Multi-Component Intervention to Improve Health Outcomes and Quality of Life Among Rural Older Adults Living With HIV: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Multi-Component Intervention to Improve Health Outcomes and Quality of Life Among Rural Older Adults Living With HIV (NCT04549259), a randomized na study. The primary outcome is Proportion of Participants With HIV Viral Load ≥832 Copies/mL (HemaSpot DBS).

2. Clinical Question

3. Trial Design

This was a randomized, unmasked, factorial study listed as phase NA. The registry reports enrollment of 61 and a completed status. The recorded start date is 2021-04-14 and the primary completion date is 2022-05-09. The sponsor was the Medical College of Wisconsin. The trial concerned HIV and was designed to pilot-test a multi-component remote intervention for rural older people living with HIV.

The four behavioral components were group-based social support, HIV stigma reduction, strengths-based case management, and personalized technology detailing. The registry lists combinations of those components, as well as an HIV Information Only arm. The arm descriptions for the component combinations are blank, so details beyond their named components are not reported in the registry record. The information-only arm is described as receiving no intervention components but information on successfully aging with HIV.

Factorial assignment is relevant to interpretation: the primary comparisons are organized by whether participants received each component, rather than presenting a single comparison of one complete intervention package against one control group. Assignment was randomized and masking was listed as none. The registry does not report the randomization sequence, allocation ratio, stratification, or implementation details. The planned sample-size justification and original design assumptions are not reported in the registry record.

The primary outcome analysis included participants with follow-up HemaSpot DBS data, N = 49, and analyzed participants in their assigned arm regardless of intervention participation or attendance. That analysis population is smaller than the enrollment of 61. The registry does not give a full account of why follow-up outcome data were unavailable for other participants or how missing values were handled. Medication adherence and depressive symptoms were also posted as secondary outcomes, both measured at 3 months following enrollment/baseline survey.

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.

Only the first 6 of 16 groups are shown.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Analysis included all participants with follow-up HemaSpot DBS data (N = 49). Participants were included in outcome analyses in assigned arm regardless of intervention participation/attendance.

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.

Only the first 6 of 17 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Proportion of Participants With HIV Viral Load ≥832 Copies/mL (HemaSpot DBS), measured over 3 months following enrollment/baseline survey.

The primary endpoint is the count of participants whose HIV viral load was ≥832 copies/mL at 3 months following enrollment/baseline survey, based on HemaSpot dried blood spot testing. Participants received DBS kits by mail to collect blood samples themselves and return them directly to a clinical laboratory. Sufficient-volume specimens were tested using the Abbott m2000 RealTime HIV-1 DBS quantitative assay, whose stated limit of detection was 832 copies/mL.

The registry describes three result categories: detected and quantifiable at ≥832 copies/mL; detected but non-quantifiable, estimated between <832 and >300 copies/mL; and not detected, estimated to be <300 copies/mL. The posted primary outcome is specifically the proportion with results at or above the quantifiable threshold. It therefore does not treat every detectable result as meeting the primary endpoint. The endpoint is used to assess a virologic outcome that the trial’s summary identifies as a preliminary impact of interest. It does not, by itself, measure medication-taking behavior, care engagement, or health-related quality of life. The registry lists viral suppression as a broader project interest, while this outcome is defined as the count above a stated viral-load threshold.

7. Results Posted in the Registry

• Social Support Intervention: No: 25.9% (7/27) versus 22.7% (5/22) on control; risk difference 3.2 percentage points (95% CI -20.9 to 27.3), risk ratio 1.14 (0.42–3.10); unadjusted two-proportion z-test p = 0.796.
• Stigma Reduction Intervention: Yes: 33.3% (8/24) versus 22.7% (5/22) on control; risk difference 10.6 percentage points (95% CI -15.1 to 36.3), risk ratio 1.47 (0.56–3.81); unadjusted two-proportion z-test p = 0.425.
• Stigma Reduction Intervention: No: 16.0% (4/25) versus 22.7% (5/22) on control; risk difference -6.7 percentage points (95% CI -29.4 to 15.9), risk ratio 0.70 (0.22–2.30); unadjusted two-proportion z-test p = 0.559.
• Strengths-Based Case Management Intervention: Yes: 25.0% (6/24) versus 22.7% (5/22) on control; risk difference 2.3 percentage points (95% CI -22.4 to 26.9), risk ratio 1.10 (0.39–3.10); unadjusted two-proportion z-test p = 0.857.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Medication Adherence

