ACHIEVE Hearing Intervention Follow-Up Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for ACHIEVE Hearing Intervention Follow-Up Study (NCT05070429), a randomized na study. The primary outcome is Average Daily Hours of Hearing Aid Use.

2. Clinical Question

The registry frames the study as a comparison of delivery models, rather than a comparison of hearing aids with no hearing aids. Both groups were existing hearing aid users, and both were described as having clinic-based visits during the study. The distinction was the delivery of audiological rehabilitative services: clinic-based in the conventional group and telehealth in the telehealth group, with the latter also able to use conventional options.

The primary outcome concerns use of hearing aids, not a direct measure of hearing ability. The registry also lists treatment satisfaction, achievement of a primary communication goal, and hearing-specific quality of life as secondary outcomes. Those measures provide other perspectives on participants’ experiences, but the primary question remains the between-group comparison of objectively logged average daily use. The registry record does not report a clinical threshold for a meaningful difference in daily use.

3. Trial Design

This was a randomized, parallel-group trial with no masking reported in the registry record. The registry lists Johns Hopkins University as the sponsor, a total enrollment of 339, and a completed status. The recorded study start was 2021-11-12 and the primary completion date was 2024-01-10. The registry describes the study as involving older adults who were existing hearing aid users.

Participants were assigned to conventional hearing healthcare or telehealth hearing healthcare. The conventional group was described as receiving clinic-based audiological rehabilitative service delivery. The telehealth group was described as receiving telehealth audiological rehabilitative service delivery, while also being able to use conventional options. Both arm descriptions specify clinic-based visits every 6 months for the duration of the 2-year study. The descriptions available in the registry record are truncated, so additional details about services or procedures are not reported in the registry record.

The main outcome was average daily hours of hearing aid use through up to 1 year. It was obtained from objective hearing aid data logging; when a participant wore a hearing aid in both ears, the ear with the greatest number of hours was selected. The posted group summaries include 159.0 participants in the conventional group and 153.0 in the telehealth group for this outcome. The record lists three secondary outcomes: treatment satisfaction, ability to hear for a primary communication goal, and hearing-specific quality of life.

The registry identifies the design as randomized, but details such as the randomization procedure, allocation concealment, stratification, and the planned sample-size justification are not reported in the registry record. The protocol’s original statistical plan, analysis populations, missing-data procedures, and any interim analyses are also not reported in the registry record. These omissions limit what can be inferred about how the study was planned and how the posted results were produced beyond the methods explicitly named in the 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 Average Daily Hours of Hearing Aid Use, measured over Up to 1 year.

The primary endpoint is average daily hours of hearing aid use, reported as a mean with a standard deviation and measured through up to 1 year. The registry says the measure comes from objective hearing aid data logging. For participants wearing hearing aids in both ears, the ear with the greatest number of hours is selected. This definition makes the outcome a measure of recorded device use rather than a participant’s estimate of use or a direct test of hearing.

Use is relevant to the stated trial question because the study compares how hearing healthcare is delivered and asks whether the telehealth model improves hearing aid use and other communication outcomes compared with clinic-based care. The endpoint can therefore describe whether logged daily use differed between the randomized groups. It does not by itself measure satisfaction, communication success, or hearing-specific quality of life; those are addressed by separate secondary outcomes.

In general, an objectively logged measure can avoid some limitations of self-reported use, but its interpretation still depends on how the measure is defined and on the data available for analysis. Here, the registry specifies the greater-use ear when both ears have hearing aids. It does not report a threshold for a difference considered important to participants, or the details of how unavailable or incomplete data were handled. Those points are not reported in the registry record.

7. Results Posted in the Registry

• Telehealth Hearing Healthcare Group: mean 7.20 versus 7.37 on control; difference -0.17 (95% CI -1.30 to 0.96), standardized effect d = -0.03; z-test p = 0.768.

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.

