Utilizing Text Messaging to Improve Vehicle Safety Among At-Risk Young Adults: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Utilizing Text Messaging to Improve Vehicle Safety Among At-Risk Young Adults (NCT03833713), a randomized na study. The primary outcome is Seat Belt Use.

2. Clinical Question

3. Trial Design

The registry record describes a completed, randomized, triple-masked, parallel-group study. It lists the phase as not applicable. The record gives total enrollment as 218 and identifies the sponsor as the University of Pittsburgh. The study start date is 2019-09-26, and the primary completion date is 2021-11-22. These dates describe the registry milestones and do not establish when every participant was enrolled or followed.

The two posted groups are SMS Intervention and SMS Assessments. Participants in the intervention group received once-weekly automated dialogue sessions or micro-interventions, with self-monitoring, performance feedback, and goal support. Participants in the assessment group received weekly SMS assessments about their target risk behavior without feedback or goal support. Both groups therefore had text-message contact, while the intervention content differed.

The brief study summary describes the Safe Vehicle Engagement (SaVE) trials as three parallel randomized clinical trials. The results in this record compare the two groups named above. The registry record does not report further details about how the three trials related to this particular comparison, how randomization was generated or implemented, or who was masked. The label “triple” is recorded, but the roles of the masked individuals are not reported in the registry record.

The primary endpoint was seat belt use at week 8, defined as the participant count reporting always using a seat belt over the past 2 weeks. The primary outcome population is described as 158 participants who completed the 8-week follow-up and were included in outcome analyses. Other posted outcomes include intervention acceptability and seat belt use at week 14. The registry record also lists feasibility of recruitment as a secondary outcome, but detailed results for that outcome are not reported in the registry record.

The registry record lists four outcome measures and no reported analyses. It does not state the original sample-size justification, the planned statistical analysis, or the procedures used to implement randomization and masking. Those omissions limit what can be inferred about the study’s original design choices.

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

Analysis population for the primary outcome, as defined in the registry: 158 participants completed the 8-week follow-up and thus were included in outcome analyses.

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 Seat Belt Use, measured over Week 8.

The primary endpoint is a count of participants reporting that they always used a seat belt over the past 2 weeks, assessed at week 8. The registry record describes it as a participant count and identifies the outcome population as those who completed the 8-week follow-up and were included in outcome analyses. The arm counts are 34 of 82 for SMS Intervention and 15 of 76 for SMS Assessments.

This endpoint captures a reported safety behavior rather than a direct observation of seat belt use. Asking about a recent period gives the response a defined time frame, while the binary response makes it possible to compare the number or proportion meeting the “always” criterion between randomized groups. It is therefore a practical way to summarize the stated behavior for this trial. It also compresses variation: the measure does not distinguish occasional use from frequent use among participants who do not report “always.”

Self-report may not match behavior in every instance, and the registry record does not report how responses were verified. The endpoint should therefore be read as reported seat belt use over the specified period, not as an objectively observed record of every trip. It also measures one behavior at one follow-up time; it does not capture all vehicle-safety behaviors described in the trial summary.

7. Results Posted in the Registry

• SMS Assessments: 19.7% (15/76) versus 41.5% (34/82) on control; risk difference -21.7 percentage points (95% CI -35.6 to -7.8), risk ratio 0.48 (0.28–0.80); unadjusted two-proportion z-test p = 0.003.

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.

Measure of Intervention Acceptability

• 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:
  • SMS Assessments: 54.6% (59/108) versus 50.9% (56/110) on control; risk difference 3.7 percentage points (95% CI -9.5 to 17.0), risk ratio 1.07 (0.83–1.38); unadjusted two-proportion z-test p = 0.582.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SMS Assessments and the control. The interval gives the range of effects that remain compatible with the data.

Seat Belt Use

• 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:
  • SMS Assessments: 30.8% (20/65) versus 42.7% (32/75) on control; risk difference -11.9 percentage points (95% CI -27.7 to 4.0), risk ratio 0.72 (0.46–1.13); unadjusted two-proportion z-test p = 0.146.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SMS Assessments and the control. The interval gives the range of effects that remain compatible with the data.

