Influenza Vaccination Digital Interventions for People Living With Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Influenza Vaccination Digital Interventions for People Living With Diabetes (NCT03870997), a randomized na study. The primary outcome is Number of Participants With Self-reported Influenza Vaccination in People With Diabetes.

2. Clinical Question

The study’s overall objective was to assess and quantify the impact of digital interventions on vaccination rates and vaccination-related outcomes in a connected population with self-reported diabetes. The primary outcome makes the vaccination question concrete by focusing on participants who said they received an influenza vaccination during the stated timeframe. It is a question about a reported behavior, not a laboratory measurement or a clinical event.

The registry also names groups of normal controls and normal controls described as similar. Those labels do not change the primary question about people with diabetes, and the record does not explain their role in that primary comparison. Without the outcome counts, the clinical question can be identified, but the direction and size of any observed difference cannot be evaluated.

3. Trial Design

The registry describes a completed, randomized, parallel-group study of behavioral digital interventions. Its overall objective was to examine vaccination rates and related outcomes among a connected population with self-reported diabetes. Participants were to receive a campaign, with the intervention varying by study arm. The registry labels masking as single and states that participants would be blinded to study participation status; who else, if anyone, was masked is not reported in the registry record.

The registered total enrollment is 94321. The primary outcome description identifies a diabetes intervention group of 5,158 participants and a diabetes control group of 5,271 participants. The record does not explain how these outcome populations relate to total enrollment or give the flow of participants from enrollment through outcome assessment. The primary comparison is described as intervention versus control, but the arm descriptions are blank. Although the registry names a Diabetes Digital Intervention, a Generic Digital Intervention, and a No Influenza Vaccination Intervention, it does not give enough detail to reconstruct the precise assignment structure or the campaign content in each group.

The study started on 2018-09-12, had a primary completion date of 2019-04-08, and is marked completed. The registered phase is NA, which is not a clinical drug-development phase designation. The sponsor is Evidation Health. These design details describe how the study was registered; they do not substitute for outcome results.

Random allocation can, in general, reduce systematic differences between groups at the point of assignment. That protection depends on how allocation was implemented and on how participants were retained and analyzed. Those procedural details, including the allocation sequence, concealment, and analysis populations, are not reported in the registry record. The record also does not report whether the intervention was delivered as intended or whether participants used or engaged with the digital campaigns.

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: 5,158 in intervention group and 5,271 in control group

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: Overall study population

Only the first 6 of 7 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Self-reported Influenza Vaccination in People With Diabetes, measured over 6 months.

The primary endpoint is the number of participants with diabetes who self-reported influenza vaccination during a six-month timeframe. The registry describes it as a count of participants and specifies an intervention-versus-control comparison. The listed outcome populations are 5,158 in the intervention group and 5,271 in the control group. The registry does not provide the number in either group who reported vaccination.

A count gives the number of participants meeting the outcome definition, but by itself it does not describe the frequency of the outcome within each group. For a group comparison, interpretation ordinarily depends on the outcome counts and the relevant group sizes, along with an estimate of uncertainty. None of those outcome-specific results is reported in the registry record. No risk difference, relative measure, confidence interval, or p-value for this endpoint is reported.

Self-reported vaccination is relevant to the study’s stated aim because it captures whether participants say they were vaccinated. It is distinct from vaccination verified through medical records or another external source. The registry does not state that vaccination reports were validated, nor does it specify the exact question, method of collection, or handling of uncertain responses. The endpoint therefore represents reported vaccination as defined in the record, and the available information does not establish how closely it corresponds to independently confirmed vaccination.

General statistical context: binary outcomes are often presented both as counts and as proportions, because proportions account for the number of participants assessed in each group. The count endpoint is the registered measure, but without the observed counts and a clear account of outcome assessment, the comparison cannot be quantified from this record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies a binary primary outcome recorded as a count of participants with self-reported influenza vaccination. It also identifies a randomized parallel design and a comparison of intervention with control among people with diabetes. These labels establish the broad statistical setting, but the registry does not report the actual outcome analysis. The concepts below explain how such information is generally interpreted; they do not describe an analysis confirmed to have been used in this trial.

What does a count endpoint represent?

For a binary outcome, each participant is classified according to whether the specified event occurred or was reported. A count is the number classified as having the event. A count alone is not a measure of the chance of the event unless it is considered alongside the number of participants assessed in the group. In this trial, the registry gives the sizes of the primary intervention and control populations, but does not give the vaccination counts. Therefore, the registered outcome cannot be converted into a group frequency or a comparison using the record.

The endpoint is based on self-report. In general, that can be a practical way to collect behavioral information, but its interpretation depends on how the question is worded, when and how the report is collected, and whether reports are checked against other sources. The registry does not report those details. It also does not state how a participant with no response or an unclear response was classified.

What does randomization contribute?