Treatment Satisfaction as Assessed by a Single Item From the International Outcome Inventory - Comprehensive Hearing Intervention (IOI-CHI) Scale

• 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:
  • Telehealth Hearing Healthcare Group: mean 4.78 versus 4.78 on control; difference 0.00 (95% CI -0.10 to 0.10), standardized effect d = 0.00; z-test p = 1.000.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Telehealth Hearing Healthcare Group and the control. The interval gives the range of effects that remain compatible with the data.

Ability to Hear for Primary Communication Goal as Assessed by a Single Item From the Client-Oriented Scale of Improvement (COSI) Goals Achievement Questionnaire

• 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:
  • Telehealth Hearing Healthcare Group: mean 4.29 versus 4.25 on control; difference 0.04 (95% CI -0.12 to 0.20), standardized effect d = 0.06; z-test p = 0.621.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Telehealth Hearing Healthcare Group and the control. The interval gives the range of effects that remain compatible with the data.

Hearing-specific Quality of Life as Assessed by the Hearing Handicap Inventory for the Elderly - Screening Version (HHIE-S) Questionnaire

• 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:
  • Telehealth Hearing Healthcare Group: mean 7.16 versus 7.33 on control; difference -0.17 (95% CI -1.68 to 1.34), standardized effect d = -0.02; z-test p = 0.825.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Telehealth Hearing Healthcare Group and the control. The interval gives the range of effects that remain compatible with the data.

Across the three posted secondary outcomes, the sponsor-reported analyses do not show clear between-group differences: all three reported confidence intervals include zero. Taken together, the pattern is broadly consistent with the primary analysis in that the posted results do not demonstrate clear differences between the telehealth and conventional groups. This is a summary of the overall pattern, not evidence that the outcomes are identical or that the delivery models have equivalent effects.

The secondary outcomes address different questions from the primary endpoint. Satisfaction, ability to hear for a primary communication goal, and hearing-specific quality of life are not interchangeable with objectively logged daily hearing aid use. Similarity in the overall direction of statistical conclusions does not mean the measures are redundant, nor does it show that one outcome explains another. The registry does not report an analysis linking changes in these outcomes to hearing aid use.

Unadjusted secondary results generally carry less confirmatory weight when several outcomes are examined, because the chance of finding an apparently unusual result can increase as more comparisons are made. In general, multiplicity procedures can address this issue, but the registry record does not report whether such a procedure was planned or used. The posted secondary p-values should therefore be read as results for individual analyses, not as a family-wise confirmatory claim.

The record lists three secondary outcomes and reports results for those three. It also lists five outcome measures and four analyses overall. The relationship between those counts and the complete set of planned or analyzed measures is not explained in the registry record. The secondary findings provide additional descriptive context, but they do not replace the primary endpoint or resolve the uncertainty in its estimate.

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

• Treatment Satisfaction as Assessed by a Single Item From the International Outcome Inventory - Comprehensive Hearing Intervention (IOI-CHI) Scale
• Ability to Hear for Primary Communication Goal as Assessed by a Single Item From the Client-Oriented Scale of Improvement (COSI) Goals Achievement Questionnaire
• Hearing-specific Quality of Life as Assessed by the Hearing Handicap Inventory for the Elderly - Screening Version (HHIE-S) Questionnaire

9. Statistical Interpretation

10. Statistical Methods Explained

The posted results include a simple unadjusted recalculation based on the group means and standard deviations, alongside the registry’s reported model-based analysis. These answer related but not necessarily identical statistical questions. Reading both helps distinguish a calculation based directly on the displayed summaries from the sponsor’s reported inferential analysis.

What does the mean difference describe?

For a continuous outcome, a mean summarizes the group’s average measured value. The reported primary means are 7.37 daily hours for conventional care and 7.2 daily hours for telehealth care. The recalculated mean difference is expressed as telehealth minus conventional care, so its negative sign indicates that the posted telehealth mean is lower. The size and uncertainty of that difference matter more than the sign alone. The standard deviations, 5.15 and 5.05, describe variability among the observed values within the respective groups; they are not confidence intervals for the group means.

