Caring for Babies During the Newborn Screening Blood Test: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Caring for Babies During the Newborn Screening Blood Test (NCT02608892), a randomized na study. The primary outcome is Pain Management Used During Newborn Screening Blood Test.

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group pilot trial of the BSweet2Babies video, registered as NCT02608892. The registry lists allocation as randomized and masking as single. It does not identify who was masked or describe the randomization sequence, allocation concealment, or the procedures used to implement masking; those details are not reported in the registry record.

The trial enrolled 100 participants. The intervention group was assigned to the video, while the control group received usual care. The registry gives an outcome count of 30 among 50 participants in the intervention group and 33 among 49 in the control group. It notes that one participant was lost to follow-up in the intervention group. Those outcome denominators therefore differ from the overall enrollment count, but the record does not provide a complete participant-flow account.

The study is identified as a pilot randomized controlled trial in its official title and summary. Its stated purpose was to inform aspects of a full-scale trial and to evaluate the video’s effect on use of pain-reduction strategies during newborn screening. The registry lists the study status as completed. The study start is recorded as 2016-05, and primary completion as 2016-08.

The registry lists the phase as NA and the sponsor as Children's Hospital of Eastern Ontario. The primary outcome was assessed within 48 hours of viewing the intervention video. The research assistant was to collect information about breastfeeding, skin-to-skin care, or sucrose from the electronic medical record. Further information about follow-up procedures, site numbers, setting, and the original sample-size justification is 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.

Before assignment: No enrolled participants were excluded from the study before assignment to groups.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: One participant was lost to follow-up in the intervention 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.

6. Primary Endpoint

The registry lists the primary outcome as Pain Management Used During Newborn Screening Blood Test, measured over Within 48 hours of viewing video intervention.

The primary endpoint counted participants whose infant received at least one of three pain-management strategies during the newborn screening blood test: breastfeeding, skin-to-skin care, or sucrose. The registry describes the outcome as use of any pain management and specifies a participant count. It was assessed within 48 hours of viewing the video intervention, with information collected from the electronic medical record.

This combined endpoint addresses the trial’s central behavioral question: whether parents used at least one of the strategies during the procedure. Combining the strategies into one outcome means the analysis does not distinguish which individual strategy was used, how often it was used, or whether more than one was used. The registry record does not report separate primary results for breastfeeding, skin-to-skin care, and sucrose.

A participant count is useful for a binary outcome because each participant can be classified according to whether any qualifying strategy was used. The comparison then concerns the proportion of participants with the outcome in each group. The endpoint reflects recorded use during the screening procedure; it does not directly measure infant pain, distress, or physiological changes. The registry record does not report a separate measurement of those outcomes as part of the primary endpoint.

7. Results Posted in the Registry

• Intervention Group: 60.0% (30/50) versus 67.3% (33/49) on control; risk difference -7.3 percentage points (95% CI -26.2 to 11.5), risk ratio 0.89 (0.66–1.20); unadjusted two-proportion z-test p = 0.447.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary: each participant either had an infant receive at least one of the listed strategies during newborn screening or did not. For a binary outcome, a group proportion describes the fraction of participants with the event. The registry reports participant counts, and the recalculation compares the group proportions using the difference between them. The risk difference is expressed as intervention minus control, so negative estimates correspond to a lower observed proportion in the intervention group.

What does the risk difference describe?

A risk difference is an absolute comparison between two proportions. It gives the size and direction of the observed gap on the probability scale. A value of zero corresponds to equal proportions. Unlike a relative measure, an absolute difference does not express one group’s result as a multiple of the other group’s result. The recalculated estimate is -0.073, with a 95% confidence interval from -0.262 to 0.115.

The registry’s reported analysis is also described as an absolute difference in proportions. Its estimate is -7.4, with a 95% confidence interval from -26.2 to 11.5. The registry record does not give the method used to obtain this estimate or a p-value for it. Because a reported analysis is part of the registry results, it should be distinguished from the simple recalculation based on the posted group counts.

How should the confidence interval be read?

A confidence interval expresses statistical uncertainty around an estimate under the assumptions of the analysis. In general, a 95% confidence interval is generated by a procedure that, over repeated use under its assumptions, would cover the underlying value in 95% of such intervals. It is not a statement that there is a 95% probability that this particular interval contains the true value. Here, the reported interval extends from a negative to a positive difference, including zero. That means the data are compatible with a range of possible comparisons, including no difference.

