Feasibility of Using sipIT Tools to Increase Compliance With Fluid Consumption Guidelines in Urolithiasis-Prone Subjects: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Feasibility of Using sipIT Tools to Increase Compliance With Fluid Consumption Guidelines in Urolithiasis-Prone Subjects (NCT03787615), a na na study. The primary outcome is Adherence to Intervention Assessed by Study Completion.

2. Clinical Question

3. Trial Design

This was a completed, single-group device study sponsored by Penn State University. The registry lists enrollment of 31 participants, phase as not applicable, allocation as not applicable, and masking as none. The intervention was the sipIT tools, described as wrist-worn sensors using a custom algorithm to detect drinking events, an H2OPal connected water bottle, and fluid-consumption monitoring mobile applications. The study was intended for people with a history of urolithiasis.

The primary outcome timeframe was three months. Its stated measure was the number of participants who continued using the app, connected water bottle, and smartwatch at the three-month follow-up. The study description also identifies acceptability and notification delivery as aims. It hypothesizes that notifications would lead to increased compliance with fluid-consumption guidelines and that notification frequency would diminish during the study. The registry record does not report whether these hypotheses were tested or supported.

The registry lists the study as completed, with a start date of 2018-11-19 and primary completion date of 2019-12-01. Completion status describes the study’s registry status; it does not establish that every enrolled participant completed follow-up or that outcome data were available for every participant. The number assessed at follow-up and the number included in any outcome analysis are not reported in the registry record.

Because there was no listed control group or randomized allocation, the design is suited to describing use and feasibility within the enrolled group, not to isolating an intervention effect from changes over time or other influences. The protocol details, setting, recruitment approach, and statistical plan are not reported in the registry record.

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:

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 Adherence to Intervention Assessed by Study Completion, measured over 3 months.

The primary endpoint is titled Adherence to Intervention Assessed by Study Completion. It counts participants who continued using all three components—the app, connected water bottle, and smartwatch—at the three-month follow-up. In this context, the endpoint operationalizes continued use as a concrete indicator of whether participants remained engaged with the tools over the stated period.

A continuation measure is relevant to feasibility because a tool that participants do not continue using may be difficult to evaluate or implement. It is distinct from a measure of fluid intake itself: the endpoint concerns use of the intervention, not whether participants reached physician-recommended fluid-consumption guidelines. It is also distinct from acceptability, which may involve participants’ reported experience or perceived burden. The registry identifies a Difficulty of Use Subscale of the User Burden Scale as a secondary outcome, but does not report its result.

The endpoint is a participant count, and the registry record describes its unit as participants. It does not provide the observed number continuing use, the number with available follow-up information, or an estimate of uncertainty. The registry’s completed status and enrollment count cannot substitute for those endpoint results. Without them, the degree of continued use cannot be assessed from the posted results.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

Statistical methods help distinguish what a study set out to measure from what its data can establish. In this study, the design is single-group and the primary endpoint is a participant count: continued use of the app, connected bottle, and smartwatch at three-month follow-up. The registry record lists zero analyses and does not report an observed endpoint count, an uncertainty estimate, or a detailed analysis plan. The explanations below are general; they should not be read as methods confirmed to have been used in this study.

What a participant-count endpoint represents

For a binary endpoint, each participant is classified according to whether the defined event occurred. Here, the event is continued use of all specified tools at follow-up. A count describes how many participants met that definition. To interpret a count fully, readers also need to know how many participants had outcome information and how missing outcomes were handled. Enrollment of 31 does not establish that all 31 contributed an observed endpoint.

A binary outcome can also be expressed as a proportion, but no such result is reported in the registry record, and no new estimate can be recovered from the enrollment count alone. The endpoint definition matters: continued use of all components is a stricter criterion than use of only one component, and it does not directly measure fluid intake or guideline compliance.

Uncertainty and confidence intervals

General explanation: a confidence interval describes the uncertainty around an estimated quantity under a statistical procedure and its assumptions. For a participant count or a proportion, uncertainty is relevant because results from a study group do not necessarily pin down the value that would be seen in a broader population. An interval cannot be interpreted without the underlying estimate, the analyzed participants, and the method used to construct it. No confidence interval or interval method is reported in the registry record for the primary endpoint.

A small or imprecise estimate should not be treated as proof that an outcome is absent, just as a precise estimate would not by itself establish that the intervention caused the outcome. Precision and causal interpretation are separate questions. In this study, the lack of a reported endpoint result prevents assessment of precision, and the single-group design limits controlled causal comparisons.

