Testing Preliminary Effectiveness of a Community Health Worker (CHW) Training Program on Caregiving: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Testing Preliminary Effectiveness of a Community Health Worker (CHW) Training Program on Caregiving (NCT06049043), a randomized na study. The primary outcome is Knowledge Pretest.

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group study with no masking. The registry lists the study as completed and records enrollment of 107. Its stated aim was to explore the impact of an online training program designed to prepare community health workers to support African American and Latino male caregivers of older adults. The experimental intervention was IN-HOME professional development training; the control intervention was AARP’s English “Care at Home” resource webpage. The study is listed with phase NA.

The primary outcome was a continuous knowledge score. The outcome description says that participants answered 16 identically worded multiple-choice questions at pretest and posttest. Individual scores were averaged into a 0-to-100 composite, and the group comparison used average scores. The outcome is titled “Knowledge Pretest” and has a baseline timeframe, while the posted statistical comparison is labeled as a mean difference in final values. Further detail reconciling these labels is not reported in the registry record.

The posted primary outcome summaries include 40 participants in the IN-HOME arm and 39 in the control arm. The registry’s enrollment figure is 107; reasons that the posted outcome counts differ from enrollment are not reported in the registry record. The registry lists one secondary outcome, satisfaction composite scores at posttest. It records nine outcome measures and 12 analyses overall, but does not report enough detail in the available record to characterize every measure or analysis. Dates of study start and primary completion are recorded as 2023-05-22 and 2023-08-15.

Randomization helps form groups for comparison, but the record does not state the allocation sequence method or whether allocation was concealed. No masking was used, so participants and study personnel were not blinded according to the registry. Details of implementation, adherence, or exposure to each intervention 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 Knowledge Pretest, measured over Baseline.

The primary outcome is a composite knowledge score based on 16 multiple-choice questions. According to the registry description, the questions were identically worded at pretest and posttest. Correct responses were averaged for each participant, then participant scores were averaged across a group. The resulting scale ranges from 0 to 100, with higher scores indicating better outcomes. This is a continuous measure, and the posted summaries use means and standard deviations to describe the groups.

A composite score can represent performance across several related questions in a single measure. In this study, it provides a way to describe knowledge relevant to the training topic rather than reporting each question separately. Comparing group means can indicate whether average scores differ between participants assigned to the professional development training and those assigned to the control resource.

The outcome is titled “Knowledge Pretest” and its timeframe is listed as baseline. At the same time, the reported analysis is described as a mean difference in final values, and the outcome text refers to both pretest and posttest measurement. The registry record does not clarify the relation among these labels. The score therefore should be interpreted according to the stated scale and the posted comparison, without assuming an unreported change-score analysis or a specific adjustment for baseline.

The record does not report a justification for selecting this endpoint, its measurement validation, or how missing answers were handled. Those details would help readers judge how well the composite reflects the intended knowledge domain and how the score was constructed when responses were incomplete.

7. Results Posted in the Registry

• Intervention to Help Orient Men to Excel (IN-HOME): mean 79.84 versus 84.94 on control; difference -5.10 (95% CI -13.85 to 3.65), standardized effect d = -0.26; z-test p = 0.253.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: it is a score on a bounded 0-to-100 scale, and the registry reports a mean and standard deviation for each group. A mean describes the average score, while a standard deviation describes how spread out participant scores are around that average. These statistics summarize different aspects of the data: group means describe central tendency, and standard deviations describe between-participant variation.

What does the mean difference represent?

The posted comparison is expressed as a mean difference, with the IN-HOME group first and the control group second. The recalculated estimate is -5.1 points. A negative value means the observed mean was lower in the first-named group under that subtraction convention. It does not, by itself, indicate whether the observed difference is more than would be expected from random variation. The confidence interval and statistical test address uncertainty in the estimate.