A wide interval indicates limited precision: the point estimate alone should not be treated as a complete description of the evidence. The interval’s breadth is relevant in this pilot because the outcome counts are 30 of 50 and 33 of 49. Confidence intervals do not correct for missing data, bias, or unreported analytic choices. Their interpretation depends on the analysis and assumptions used to calculate them.

What does the p-value add?

The unadjusted p-value from the recalculation is 0.447. In general, a p-value describes how unusual data at least as discrepant as those observed would be under a specified null model. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of a difference. It should be considered alongside the estimate and its confidence interval. The registry does not report a p-value for its own analysis.

Why can an unadjusted recalculation differ from a trial analysis?

A recalculation from group-level counts is a simple, unadjusted analysis. It does not account for any covariates, stratification, clustering, or other design features unless those are explicitly included in the calculation. The registry record does not report such features or identify the sponsor’s analysis method. Differences in analytic method, rounding, or the data used can affect results; the registry record does not establish which, if any, explains the presentation of the two estimates. The posted sponsor analysis and the recalculated result should therefore be kept distinct rather than treated as interchangeable.

Why can over-dispersion matter in general?

For count or binary data, a model may assume a particular amount of variability. Over-dispersion means the observed variability is greater than that assumption allows. When relevant, ignoring it can make standard errors too small and uncertainty appear narrower than it is. This is a general statistical issue, not a reported feature of this trial. The primary outcome is a participant-level binary outcome, and the registry record does not report an over-dispersion assessment or a model requiring one.

What does randomization contribute?

In general, random allocation aims to make comparison groups similar on average with respect to measured and unmeasured factors. It does not guarantee identical groups, especially in a pilot study, and the registry does not report baseline characteristics for evaluating group balance. The record identifies randomized allocation but does not describe the sequence-generation or concealment methods. Accordingly, the design label supports describing the study as randomized, while the fuller implementation details remain not reported in the registry record.

10. Confidence Intervals and Precision

The recalculated risk difference is -0.073, with a 95% confidence interval from -0.262 to 0.115. The interval spans zero and includes estimates in both directions. The point estimate alone therefore gives an incomplete account: the uncertainty range allows for a lower proportion in the intervention group, little or no difference, or a higher proportion. The data do not pin down the size or direction of the underlying difference with precision.

The sponsor’s reported absolute difference in proportions is -7.4, with a 95% confidence interval from -26.2 to 11.5. That interval also includes zero and extends to either side of it. The registry record does not report a p-value for this analysis, and it does not describe the calculation method. The confidence interval and point estimate should be read as an estimate with uncertainty, not as a definitive classification of the groups as different or equivalent.

In general, confidence intervals reflect sampling uncertainty under the assumptions of the method used. They do not account automatically for possible bias, incomplete outcome data, or uncertainty about how the analysis was conducted. The registry notes one intervention-group participant lost to follow-up, but does not report how missing outcome data were handled. The analysis population and any sensitivity analyses are also not reported in the registry record.

The sample-size planning illustrations are based on the observed effect and show how participant requirements change under specified assumptions. They do not make the current estimate more precise, and they do not replace the uncertainty interval around the trial result. The registry record does not report the trial’s original sample-size justification. Precision should therefore be judged from the interval around the observed comparison, while planning illustrations should be understood as prospective planning scenarios.

11. 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 planning figures give participants per arm, not total participants or total events. They illustrate the sample size that would be needed under the listed assumptions when the effect to detect is set to a stated fraction of the observed effect. For this binary outcome, the figures are participant counts per group. The registry record’s general sample-size note distinguishes these from time-to-event outcomes, for which a planning figure may instead refer to a total number of events; that is not the format used for this outcome.

The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at 100% of the observed effect, 75% of the observed effect, or 50% of the observed effect. The registry record does not report the trial’s own original sample-size assumptions or justification, so these figures should not be read as the original design target.

The 80% power column gives the participants per arm for a design with 80% power under those assumptions. The 90% power column gives the participants per arm for a design with 90% power. In general, power is the probability that a specified statistical procedure will identify an effect of the assumed size at the chosen significance level, if that effect is present and the assumptions hold. These are planning quantities, not guarantees about a future result.

The figures increase as the effect to detect becomes smaller: planning for 75% or 50% of the observed effect requires more participants than planning for 100% of it. That is a general feature of study planning, because smaller differences are harder to distinguish from sampling variation. These figures are planning illustrations based on the observed effect, not observed power.

