A Pilot Study Comparing the Effectiveness of Campus Intervention to Increase HPV Vaccine Rate Among College Aged Men: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Pilot Study Comparing the Effectiveness of Campus Intervention to Increase HPV Vaccine Rate Among College Aged Men (NCT02508701), a non-randomized na study. The primary outcome is Number of Participants With 1st Uptake Shots.

2. Clinical Question

The study asks whether the message students receive and the location where HPV vaccination is available are associated with uptake of the vaccine series among college-aged men. Its registry description contrasts an altruistic and personal message with a direct recommendation against a generic message, and on-site access inside a dorm against off-site access at the student health center. The stated hypotheses concern uptake at Time 1 and at Times 2 and 3.

3. Trial Design

The registry record describes a pilot study at Purdue University, with enrollment of 24 and status listed as terminated. The recorded start was 2015-08 and primary completion was 2016-05. The phase is listed as NA. The record does not report why the study was terminated or provide further detail about its conduct.

The official title calls the study a 2 X 2 repeated design, and the registry classifies its model as factorial. The crossed factors are message type and vaccine access location. The four conditions combine an altruistic, personal message with a direct recommendation or a generic message, and on-site access inside the dorm or off-site access at the student health center. The record lists one behavioral intervention, named “Message X Onsite/Offsite Vaccination.”

Allocation is listed as non-randomized, and masking as none. These features matter when comparing uptake across conditions: the groups may differ in ways other than the message and access offered. The record does not describe how participants were assigned, whether condition assignment was linked to residence or another characteristic, or whether any adjustment was planned to address group differences.

The primary outcome is the number of participants with first uptake shots, with a timeframe of up to 12 months. Secondary outcomes are the number of participants with second uptake shots and the number with third uptake shots. Although the title and objectives describe assessments at Time 1 and Times 2 and 3, the registry record does not report the specific assessment schedule, the operational definition of uptake at each time, or numerical outcome findings.

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: Frequency

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 Number of Participants With 1st Uptake Shots, measured over Up to 12 months.

The primary endpoint is the number of participants with first uptake shots, expressed as a participant count. The registry classifies it as a frequency outcome and gives its timeframe as up to 12 months. It is a measure of whether participants began vaccination, rather than a measure of the message they received, their intentions, or a clinical outcome of HPV infection.

Counting participants with an event is a binary-outcome approach at the individual level: each participant either meets the stated event definition or does not. Group counts can describe uptake, while comparisons of those counts can address whether uptake differs across study conditions. Such comparisons need clearly defined denominators and an analysis suited to the design. A count alone does not establish the proportion of participants who experienced the event unless its denominator is also known and the rate is reported.

The registry record lists secondary outcomes for second and third uptake shots, which address continuation beyond the first shot. The record does not provide numerical results for the primary or secondary outcomes, nor does it define how partial series, timing, or missing vaccination information were handled. Consequently, the endpoint description identifies what was intended to be counted, but the posted record does not allow readers to assess the observed uptake pattern or its precision.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

Several features of the design are important when interpreting results from a campus intervention study. The explanations below describe general statistical principles; they do not imply that a particular analysis was performed in this study. The registry record lists zero analyses and does not report a statistical analysis plan.

What does a factorial design describe?

In general, a factorial design considers combinations of intervention components. In this study, the registry’s 2 X 2 repeated-design description and factorial classification correspond to the message dimension and the access-location dimension. The conditions combine an altruistic, personal message with a direct recommendation or a generic message, and on-site access inside the dorm or off-site access at the student health center.

A factorial analysis can examine contrasts for each component and, when planned and supported by the data, whether the association with one component differs according to the level of the other component. Such an interaction question is different from comparing each condition separately. The registry record does not report whether component effects, an interaction, or only condition-specific comparisons were planned or analyzed.

Why does non-randomized allocation matter?

Random assignment is one way to make comparison groups similar, on average, with respect to both measured and unmeasured characteristics. Here, allocation is listed as non-randomized. General statistical adjustment can address measured differences when the relevant information is available and an appropriate model is specified, but it cannot guarantee removal of unmeasured confounding. The registry record does not report an adjustment strategy or the participant characteristics needed to assess comparability.

Masking is listed as none. In general, an unmasked behavioral intervention may affect participant awareness, reporting, or how outcome information is collected. Whether such pathways mattered in this study cannot be assessed from the registry record; measurement procedures are not reported.

How should participant counts be understood?

The primary outcome is a count of participants with first uptake shots. For a binary event, a count needs a clear denominator to convey how frequently the event occurred. A proportion or risk can aid comparisons across groups of different sizes, while an effect estimate and confidence interval can describe both the direction and precision of a contrast. The registry record provides no primary event counts, effect estimates, or confidence intervals.