The secondary results cover intervention acceptability during 2 weeks to 8 weeks and seat belt use at week 14. Together, they do not provide a uniformly clear statistical pattern: their posted risk-difference intervals include zero, and their unadjusted p-values do not indicate clear evidence of a group difference at the conventional 0.05 level. The registry record also lists feasibility of recruitment as a secondary outcome, but does not report its detailed results.

These secondary outcomes offer context for the primary week 8 seat belt use result, but they address different questions. Acceptability concerns participants’ responses to the intervention over a period of weeks, while the week 14 outcome concerns reported seat belt use at a later follow-up. Differences in outcome, time point, and analyzed participants mean that the results are not direct replications of the primary comparison. The secondary findings therefore neither confirm nor overturn the primary result.

Unadjusted secondary results carry less weight when several outcomes or time points are assessed without a reported multiplicity strategy. General explanation: The more separate tests considered, the greater the opportunity for at least one apparently noteworthy result to occur by chance. No adjustment, ordering, or confirmatory status for the secondary tests is reported in the registry record. The secondary comparisons are best treated as supporting or exploratory information, rather than independent confirmation of a primary finding.

The registry record does not report a detailed statistical analysis plan, and it lists no reported analyses. It is therefore not possible to determine from the record whether all secondary outcomes and time points were specified before results were examined. This uncertainty is another reason to interpret the overall secondary pattern cautiously and to avoid drawing a broad conclusion from any one secondary estimate.

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

• Feasibility of Recruitment
• Measure of Intervention Acceptability
• Seat Belt Use

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

General explanation: For a binary outcome, a risk difference subtracts one group’s event proportion from the other group’s event proportion. It is expressed on the probability scale, so its sign depends on the order of the groups in the comparison. A negative difference for SMS Assessments compared with SMS Intervention means the observed event proportion was lower in SMS Assessments. The risk difference is an absolute contrast, not a relative one. The posted primary estimate is -0.217 for this stated ordering.

The arm-level counts provide the underlying quantities for interpreting that contrast: 34 of 82 participants in SMS Intervention and 15 of 76 in SMS Assessments reported always using a seat belt at week 8. Counts and proportions answer related but different descriptive questions. Counts show how many participants met the criterion; proportions account for the different numbers analyzed in the two groups.

What does a confidence interval add?

General explanation: A confidence interval describes the uncertainty around an estimated contrast under the assumptions of the method used to construct it. It is not a range containing a known fixed share of individual participant outcomes, and it is not the probability that the true effect lies within the particular interval. For the primary risk difference, the posted interval is -0.356 to -0.078. Both ends are negative, so the interval is on the same side of zero as the estimated difference. The registry record does not report the procedure used to calculate this interval.

How should the p-value be read?

General explanation: A p-value describes how unusual results at least as incompatible with a null hypothesis would be under a specified statistical model, if the null hypothesis and model assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of a difference. The primary comparison has an unadjusted p-value of 0.003. The record does not report the test used to obtain that value or whether any covariates were included in the analysis. Accordingly, it is appropriate to describe it as the posted unadjusted p-value rather than attribute it to a particular test.

Why are relative measures also displayed?

The posted comparison includes a risk ratio of 0.476, with a 95% confidence interval from 0.283 to 0.802, and an odds ratio of 0.347, with a 95% confidence interval from 0.170 to 0.710. These are relative contrasts for the same outcome and group ordering. General explanation: A risk ratio compares event proportions by division, while an odds ratio compares event odds. They use different scales and should not be interpreted as interchangeable. When an event is not rare, an odds ratio can appear farther from its null value than a risk ratio. The registry record does not identify the method used to estimate these relative measures.

The risk difference is often easier to relate to an absolute change in the proportion meeting an outcome criterion. Relative measures can give a complementary view of how the groups compare proportionally. Neither scale removes uncertainty or limitations in how the outcome was measured. The primary endpoint is self-reported, and the analysis population is described as participants completing week 8.

What does over-dispersion mean for these results?

General explanation: Over-dispersion means that the observed variation is greater than a statistical model expects. It can arise when outcomes are more heterogeneous or clustered than assumed. In such settings, standard errors may be too small if the extra variation is ignored, which can make confidence intervals too narrow and p-values too small. Over-dispersion is especially relevant to certain count or clustered-data models; the primary endpoint is a binary participant count rather than a reported rate with a dispersion estimate. The registry record does not report an over-dispersion assessment or model-based adjustment, so no claim about such an assessment can be made.

