event counts were 4 and 8. With relatively few events, estimates of absolute and relative effects can be sensitive to the outcomes of individual participants.

The registry’s own chi-squared result is reported as p = .52, without an effect estimate or confidence interval. Thus, the sponsor’s analysis communicates a test result but not a corresponding interval that would describe the range of effect sizes compatible with that analysis. The posted recalculation supplies an interval for an unadjusted risk difference, but it is not the sponsor’s reported estimate. The two should be kept distinct.

Precision is also affected by the available-data approach. The registry gives an overall analyzed number of 55 for smoking abstinence and notes that missing values were not coded as smoking. The number of missing outcomes by arm and the reasons for missingness are not reported in the registry record. Consequently, the interval captures sampling uncertainty in the recalculated comparison but does not resolve uncertainty from missing-data assumptions or other unreported analysis choices.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The sample-size figures are planning illustrations based on the observed effect, not the trial’s own design justification. They give participants per arm for the binary outcomes, rather than total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at the stated fraction of the observed effect. The original trial’s sample-size assumptions are not reported in the registry record.

The row for planning for 100% of the observed effect uses the observed estimate as the target effect. Rows for planning for 75% and 50% of the observed effect use smaller target effects. Under the listed assumptions, the table gives participants per arm for 80% power and participants per arm for 90% power. In plain terms, those columns describe the planned group size needed to have the stated chance of detecting the selected target effect if the assumptions hold and that effect is real. The 90% power target requires more participants per arm than the corresponding 80% target.

The same direction applies across effect-size rows: smaller effects need more participants to detect than larger effects, all else equal. For example, the displayed primary-outcome planning values rise from 314 participants per arm for 80% power when planning for 100% of the observed effect, to 536 for 75%, and 1,154 for 50%. These are illustrations for future planning, not a reconstruction of the trial’s enrollment target.

The curve should be interpreted using the same planning assumptions and as a relation between target effect and required group size, not as a plot of the trial’s observed power. This is not observed power. The registry record does not report the study’s original power calculation or explain whether these illustration assumptions match the original design.

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

Worked calculation for this trial

1. Control proportion p₀ = 0.167; treatment proportion p₁ = 0.258; average p̄ = 0.212.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5784 = 1.1336.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5748 = 0.4837.
4. n = (1.1336 + 0.4837)² / (0.0914)² = 313.1, rounded up to 314 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 <- 0.166666666666667                          # control proportion
p1 <- 0.258064516129032                          # 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(3029819)
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 = 314 (80% power), 419 (90% power)
 75% of observed effect: n per arm = 536 (80% power), 717 (90% power)
 50% of observed effect: n per arm = 1,154 (80% power), 1,544 (90% power)
power.prop.test: 313.1 
Simulated power at n = 314 per arm: 0.799 (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.

14. Analyses Reported by the Sponsor

The registry’s own primary analysis is a chi-squared superiority test, reported with p = .52. The simple recalculation from the posted counts gives an unadjusted p-value of 0.416 and estimates the risk difference with a confidence interval. These are different presentations of the primary comparison: the registry’s test is the sponsor’s reported analysis, while the recalculation is based directly on the posted summary statistics.

The discrepancy flag is false, so the sponsor’s own analysis takes precedence. The registry does not provide a sponsor-reported effect estimate or confidence interval for the primary outcome, and it does not report enough test details to explain why the recalculated p-value differs. The recalculated result should therefore not be presented as the sponsor’s result or used to overwrite the registry’s stated analysis.

The recalculation is still useful for understanding the direction and uncertainty of the observed comparison. Its interval crosses zero and is broad, so the available summary data do not give a precise estimate of the absolute difference. The sponsor’s p-value also does not establish equivalence or a definitive absence of an effect. Both readings should remain tied to their methods, and neither provides a basis for claims beyond the registry’s reported outcome and analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry reports 7 outcome measures and 1 analysis, lists participant engagement, participant ratings, and attrition among secondary outcomes, and provides a reported chi-squared analysis for the primary endpoint. It does not report a statistical analysis plan detailing which outcomes or time points were prespecified, how multiple comparisons were handled, or whether any outcomes were designated exploratory. A multiplicity adjustment is not reported in the registry record.