12. 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 = 0.673; treatment proportion p₁ = 0.600; average p̄ = 0.637.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6802 = 1.3331.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6782 = 0.5708.
4. n = (1.3331 + 0.5708)² / (-0.0735)² = 671.5, rounded up to 672 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 <- 0.673469387755102                          # control proportion
p1 <- 0.6                          # 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(2608892)
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 = 672 (80% power), 899 (90% power)
 75% of observed effect: n per arm = 1,182 (80% power), 1,581 (90% power)
 50% of observed effect: n per arm = 2,628 (80% power), 3,517 (90% power)
power.prop.test: 671.5 
Simulated power at n = 672 per arm: 0.799 (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.

13. Analyses Reported by the Sponsor

The registry’s reported analysis gives an absolute difference in proportions of -7.4, with a 95% confidence interval from -26.2 to 11.5. The simple unadjusted recalculation from the posted group counts gives a risk difference of -0.073, with a 95% confidence interval from -0.262 to 0.115. The sponsor’s result is expressed on a percentage-point scale, while the recalculated result is expressed as a proportion. Both estimates have a negative point estimate, and both confidence intervals include zero.

The recalculation also gives an unadjusted p-value of 0.447. The registry does not report a p-value for the sponsor’s analysis. Its method is not specified, so the two analyses cannot be assumed to use identical procedures. The recalculation is not a replacement for the trial’s reported analysis; it is a basic comparison derived from the posted group counts.

The record does not flag a discrepancy between the reported analysis and the recalculation. Even so, the reported estimate and the recalculated estimate should be identified by their source and scale. No conclusion about why their numerical presentations differ is warranted from the registry information alone.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists four outcome measures in total and names three secondary outcomes: parents’ intentions to use or advocate for at least one strategy during future procedures, their intention to recommend the video, and their perception of whether the video duration was acceptable. The primary outcome concerns use of any listed strategy during newborn screening. The registry record does not report a multiplicity adjustment or explain how the several outcomes were considered together.

Multiplicity matters in general when several outcomes or analyses are tested, because repeated testing can increase the chance of at least one apparently unusual result. Whether an adjustment is appropriate depends on the analysis plan and the intended interpretation of the outcomes. The registry record does not report a prespecified hierarchy, adjustment method, or complete analysis plan. It lists one reported analysis, but does not establish whether other analyses were conducted.

The record notes that one participant was lost to follow-up in the intervention group. The primary outcome counts are 30 of 50 in that group and 33 of 49 in control. The registry does not describe the reason for the loss, the missing outcome value, or how missing data were handled. It also does not report whether an intention-to-treat, per-protocol, or other analysis population was used. The participant counts alone do not establish the handling of missingness.

The registry describes the study as randomized but does not report baseline comparisons, covariate adjustment, a prespecified statistical analysis plan, interim analyses, or a sample-size justification. These details are not reported in the registry record. Their absence from the record limits assessment of how closely the posted analysis follows any original plan, but it is not evidence that a particular procedure was or was not used.

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 registry reports zero serious adverse events and zero other adverse events in both groups. For serious adverse events, the record lists 51 participants at risk in the intervention group and 49 in the control group, with zero affected in each. For other adverse events, it likewise lists 51 at risk in the intervention group and 49 in control, with zero affected in each. Deaths are listed as zero in both groups, and no top serious-event terms are listed.

These are the figures recorded for the adverse-event categories; they should not be interpreted as proof that no events could occur or that the intervention has no risks. The record does not define the event categories, describe the collection or review procedures, or state the adverse-event observation period. The intervention-group at-risk count in the adverse-event record differs from the intervention-group primary-outcome denominator; the registry does not explain this accounting difference. The figures describe what was posted, with those reporting details left unspecified.

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

The primary comparison concerns whether any one of breastfeeding, skin-to-skin care, or sucrose was used during a newborn screening blood test. The recorded outcome occurred in 30 of 50 intervention participants and 33 of 49 control participants. The recalculated estimate is a negative risk difference, but its 95% confidence interval includes zero and covers values on either side. The data therefore leave substantial uncertainty about the direction and size of the difference.

This result does not establish that the video changed behavior, and it does not establish that it had no effect. A confidence interval spanning zero is not evidence that the groups are equivalent. The trial’s pilot designation and stated role in informing a full-scale study are relevant context: the registry presents a small set of group counts and an imprecise comparison, rather than a conclusive estimate.