What analysis details are available?

The registry record posts the arm counts, risk-difference estimates, intervals, and unadjusted p-values for the comparisons. It does not report a statistical analysis plan, a named test, adjustment variables, a prespecified model, or sensitivity analyses. It also reports no analyses under its analysis listing. The absence of those details makes it impossible to assess whether the methods used matched a detailed prespecified plan or how robust the results are to alternative analytic choices.

The registry record identifies the primary outcome population as 158 participants who completed the 8-week follow-up and were included in outcome analyses. It does not describe whether an intention-to-treat analysis was planned or conducted, how missing outcome values were handled, or how participants who did not complete follow-up were treated. General explanation: Analysis-population definitions matter because conclusions can change when people with missing follow-up differ from those with observed outcomes. A complete-case comparison describes participants with observed outcomes and may not represent all randomized participants if follow-up is related to outcome or group.

Finally, the posted p-values for secondary outcomes are unadjusted, and no multiplicity strategy is reported. General explanation: When several outcomes or time points are examined, interpreting each nominal p-value as if it were the only test can overstate the strength of evidence across the whole set. A prespecified hierarchy or multiplicity adjustment can address that issue, but neither is reported in the registry record. The appropriate reading is therefore to distinguish the primary comparison from exploratory or secondary comparisons and to retain the uncertainty around all estimates.

11. Confidence Intervals and Precision

The week 8 risk difference comparing SMS Assessments with SMS Intervention is -0.217, with a 95% confidence interval from -0.356 to -0.078. The interval is entirely below zero, consistent with a lower observed proportion in SMS Assessments for the reported “always used a seat belt” outcome. Its width also shows that the estimate is not exact: values across a range remain compatible with the interval procedure and its assumptions. The registry record does not report how the interval was calculated.

General explanation: A confidence interval is a way to communicate sampling uncertainty around an estimate. Under repeated use of a valid procedure and its assumptions, intervals constructed at the stated confidence level would cover the fixed quantity a specified proportion of the time. The interval is not a guarantee that the true value lies within these particular endpoints, and it does not account automatically for bias, outcome misclassification, missing data, or unreported design features.

The secondary intervals are broader in relation to their estimates and include zero: the acceptability risk difference is 0.037, with an interval from -0.095 to 0.170; the week 14 seat belt use risk difference is -0.119, with an interval from -0.278 to 0.040. These ranges are compatible with differences in either direction as well as values near no difference. They do not establish that the groups are equivalent.

Precision depends on the amount of information in the analysis, including the number of participants with observed outcomes and the variability of the endpoint. The primary outcome analysis includes 158 participants who completed week 8. The registry record does not report a target precision, a clinically meaningful difference, or a prespecified interval-width goal. Precision should therefore be judged from the posted intervals and the limitations of the observed outcome data, rather than against a threshold not reported in the registry record.

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 illustrations are planning scenarios based on the observed effect, not the trial’s original design justification. Because the posted outcomes are binary participant counts rather than time-to-event outcomes, the figures are participants per arm, not total events. The planning assumptions listed in the registry record are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each scenario uses an effect to detect equal to the stated fraction of the observed effect.

The 80% power column gives the number of participants per arm that the planning calculation associates with an 80% chance of detecting the specified effect under those assumptions, if that effect and the model assumptions apply. The 90% power column gives the corresponding number for a 90% chance. These are design probabilities for a hypothetical future study under the specified scenario, not probabilities that the reported trial result is correct.

The rows vary the assumed effect: 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. The smaller the effect a study is intended to detect, the more participants are generally needed to distinguish it from random variation with the same power and significance level. The displayed planning values illustrate that relationship. A planning curve, if considered alongside the figures, represents this same dependence between the effect size to be detected and the required sample size under the stated assumptions.

The registry record does not report the assumptions used for the trial’s original design or its original sample-size justification. These calculations use the observed effect as a starting point, so they are sensitive to the uncertainty in that estimate. This is not observed power.