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Social Support Intervention: No: 51.9% (14/27) versus 54.2% (13/24) on control; risk difference -2.3 percentage points (95% CI -29.7 to 25.1), risk ratio 0.96 (0.57–1.61); unadjusted two-proportion z-test p = 0.869.
  • Stigma Reduction Intervention: Yes: 50.0% (13/26) versus 54.2% (13/24) on control; risk difference -4.2 percentage points (95% CI -31.9 to 23.5), risk ratio 0.92 (0.54–1.57); unadjusted two-proportion z-test p = 0.768.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Social Support Intervention: No and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Stigma Reduction Intervention: Yes and the control. The interval gives the range of effects that remain compatible with the data.

Depressive Symptoms

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Social Support Intervention: No: mean 9.33 versus 6.84 on control; difference 2.49 (95% CI -1.18 to 6.16), standardized effect d = 0.37; z-test p = 0.184.
  • Stigma Reduction Intervention: Yes: mean 8.47 versus 6.84 on control; difference 1.63 (95% CI -2.03 to 5.29), standardized effect d = 0.25; z-test p = 0.383.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Social Support Intervention: No and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Stigma Reduction Intervention: Yes and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists medication adherence and depressive symptoms as secondary outcomes at the same follow-up time as the primary endpoint. The posted results show several group-level summaries and a limited set of reported comparisons. The overall pattern is not a consistent shift across all components and outcomes: estimates vary in direction, and the reported analyses do not present a uniform signal across the secondary measures. The primary viral-load outcome likewise has imprecise component comparisons. Taken together, these records do not establish a coherent pattern of effects across the outcomes.

Secondary results can help characterize a pilot study and identify questions for further evaluation, but they generally carry less evidential weight than a prespecified primary outcome. The registry lists multiple outcomes and analyses, while the multiplicity plan is not reported. When many comparisons are considered, an isolated low p-value may occur by chance, particularly if no adjustment or hierarchy was prespecified. This is why the medication-adherence sponsor result with p = .049 should not be treated on its own as definitive evidence. The model details and confidence limits for that analysis are not reported in the registry record.

Secondary findings also have their own measurement and missing-data considerations. The posted record does not fully explain outcome definitions, scoring details for depressive symptoms, or the analysis methods for every secondary comparison. Results should be considered exploratory and interpreted alongside the number of outcomes examined, the small sample, and the uncertainty around estimates. They do not override the primary endpoint or establish effects on broader health outcomes and quality of life.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Medication Adherence
• Depressive Symptoms

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is binary at the participant level: each included participant either met the stated threshold of HIV viral load ≥832 copies/mL or did not. The registry reports counts and group sizes, so the displayed proportions and risk differences describe the observed frequency of that outcome in each comparison group. A risk difference expresses the absolute difference between two proportions. A positive value means the group designated as the comparison has a larger observed proportion than the reference group under the ordering used for that calculation; a negative value means a smaller proportion. It does not express a relative change.

What does randomization contribute?

Random assignment can help balance baseline characteristics on average across groups, but it does not guarantee balance in a small sample. The registry describes randomized assignment and an unmasked study. It does not report the randomization procedure or enough detail to judge whether additional design features affected the analysis. The primary outcome analysis included participants with follow-up DBS results and retained their assigned-arm classification regardless of intervention attendance. This is an assigned-group approach among those with outcome data; it does not remove uncertainty caused by unavailable follow-up results.

How should the factorial comparisons be understood?

A factorial study evaluates multiple intervention components within the same trial. Here, the primary comparisons are organized around receiving or not receiving a component. This structure differs from a simple comparison of one intervention package against one control package. Component comparisons can pool participants across different combinations of the other components. The registry does not report the model specification, interactions between components, or the rationale for the chosen comparisons. It is therefore not possible to determine from the registry record whether component interactions were tested or how they were handled.

The recalculated primary comparisons are unadjusted risk differences from the posted counts. Their p-values are also unadjusted. The sponsor’s analysis is described as mixed models analysis and reports odds ratios, but the model details, covariates, and coding conventions are not reported in the registry record. Odds ratios and risk differences use different scales. An odds ratio compares odds, whereas a risk difference compares proportions directly. They should not be treated as numerically equivalent or as if they answer precisely the same scale-based question.