The outcome also has a specific scope. It records use of at least one strategy during newborn screening, not the amount or quality of use, the particular strategy chosen, or a direct measure of infant pain. Although the study summary describes pain, distress, and physiological changes as concerns motivating the work, the posted primary endpoint is strategy use. The registry lists parent intention and video acceptability among secondary outcomes, but does not provide their results in the information recorded.

Interpretation is further limited by details not reported in the registry record, including the original sample-size justification, the statistical analysis method, missing-data handling, and the full analysis population. These omissions do not alter the posted counts, but they constrain how fully the analysis can be assessed. The most defensible reading is descriptive: the observed group proportions and their uncertainty are reported, while broader conclusions about pain outcomes or behavior beyond this procedure are not established by this endpoint.

17. Why This Trial Matters Statistically

This trial raises an important statistical distinction between a behavioral outcome and a clinical experience. The primary endpoint is recorded use of one or more specified strategies during a procedure. It does not directly quantify pain or distress. Keeping the endpoint’s meaning clear prevents an observed difference in strategy use from being interpreted as a direct difference in infant pain.

The pilot design also makes precision central to interpretation. The estimated risk difference is negative, but the confidence interval ranges from negative to positive values and includes zero. That interval communicates uncertainty that a point estimate or a significance test alone cannot convey. The result is not a simple yes-or-no verdict about an intervention; it is an estimate whose precision is limited in this pilot comparison.

Planning from an observed effect requires care. The registry’s sample-size illustrations show that planning around smaller fractions of an observed effect requires more participants per arm. Such illustrations can support thinking about a future study, but they depend on assumptions and do not supply the original rationale for this trial’s enrollment. The record does not report that original justification.

Finally, the registry demonstrates why a transparent distinction between reported and recalculated analyses matters. The reported estimate and the simple unadjusted recalculation are close in direction and both have intervals that include zero, while the registry does not specify the sponsor’s method or p-value. Clear reporting of the outcome definition, analysis population, missing-data handling, and statistical plan would help readers assess how the estimated difference was obtained and how it should inform future study planning.

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.

The posted primary outcome is based on a relatively limited number of participants, with 30 events in the intervention group and 33 in control. The confidence interval is broad and includes zero, so the estimate is imprecise. As a pilot trial, the study was described as intended to inform a full-scale trial, and the registry’s planning illustrations do not substitute for an original sample-size justification, which is not reported in the registry record.

One intervention-group participant was lost to follow-up. The registry does not explain the reason, specify the missing outcome, or describe the handling of missing data. The analysis population is not reported. The primary-outcome denominator is 50 in the intervention group and 49 in control, while adverse-event records list 51 at risk in the intervention group and 49 in control; the record does not reconcile these counts.

The endpoint combines breastfeeding, skin-to-skin care, and sucrose. The registry does not report separate primary results for the individual strategies or direct measurements of infant pain. The outcome is limited to use during newborn screening within 48 hours of viewing the intervention video; later use and outcomes beyond that procedure are not reported as part of the primary endpoint.

Although allocation is listed as randomized and masking as single, the sequence-generation, concealment, and masking details are not reported in the registry record. The method for the sponsor’s analysis, baseline participant characteristics, and handling of multiple outcomes are also not reported. These gaps limit assessment of the conduct and analysis, without showing that any specific problem occurred.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Caring for Babies During the Newborn Screening Blood Test — NCT02608892.
• Registry record last updated 2019-03-27; status last verified 2019-03.
• Results first posted 2019-03-27.
• 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

NCT02608892 is a completed randomized, single-masked, parallel-group pilot trial sponsored by Children's Hospital of Eastern Ontario. It enrolled 100 participants and compared the BSweet2Babies video with usual care for parents of newborns undergoing newborn screening blood tests.

The primary outcome was use of breastfeeding, skin-to-skin care, or sucrose within 48 hours of viewing the video. The registry reports 30 of 50 participants with the outcome in the intervention group and 33 of 49 in control. The recalculated risk difference is -0.073, with a 95% confidence interval from -0.262 to 0.115 and an unadjusted p-value of 0.447. The sponsor’s reported absolute difference is -7.4, with a 95% confidence interval from -26.2 to 11.5.

The registry lists three secondary outcomes and reports zero serious adverse events, zero other adverse events, and zero deaths in both groups. Further details about the statistical plan, missing-data handling, and original sample-size justification are not reported in the registry record.