The recalculated result uses the posted group means, standard deviations, and group sizes to form a simple unadjusted comparison. It is not an adjusted model, and it does not incorporate participant-level data that are not included in the posted summaries. The sponsor’s reported analysis is a two-sided t-test of mean difference in final values. A t-test evaluates whether a difference in group means is compatible with a null hypothesis of no mean difference, subject to the test’s assumptions. A two-sided test allows evidence in either direction to count against that null hypothesis.

What does a confidence interval add?

A confidence interval gives a range of values that are compatible with the observed data under the method’s assumptions. It communicates the uncertainty around an estimate in the same units as the outcome. The recalculated 95% interval is -13.85 to 3.649. Because this range crosses zero, it includes both negative and positive differences. The interval is not a guarantee that the true difference lies within its endpoints, and it does not assign a probability to a particular value after the data have been observed. Its width is a useful indication that the estimate is not highly precise.

What assumptions underlie a mean comparison?

In general, a t-test relies on the observations being appropriately independent and on the sampling distribution of the mean difference being adequately represented by the test procedure. The exact robustness of a mean comparison depends on features such as the distribution of scores, the group sizes, and whether the spread differs substantially between groups. The registry record reports group standard deviations but does not provide participant-level distributions or diagnostic checks. It also does not say whether a pooled-variance or unequal-variance version of the t-test was used. The recalculation is therefore descriptive of the posted summaries and should not be treated as a full audit of model assumptions.

The score has stated minimum and maximum values of 0 and 100. Bounded scales can have distributional features that differ from an unbounded continuous measure, particularly if scores cluster near a boundary. The posted means and standard deviations do not establish whether such clustering occurred. The registry does not report score distributions, question-level results, or a transformation or alternative model. No specific concern about the score distribution can be concluded from the summary statistics alone.

How should the p value be read?

In general, a p value measures how incompatible the observed data are with a specified null hypothesis, given the statistical model and its assumptions. The recalculated unadjusted p value is 0.253; the sponsor’s reported p value is 0.26. These values do not measure the probability that the intervention has no effect, and they do not quantify the probability that the result occurred “by chance.” They also do not describe the magnitude of the mean difference. The mean estimate and confidence interval are needed to discuss direction and precision alongside the test result.

The registry reports a two-sided t-test. It does not report a prespecified significance threshold for the primary analysis, a hierarchy of hypotheses, an adjustment for multiple comparisons, or whether the reported test was adjusted for any covariates. Such details are not reported in the registry record and should not be inferred from the analysis type alone.

What does randomization contribute?

In general, random assignment is intended to make treatment groups comparable at baseline in expectation, including on measured and unmeasured characteristics. It does not ensure that every realized group is balanced, especially in a study with limited outcome counts. Nor does randomization remove the need to describe who was analyzed, how missing outcomes were handled, or whether participants followed their assigned intervention. The registry identifies the allocation as randomized but does not report the sequence-generation method, concealment procedures, or detailed participant flow.

There was no masking. Lack of masking can matter for outcomes affected by participants’ knowledge of assignment or by the way measures are administered, although the registry does not report whether these issues influenced the knowledge assessment. It is not possible to determine from the record whether the assessment was self-administered, independently scored, or otherwise protected from knowledge of assignment.

The outcome description mentions pretest and posttest measurement, but the outcome is titled “Knowledge Pretest” and tagged as baseline, while the sponsor’s test is labeled as a comparison of final values. The record does not describe a change-score analysis, a baseline-adjusted model, or the exact relationship between those labels. Statistical interpretation should stay with the stated mean comparison and avoid attributing a more specific model to the study.

10. Confidence Intervals and Precision

Precision concerns how tightly an estimate is determined by the data and analysis. For the recalculated mean difference of -5.1 points, the 95% confidence interval extends from -13.85 to 3.649. That span includes zero and values on both sides of zero. It therefore allows for a range of plausible differences, including one favoring the IN-HOME group and one favoring control. The result is not precise enough to locate the underlying group contrast narrowly.

