Efficacy of Self-Directed Auditory Rehabilitation in Individuals With Hearing Loss: A Systematic Review and Meta-Analysis

Article information

J Audiol Otol. 2026;30(1):23-33

Publication date (electronic) : 2026 January 20

doi : https://doi.org/10.7874/jao.2025.00591

Sangmin Park ¹^,²

, Sunmi Ma ¹^,²

, Jieun Joo ¹^,²

, Seunghee Ha ²^,³

, Tae-Jin Yoon ⁴

, Woojae Han ¹^,²^,³

¹Laboratory of Hearing and Technology, College of Natural Sciences, Hallym University, Chuncheon, Korea

²Division of Speech Pathology and Audiology, College of Natural Sciences, Hallym University, Chuncheon, Korea

³Research Institute of Audiology and Speech Pathology, Hallym University, Chuncheon, Korea

⁴Department of English Language and Literature, Sungshin Women’s University, Seoul, Korea

Address for correspondence: Woojae Han, PhD, Laboratory of Hearing and Technology, Division of Speech Pathology and Audiology, College of Natural Sciences, Hallym University, 1 Hallymdaehak-gil, Chuncheon 24252, Korea, Tel +82-33-248-2216, Fax +82-33-256-3420, E-mail woojaehan@hallym.ac.kr

Received 2025 September 24; Revised 2025 December 10; Accepted 2025 December 26.

Abstract

Background and Objectives

Hearing loss negatively affects communication and quality of life. While clinician-led rehabilitation is beneficial, access barriers and poor long-term adherence limit its overall impact. This systematic review evaluated the efficacy of self-directed auditory rehabilitation across the lifespan.

Materials and Methods

A systematic search was conducted using five electronic databases for peer-reviewed studies involving children, adults, and older adults with at least mild hearing loss, who participated in self-directed auditory rehabilitation and reported behavioral, objective, or patient-reported auditory outcomes.

Results

Twenty-two studies with 1,851 screened records were included in the synthesis, which encompassed varied populations, devices, and rehabilitation formats. Random-effects meta-analyses showed significant speech recognition improvement in pediatric participants (Cohen’s d=1.32, standard error [SE]=0.12, 95% confidence interval [CI]: 1.08–1.56; p<0.05), with effects maintained at 1–3 months. A moderately significant benefit was observed in both adults and older adults (Cohen’s d=0.55, SE=0.05, 95% CI: 0.45–0.65). Although publication bias was present in some adult studies, the sensitivity analyses confirmed the robustness of the results.

Conclusions

Self-directed auditory rehabilitation produces meaningful and sustained speech recognition benefits in individuals with hearing loss, endorsing its integration as an accessible adjunct to conventional audiologic care. Future studies should refine the program content and reduce intervention variability.

Keywords: Hearing loss; Aural rehabilitation; Self-management; Speech perception; Meta-analysis

Introduction

Hearing loss is a major global health concern [1], affecting people across the lifespan and resulting in profound consequences for communication, social participation, daily functioning, and cognitive well-being [2]. According to the World Health Organization, hundreds of millions of individuals worldwide live with disabling hearing impairment, which contributes to a substantial socioeconomic burden and diminished quality of life [1]. Traditionally, the management of hearing loss has relied on clinician-guided strategies, including professional assessment, customized device fitting (such as hearing aids and cochlear implants), and structured in-person auditory training programs [2,3]. Despite the demonstrated efficacy of these conventional approaches [2], their widespread adoption is often limited by restricted geographic and financial access, dependency on specialist availability, and difficulty maintaining long-term patient engagement and adherence [3,4].

In recent years, advances in digital health and remote care delivery have supported the emergence of self-directed auditory rehabilitation as a promising and accessible complement to traditional models of care [3]. Self-directed interventions encompass a diverse range of resources—including computer-based auditory training, interactive software, mobile applications, instructional videos, and telehealth platforms—that enable individuals with hearing loss to engage in rehabilitation autonomously, in ways that accommodate their unique needs and schedules [3].

Self-directed auditory rehabilitation refers specifically to digitally delivered or computer-based auditory training and self-management programs that are completed independently at home or in other unsupervised settings [3]. As a patient-led approach, it allows individuals to enhance auditory recognition, speech understanding, and communication strategies with minimal clinician involvement [5], while still permitting brief orientation, remote monitoring, or periodic technical support to promote adherence and accessibility [3,4].