The recalculation is unadjusted: it compares the posted summaries without adjustment for other variables. Its mean difference is -0.17, with a 95% confidence interval from -1.302 to 0.962 and p = 0.768. It is useful as a transparent summary-based comparison, but it should not be mistaken for the trial’s full planned analysis. The registry’s original analysis plan and details of any adjustment variables are not reported in the registry record.

What is the role of the reported model?

The registry lists a generalized linear model (GLM) and maximum likelihood estimation (MLE) for the primary comparison. In general, a model-based analysis estimates a relationship between outcome and group according to the model specification, while maximum likelihood is a way of estimating model parameters from the observed data. A GLM is a broad class of models; its specific form depends on choices such as the outcome distribution, link function, covariates, and treatment of repeated observations. Those details are not reported in the registry record, so the model should not be described more specifically than the record allows.

The model-based result is -0.035, with a 95% confidence interval from -0.727 to 0.657 and p = 0.92. It is this sponsor-reported analysis that should be treated as the trial’s reported inferential result. Because the registry record does not describe the model specification, the simple summary-based recalculation cannot establish why its estimate and interval differ from the GLM result.

How should a confidence interval be read?

In general, a confidence interval conveys the uncertainty around an estimated effect under the statistical method used. A 95% confidence interval is generated by a procedure that, under its assumptions, would cover the underlying quantity in 95% of repeated applications. It is not a statement that there is a 95% probability that the particular interval contains the true effect. Both the reported model interval and the recalculated interval include zero, which means that no difference is among the values compatible with those intervals. The intervals also include non-zero values, so the data do not establish that the true difference is exactly zero.

A p-value measures how unusual the observed result, or a more extreme result, would be under a specified null hypothesis and the assumptions of the analysis. It is not the probability that the null hypothesis is true, nor a measure of the size or importance of an effect. Here, the sponsor-reported p-value is 0.92 and the unadjusted recalculated p-value is 0.768. The registry identifies the analysis type as superiority; it does not report an equivalence or non-inferiority objective.

Why might the analyses differ?

In general, a model-based analysis can differ from a comparison reconstructed from group means and standard deviations because the model may use a different outcome distribution, covariates, or other assumptions. The registry record does not report enough detail to identify the reason in this trial. The reported result and the summary-based recalculation should therefore be presented as distinct analyses, not combined into a new estimate. The record does not indicate a discrepancy that would call the sponsor’s analysis into question; the model result remains the principal result reported by the registry.

The registry reports standard deviations for the primary group summaries. In general, dispersion matters because greater variability makes it harder to estimate a group difference precisely for a fixed amount of information. Confidence intervals reflect both the estimated effect and its uncertainty; a small estimated difference does not necessarily imply a precise estimate. The broad span of the recalculated interval illustrates why the point estimate alone is insufficient for interpretation.

What cannot be determined from the posted methods?

Randomized allocation is reported, but methods for sequence generation, allocation concealment, analysis populations, missing observations, and handling of protocol deviations are not reported in the registry record. The registry also does not report a prespecified sample-size justification or interim-analysis plan. These omissions mean readers cannot fully assess whether the posted model follows the original protocol, whether all randomized participants were analyzed as assigned, or how missing outcome data may affect the estimates.

The calculations in the accompanying planning section are illustrations based on observed effects, not evidence about the trial’s original design or conduct. Generalized linear models can be useful when their assumptions suit the data, but the particular assumptions and diagnostics for this analysis are not reported in the registry record. The appropriate interpretation is consequently anchored in the results as posted, with the model’s reported estimate and uncertainty distinguished from the unadjusted recalculation.

11. Confidence Intervals and Precision

Precision is about how tightly an analysis estimates a difference, not simply whether a p-value crosses a conventional threshold. For the primary outcome, the sponsor-reported GLM estimate is -0.035 daily hours, with a 95% confidence interval from -0.727 to 0.657. This interval includes zero and also includes values on either side of zero. The estimate is therefore not precise enough to rule out all non-zero differences within the range covered by the interval.