In general, when researchers test multiple outcomes or comparisons, the chance of at least one apparently unusual result can increase. Adjustment methods or a clearly prespecified hierarchy can help interpret that issue. Without a reported plan, secondary results should not be treated as if each were an independent confirmatory test, and an isolated unadjusted result should be interpreted cautiously. This does not change the meaning of the primary comparison, but it limits the evidential weight of secondary analyses.

For the primary endpoint, the registry explicitly states that available data were analyzed and that missing data were not coded as smoking because that approach can severely bias results. It gives an overall analyzed number of 55. The numbers analyzed by arm are 24 for MBAT and 31 for iQuit Mindfully. The record does not report the reasons for missingness, the timing of missingness, or whether missingness was related to participant characteristics or outcomes.

In general, analyzing available observations avoids assigning an outcome value to participants with missing measurements, but the result can still be biased if the availability of outcome data is related to the outcome or treatment group. The registry’s stated concern about coding missing observations as smoking does not establish that the available-data analysis is unbiased. Sensitivity analyses using alternative assumptions, an imputation approach, or an intention-to-treat analysis are not reported in the registry record.

The original sample-size justification, interim analyses, and detailed statistical plan are also not reported in the registry record. Their absence means the posted summary cannot establish whether the trial had adequate planned precision for its intended effect or whether analysis decisions followed an original protocol. These are limitations of what can be assessed from the record, not evidence that a particular procedure was or was not used.

16. 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 non-serious adverse event terms

The registry reports serious adverse events for 33 participants at risk in the MBAT group and 39 at risk in the iQuit Mindfully group, with 0 serious adverse events in each group. It also reports 0 deaths in both groups. These figures describe the serious-event counts recorded in the registry; zero recorded events does not prove that an intervention has no risk.

For other adverse events, the registry reports 7 affected participants in the MBAT group and 5 in the iQuit Mindfully group. These are counts, not rates, and the registry’s safety denominators differ from the available-data denominators used for smoking abstinence. The record does not explain the difference between those denominators or provide additional detail about event types, severity, timing, or attribution. The top serious-event terms list is empty.

In general, safety counts need to be interpreted in light of the number monitored, the event definitions, and the period of observation. The registry record does not report enough detail to assess all of those factors. These figures should be read as the posted adverse-event summaries, not as a comprehensive comparison of safety.

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

The randomized comparison addresses whether adding text messaging to a package of nicotine patch, self-help guide, and mindfulness-based addiction treatment was associated with a different end-of-treatment abstinence result than the shared package without text messaging. The posted counts were higher in the iQuit Mindfully arm, but the recalculated interval is broad and includes no difference. The registry’s own chi-squared analysis reports p = .52. Together, these findings indicate uncertainty rather than a definitive difference.

The result does not show that the arms are equivalent. A non-significant test is not proof of no effect, and an interval crossing zero can include both benefit and harm in the direction of the chosen contrast. Conversely, the higher observed count in one arm does not establish that text messaging caused a higher abstinence rate. Interpretation should account for the small available-data groups, the limited number of events, and the uncertainty around the effect estimate.

The endpoint is specific: self-reported 7-day abstinence at the end of treatment, biochemically verified by expired carbon monoxide <6 ppm. It is not a measure of long-term abstinence or every aspect of smoking behavior. Longer-term outcomes are not reported in the registry record. The posted result also pertains to the full treatment package comparison described in the trial, not to text messaging in isolation from the other treatment components.

Missing primary outcome data were handled through an available-data analysis rather than coding missing values as smoking. The registry states this choice was made because coding missing data as smoking can severely bias results. However, the reasons and pattern of missingness and sensitivity analyses are not reported. Consequently, the outcome comparison should not be treated as a definitive estimate for all enrolled participants.

These results describe what the registry reports for this trial. They do not establish a treatment recommendation, prove effectiveness or ineffectiveness, or determine what would happen in other populations or treatment settings. The record supports a cautious reading centered on the observed counts, the sponsor’s stated test, and the substantial uncertainty.