What does a confidence interval convey?

A confidence interval communicates uncertainty around an estimate under the assumptions of the method used to construct it. For a risk difference, intervals extending to both negative and positive values indicate that the posted data are compatible with a range that includes differences in either direction and a value of zero. An interval is not a guarantee that the true value lies within its endpoints, and its width reflects precision as well as the analysis method. The confidence level and exact interval method are not reported in the registry record, so they should not be inferred.

Why do small groups matter?

When a binary outcome is observed in groups with relatively few participants, a small count change can shift the observed proportion noticeably. This can produce wide intervals and limited ability to distinguish a real difference from sampling variation. The primary outcome analysis included N = 49, split across component-level comparison groups of 22 to 27 participants. The observed counts were between 4 and 8 in those groups. These features call for emphasis on uncertainty and the exploratory pilot context, rather than a binary reading of p-values alone.

What is the role of the planning calculations?

The planning illustrations use the observed effect as a starting point and show hypothetical participant requirements under stated assumptions. They are not the original design justification, which is not reported in the registry record. For the binary primary endpoint, the illustrations vary the effect used as a fraction of the observed effect and report participants per arm for selected power targets. Smaller target effects require larger participant counts under the same planning framework. The calculations do not show how likely this completed trial was to detect an effect, and they do not replace interpretation of the observed estimates and their uncertainty.

In general, multiplicity matters when several outcomes or comparisons are tested: the chance of at least one apparently notable result can increase as the number of tests grows. The registry lists 32 analyses overall and four outcome measures, but the statistical plan for handling multiple comparisons is not reported in the registry record. The p-values should therefore be read as unadjusted where indicated, not as evidence that a multiplicity correction was or was not applied in the sponsor’s model.

11. Confidence Intervals and Precision

The primary recalculated estimates are accompanied by intervals that are wide in relation to the point estimates. For social support, the risk difference for no versus yes is 0.032, with endpoints -0.209 and 0.273. For stigma reduction, the yes comparison is 0.106 with endpoints -0.151 and 0.363, while the no comparison is -0.067 with endpoints -0.294 and 0.159. The strengths-based case-management estimates are 0.023 (-0.224 to 0.269) for yes and 0.013 (-0.230 to 0.255) for no. The technology-detailing estimates are 0.069 (-0.177 to 0.315) for yes and -0.045 (-0.283 to 0.193) for no.

Each interval includes zero. This means that the interval estimates do not rule out no difference, while also spanning values in both directions. The endpoints also include differences that could be meaningful in magnitude; the registry does not identify a threshold for what would count as clinically important. The point estimates alone should not be read as precise estimates of the underlying effect.

Precision is limited in part by the modest numbers in the primary outcome groups and the small event counts. A confidence interval is a range reflecting uncertainty under a statistical procedure, not a range containing every plausible explanation of the data. The confidence level and method used for the recalculated intervals are not reported in the registry record. The sponsor’s mixed-model odds ratios have no confidence limits reported, which further limits assessment of their precision. Their p-values do not substitute for interval estimates, because they do not show the range of effect sizes compatible with the model.

12. 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 illustrations are expressed as participants per arm, not total participants or total events. They use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The target effect is stated as a fraction of the observed effect. For each fraction, the 80% power column gives the estimated number of participants per arm under those assumptions for a design with an 80% chance of detecting that specified effect if it were present. The 90% power column gives the corresponding estimate for a design with a 90% chance under the same assumptions.

Rows labeled planning for 100% of the observed effect use the full observed estimate as the hypothetical target. Rows for 75% and 50% use progressively smaller targets. Smaller effects are harder to distinguish from random variation, so they require more participants under the stated assumptions. The calculations are illustrations based on observed effects, not the trial’s original design assumptions; those original assumptions are not reported in the registry record. They are not observed power.

The estimates can be very large because the observed component differences are small or uncertain in this pilot sample. They should not be read as a recommended enrollment target without a separate design decision about the effect of interest, outcome, analysis, and feasibility. They also do not account for any design features beyond the listed planning assumptions. The registry record does not report whether the original enrollment target was chosen using these calculations or another approach.