The summary-based recalculation has a mean difference of -0.17 daily hours and a 95% confidence interval from -1.302 to 0.962. This is a separate, unadjusted calculation and not a replacement for the registry’s reported GLM result. The two intervals both include zero, but they have different estimates and widths. The registry record does not provide enough model detail to explain why.

In general, a confidence interval gives readers more information than a point estimate alone: it shows the uncertainty and the range of effect sizes that are compatible with the data and method. It does not show that every value in the interval is equally plausible, nor does it identify which value is correct. Because the registry does not report a threshold for a meaningful difference in daily hours, the interval cannot be translated into a judgment about clinical importance from this record alone.

The reported standard deviations are 5.15 for conventional care and 5.05 for telehealth care. These describe variation in individual measurements, whereas the confidence interval describes uncertainty about a group contrast. The number of analyzed participants, variability, analysis method, and any model adjustments all affect precision. Details needed to assess some of those features, including missing-data handling and model specification, are not reported in the registry record.

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 sample-size table and curve are planning illustrations based on fractions of the observed effect; they are not a record of the trial’s original sample-size calculation. For these continuous outcomes, the entries are participants per arm, not total events. 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 the stated fraction of the observed effect. The original design assumptions and sample-size justification are not reported in the registry record.

The column for 80% power gives the illustrated number of participants per arm for a design with an 80% chance of detecting the specified effect under the stated assumptions, if that effect and assumptions were correct. The 90% power column describes the corresponding planning target with a 90% chance. These percentages refer to properties of a hypothetical study design under specified assumptions, not the probability that the posted trial result is correct.

Rows describe planning for 100%, 75%, and 50% of the observed effect. As the target effect becomes smaller, more participants are needed to distinguish it from random variation under the same planning assumptions. The table makes that relationship visible; it should not be read as a recommendation or as evidence that the original trial was designed around any of those target effects.

These figures are not observed power. They are calculations for hypothetical future designs using the observed effect as a planning reference. Because the observed effect is itself uncertain, and the registry does not report a clinically important target difference or the trial’s own design rationale, the illustrations should be interpreted cautiously. The record does not report whether the original enrollment target was based on this endpoint, a different outcome, or other assumptions.

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

Worked calculation for this trial

1. Observed difference Δ = -0.170; pooled standard deviation σ = 5.101.
2. n = 2 × (1.96 + 0.842)² × 5.101² / -0.170² = 14,134.7, rounded up to 14,135 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 <- -0.17                      # observed difference in means
sigma <- 5.10121269579518                     # 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(5070429)
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 = 14,135 (80% power), 18,923 (90% power)
 75% of observed effect: n per arm = 25,129 (80% power), 33,640 (90% power)
 50% of observed effect: n per arm = 56,539 (80% power), 75,690 (90% power)
power.t.test: 14135.7 
Simulated power at n = 14,135 per arm: 0.805 (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.

14. Analyses Reported by the Sponsor

The registry’s reported primary analysis is the GLM with maximum likelihood estimation: an estimate of -0.035, a 95% confidence interval from -0.727 to 0.657, and p = 0.92. This is the sponsor-reported analysis and is the main inferential result to use when describing what the trial reported.

The simple recalculation from posted group means and standard deviations gives a mean difference of -0.17, a 95% confidence interval from -1.302 to 0.962, and an unadjusted p-value of 0.768. It is a summary-based, unadjusted calculation, not the same analysis as the GLM. The estimates differ, although both intervals include zero. The registry record does not describe the GLM specification or explain the difference between the estimates.

