mLab App Plus: A Randomized Controlled Trial of a Mobile Health (mHealth) Intervention: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for mLab App Plus: A Randomized Controlled Trial of a Mobile Health (mHealth) Intervention (NCT06059443), a randomized na study. The primary outcome is The Number of Participants Who Are Able to Self-administer the DPP® HIV-Syphilis Test With mLab App Plus.

2. Clinical Question

The study is framed as a pilot of whether the app can support self-testing and interpretation, with the broader goal of increasing initiation of HIV and syphilis self-testing. The main endpoint is not described as a between-arm comparison: the Standard of Care arm did not have access to the app, and the registry record flags fewer than two arms for the primary outcome. That limits what can be learned from this endpoint about differences between randomized groups.

3. Trial Design

The registry identifies this as a randomized, parallel-group study with single masking. It lists Columbia University as the sponsor and gives the enrollment as 40. The study status is completed; the recorded start date is 2023-10-17 and the primary completion date is 2024-06-21. The phase is listed as NA.

Participants were assigned to mLab App Plus or Standard of Care. Both arm descriptions include standard of care counseling and online surveys. The intervention description additionally names the mLab App Plus and a box of condoms, while the Standard of Care description names an email linking to mobile-optimized prevention information. The app arm also includes testing activity involving the DPP® HIV-Syphilis Test. The registry record does not fully describe the intervention arm text, and it does not identify which parties were masked.

Random allocation can help balance participant characteristics across groups on average, but it does not guarantee balance in a study of this size. The parallel design means the groups are assigned to different study conditions rather than crossing over between them. These are general features of randomized parallel trials; the registry does not report allocation procedures or masking procedures in enough detail to assess their implementation.

The record describes a pilot focused on participants’ ability to self-administer and interpret tests. It does not report a sample-size justification, a planned enrollment rationale, or the statistical analysis plan. The completed status and dates describe the registry record’s study timeline, not the completeness or precision of the posted outcome evidence.

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: The Standard of Care arm did not receive access to the mLab App Plus.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as The Number of Participants Who Are Able to Self-administer the DPP® HIV-Syphilis Test With mLab App Plus, measured over 3-Month Follow-up.

The primary endpoint is the number of participants able to self-administer the DPP® HIV-Syphilis Test with mLab App Plus at 3-Month Follow-up. The registry defines success as completing the test independently and accurately identifying and interpreting HIV and syphilis statuses, as judged by the supervising clinician. If the clinician rather than the participant administers the test, it does not count as a successful self-test.

This endpoint combines practical test completion with correct interpretation. That makes it relevant to a pilot asking whether an app can support self-testing, rather than measuring only whether a test was attempted. The clinician’s assessment is part of the stated definition; the registry does not describe how disagreements or uncertain readings were handled.

The endpoint is a count of participants, so interpreting a count ordinarily requires knowing the relevant group denominator and the rules for participants whose follow-up data are unavailable. Those details, along with the observed count, are not reported in the registry record. The record states that the Standard of Care arm did not receive access to the app and flags fewer than two arms in the primary outcome. Therefore, this endpoint as registered does not provide a two-arm comparison of app versus Standard of Care.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies a randomized, parallel design, but does not report the statistical analysis plan. The distinctions below explain general methods relevant to the described endpoint and are not claims about analyses performed in this trial.

What the endpoint counts. The primary endpoint is a count of participants meeting a binary success definition: a participant either satisfies the stated criteria for successful self-testing or does not. A count is not, by itself, a rate or proportion. To interpret it as a proportion, the analyzed denominator and handling of participants without an observed assessment must also be known. The registry record does not report the primary outcome count or its denominator.

Why the group definition matters. A between-group treatment effect requires comparable outcome definitions and results for the groups being contrasted. In this record, the primary endpoint is tied to access to mLab App Plus, while the Standard of Care arm did not receive the app. The registry flags fewer than two arms in the primary outcome. This means the posted primary outcome information does not support a randomized contrast between the two arms. Randomization alone does not create a comparative result when outcome results for both groups are not reported.

Counts, proportions, and uncertainty. For a binary participant outcome, analyses often describe the number meeting the definition in relation to the number assessed. Comparative analyses may estimate an absolute difference or relative effect, depending on the question and analysis plan. Uncertainty is commonly conveyed with a confidence interval. These are general approaches; no such primary effect estimate or interval is reported in the registry record. No estimate should be reconstructed from enrollment or safety denominators, because those may not be the outcome-specific analysis populations.