A confidence interval is not a direct measure of practical importance. To judge the relevance of a score difference, readers would need an interpretation of what changes on this 0-to-100 composite mean in context. A threshold for an important difference is not reported in the registry record. Without that benchmark, the interval can be described statistically but not classified as clinically or practically important.

The sponsor’s reported 95% confidence interval is -14.02 to 3.84, with an estimate of -5.09. It has the same general implication as the recalculated interval: the estimated contrast is uncertain and the interval includes zero. The small differences between the sponsor and recalculated endpoints arise from the distinct posted calculations and rounding; the registry does not indicate a substantive disagreement. The sponsor’s own analysis takes precedence for the reported trial result.

Precision is affected by the amount of information available and by variation in scores. The posted group standard deviations are 23.02 for IN-HOME and 16.14 for control, with outcome counts of 40 and 39, respectively. The registry does not report a precision target or the assumptions used in the original study design. The confidence interval should be read as uncertainty around this estimate, not as proof that effects outside its range are impossible.

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 concern a continuous mean comparison and are expressed as participants per arm, not total events. The planning illustration assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. It considers effects equal to 100%, 75%, and 50% of the observed effect. These are planning scenarios based on the observed estimate, not the original design assumptions; the trial’s own design assumptions are not reported in the registry record.

For planning for 100% of the observed effect, the illustration gives 240 participants per arm for 80% power and 321 participants per arm for 90% power. For planning for 75% of the observed effect, it gives 426 participants per arm for 80% power and 571 participants per arm for 90% power. For planning for 50% of the observed effect, it gives 959 participants per arm for 80% power and 1,283 participants per arm for 90% power.

In plain terms, the 80% power column represents the planned number per arm under which the assumed design would have an 80% chance of detecting the specified effect at the stated significance level, if the assumptions hold. The 90% column describes the corresponding target for a higher chance of detection. These figures are planning illustrations, not observed power. Smaller effects require more participants because they are harder to distinguish from random variation. Since the observed effect itself is uncertain, planning based on a fraction of it is also uncertain; these numbers should not be read as a recommendation or as evidence that the trial was designed with these targets.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -5.100; pooled standard deviation σ = 19.924.
2. n = 2 × (1.96 + 0.842)² × 19.924² / -5.100² = 239.6, rounded up to 240 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
delta <- -5.09999999999999                      # observed difference in means
sigma <- 19.9238421423752                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(6049043)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 240 (80% power), 321 (90% power)
 75% of observed effect: n per arm = 426 (80% power), 571 (90% power)
 50% of observed effect: n per arm = 959 (80% power), 1,283 (90% power)
power.t.test: 240.5 
Simulated power at n = 240 per arm: 0.801 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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 sponsor’s reported analysis is a two-sided t-test comparing final values. It reports a mean difference of -5.09, a 95% confidence interval from -14.02 to 3.84, and p = 0.26. The simple unadjusted recalculation from the posted group summaries gives a mean difference of -5.1, a 95% confidence interval from -13.85 to 3.649, and an unadjusted p value of 0.253.

The two results are close in estimate and lead to the same broad interpretation: uncertainty remains around the group difference, and the reported interval includes zero. The recalculation is an independent summary-based check, not a replacement for the sponsor’s analysis. It uses only the posted summary statistics and is not able to reproduce any analysis details that depend on participant-level data or unreported modeling choices. The registry record does not indicate a discrepancy requiring a different interpretation. The sponsor’s own analysis takes precedence for the trial’s reported inferential result.

The endpoint is described as “Knowledge Pretest” at baseline, whereas the sponsor’s analysis is labeled as a comparison of final values. The record does not explain how these descriptions relate. This uncertainty about endpoint timing is separate from the close numerical agreement between the reported test and the recalculation. It limits how specifically the result can be characterized, even though the numerical comparison itself is broadly consistent.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists nine outcome measures, 12 analyses, and one posted secondary outcome, satisfaction composite scores at posttest. The primary outcome comparison is a mean difference in knowledge scores. The record does not describe a prespecified hierarchy among outcomes, identify which analyses were designated confirmatory, or report an adjustment for testing multiple outcomes or analyses. Without those details, the primary result should be read as the reported comparison rather than as an analysis known to account for all testing across the study.