The record does not flag a discrepancy between the posted analysis and the recalculation. The recalculation can help readers see how the displayed summaries compare without adjustment, but it should not supersede the sponsor’s own reported model analysis. It also cannot establish whether the model’s assumptions were met, because the relevant details are not reported in the registry record.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and three posted secondary outcomes. It also records five outcome measures and four analyses overall. The record does not explain the difference between the total number of outcome measures and the analyses listed, or identify whether every measure was planned, analyzed, and reported. Details of an outcome hierarchy or a prespecified testing sequence are not reported in the registry record.

In general, when multiple outcomes or comparisons are tested, the chance of at least one apparently notable result can increase. Statistical plans may address this through a prespecified hierarchy or adjustment for multiple testing. The registry record does not report whether multiplicity was addressed for the secondary outcomes. Their p-values should therefore be treated as individual, unadjusted findings unless otherwise specified in the record, rather than as a set of results that has been shown to control a family-wise error rate.

Missing-data procedures are also not reported in the registry record. The primary outcome summaries include 159.0 participants in the conventional group and 153.0 in the telehealth group, while total enrollment is 339. The record does not provide participant flow, the reasons for unavailable outcome data, or a description of how missing measurements were handled. These figures alone do not establish why some enrolled participants are not represented in the posted group summaries.

Analysis-population definitions are not reported in the registry record. It is therefore not possible to determine from the posted information whether the GLM used all randomized participants, only participants with observed endpoint data, or another defined population. The record also does not state how adherence to assigned care, withdrawals, or protocol deviations were addressed. These omissions limit assessment of potential bias and prevent a full reconstruction of the analysis from the registry results.

The registry does not report the original statistical analysis plan, interim analyses, or sample-size justification. These are not details that can be inferred from the posted p-values or planning illustrations. The available findings can be described accurately, but the record does not permit a complete audit of prespecification, selective reporting, or the treatment of incomplete data.

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.

Most frequent non-serious adverse event terms

The registry lists zero serious adverse events among 176 participants at risk in the conventional group and zero among 163 participants at risk in the telehealth group. It lists 7 other adverse events among 176 at risk in the conventional group and 11 among 163 at risk in the telehealth group. The record also lists 0 deaths for the conventional group and 4 for the telehealth group.

These are registry counts, not a comparative statistical analysis. The record does not list serious adverse event terms, and it does not provide event descriptions or an explanation of the deaths. The death counts should not be assumed to be caused by, or unrelated to, either care-delivery model based on these figures alone. The record does not report a causal assessment.

In general, adverse-event counts need context, including definitions, timing, participant follow-up, and how events were collected. Such details are not reported in the registry record. The figures should be read as the posted safety summary, not as evidence on their own of a difference in risk between groups.

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

The posted primary results do not demonstrate a clear difference in average daily hearing aid use between telehealth and conventional hearing healthcare. The sponsor-reported GLM estimate is close to zero, its 95% confidence interval includes zero, and its p-value is 0.92. The unadjusted recalculation from the group summaries likewise has an interval including zero. The appropriate conclusion is that the registry’s posted analyses did not establish a between-group difference in this endpoint.

This does not show that the groups were exactly the same. Both intervals permit non-zero differences, and the registry does not report a threshold that would distinguish a trivial difference from one important to participants. Nor does a non-significant superiority analysis establish equivalence or non-inferiority. Such claims require a suitable design and a prespecified margin, neither of which is reported in the registry record.

The primary endpoint is logged daily hearing aid use through up to 1 year. It cannot, by itself, answer whether participants communicated more effectively, were more satisfied, or experienced different hearing-specific quality of life. The record reports secondary measures addressing those areas, but their posted analyses also do not demonstrate clear differences. They remain distinct outcomes, and their interpretation is limited by the lack of reported multiplicity procedures and analysis details.

The trial compares models of healthcare delivery among older adults who were existing hearing aid users. It does not compare hearing aids with no hearing aids, and the posted primary outcome does not establish whether either model is preferable for every participant or setting. The registry record does not report enough detail about the population beyond the stated description to extend the findings to groups not represented in the study.