These programs also differ in the types of auditory stimuli they employ. Most self-directed auditory rehabilitation interventions are predominantly speech-based, incorporating tasks such as phoneme discrimination, word and sentence recognition, and speech-in-noise training to target communication-related auditory skills [3,5]. Some programs additionally include supplementary non-speech elements—such as environmental sounds, musical tones, or other complex auditory cues—particularly within game-based or multimodal platforms designed to enhance engagement [5].

Such flexible approaches are especially advantageous for individuals who face barriers to regular clinic visits, including those living in rural areas, working adults with limited scheduling flexibility, and people with mobility constraints [4,6].

Emerging evidence indicates that self-directed auditory rehabilitation may provide benefits comparable to those achieved through clinician-led programs, particularly for individuals with mild-to-moderate hearing loss and those utilizing auditory devices [5–7]. Nevertheless, the overall efficacy, optimal content, and long-term impact of self-directed auditory rehabilitation remain uncertain; previous reviews have predominantly focused on clinical settings or on narrow age groups, leaving critical gaps in understanding about effectiveness across the lifespan and various delivery modalities [3]. The considerable heterogeneity of intervention strategies, diversity of outcome measures, and variations in participant characteristics have all contributed to inconsistent findings regarding the true value and limitations of these approaches [7].

Given the global emphasis on increasing access to personalized and cost-effective rehabilitation, a rigorous evaluation of self-directed auditory rehabilitation efficacy in real-world populations is urgently needed [7,8]. Systematic synthesis and quantitative analysis of recent evidence are essential for clinicians, healthcare policymakers, and patients to make informed decisions about integrating these interventions into standard audiological practice [7].

Therefore, this review systematically assesses and synthesizes the literature on the efficacy of self-directed auditory rehabilitation for individuals with hearing loss. Specifically, the review addresses the following research questions: 1) Does self-directed auditory rehabilitation yield measurable and durable improvements in speech recognition outcomes for individuals with hearing loss? and 2) Is the effectiveness of such training consistent across age groups? By conducting this comprehensive evaluation, the study not only clarifies the role and benefits of self-directed auditory rehabilitation, but also identifies key determinants of successful outcomes and provides recommendations for optimizing rehabilitation strategies in the evolving landscape of audiological care.

Materials and Methods

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure the transparency and accuracy of reporting [9]. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251120180). Eligibility criteria for study inclusion and exclusion were developed following the Population, Intervention, Comparator, Outcomes, and Study Design (PICOS) framework.

Search strategy

Three authors (SP, SM, JJ) independently conducted comprehensive searches of five electronic databases—PubMed, CINAHL, Cochrane Library, Web of Science, and Embase—covering literature published between June and August 2025. Search strategies were developed using combinations of terms such as “auditory rehabilitation,” “aural rehabilitation,” “audiologic rehabilitation,” “hearing therapy,” “listening therapy,” and “listening rehabilitation” combined with “speech recognition,” “voice recognition,” and “spoken recognition.” The full list of search terms is provided in Supplementary Table 1 (in the online-only Data Supplement).

Inclusion criteria

Studies were eligible for inclusion if they met all of the following criteria: 1) included children, adults, or older adults with at least mild hearing loss (≥2 years of age); 2) employed self-directed auditory rehabilitation interventions, excluding non-speech-based auditory approaches; 3) reported post-training outcomes compared with pre-training outcomes (repeated-measures design) or with a control group (active or inactive); 4) reported at least one outcome measure based on behavioral or objective auditory tests, or on patient-reported functional or quality-of-life outcomes; and 5) used randomized controlled trials (RCTs), non-randomized controlled trials, cohort studies with control groups, or repeated-measures designs. Review articles, editorials, and grey literature were excluded.

Data extraction

Data from eligible studies were independently extracted by three authors (SP, SM, JJ) using a standardized, pilot-tested form. Extracted information included: 1) study identification details (first author, year of publication, journal, and title); 2) study characteristics (design, duration, location, original eligibility criteria); 3) participant characteristics (sample size, sex distribution, age); 4) intervention details (nature, duration, frequency); and 5) outcomes (types of outcome measures, effect estimates, follow-up duration, attrition/dropout rates, and any adjusted confounders). For studies with control groups, data from both intervention and control groups were extracted where available; for single-group studies, only intervention data were included. Discrepancies in data extraction were resolved by consensus with another author (WH). This process was intended to enhance reliability and minimize bias.