In general, random assignment is intended to make comparison groups similar on average at the start of a study, including with respect to factors that are measured and factors that are not measured. This supports a causal interpretation when allocation is implemented appropriately, outcome assessment is sufficiently complete, and the analysis respects the assigned groups and study design. Randomization does not ensure that every realized group is identical, nor does it protect against bias from differential loss to follow-up, inaccurate measurement, or departures from the assigned intervention.

The registry labels the study randomized and parallel, but does not report the sequence-generation procedure, concealment method, allocation ratio, or group-level baseline characteristics. It therefore documents the design category without enough operational detail to evaluate those aspects. The arm descriptions are blank, so the precise content of each condition cannot be reconstructed from the registered descriptions alone.

What would an effect estimate and confidence interval add?

General statistical context: a between-group effect estimate expresses the size and direction of a contrast under a chosen scale. For a binary endpoint, possible scales include an absolute difference in outcome frequency or a relative comparison. These measures answer different questions and can be affected by the frequency of the outcome in the control group. The registry does not report an effect estimate on any scale, and none can be obtained without outcome data.

A confidence interval communicates the uncertainty around an estimate under the analysis model. A narrow interval indicates greater precision than a wide interval, while an interval spanning values that would matter in different directions may leave the interpretation uncertain. The interval does not guarantee that the true effect lies within its bounds, and it does not correct bias in measurement, missing data, or study conduct. No confidence interval is reported for this endpoint.

What would a significance test mean?

In general, a p-value describes the compatibility of observed data with a specified null hypothesis under a statistical model. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of an effect. A p-value should be interpreted with the effect estimate, its uncertainty, and the analysis plan. The registry has no analysis entry and reports no p-value for the primary outcome, so there is no trial-specific significance test to interpret.

The registry’s sample-size assumptions refer to a planning illustration using a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect specified as a fraction of the observed effect. Those assumptions describe the illustration, not necessarily the trial’s design calculation or final analysis. No calculated planning sample sizes are available in the record. The illustration is not observed power, and it does not establish that the trial had a particular chance of detecting an effect.

Why do missing outcome data matter?

General statistical context: if outcome availability differs between groups, the participants with observed outcomes may no longer represent the groups originally assigned. The consequences depend on why observations are missing and how missingness relates to vaccination status and assignment. Analysts may use different approaches, such as complete-case analyses or methods that model or impute missing outcomes, but each approach relies on assumptions. The registry does not report outcome completeness, reasons for missingness, or a method for handling missing data.

Likewise, the record does not specify whether the primary analysis was based on all randomized participants, participants who completed follow-up, or another population. These distinctions can affect the interpretation of a randomized comparison. Without the analysis population and outcome accounting, the reported population sizes alone cannot show how many participants contributed to the primary endpoint.

Finally, the registry names multiple intervention and control labels, but provides no arm descriptions and no analysis details. The methods used to distinguish or combine groups are not reported. This limits what can be inferred about the estimand, meaning the precise treatment contrast the analysis was intended to estimate. The registered primary comparison is clear at a broad level, but its operational and analytical details are not.

10. Multiplicity, Missing Data and Analysis Populations

The registry identifies one primary outcome measure: the number of participants with diabetes who self-reported influenza vaccination within six months. It lists zero analysis entries. No statistical analysis plan, protocol-level multiplicity strategy, or adjustment for testing multiple hypotheses is reported in the registry record.

Multiplicity is a general concern when a study examines more than one outcome, time point, population, or treatment contrast. The chance of a false-positive finding can increase when many hypotheses are tested without an appropriate plan. The number of registered outcome measures alone does not establish how many analyses were conducted or how many comparisons were considered. The record lists one outcome measure, but does not provide the analysis details needed to assess multiplicity in the completed study.

Missing-data handling is not reported. The registry does not state how many participants provided a vaccination response, how nonresponse was handled, whether participants were followed for the full timeframe, or whether any imputation or sensitivity analysis was used. The listed intervention and control population sizes do not reveal outcome completeness.

Analysis populations are also not described. The record does not say whether the primary comparison followed randomized assignment for all participants, was restricted to those with available responses, or used another defined group. It does not report exclusions after allocation or how participants with uncertain vaccination status were treated. These omissions limit assessment of potential bias and reproducibility. Since no endpoint counts or analysis estimates are reported, the primary comparison cannot be reconstructed from the registry entry.

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

The record establishes that a completed randomized study was registered to assess digital interventions intended to increase vaccination-related outcomes in a connected population with self-reported diabetes. It identifies self-reported influenza vaccination at six months as the primary endpoint and gives the population sizes associated with the intervention-versus-control comparison. Those details describe the question the study set out to address.

The record does not report the number of participants who self-reported vaccination in either group, an effect estimate, or uncertainty around a comparison. It therefore does not show whether the intervention group had a higher, lower, or similar reported vaccination count than the control group. Absence of these results should not be interpreted as evidence that there was no difference, and it should not be interpreted as evidence that a difference was present.

Even if an estimated difference were available, a result based on self-reported vaccination would represent reported vaccination as collected under the study’s procedures. It would not automatically establish that vaccination was verified, explain why participants did or did not report vaccination, or show that the result applies beyond the studied population. The registry does not describe verification or the campaign content in enough detail to support those additional claims.