What a comparison would require

General explanation: comparative analyses estimate how outcomes differ between groups or conditions. Random allocation can help make groups comparable at the outset, though it does not eliminate every source of uncertainty. This registry record lists a single group and allocation as not applicable; it does not identify a randomized control group. Accordingly, no between-group treatment contrast is described. A before-and-after contrast would require reported measurements at both times and a defined analysis, neither of which is reported in the registry record.

The study’s stated hypothesis about increased compliance with fluid-consumption guidelines is not an observed statistical result. Testing that hypothesis would require a clearly defined intake or compliance measure, its measurement schedule, and an analysis comparing relevant observations. Those details and results are not reported in the registry record.

Planning assumptions are not trial results

General explanation: sample-size planning uses assumptions about the outcome, effect to detect, variability, significance threshold, and desired power. The planning illustration associated with this record assumes a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. It describes a hypothetical two-arm calculation based on a stated share of an observed effect; it is not the design of this single-group study. The registry record does not report the trial’s own sample-size justification, and a planning illustration cannot be interpreted as observed power or as evidence of an effect.

General explanation: power is a design property defined under specified assumptions; it is not a post hoc measure of whether a finding is true. Sample-size illustrations can show how planning requirements change under alternative assumed effects, but they do not replace an analysis of observed data. The registry record does not report an outcome estimate or inferential analysis to which such calculations could be tied.

Why over-dispersion can matter

General explanation: over-dispersion occurs when variation in observed data is greater than a statistical model assumes. If a model underestimates variability, its uncertainty estimates may be too narrow and its inferential results overly optimistic. Whether over-dispersion is relevant depends on the outcome and model. The registry record does not report a model, repeated count data, or an analysis that would allow this issue to be assessed for the sipIT study.

In general, repeated fluid-intake observations or notification counts may have different statistical structures from a single participant-level adherence outcome. Methods appropriate for one outcome should not automatically be applied to another. The registry record does not describe such outcome-specific methods or results, so no model-based interpretation can be attributed to this study.

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("The sipIT Tools")
n      <- c(31)
events <- c(27)
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  The sipIT Tools  31  27  87.1  70.2  96.4  71.1  94.9  71.0  94.7

11. Multiplicity, Missing Data and Analysis Populations

The registry lists two outcome measures: the primary adherence endpoint and the secondary Difficulty of Use Subscale of the User Burden Scale. It reports zero analyses. No multiplicity procedure or hierarchy for interpreting multiple outcomes is reported in the registry record. General explanation: when several outcomes or statistical tests are examined, the chance of at least one apparently unusual result can increase; prespecified priorities and appropriate methods help readers understand how results were selected and interpreted. Without reported analyses, there are no posted p-values or outcome estimates to assess for multiplicity.

The registry record does not describe missing-data handling, the analysis population, or the number of participants with data at the three-month follow-up. A missing outcome is not equivalent to failure to continue using the tools, and it is not equivalent to success. The distinction depends on the study’s definitions and analysis rules, which are not reported in the registry record. Enrollment of 31 and completed status do not reveal how many participants contributed to each outcome.

It is also not reported whether the primary endpoint was analyzed among all enrolled participants, only those with follow-up information, or another defined group. No imputation method, sensitivity analysis, or approach to incomplete records is described. These omissions limit interpretation of any result that might otherwise be associated with the study; in the posted results, the endpoint result itself is not reported.

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 registry’s adverse-event fields list 31 participants at risk for serious adverse events and 0 serious events. It also lists 31 at risk and 0 other adverse events, alongside 0 deaths. No serious-event terms are listed. These are the event counts recorded for the sipIT Tools group.

Such counts describe what is recorded in the registry; they do not show that the possibility of an event was ruled out. Interpretation depends on how events were defined, how they were collected, the period of observation, and whether participants had complete safety follow-up. Those details are not reported in the registry record. The listed denominator of 31 is not necessarily evidence that every participant had the same duration or completeness of follow-up.

Zero recorded events should therefore be read as a report of zero events in the registry fields, not as proof of no risk. The record does not provide event narratives, severity breakdowns beyond the serious-event field, or a detailed safety analysis. These counts also do not establish anything about the primary adherence endpoint, which is not reported.

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

The record establishes that a single-group study of sipIT tools enrolled 31 participants and was marked completed. It defines a primary feasibility outcome: continued use of the app, connected bottle, and smartwatch at the three-month follow-up. That definition makes clear what the study intended to count, but the observed count is not reported in the registry record.