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 = 0.415; treatment proportion p₁ = 0.197; average p̄ = 0.306.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6517 = 1.2773.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6333 = 0.5330.
4. n = (1.2773 + 0.5330)² / (-0.2173)² = 69.4, rounded up to 70 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 <- 0.414634146341463                          # control proportion
p1 <- 0.197368421052632                          # 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(3833713)
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 = 70 (80% power), 93 (90% power)
 75% of observed effect: n per arm = 131 (80% power), 174 (90% power)
 50% of observed effect: n per arm = 306 (80% power), 409 (90% power)
power.prop.test: 69.4 
Simulated power at n = 70 per arm: 0.813 (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. Multiplicity, Missing Data and Analysis Populations

The registry record lists four outcome measures and includes secondary outcomes concerning recruitment feasibility, intervention acceptability, and seat belt use. It posts results for acceptability and week 14 seat belt use, as well as the primary week 8 endpoint. No reported analyses are listed, and no analysis plan is described. The record does not report whether outcomes were ordered in a hierarchy, whether particular comparisons were designated confirmatory, or whether the statistical significance threshold was adjusted for multiple comparisons.

The posted p-values are unadjusted. General explanation: If multiple outcomes or follow-up times are tested, each test adds an opportunity for a chance finding. A multiplicity procedure can control the overall false-positive risk across a family of tests, while a prespecified hierarchy can define which tests carry confirmatory weight. Neither approach is reported in the registry record. The primary endpoint should be distinguished from the secondary comparisons, and the latter should be interpreted with this uncertainty in mind.

Missing-data handling is also not reported. For the primary outcome, the record states that 158 participants completed the 8-week follow-up and were included in outcome analyses. The analysis denominators are 82 in SMS Intervention and 76 in SMS Assessments. The record does not report how many participants were randomized to each group, why some did not contribute week 8 outcome data, whether missingness was related to group or outcome, or whether imputation or other methods were used.

Outcome populations differ across the reported time points. The record gives arm denominators of 110 and 108 for acceptability, and 75 and 65 for week 14 seat belt use. It does not explain the differences in denominators, give a participant flow account, or state how participants with incomplete follow-up were handled for those outcomes. No intention-to-treat population, per-protocol population, or other analysis-population definition is reported.

General explanation: If the chance of having a measured outcome is related to participants’ outcomes or group assignment, analysis restricted to observed cases can produce a different estimate from an analysis of all randomized participants. Without details on missingness and analysis populations, the extent to which this issue affects the posted results cannot be assessed. The registry record also does not report sensitivity analyses addressing missing outcomes.

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 safety listings report zero serious adverse events, zero other adverse events, and zero deaths in each group. The record gives 110 participants at risk for the serious and other adverse-event listings in SMS Intervention and 108 in SMS Assessments. No serious adverse-event terms are listed.

These figures describe the events recorded in the registry safety results for the stated groups and at-risk counts. They do not establish that no participant experienced any event outside the definitions, collection procedures, or reporting period used for the registry results. The record does not provide detailed safety-monitoring methods, the event collection period, or further definitions of serious and other adverse events.

General explanation: When no events are observed or recorded, the data still have limited ability to rule out uncommon events. A zero count is not proof that an event is impossible, and it does not compare risks precisely without considering the amount and duration of observation. No further inference about safety can be made from these counts alone.

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

The most direct reading is that the two randomized SMS groups had different observed proportions of participants reporting always using a seat belt over the past 2 weeks at week 8. The posted comparison is for participants included in the follow-up outcome analysis, and the risk-difference interval is entirely below zero when the estimate is expressed as SMS Assessments compared with SMS Intervention. This describes the result for the recorded outcome and analysis population.

It does not mean that every participant in one group behaved alike, or that a group assignment explains every participant’s report. A group-level estimate summarizes an average contrast; it does not predict an individual participant’s behavior. The endpoint is self-reported, and the registry record does not report objective verification. The result also does not establish whether any difference was caused by the dialogue, feedback, goal support, self-monitoring, or another feature of the trial experience.

The primary result does not answer every question raised by the trial summary. The summary mentions seat belt use, distracted driving, and drink driving, but the reported primary endpoint is seat belt use. The posted record does not provide corresponding primary results for distracted driving or drink driving. Nor does the week 8 outcome establish how behavior changed over time or whether the same pattern applied at week 14.

The secondary results are uncertain and should not be treated as proof that groups were the same or different. Their intervals include zero, and no multiplicity approach is reported. The registry record also does not report missing-data methods, a detailed analysis plan, or the original sample-size justification. These gaps limit assessment of how the estimates might change under alternative assumptions.