Risk of bias assessment

The risk of bias for RCTs was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool [10], which evaluates five domains: bias arising from randomization, deviations from intended interventions, missing outcome data, outcome measurement, and selective reporting. Each domain was rated as low risk, some concerns, or high risk of bias. For non-randomized studies, including quasi-experimental trials, single-group pre-post designs, and natural experiments, we employed the ROBINS-I tool (Risk Of Bias In Non-randomized Studies of Interventions) [11], which evaluates seven domains: confounding, selection of participants, classification of interventions, deviations from intended interventions, missing data, measurement of outcomes, and selection of the reported result, with the overall risk categorized as low, moderate, serious, or critical. Two authors (SM, WH) independently conducted the assessments, and disagreements were resolved through discussion until consensus was reached.

Statistical analysis

Both qualitative synthesis and quantitative meta-analysis were performed. Statistical heterogeneity across studies was assessed using the I² statistic and Cochran’s Q test. For subgroup analyses, studies were stratified into two categories: children and adults/older adults. When substantial heterogeneity was observed (I²≥30%), pooled effect sizes were estimated using a DerSimonian-Laird random-effects model. Publication bias was evaluated by funnel plots and Egger’s regression test.

Results

Study selection

A total of 1,851 records were identified through database searches. After removal of 47 duplicates, 1,804 unique articles remained for title and abstract screening. Of these, 126 articles underwent full-text review, with 104 excluded for not meeting PICOS criteria (Table 1). Ultimately, 22 studies were included for qualitative and quantitative synthesis (Fig. 1).

Table 1

PICOS-based inclusion criteria for study selection

Fig. 1

PRISMA flow diagram illustrating the identification, screening, eligibility assessment, and final inclusion of studies in the systematic review and meta-analysis. The diagram summarizes the number of records at each stage, the reasons for exclusion, and the final number of studies included in the qualitative and quantitative syntheses. CI, cochlear implant; HA, hearing aid; BM, bimodal; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Risk of bias assessment

The risk of bias assessments for the 22 included studies [12–33] are summarized in Table 2 (RCTs) and Table 3 (non-randomized studies). Among the 10 RCTs evaluated using the RoB 2 tool (Table 2), three studies were judged to have a low risk of bias, whereas seven were rated as having some concerns, primarily due to issues with the randomization process (e.g., quasi-randomization based on recruitment order) or the absence of blinding for self-reported outcomes.

Table 2

Cochrane risk of bias assessment (RoB2) for randomized controlled trials

Table 3

Cochrane risk of bias assessment (ROBINS-I) for non-randomized studies

For the 12 non-randomized studies evaluated with the ROBINS-I tool (Table 3), the overall risk of bias was generally higher. Three studies were classified as having moderate risk of bias, indicating acceptable methodological rigor for non-randomized designs [13,14,23]. Eight studies were rated as having a serious risk, largely due to confounding inherent in single-arm designs or self-selection bias (e.g., [19]). One case study [22] was judged to be at critical risk of bias; this was taken into account in sensitivity analyses and may justify excluding the study from meta-analytic pooling under certain conditions.

Study characteristics

The included studies encompassed a broad range of participant ages (from preschool children to older adults), intervention modalities (various digital and computer-based auditory training programs), control conditions (active, passive, or none), outcome measures (behavioral, objective, and patient-reported), and study designs (RCTs, crossover trials, cohort studies, and pilot studies). Across studies, all interventions focused on self-directed auditory rehabilitation, typically delivered through home-based or gamified platforms, with substantial variations in both duration and intensity. Classification of the 22 included interventions identified three principal categories: 1) standard auditory training (standard AT), the most common approach, typically involving repetitive phoneme- or word-level identification tasks; 2) gamified AT, primarily observed in pediatric studies, in which digital toys such as Tiptoi [20] or serious-game platforms [21] were employed to enhance engagement; and 3) AT combined with counseling/education, mainly represented by Listening and Communication Enhancement (LACE)-based programs that integrated auditory training with communication strategy instruction. Further details are provided in Table 4.

Table 4

Summary of characteristics of included studies on self-directed auditory rehabilitation

Meta-analysis: pediatric populations

A random-effects meta-analysis was conducted on four studies [12,20,24,29] of pediatric participants with hearing loss who completed self-directed auditory training. The primary outcomes were the pre-post mean differences or intervention-control differences on standardized speech recognition tasks. Pooled analysis yielded a statistically significant effect (Cohen’s d=1.32, standard error [SE]=0.12, 95% confidence interval [CI]: 1.08–1.56; p<0.05), indicating that auditory training conferred measurable improvements in speech recognition for children. Between-study heterogeneity was moderate, reflecting differences in study protocols and participant characteristics (Supplementary Table 2 in the online-only Data Supplement and Fig. 2).