As a result, the record does not establish how often participants continued using the tools, whether they found them acceptable, or whether fluid consumption changed. It also does not report whether the hypothesized decline in notification frequency occurred. Study aims and hypotheses describe questions the research was designed to address; they are not findings.

The design also matters to interpretation. With one group and no listed randomized comparator, an outcome observed during tool use would not by itself show what would have happened without the tools. A single-group description can inform feasibility within the enrolled participants, but it cannot provide the same controlled contrast as a comparative design. No effect estimate or inferential analysis is reported in any case.

Statistical uncertainty cannot be evaluated without an observed endpoint result and a measure of precision. The number enrolled does not establish how many had complete follow-up, and the registry record does not report missing-data methods or the analysis population. The posted safety counts are limited to the listed event fields and do not establish absence of risk. The appropriate conclusion is therefore limited: the record describes the intervention and planned feasibility question, while leaving its primary and secondary outcome results unreported.

14. Why This Trial Matters Statistically

Feasibility studies ask whether an intervention can be used and evaluated in a particular setting or group. For connected devices and mobile applications, continued use is a practical outcome because a system that participants stop using may be difficult to assess in later research. Defining continued use across the app, connected bottle, and smartwatch gives the primary endpoint a specific operational meaning.

The study also illustrates why endpoint definitions and outcome results must be kept distinct. The registry identifies a three-month adherence measure, but does not report its observed count. Without that result, readers cannot judge the level of continued use or its statistical precision. The distinction is especially important when a record includes a completed status: completion of a study in registry terms is not the same as documented completion by every participant or a reported endpoint finding.

Statistically, the single-group design supports description rather than a controlled estimate of intervention effect. This matters for clinical researchers interpreting behavior-change technologies: a change observed while participants are using a tool cannot automatically be attributed to the tool without an appropriate comparison and analysis. The record’s hypotheses about fluid guideline compliance and notification frequency should accordingly remain hypotheses in the absence of posted results.

The record is also a useful reminder that registration details alone do not substitute for a statistical report. Outcome counts, denominators, uncertainty, missing-data handling, and analysis methods all contribute to an interpretable result. Those elements are not reported for the primary endpoint. The listed adverse-event counts can be described, but they do not answer the feasibility question or establish safety beyond the information recorded.

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 important trial-specific limitation of the posted record is that it defines the primary endpoint but does not report its observed result. The secondary outcome, the Difficulty of Use Subscale of the User Burden Scale, also has no reported result. Although the record lists two outcome measures, it lists zero analyses. This prevents assessment of the study’s stated feasibility and acceptability aims.

The study is single-group, with no listed randomized comparator. Any outcome observed in that group would therefore lack a direct concurrent control contrast in this design. The registry record does not report baseline or follow-up fluid-consumption results, so the hypotheses about guideline compliance and notification frequency cannot be evaluated from the posted results.

Enrollment was 31, but the number with outcome data and the endpoint analysis denominator are not reported. The record does not describe missing-data methods, participant flow, or the analysis population. It also does not report the statistical plan, sample-size justification, interim analyses, or a multiplicity approach. The available information therefore does not establish how results were intended to be analyzed or whether outcomes were fully observed.

Other details that would aid interpretation—including participant characteristics, eligibility criteria, and event-collection procedures—are not reported in the registry record. The adverse-event fields list zero events, but without further details those counts should not be generalized beyond the recorded categories. These limitations concern the information available in the registry record and do not establish what may appear in other study materials.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Feasibility of Using sipIT Tools to Increase Compliance With Fluid Consumption Guidelines in Urolithiasis-Prone Subjects — NCT03787615.
• Registry record last updated 2021-03-17; status last verified 2021-03.
• Results first posted 2021-03-17.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

19. Record Summary

The registry record describes a completed, single-group study of sipIT tools in participants with a history of urolithiasis. Penn State University is listed as sponsor, enrollment is 31, masking is none, and allocation and phase are listed as not applicable. The intervention combines wrist-worn drinking-event sensors, a connected water bottle, and mobile applications.

The primary endpoint counts participants continuing to use the app, bottle, and smartwatch at three-month follow-up. The record also lists a Difficulty of Use Subscale of the User Burden Scale as a secondary outcome. It lists two outcome measures and zero analyses; observed outcome results are not reported in the registry record.

The safety fields list 0 serious events, 0 other events, and 0 deaths. The record does not report the primary endpoint result, analysis denominator, missing-data methods, statistical plan, or sample-size justification. Its hypotheses about fluid-consumption compliance and notification frequency therefore remain unconfirmed by the posted results.