Multiplicity arises when many hypotheses are tested: the chance of at least one apparently unusual result can increase as the number of tests grows. In general, prespecification and an explicit testing strategy help readers distinguish a primary analysis from exploratory comparisons. The registry record does not report whether such a strategy was used, so it is not possible to assess its effect on interpretation. The fact that multiple outcomes and analyses are listed does not, by itself, establish how they were selected or interpreted.

Missing-data handling is not reported in the registry record. The primary outcome summaries contain 40 participants in the IN-HOME arm and 39 in control, while the recorded enrollment is 107. The record does not explain the difference between enrollment and the outcome counts, whether participants lacked measurements, or how any incomplete responses were handled. The number of participants randomized to each arm and the reasons for any exclusions or missing outcomes are also not reported in the information available.

The analysis population is not described as intention-to-treat, per-protocol, or another defined population. The registry does not report whether participants were analyzed according to their randomized assignment, whether all randomized participants were included, or how intervention exposure affected inclusion. These details matter because the analysis population can affect the meaning of a randomized comparison.

The record does not describe interim analyses, stopping rules, or a statistical analysis plan. These items should be treated as not reported in the registry record, rather than assumed to have been absent or present. Similarly, no methods for handling multiple imputation, sensitivity analyses, or missing outcome data are described. These reporting gaps limit evaluation of robustness but do not alter the posted numerical result.

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

The result describes average knowledge scores in two randomized groups: participants assigned to IN-HOME training and participants assigned to the control resource. The posted mean was 79.84 for IN-HOME and 84.94 for control. The recalculated contrast was -5.1 points, with a 95% confidence interval from -13.85 to 3.649. This is an uncertain estimate, and the interval includes zero. The sponsor’s reported result is similar in direction and precision.

These data do not establish that the groups had the same average score. A result that does not clearly distinguish the groups can reflect uncertainty, and the interval allows differences in either direction. Nor does the observed difference alone establish that assignment to one condition caused a change in knowledge. The study’s randomization is relevant to causal comparison, but interpretation also depends on the analyzed population, missing outcomes, implementation, outcome timing, and analysis details, several of which are not reported in the registry record.

The outcome is a knowledge composite, not a direct measure of caregiver well-being, care quality, health outcomes, or the effectiveness of outreach in practice. The study’s stated aim concerned training CHWs to support African American and Latino male caregivers of older adults, but the posted primary result concerns knowledge scores. The registry record does not report a primary result measuring caregiver outcomes. The posted secondary outcome is satisfaction composite scores at posttest; further details of its results are not included in the registry record for this analysis.

The result also does not establish whether the knowledge score is an adequate proxy for successful CHW outreach or improved support for caregivers. The registry record does not report a threshold for an important score difference, a validated interpretation of the composite, or whether knowledge gains were retained. The score’s stated direction is clear—higher scores indicate better outcomes—but the practical meaning of a particular difference is not specified.

Finally, the planning illustrations are not evidence about what was observed in the trial and are not observed power. They show how participant requirements vary under stated assumptions and assumed effect sizes. They do not remedy the uncertainty in the result or establish that the original study was intended to meet any particular sample-size target.

16. Why This Trial Matters Statistically

This study raises a useful statistical question about how to evaluate a training program when the intended benefit is indirect. The training was designed to prepare community health workers to support African American and Latino male caregivers of older adults, while the primary outcome captures knowledge through a composite score. That distinction matters: evidence about knowledge is not automatically evidence about outreach quality or caregiver outcomes. Keeping the measured endpoint separate from the broader program goal prevents overinterpretation.