Fig. 2

Forest plot showing individual study effect sizes (Cohen’s d, 95% CI) and the pooled random-effects estimate for the efficacy of self-directed auditory training on speech recognition in pediatric populations with hearing loss. The 95% CIs for each study indicate an overall statistically significant benefit. CI, confidence interval.

Assessment of publication bias: pediatric studies

A funnel plot showed no obvious asymmetry (Fig. 3), and Egger’s regression test yielded a non-significant regression intercept (−0.92, p=0.23). However, because only four studies were included (k=4), the statistical power of Egger’s test is limited, so these quantitative findings are reported for transparency but should be interpreted with caution; in this context, evaluation of publication bias relies primarily on visual inspection of the funnel plot, which did not suggest marked asymmetry.

Fig. 3

Funnel plot assessing potential publication bias among pediatric studies included in the meta-analysis, with standard error plotted against observed effect sizes (Cohen’s d). Visual inspection suggests no marked asymmetry, and Egger’s regression test yielded a non-significant intercept (−0.92, p=0.23); however, these results should be interpreted cautiously given the small number of included studies. CI, confidence interval.

Duration and durability of pediatric training effects

Intervention durations ranged from several days to four weeks, with total training times from 5 to 16 hours. The meta-analysis indicates that even relatively brief, self-directed programs can yield clinically meaningful gains in speech recognition. Follow-up assessments available in three studies [18,24,28] confirmed that post-training gains were generally maintained for 1 to 3 months after the intervention, with no evidence of regression to baseline.

Meta-analysis: adults and older adults

Eighteen studies [13–19,21–23,25–28,31–33] were pooled in a separate random-effects meta-analysis for adults and older adults. The aggregated effect size (Cohen’s d) was 0.55 (SE=0.05, 95% CI: 0.45–0.65), representing a moderate, statistically significant improvement in speech recognition following self-directed auditory training (Supplementary Table 3 in the online-only Data Supplement and Fig. 4). Substantial between-study heterogeneity was observed, consistent with the variation in program intensity, modality, and participant characteristics.

Fig. 4

Forest plot presenting individual and pooled effect sizes (Cohen’s d, 95% CI) for speech recognition outcomes following self-directed auditory rehabilitation in adult and older adult populations. The pooled estimate demonstrates a moderate, statistically significant overall effect. CI, confidence interval.

Assessment of publication bias: adult/older adults studies

Visual inspection of the funnel plot, together with Egger’s regression test (intercept=2.62, p<0.001), revealed evidence of publication bias (Fig. 5), suggesting that published effect sizes may be overestimated. To assess the impact of this bias, a trim-and-fill sensitivity analysis was performed, imputing six potentially missing studies to the left of the mean to correct for funnel-plot asymmetry; the adjusted pooled effect size decreased to 0.42 (95% CI: 0.31–0.53), compared with the original estimate of 0.55 (95% CI: 0.45–0.65), yet remained statistically significant, indicating that the beneficial effect of self-directed auditory rehabilitation persists even after accounting for small-study effects.

Fig. 5

Funnel plot evaluating publication bias in adult and older adult studies included in the meta-analysis, with standard error plotted against observed effect sizes (Cohen’s d). Open circles indicate the six imputed studies added using the trim-and-fill method to correct for the asymmetry detected by Egger’s regression test (intercept=2.62, p<0.001). The vertical red dashed line denotes the original pooled effect size (0.55), and the vertical gray dotted line denotes the trim-and-fill–adjusted effect size (0.42).

Duration, intensity, and durability in adults/older adults

Most interventions were delivered as 1–2 hour sessions, 3–5 times per week, over 4–12 weeks. Studies with the largest gains typically provided a cumulative training duration of at least 20 hours. Longer total duration and consistent engagement were associated with enhanced improvements, although there was some evidence of a plateau effect for programs extending beyond 8–12 weeks [32]. Follow-up assessments at 1–3 months post-training showed that both objective (speech and phoneme recognition) and patient-reported outcomes were maintained, confirming the lasting benefits of self-directed auditory rehabilitation.

Discussion

Efficacy across age groups

This systematic review and meta-analysis confirm that self-directed auditory rehabilitation leads to significant and sustained improvements in speech recognition across the lifespan, benefiting both pediatric and older adult populations with hearing loss. In pediatric cohorts, the observed large effect size of Cohen’s d=1.32 (SE=0.12) in standardized speech recognition scores aligns with recent studies [12,24], which have also documented the effectiveness of digital home-based training for children. These findings bolster the emerging consensus that early, self-directed auditory intervention outside the traditional clinic setting can yield clinically meaningful gains in listening skills [8].