18. Why This Trial Matters Statistically

This trial illustrates several statistical issues that arise when behavioral interventions are compared using a binary clinical outcome. The primary endpoint is easy to state as a participant count, but the interpretation depends on its definition, the denominator with available data, and the uncertainty around the between-arm contrast. Reporting both counts and analyzed numbers makes the outcome more interpretable than counts alone.

The record also shows why a point estimate and a test result answer different questions. The recalculated risk difference communicates an absolute contrast, while the sponsor’s chi-squared p-value summarizes evidence relative to a null hypothesis under its test. Neither should be read alone as a complete account. The recalculated interval spans zero, emphasizing that the observed direction is not estimated precisely.

Missing outcome data are particularly important in a smoking-abstinence analysis because the registry explicitly warns that coding missing observations as smoking can severely bias results. Choosing not to use that rule does not by itself remove missing-data uncertainty. Without reported reasons for missingness or sensitivity analyses, readers cannot determine whether the available-data result is robust to alternative assumptions.

The planning illustration further demonstrates how sample-size requirements depend on the effect targeted: smaller effects require more participants under the stated assumptions. Such illustrations are not the original design justification and cannot retrospectively establish the trial’s planned power. The record does not report the original sample-size rationale.

Finally, the distinction between a component comparison and a whole treatment comparison matters. Both groups received MBAT, nicotine patch, and a self-help guide; the additional component in iQuit Mindfully was text messaging. The trial therefore informs the comparison as implemented, while the posted findings remain imprecise and limited to the recorded outcomes and follow-up.

19. 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 based on available data rather than all enrolled participants. The registry reports 55 participants analyzed overall, with 24 in the MBAT arm and 31 in iQuit Mindfully. The reasons for missing outcome data, their timing, and their relationship to treatment assignment or abstinence are not reported in the registry record. The stated decision not to code missing data as smoking avoids one potentially biased approach but does not establish that the available-data analysis is unbiased.

The outcome assessment is limited to end of treatment at 8 weeks and to the stated 7-day self-report with biochemical verification threshold. Longer-term abstinence outcomes are not reported in the registry record. The record does not provide further details on verification procedures or adjudication.

The analyzed groups and event counts are small, and the recalculated confidence interval is broad. The registry’s own primary analysis reports a p-value but no effect estimate or interval, while detailed test specifications are not reported. The original statistical analysis plan, planned sample-size justification, and any interim analyses are not reported in the registry record. It is therefore not possible to assess from the record whether the reported analysis fully follows the original plan.

The registry lists engagement, ratings, and attrition as secondary outcomes, but the posted results available for interpretation include attrition only. A multiplicity strategy is not reported. The safety summaries also have denominators different from the primary-outcome analysis, without an explanation in the record. Finally, the shared treatment components mean the contrast concerns the added text-messaging package in this trial, not mindfulness treatment versus no treatment or messaging as an isolated intervention.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: iQuit Mindfully: Text Messaging for Smoking Cessation — NCT03029819.
• Registry record last updated 2019-01-08; status last verified 2018-12.
• Results first posted 2018-12-17.
• 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.

23. Record Summary

NCT03029819 is a completed randomized parallel-group trial sponsored by Georgia State University, titled “iQuit Mindfully: Text Messaging for Smoking Cessation.” It compared MBAT, nicotine patch, and a self-help guide with the same package plus text messaging. The registry lists enrollment of 72, with study start on 2017-01-18 and primary completion on 2017-08-10.

The primary outcome was smoking abstinence at the end of treatment, 8 weeks, defined by self-reported 7-day abstinence with expired carbon monoxide <6 ppm verification. Available data were analyzed for 55 participants overall. The registry reports 4 events among 24 analyzed in the MBAT arm and 8 among 31 in iQuit Mindfully. Its own chi-squared superiority analysis reports p = .52; the simple unadjusted recalculation is imprecise and its confidence interval crosses zero.

The registry lists participant engagement, participant ratings, and attrition as secondary outcomes. Serious adverse events and deaths are reported as 0 in both groups. Missing-data details, the original sample-size justification, and a full analysis plan are not reported in the registry record.