For a binary outcome, statistical methods may compare event probabilities or model event counts relative to group size. The choice depends on the planned estimand, data structure, and adequacy of model assumptions. The registry record does not identify a model, test, estimand, or method for handling the four intervention conditions. It is therefore not possible to attribute a specific statistical method to the posted results.

What does a confidence interval contribute?

In general, a confidence interval gives a range of effect values compatible with the data under the assumptions of the analysis. A narrow interval indicates greater precision than a wide interval, but it does not resolve bias in a non-randomized comparison. An interval that includes no difference does not prove equivalence; it may reflect uncertainty. No confidence interval for the uptake outcome is reported in the registry record.

How should planning calculations be read?

The stated sample-size assumptions describe planning illustrations based on the observed effect, with a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The assumed effect is a stated fraction of the observed effect. For non-time-to-event calculations, the illustrations are expressed as participants per arm for 80% or 90% power; time-to-event calculations are described as total event counts. These are planning illustrations, not observed power and not evidence that the original trial was designed around those assumptions. The registry record does not report numerical sample-size illustration results or a sample-size justification for the trial.

In general, a planning calculation depends on assumptions about the target effect, outcome variability or event frequency, significance threshold, allocation, and analysis. A calculation based on an observed effect can be especially unstable when that effect comes from a small pilot study. It should be interpreted as a scenario for planning, not as a definitive estimate of the effect likely in a future study. The registry record does not report enough outcome information to independently assess the effect used for these illustrations.

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("Altruistic Inside-dorm", "Generic Inside-dorm", "Generic Outside-dorm", "Altruistic Outside-dorm")
n      <- c(9, 6, 5, 4)
events <- c(9, 6, 5, 4)
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  Altruistic Inside-dorm  9  9  100.0  66.4  100.0  70.1  100.0  69.2  99.7
ARM  Generic Inside-dorm  6  6  100.0  54.1  100.0  61.0  100.0  59.0  99.6
ARM  Generic Outside-dorm  5  5  100.0  47.8  100.0  56.6  100.0  54.1  99.6
ARM  Altruistic Outside-dorm  4  4  100.0  39.8  100.0  51.0  100.0  47.8  99.5

11. Multiplicity, Missing Data and Analysis Populations

The study description includes a primary first-shot outcome, secondary second- and third-shot outcomes, four intervention conditions, and stated objectives involving Time 1 and Times 2 and 3. Considering several outcomes, time points, or contrasts raises a general multiplicity issue: the more statistical questions examined, the greater the chance of obtaining a seemingly notable result by chance if all are interpreted as confirmatory. A prespecified testing hierarchy or multiplicity adjustment can help define how such results should be interpreted.

The registry record does not report a multiplicity strategy, a hierarchy among the contrasts, or which comparisons were designated confirmatory. It also lists zero analyses. Therefore, readers cannot determine whether the planned objectives were tested, whether any adjustment was used, or how any potential findings would have been prioritized. The hypotheses in the study description should not be read as evidence that those hypotheses were supported.

Missing-data handling is also not reported in the registry record. The record does not say how participants without known vaccination status were treated, whether outcomes were collected for everyone, or whether an analysis used all enrolled participants or a defined subset. These choices can affect both the estimated uptake and its uncertainty, especially if missingness differs by study condition.

Analysis populations are not reported in the registry record. There is no description of whether analyses were based on assignment, intervention received, participants with available outcome information, or another population. The registry’s non-randomized allocation makes the definition and reporting of the compared groups particularly important, but the available record does not specify those analysis details.

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 1% reporting threshold.

The registry’s adverse-event information lists, by condition, the numbers at risk for serious and other adverse events and the numbers affected. For Altruistic Inside-dorm, the at-risk counts are 9 for serious and 9 for other adverse events; affected counts are 0 for each. For Generic Inside-dorm, the at-risk counts are 6 and 6, with 0 affected for each. For Generic Outside-dorm, the at-risk counts are 5 and 5, with 0 affected for each. For Altruistic Outside-dorm, the at-risk counts are 4 and 4, with 0 affected for each. Deaths are recorded as 0 in each condition.

These figures mean that the registry record reports no serious or other adverse events in the listed groups during the recorded period. They do not establish that no adverse events occurred outside the registry’s reporting or ascertainment procedures. The record does not report how adverse events were collected, the observation window for safety, or the criteria used to classify events. It also does not provide event descriptions. The figures should therefore be read as registry-reported counts, not as proof of absence of risk or a comparison showing one condition to be safer.

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

The record describes a pilot investigation of whether message content and access location could influence HPV vaccine uptake among college-aged men. The study’s four conditions combine two types of message with on-site or off-site access. Its primary endpoint is the number of participants with first uptake shots, and the registry also identifies second- and third-shot outcomes.