13. 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 = 0.227; treatment proportion p₁ = 0.259; average p̄ = 0.243.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6068 = 1.1893.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6064 = 0.5103.
4. n = (1.1893 + 0.5103)² / (0.0320)² = 2,823.2, rounded up to 2,824 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 <- 0.227272727272727                          # control proportion
p1 <- 0.259259259259259                          # 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(4549259)
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 = 2,824 (80% power), 3,780 (90% power)
 75% of observed effect: n per arm = 4,964 (80% power), 6,645 (90% power)
 50% of observed effect: n per arm = 11,041 (80% power), 14,780 (90% power)
power.prop.test: 2823.2 
Simulated power at n = 2,824 per arm: 0.801 (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.

14. Analyses Reported by the Sponsor

The registry reports the sponsor’s primary-outcome analyses as mixed models analyses with odds ratios. The reported component-comparison odds ratios are 3.23 for social support, 1.76 for stigma reduction, 0.68 for strengths-based case management, and 0.87 for technology detailing. The associated p-values are .33, .63, .78, and .90, respectively. Confidence limits are not reported, and the record does not explain the odds-ratio reference coding, model specification, or adjustment variables.

The simple recalculations use posted counts to estimate unadjusted risk differences. They are not intended to replace the sponsor’s model-based analysis. Odds ratios and risk differences express contrasts on different scales, and model adjustment can also make estimates differ from unadjusted calculations. The registry reports no discrepancy flag, so there is no stated conflict requiring one analysis to take precedence. The extra mixed-model outputs labeled as other analyses are not fully described; their purpose and interpretation are not reported in the registry record. The available details do not support a full audit or reconstruction of the sponsor’s models.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 32 analyses and four outcome measures. The primary endpoint alone includes several component-level comparisons, and secondary outcomes add further opportunities for testing. The statistical plan for multiplicity control, including any prespecified hierarchy or adjustment, is not reported in the registry record. Consequently, the reported unadjusted p-values should not be interpreted as if they account for the full set of analyses. General statistical principle: as the number of tests increases, the chance of observing at least one result that appears notable by chance can increase.

The missing-data details are also limited. The primary analysis included all participants with follow-up HemaSpot DBS data, N = 49, and assigned participants to their randomized arm regardless of intervention attendance. Enrollment was 61, but the registry does not explain the reasons follow-up results were unavailable, whether missingness differed among groups, or whether any sensitivity analyses were conducted. The handling of missing outcome values beyond restricting the primary analysis to participants with follow-up data is not reported in the registry record.

The analysis population therefore differs from everyone enrolled. This can matter if participants with observed follow-up differ systematically from those without observed follow-up. The available record does not establish whether that occurred. Nor does it report a detailed participant flow or the number assessed for eligibility. The protocol’s planned population, analysis populations for every outcome, and any per-protocol analyses are not reported in the registry record.

The registry identifies the primary endpoint and timeframe, but does not provide the complete statistical analysis plan, model specification, covariates, confidence-interval level, or rules for handling multiple components. These omissions limit the ability to determine whether the posted analyses match a prespecified plan. They do not demonstrate that the analyses were inappropriate; they mean that this information cannot be assessed from the registry record.

16. 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 safety record lists 16 intervention-combination groups. For every listed group, the reported number affected by serious adverse events is 0, the number affected by other adverse events is 0, and deaths are 0. The number at risk for each event category is reported as 3 or 4 in the individual groups. No serious adverse-event terms are listed.

These figures describe what was recorded in the registry for the listed groups. They should be read in light of the small numbers at risk shown for each group and the pilot nature of the study. Zero recorded events in these groups does not establish that an intervention has no safety risks or that uncommon events could be excluded. The registry does not provide further detail about event collection procedures, the period covered by the safety assessment, or whether there were events outside the reported categories. Those details are not reported in the registry record.

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

The posted primary results describe the proportion of participants with follow-up DBS data whose viral load met or exceeded 832 copies/mL, compared across component-level groups. The recalculated risk differences are imprecise, and every interval includes zero. The mixed-model p-values reported by the sponsor do not provide confidence limits, and the model details are limited. These results therefore do not precisely establish the size or direction of a component-related difference.