Why follow-up and outcome assessment matter. The endpoint is scheduled at 3-Month Follow-up and relies on clinician determination of whether a test was completed and interpreted accurately. Follow-up completeness can affect how representative the observed participants are of those randomized. If participants without a recorded endpoint differ systematically from those with one, a complete-case summary may not describe the full randomized group. The registry record does not report follow-up completion, missing endpoint counts, or a missing-data method. It also does not report further procedures for clinician assessment or interpretation disagreements.

Over-dispersion in count data. In general, count outcomes can vary more than a simple statistical model expects; this is called over-dispersion. It can arise when observations are more heterogeneous than the model assumes. When present, an analysis that fails to account for it may understate uncertainty. This concept is relevant to some count outcomes, but the primary endpoint is a participant count and the registry record does not report a model, a dispersion estimate, or an over-dispersion assessment. There is no basis to say that over-dispersion was present or that a particular model was used.

Significance testing and planning assumptions. The record describes a sample-size planning illustration based on an observed effect, with a two-sided significance level of 0.05, equal allocation, and a normal approximation. It says the illustration concerns detecting a stated fraction of the observed effect. These are planning assumptions, not evidence of the trial’s original design rationale and not an analysis of the trial results. The numerical planning outputs are not reported in the registry record. Because the observed primary effect is also not reported, the illustration cannot be interpreted as demonstrating that the trial had adequate power. Sample-size calculations are planning exercises; they are not observed power.

What the design details do not establish. The record says the trial was single masked, but does not say who was masked or how masking was maintained. It records randomization, but does not describe sequence generation, allocation concealment, stratification, or adherence to assigned conditions. Those procedures can affect risks of bias, but their absence from the record does not prove they were not used. The statistical analysis plan, interim analyses, and sample-size justification are not reported in the registry record.

Reading the absence of an analysis. The registry lists 0 analyses. This should be read as an absence of posted analyses in the record, not as a result of no effect or a null test. An analysis would require a specified outcome population, an approach to missing observations, and a summary or model suited to the question. Without reported results and methods, the clinical question cannot be answered quantitatively from the registry record.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("mLab App Plus")
n      <- c(20)
events <- c(12)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  mLab App Plus  20  12  60.0  36.1  80.9  38.7  78.1  38.4  78.2

11. Multiplicity, Missing Data and Analysis Populations

The registry lists 4 outcome measures, including the primary endpoint and secondary outcomes concerning test results, referrals, and linkage to services. It does not report statistical analyses for these outcomes. A plan for handling multiple comparisons is not reported in the registry record.

Multiplicity arises when several outcomes or contrasts are tested: the more tests considered, the greater the chance that at least one result may appear noteworthy by chance, depending on the testing strategy. Researchers may address this through a prespecified hierarchy, adjusted significance thresholds, or by treating secondary analyses as exploratory. These are general options, not methods attributed to this trial. The registry does not say whether a hierarchy or adjustment was planned.

Missing data are also not characterized. The record does not report how many participants completed the primary assessment, whether any endpoint values were unavailable, or what approach was intended for missing observations. It does not describe analysis populations, such as whether participants would be analyzed according to randomized assignment or according to intervention received. These details are important because exclusions after randomization can affect how group comparisons are interpreted.

The registry record also does not report interim analyses or stopping rules. Their absence from the record should not be read as proof that none were planned; the relevant information is not reported in the registry record. With no posted analysis plan or results, the impact of multiplicity, missingness, or analysis-population choices cannot be evaluated.

12. 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 safety record lists the mLab App Plus group with 20 participants at risk and 0 serious adverse events, 0 other adverse events, and 0 deaths. The Standard of Care group likewise lists 20 participants at risk, 0 serious adverse events, 0 other adverse events, and 0 deaths. No top serious adverse-event terms are listed.

These figures indicate that no events were recorded in those categories for the participants represented in the registry safety groups. They should not be read as proof that the intervention has no risk. Event counts alone do not quantify the precision of a safety estimate, and rare events may not be observed in a study with limited enrollment. The registry record does not provide further detail on event definitions, ascertainment procedures, exposure time, or the period covered by the safety counts. It also does not report whether any events were considered related to the intervention. These limitations prevent a fuller assessment of safety from the posted counts alone.

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

This record describes a completed randomized pilot focused on whether young men who have sex with men and young transgender women can use mLab App Plus to self-administer and interpret HIV and syphilis tests. It specifies a clinician-assessed definition of success and a 3-Month Follow-up endpoint. The safety groups each report 20 participants at risk and no recorded serious adverse events, other adverse events, or deaths.