The randomized, parallel-group design gives the study a comparative structure, and the posted results permit a direct description of group means and their uncertainty. The confidence interval communicates more than a binary conclusion: it shows that the estimate is compatible with a range of differences, including values favoring either group. This is important in a study where a non-significant test should not be mistaken for proof of equivalence.

The record also illustrates why clarity about endpoint timing and analysis populations matters. The outcome is labeled “Knowledge Pretest” and baseline, yet the reported test concerns final values. The record does not explain the relationship. Likewise, enrollment is recorded as 107, while the outcome summaries give counts of 40 and 39; participant flow and missing-data handling are not reported. These are not minor editorial details: they shape what population and timepoint the estimate represents.

Finally, the planning illustration makes explicit that sample-size requirements depend strongly on the effect assumed for planning. It is a useful reminder that the observed effect is itself uncertain and that smaller effects need more participants to detect. Because the trial’s own design assumptions are not reported, the illustration should not be confused with the study’s original planning or treated as a judgment on its design. Overall, the statistical value of the record lies in showing both the estimate and the limits of what can be concluded from it.

17. 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 outcome counts are 40 in the IN-HOME arm and 39 in control, compared with recorded enrollment of 107. Participant flow and reasons for the difference are not reported in the registry record. Without those details, readers cannot determine how many enrolled participants were randomized, how many contributed to the primary outcome, or whether exclusions or missing measurements differed between groups.

The primary outcome’s description is not fully aligned across the record: it is titled “Knowledge Pretest” and assigned a baseline timeframe, while the sponsor’s analysis is described as a comparison of final values. The registry does not clarify whether the reported contrast is at posttest, whether baseline scores were used, or how pretest and posttest observations contributed to the analysis. The result should not be interpreted as a change from baseline unless that analysis is documented.

The registry identifies randomized allocation but does not report the sequence-generation method or allocation concealment. It records no masking. Further details about intervention adherence, use of the control webpage, assessment administration, or fidelity are not reported. These omissions prevent a fuller assessment of how the assigned conditions were implemented and how measurement might have been influenced.

Missing-data methods, the analysis population, multiplicity handling, an analysis plan, and the original sample-size assumptions are not reported in the registry record. The record also does not provide a benchmark for a practically important difference on the knowledge composite. These limitations make it difficult to judge robustness, the role of the result among the study’s multiple analyses, and the practical meaning of the observed score contrast.

The primary comparison is based on a knowledge score and does not directly report outcomes for caregivers. Accordingly, the posted result cannot establish whether caregiver support or outreach changed. This is a limitation of the measured outcome for answering broader questions about program impact, not a claim that such outcomes were or were not assessed elsewhere.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Testing Preliminary Effectiveness of a Community Health Worker (CHW) Training Program on Caregiving — NCT06049043.
• Registry record last updated 2025-04-11; status last verified 2025-04.
• Results first posted 2025-04-11.
• 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.

21. Record Summary

NCT06049043 is a completed randomized, parallel-group study with no masking and recorded enrollment of 107. It examined IN-HOME professional development training for CHWs, compared with AARP’s English “Care at Home” resource webpage. The study aimed to explore training intended to help CHWs support African American and Latino male caregivers of older adults.

The primary outcome is a 0-to-100 composite knowledge score, with higher scores indicating better outcomes. The posted group means were 79.84 for IN-HOME and 84.94 for control. The sponsor reported a mean difference of -5.09, a 95% confidence interval from -14.02 to 3.84, and p = 0.26. The recalculated unadjusted contrast is similar and remains imprecise.

The registry lists satisfaction composite scores at posttest as a secondary outcome. Reasons for the difference between recorded enrollment and the primary-outcome counts, missing-data methods, analysis population, and the relation between the baseline endpoint label and final-values analysis are not reported in the registry record. The statistical record supports a cautious description of an uncertain knowledge-score contrast, not a conclusion about caregiver outcomes.