What the record does not establish is whether uptake differed across conditions. Numerical results for the primary outcome are not reported in the registry record, and the record lists zero analyses. No effect estimate, confidence interval, or test result is reported. The hypotheses in the study description state what the investigators aimed to examine; they do not show that any message or access arrangement increased uptake.

Even if a comparison of uptake were reported, the non-randomized allocation would limit causal interpretation. Participants in different conditions may have differed for reasons beyond the intervention, and the record does not describe adjustment for such differences. With masking listed as none, outcome measurement and participant awareness would also need consideration, although the registry record does not provide measurement details.

The listed enrollment and group sizes describe how many participants were recorded in each condition, not how many received a vaccine shot. The adverse-event entries report zero events in the listed groups, but incomplete information about event collection and follow-up prevents interpreting those entries as proof that no harms occurred. The registry record also does not explain the terminated status or report the reason for termination.

Accordingly, the appropriate reading is descriptive: the study posed a relevant comparison and documented its intended outcomes, while the posted record does not provide enough outcome or analysis information to judge intervention effects or their precision. The record should not be treated as evidence for or against any particular message or access strategy.

14. Why This Trial Matters Statistically

This study is statistically informative as an example of a behavioral intervention question with more than one component. Message content and access location are distinct features, and their combination can motivate different scientific questions: whether either component is associated with uptake, whether a particular combination differs from the others, and whether the effect of one component depends on the other. These questions need to be distinguished before interpreting comparisons.

The non-randomized design also illustrates why design features shape the strength of conclusions. Statistical adjustment can be useful for measured differences, but it does not provide the same protection against confounding as random allocation. A clear account of assignment, baseline characteristics, outcome ascertainment, and analysis is important for evaluating the credibility of condition comparisons. Those details are not reported in the registry record.

Uptake at the first shot and uptake at later shots represent related but different outcomes. A count for the initial shot does not describe completion of the series. Reporting the outcome definition, assessment timing, denominators, and uncertainty for each outcome would help readers understand both initiation and continuation. The registry record identifies these outcomes but does not report numerical findings.

The study is designated a pilot and has a recorded enrollment of 24. Pilot data can be useful for refining intervention delivery and informing future study planning, but a planning illustration based on an observed effect is not a substitute for a prespecified design rationale or precise evidence about an effect. Since the registry record does not report the primary outcome results or a sample-size justification, the contribution that can be assessed is mainly the study question and design structure, rather than the size or reliability of any intervention effect.

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.

Several trial-specific limitations affect interpretation. First, the registry record lists allocation as non-randomized. This leaves open the possibility that participants in the four conditions differed in factors related to vaccine uptake. The record does not report the assignment procedure, baseline characteristics, or an adjustment strategy, so the extent of this concern cannot be assessed.

Second, masking is listed as none. The record does not describe how uptake was verified or whether outcome assessment was independent of intervention delivery. It also does not report how the message was delivered in practice, participant exposure, or adherence to the intervention conditions.

Third, the primary and secondary outcome results are not reported in the registry record, which lists zero analyses. Event counts, denominators for uptake, effect estimates, uncertainty intervals, and analysis populations are not given. The record also does not state how missing vaccination information was handled or whether outcomes were available for all enrolled participants.

Fourth, the registry status is terminated, but the reason and timing of termination are not reported in the registry record. Without that context, readers cannot assess whether termination affected recruitment, follow-up, or outcome reporting. The record does not report a formal sample-size justification, a prespecified statistical analysis plan, or a strategy for multiplicity across conditions and time points.

Finally, the group counts listed in the adverse-event information are modest and uneven, and no uptake counts are available for comparison. The record does not report adverse-event ascertainment procedures or detailed follow-up. These limitations mean that neither intervention differences nor safety comparisons can be evaluated from the posted registry information.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: A Pilot Study Comparing the Effectiveness of Campus Intervention to Increase HPV Vaccine Rate Among College Aged Men — NCT02508701.
• Registry record last updated 2018-09-20; status last verified 2018-08.
• Results first posted 2018-09-20.
• 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

The registry record for NCT02508701 describes a Purdue University pilot study of campus interventions intended to encourage HPV vaccination among college-aged men. The official title describes a 2 X 2 repeated design; the registry classifies the model as factorial, allocation as non-randomized, and masking as none. Enrollment is listed as 24, phase as NA, and status as terminated. The recorded start was 2015-08, with primary completion in 2016-05.

The intervention conditions combine an altruistic, personal message with a direct recommendation or a generic message, and on-site access inside the dorm or off-site access at the student health center. The primary outcome is the number of participants with first uptake shots, with a timeframe of up to 12 months. Second- and third-shot uptake are listed as secondary outcomes.

Numerical uptake results and analysis findings are not reported in the registry record, which lists zero analyses. The reason for termination, statistical analysis plan, missing-data procedures, and analysis populations are also not reported. Registry-reported adverse-event counts are zero in each listed condition.