The findings do not show that the intervention components changed viral load, medication adherence, depressive symptoms, or quality of life. The trial summary describes a pilot intended to examine acceptability, remote feasibility, and preliminary impact, but posted results for acceptability and feasibility are not included in the record summarized by the primary outcome data. The record does not provide enough information to infer a clinical benefit or lack of benefit.

The endpoint is a particular viral-load threshold measured at one follow-up time. It is not a complete assessment of viral suppression at all thresholds, treatment adherence, care engagement, or broader health status. Nor does a component comparison establish the effect of every possible combination of components. Factorial comparisons may combine participants from different component combinations, and interaction results are not reported in the registry record.

The sample was small, the primary outcome analysis included 49 participants, and the confidence intervals allow a range of possible differences. The results are best understood as descriptive, exploratory evidence from a pilot. They may help frame further research questions, but they do not settle whether the components have an effect in a broader population of rural older adults living with HIV.

18. Why This Trial Matters Statistically

This trial is statistically informative because it examines several behavioral components within a randomized factorial pilot, rather than testing only one fixed package. That design can be useful when the research question concerns the potential contributions of different components. It also makes careful interpretation important: component comparisons, combinations, and possible interactions are not interchangeable questions. The registry does not report interaction estimates or a complete account of the model, so conclusions must stay close to the comparisons actually posted.

The primary endpoint is based on a mailed, self-collected DBS specimen and a specified assay threshold. This creates a clear operational outcome for the pilot, while also narrowing what the measure represents. The outcome analysis used 49 participants with follow-up data, and the group counts were small. The broad uncertainty around risk differences illustrates how a randomized design can still yield limited precision when the available outcome data are sparse.

The registry also makes visible a distinction that matters in clinical research: observed estimates, inferential analyses, and sample-size planning calculations answer different questions. The unadjusted recalculations describe contrasts from the posted counts; the sponsor’s mixed models provide a separate model-based analysis; the planning illustrations show hypothetical enrollment under stated assumptions. None should be confused with another. The pilot can inform how later studies frame outcomes and component comparisons, but the original design rationale, multiplicity plan, and several analysis details are not reported in the registry record.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several limitations specific to this record constrain interpretation. The primary outcome analysis included 49 participants with follow-up HemaSpot DBS results, compared with enrollment of 61. Reasons for missing follow-up results and their distribution across groups are not reported in the registry record. The available results therefore cannot show whether the analyzed participants represent everyone enrolled.

The outcome threshold is 832 copies/mL, with separate categories described for detectable non-quantifiable results and results below the stated estimate of 300 copies/mL. The posted primary result focuses on the count at or above 832 copies/mL; it does not give enough information to characterize the full distribution across all three categories. The registry does not report a confidence level for the posted intervals or a full method description for the recalculated estimates.

The trial used factorial assignment among components, but details about allocation implementation, interaction analyses, model covariates, and model coding are not reported. Sponsor odds ratios are posted without confidence limits, and the definitions of the additional outputs labeled as other analyses are unclear. The number of analyses is 32, while multiplicity handling is not reported.

Finally, enrollment was modest and the trial was described as a pilot. The population is characterized as rural older adults living with HIV, but a specific age definition and detailed eligibility criteria are not reported in the registry record. The posted primary results do not themselves establish acceptability or remote feasibility, and the available information cannot support broad generalization beyond the studied participants.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Multi-Component Intervention to Improve Health Outcomes and Quality of Life Among Rural Older Adults Living With HIV — NCT04549259.
• Registry record last updated 2023-07-12; status last verified 2023-06.
• Results first posted 2023-07-12.
• 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.

23. Record Summary

NCT04549259 is a completed randomized, unmasked factorial pilot sponsored by the Medical College of Wisconsin. It tested four remotely delivered behavioral components for rural older adults living with HIV, with combinations of components and an HIV Information Only arm listed. Enrollment was 61.

The primary outcome was the count of participants with HIV viral load ≥832 copies/mL at 3 months following enrollment/baseline survey. The analysis included 49 participants with follow-up DBS data. Component-level recalculated risk differences have broad intervals that include zero. Sponsor-reported mixed-model odds ratios have no confidence limits in the registry record. Medication adherence and depressive symptoms were also listed as secondary outcomes. Details about multiplicity, missing-data handling, and several analysis methods are not reported in the registry record.