General statistical context: an estimate is most informative when considered with its uncertainty, the outcome definition, the analysis population, and the methods used to handle incomplete data and multiple comparisons. A p-value alone would not establish importance, and a statistically detectable difference would not by itself resolve limitations in measurement or generalizability. In this case, the registry contains no primary analysis estimate or p-value to assess.

The appropriate interpretation is limited to the registered design and question. The posted registry record does not contain the results needed to conclude what the trial observed about self-reported influenza vaccination. It also does not support a clinical recommendation or a conclusion about whether a digital intervention should be used.

12. Why This Trial Matters Statistically

This study is statistically notable because it links a randomized design to a behavioral outcome collected by self-report. That combination raises useful questions about how random assignment, intervention exposure, outcome measurement, and follow-up should be described when evaluating digital campaigns. The registry identifies the intended comparison and endpoint, making clear what outcome the trial was registered to assess.

The total registered enrollment is 94321, while the primary outcome comparison is described for 5,158 intervention participants and 5,271 control participants. These figures identify different scopes within the record, but the participant flow connecting them is not reported. Transparent accounting of enrollment, assignment, follow-up, outcome availability, and analysis populations is important because readers need to know which participants contribute to the estimated comparison.

The endpoint also illustrates why outcome definition matters. A participant’s self-report may be relevant to a campaign’s goal, but it is not interchangeable with independently verified vaccination. The registry does not state whether reports were verified or how incomplete responses were managed. Those details bear on both measurement quality and the possible influence of missing data.

Most importantly, a completed trial registration is not the same as a posted outcome analysis. The registry names one primary outcome but contains no analysis entries and no outcome counts, effect estimate, confidence interval, or p-value. This makes the record useful for understanding the intended question and the limits of what can be inferred, while preventing a statistical evaluation of the trial’s primary result.

For statistical interpretation, the distinction between a defined research question and a reported result is fundamental. Randomization describes an approach to group assignment, not a finding. Enrollment describes the study’s scale, not the precision of an unavailable endpoint estimate. Without outcome data and analysis details, neither the magnitude nor the uncertainty of the primary comparison can be judged.

13. 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 main trial-specific limitation of the registry record is that the primary outcome results are absent. The endpoint is described, and the comparison populations are identified, but the number of participants reporting vaccination in either group is not reported. No effect estimate, confidence interval, or p-value is available, so the direction, magnitude, and precision of the primary comparison cannot be assessed.

The outcome is self-reported. The record does not provide the question wording, mode of collection, validation procedure, or criteria for classifying uncertain answers. It also does not report the number of participants with an available outcome or how missing responses were handled. These omissions make it difficult to evaluate the completeness and measurement properties of the endpoint.

Intervention and comparator details are limited. The registry names a Diabetes Digital Intervention, a Generic Digital Intervention, and a No Influenza Vaccination Intervention, but leaves the arm descriptions blank. It says intervention content varied by arm, but does not specify the campaigns or explain fully how the named groups correspond to the primary intervention and control comparison. This limits understanding of the exact contrast under study.

The relationship between the total enrollment of 94321 and the primary comparison populations is not explained. The record does not give participant flow, allocation counts for all study groups, or reasons why the primary population sizes differ from total enrollment. The role of the additional normal-control groups in the broader study is also not described in the primary outcome entry.

Finally, the registry gives no analysis entries, statistical plan, multiplicity approach, or analysis-population definition. It does not describe implementation fidelity, participant engagement, or the extent of masking beyond its single-masking label and statement about participants being blinded to study participation status. These limitations concern what can be understood from the registry record; they do not establish that the underlying study lacked these procedures or information.

14. Related Tutorials

15. Related Statistical Calculators

16. Sources

• ClinicalTrials.gov: Influenza Vaccination Digital Interventions for People Living With Diabetes — NCT03870997.
• Registry record last updated 2020-06-09; status last verified 2020-06.
• Results first posted 2020-06-04.
• 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.

17. Record Summary

The registry describes a completed randomized, parallel-group behavioral study sponsored by Evidation Health. Its overall aim was to assess digital interventions intended to increase vaccination rates and vaccination-related outcomes in a connected population with self-reported diabetes. Participants were to receive campaigns that varied by study arm, and the record states that participants were blinded to study participation status.

The registered primary endpoint is the number of participants with diabetes who self-reported influenza vaccination during six months, comparing intervention and control groups. The listed primary populations are 5,158 intervention participants and 5,271 control participants. Total enrollment is 94321. The study started on 2018-09-12, reached primary completion on 2019-04-08, and is marked completed.

The registry names digital intervention conditions but leaves arm descriptions blank. It lists one outcome measure and no analysis entries. Outcome counts, the primary statistical comparison, and details of missing-data handling and analysis populations are not reported in the registry record. Consequently, the registered question and design can be described, but the trial’s primary result cannot be interpreted from this record.