More broadly, statistical evidence about a group contrast is not equivalent to a judgment about clinical or public-health importance. The registry record does not report a threshold for a meaningful difference in seat belt use. It is therefore possible to describe the direction, magnitude, and uncertainty of the posted comparison without assigning a value judgment to its importance or making a recommendation about behavior or treatment.

17. Why This Trial Matters Statistically

This trial is statistically informative because it compares two active messaging approaches rather than text messaging with no contact. Both groups received weekly SMS contact, while the intervention arm also received dialogue or micro-interventions with feedback and goal support. That design makes the comparison relevant to the incremental contrast between those approaches, while also meaning that the results should not be interpreted as an estimate of messaging versus no messaging.

The primary endpoint is a binary self-reported behavior measured at a clearly specified follow-up. The posted risk difference gives an absolute comparison that can be read alongside the arm counts and the confidence interval. Considering all three—the number meeting the outcome criterion, the relative group proportions, and the uncertainty interval—gives a fuller statistical interpretation than relying on a p-value alone.

The record also illustrates why follow-up and analysis populations matter. Although total enrollment is 218, the primary outcome population is described as 158 week 8 completers. Different denominators are reported for other outcomes. Without details on missing-data handling or a participant flow account, the observed comparisons cannot automatically be generalized to every enrolled participant.

Finally, the separate secondary outcomes and follow-up times raise questions about multiplicity and the strength of confirmatory claims. The registry record does not report a plan for handling multiple comparisons. Distinguishing the primary result from the secondary pattern, and describing estimates with their intervals, helps avoid treating every posted result as equally conclusive. These are broadly useful statistical considerations for clinical and behavioral trials.

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.

Several limitations specific to the record affect interpretation. First, the primary outcome is self-reported seat belt use over the past 2 weeks. The registry record does not report a method for verifying participants’ reports, so the endpoint should not be treated as a direct observation of vehicle behavior. It also applies to one stated behavior and time window, rather than all aspects of vehicle safety.

Second, the primary outcome analysis includes participants who completed the 8-week follow-up. The registry record does not describe the handling of missing outcomes, the reasons for noncompletion, or whether missingness differed by group. The posted denominator is therefore important when interpreting the primary estimate, and the result may not represent every enrolled participant.

Third, the registry record does not provide the detailed analysis plan, the method used to calculate the estimates and intervals, any adjustment variables, or sensitivity analyses. It lists no reported analyses. It also does not report a multiplicity strategy for the several outcomes and follow-up times. These omissions limit assessment of whether the reported analyses were prespecified and how robust they may be to alternative analytic choices.

Fourth, the description of three parallel SaVE trials appears in the brief summary, while this record posts results for the SMS Intervention and SMS Assessments groups. Further details about the relationship between those trials and this comparison are not reported. The masking designation is listed as triple, but the record does not identify which roles were masked or how masking was maintained.

The registry record does not report the specific eligibility criteria, the original sample-size justification, detailed intervention message content, or the outcome results for recruitment feasibility, distracted driving, and drink driving. These limitations do not invalidate the posted comparison, but they constrain the questions it can answer and the strength of broader conclusions.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Utilizing Text Messaging to Improve Vehicle Safety Among At-Risk Young Adults — NCT03833713.
• Registry record last updated 2024-08-09; status last verified 2024-03.
• Results first posted 2024-08-09.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry record describes a completed randomized, triple-masked, parallel-group comparison of weekly SMS vehicle-safety approaches among at-risk young adults identified in emergency departments. Total enrollment was 218. The primary endpoint was self-reported always using a seat belt over the past 2 weeks at week 8; 158 follow-up completers were included in the outcome analyses.

At week 8, the posted risk difference comparing SMS Assessments with SMS Intervention is -0.217, with a 95% confidence interval from -0.356 to -0.078 and an unadjusted p-value of 0.003. Secondary acceptability and week 14 seat belt use comparisons have intervals that include zero. The record reports zero serious adverse events, zero other adverse events, and zero deaths in both groups.

The registry record does not report the original sample-size justification, a detailed analysis plan, multiplicity procedures, or missing-data methods. The posted estimates should be interpreted as comparisons of the recorded outcomes in the stated analysis populations.