The primary result itself is not reported in the registry record. There is no posted count of successful self-tests, no outcome-specific denominator, and no estimate with an uncertainty interval. The record also flags fewer than two arms in the primary outcome. As a result, it does not provide a comparative estimate of the app versus Standard of Care for this endpoint.

These registry entries do not establish that the app increased self-testing, improved interpretation, or changed linkage to prevention or care. They also do not establish that it had no effect. The appropriate conclusion is that the posted registry information is insufficient to quantify the primary outcome or its comparative effect.

In general, pilot studies can be useful for assessing feasibility and refining outcome measurement, but a pilot’s purpose and evidence need to be distinguished from a definitive estimate of intervention effectiveness. Here, the study is described as a pilot, while its outcome results and detailed analysis plan are not reported. Any broader claims about behavior change, service use, or clinical outcomes would go beyond the posted results.

14. Why This Trial Matters Statistically

This trial raises a statistical question that is distinct from whether participants were offered an app: can participants independently complete a combined HIV and syphilis test and accurately interpret the results? The primary endpoint’s definition reflects that distinction by requiring both self-administration and correct identification and interpretation, assessed by a supervising clinician.

For this question, outcome ascertainment is central. A completed test alone would not meet the registered success definition, and clinician administration would not count as a successful self-test. Clear, reproducible assessment therefore matters to the validity of a participant count. The registry identifies the clinician’s role but does not report detailed assessment procedures or the observed endpoint count.

The randomized design is also important because the intervention and Standard of Care are different study conditions. However, a randomized design supports comparative inference only when outcomes are reported for the groups being compared and the analysis is described. The registry identifies the primary endpoint as app-related and flags fewer than two arms for that outcome. This makes transparency about the estimand and outcome population especially important.

The distinction between feasibility evidence and comparative effect estimation is broadly useful in biostatistics. A pilot may inform whether a measurement process is workable, while a claim about between-group differences requires outcome data, an analysis plan, and an account of uncertainty. The posted record documents the question and design but does not provide the primary result needed to evaluate either the observed success level or an app-versus-care difference.

15. 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 most consequential limitation of the registry record for interpretation is that it does not report the primary outcome count, its denominator, or an effect estimate. Although the study is marked completed, completion status alone does not provide the outcome results needed to assess test-taking ability or precision. The record lists 0 analyses.

The primary endpoint is not presented as a two-arm comparison. The Standard of Care arm did not receive access to the app, and the record flags fewer than two arms in the primary outcome. This limits the comparative information available from the registered endpoint. The record also does not report results for the listed secondary outcomes, including referrals and linkage to services.

Several features needed to judge the analysis are not reported in the registry record: the statistical analysis plan, sample-size justification, analysis populations, follow-up completeness, missing-data handling, allocation procedures, and the identity of the party or parties masked. The intervention arm description is incomplete in the record. These omissions mean that the conduct and analysis cannot be fully evaluated from the registry information.

The enrollment was 40, and the safety groups each list 20 participants at risk. This enrollment limits the amount of information available for estimating uncommon outcomes, though the registry does not report a rationale for the planned sample size. The zero recorded adverse-event counts should therefore be interpreted as counts, not as precise evidence about the likelihood of rare events. These limitations concern what can be concluded from the registry record and do not establish what may be available from other sources.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: mLab App Plus: A Randomized Controlled Trial of a Mobile Health (mHealth) Intervention — NCT06059443.
• Registry record last updated 2025-03-05; status last verified 2025-02.
• Results first posted 2025-03-05.
• 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.

19. Record Summary

NCT06059443 is a completed randomized, parallel-group, single-masked pilot sponsored by Columbia University. Enrollment is listed as 40, with a recorded start date of 2023-10-17 and primary completion date of 2024-06-21. The study compares mLab App Plus with Standard of Care for a population that includes young men who have sex with men and young transgender women.

The primary endpoint counts participants able to self-administer and accurately interpret the DPP® HIV-Syphilis Test at 3-Month Follow-up, as determined by a supervising clinician. The registry record does not report the primary result, a comparative estimate, or statistical analyses. It lists three secondary outcomes and safety counts of 0 serious adverse events, 0 other adverse events, and 0 deaths in each group, with 20 participants at risk per group.

The registry does not report the statistical analysis plan, sample-size justification, missing-data procedures, or analysis populations. It therefore documents the trial question and selected design and safety information, but does not provide enough outcome information to quantify the primary result.