Interpretation is also constrained by absent information on missing data, analysis populations, model specification, and the original statistical plan. The posted numbers support a careful description of the analyses and their uncertainty, but not a broader causal explanation or a conclusion about unreported outcomes. No medical decision should be based on these results alone.

18. Why This Trial Matters Statistically

This trial illustrates why statistical interpretation should not stop at comparing point estimates or p-values. The primary group means are close, but the confidence intervals are essential for understanding what the data do and do not rule out. Both the reported model analysis and the summary-based recalculation include zero, yet neither establishes that the true difference is exactly zero.

The record also provides a useful contrast between an analysis reported by the sponsor and a simple unadjusted recalculation. These are not interchangeable: one is a GLM using maximum likelihood estimation, while the other is reconstructed from posted group summaries. The registry does not give enough detail to explain their differences, making transparent labeling of each result important. The model-based result remains the principal reported analysis.

Planning illustrations based on an observed effect can be informative about the relationship between target effect size and required sample size. They are not a substitute for a documented design rationale, and they cannot retrospectively show that a trial was adequately powered. Here, the original sample-size justification is not reported in the registry record. The distinction between planning calculations and properties of the completed trial is therefore central.

Finally, the trial shows the value of separating an objectively logged primary endpoint from secondary measures of satisfaction, communication goals, and quality of life. These outcomes capture different dimensions, and their pattern should be summarized without treating them as interchangeable. Missing information about multiplicity, analysis populations, and missing data further demonstrates why a registry result is informative but not always a complete statistical report.

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.

Important trial details are not reported in the registry record. These include the randomization procedure and allocation concealment, the original sample-size justification, the full statistical analysis plan, the model specification, analysis populations, and missing-data methods. The registry also does not report whether interim analyses were conducted. Without these details, readers cannot fully assess how the reported model was specified or how incomplete observations may have affected the results.

The primary endpoint summaries cover 159.0 participants in the conventional group and 153.0 in the telehealth group, while the registry lists enrollment of 339. Participant flow and reasons for the differing counts are not reported in the registry record. It is not possible to tell from these figures alone whether the difference reflects missing endpoint measurements, exclusions, or another aspect of reporting.

The registry’s arm descriptions are truncated. They state that both groups had clinic-based visits every 6 months during the 2-year study, but do not provide complete descriptions of all services and options. The record therefore does not support a detailed assessment of treatment fidelity, the amount of telehealth actually used, or differences in contact between groups.

The primary outcome is defined through up to 1 year, while the arm descriptions refer to a 2-year study. The registry record does not explain the relationship between that outcome timeframe and the full follow-up period. It also does not report a threshold for a meaningful difference in daily use. As a result, the statistical interval cannot be translated into a clinical importance judgment using this record alone.

There are three posted secondary outcomes, while the record lists five outcome measures and four analyses overall. The relationship between these counts and any unposted results is not explained. Multiplicity procedures are not reported. These limitations do not invalidate the posted values, but they narrow the conclusions that can be drawn from them.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: ACHIEVE Hearing Intervention Follow-Up Study — NCT05070429.
• Registry record last updated 2026-06-11; status last verified 2026-05.
• Results first posted 2025-01-31.
• 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

The ACHIEVE Hearing Intervention Follow-Up Study (NCT05070429) is a completed randomized, parallel-group trial sponsored by Johns Hopkins University. It compared telehealth and conventional clinic-based hearing healthcare delivery among older adults who were existing hearing aid users. The registry lists enrollment of 339 and no masking.

The primary outcome was average daily hours of hearing aid use through up to 1 year, measured using objective hearing aid data logging. The sponsor-reported GLM estimate was -0.035, with a 95% confidence interval from -0.727 to 0.657 and p = 0.92. The interval includes zero, so the posted analysis did not establish a clear between-group difference.

Three secondary outcomes are posted, and their reported confidence intervals also include zero. The record does not report the original sample-size justification, full model specification, analysis populations, missing-data methods, or multiplicity procedure. The results should be read as registry-reported findings with these reporting limitations in view.