Among adult and older adult participants, the meta-analysis revealed a moderate but statistically robust improvement in speech recognition following self-directed rehabilitation, with a pooled effect size of Cohen’s d=0.55 (SE=0.05, 95% CI: 0.45–0.65). These effects were consistent across intervention platforms and generally persisted for up to 3 months post-training, underscoring that self-directed programs are both effective and durable for older individuals [2–4]. This observation is consistent with prior meta-analyses, reinforcing that adults and older adults can attain comparable auditory outcomes from autonomous digital interventions, and supporting their broader implementation in contemporary hearing healthcare [7].

Program modality and delivery

A diverse range of digital and gamified platforms—including computer-based phoneme training, interactive games, and tablet applications—proved effective in delivering self-directed auditory rehabilitation. This is in line with previous literature indicating that computerized auditory training offers benefits similar to those of conventional clinic-based or clinician-led modalities for adult populations [3,16]. The wide variety of digital solutions has the potential to overcome major barriers such as accessibility and long-term adherence [4], although specific challenges remain for some older adults, particularly in regard to digital literacy. Such issues likely contribute to the between-study heterogeneity observed in effect sizes for older adult cohorts.

Magnitude and durability of effects

For adult and older adult individuals, the moderate effect size observed in this review is supported by earlier meta-analyses [2,15] and reinforced by independent studies demonstrating similar outcomes with computer-based auditory training. Furthermore, the persistence of benefits for at least three months post-intervention, as noted in this and other studies [5], attests to the potential for durable improvement through self-directed rehabilitation. However, some recent trials have failed to observe long-term gains in specific domains [18], such as complex sentence comprehension, which may be attributable to lower engagement levels or less intensive training protocols.

Training dose and optimization

Intervention duration and intensity emerged as key factors in determining rehabilitation success. Programs totaling 20 or more hours of cumulative training consistently achieved the most substantial gains, a pattern consistent with the dose-response relationship reported in earlier reviews [7]. Still, there is evidence that extending the intervention beyond 8–12 weeks may result in a plateau effect [32], indicating that training regimens should be personalized, taking into account age, baseline abilities, and motivational factors.

Publication bias and heterogeneity

While publication bias appeared minimal among pediatric samples according to funnel plot and Egger’s regression analyses, it is important to note that in the pediatric group (k=4), Egger’s regression has limited statistical power due to the small number of included studies. Thus, the non-significant result (intercept=−0.92, p=0.23) is reported for transparency but should be interpreted with caution, and the assessment of publication bias in this subgroup relies primarily on the visual inspection of the funnel plot. In contrast, publication bias was evident in the literature on adult and older adult individuals [23,25], suggesting that published effect sizes in older cohorts may be overestimated. Heterogeneity also remained substantial across studies, likely reflecting differences in intervention type, participant demographics, device use, and selected outcome measures. These insights underscore the necessity for transparent reporting of null or modest results and advocate for greater standardization in future research design and reporting.

Limitations of the present study

Several limitations warrant consideration. There was considerable variability among included studies regarding intervention content, intensity, delivery platform, and outcome measures, which may compromise the comparability of results and the reliability of pooled effect sizes, especially for long-term outcomes. Despite rigorous methodology, a subset of studies displayed moderate-to-high risk of bias and evidence of publication bias in adult and older adult groups, which could potentially inflate effect estimates. The scarcity of studies with follow-up durations beyond three months also limits understanding of the long-term sustainability of observed benefits. Moreover, most interventions were tested in controlled research settings rather than real-world clinical environments, potentially restricting the generalizability of the findings. Participant pools were also not always representative of individuals with additional disabilities, severe to profound hearing loss, low digital literacy, or diverse cultural and linguistic backgrounds. Finally, the predominant focus on speech recognition means that important patient-reported outcomes—such as satisfaction, psychosocial well-being, and overall quality of life—remain insufficiently explored. Future research should emphasize methodological consistency, extended follow-up, comprehensive patient outcomes, and greater inclusion of underserved groups to further delineate and strengthen the evidence base.

Integration into clinical practice

Taken together, these findings support the integration of self-directed auditory rehabilitation as an adjunct to traditional clinician-led care. Recent international guidelines recommend broadening access to digital and autonomous interventions [3,13], especially in settings where specialist availability is limited [7,24]. The present evidence adds further impetus for such policy developments and highlights the need for ongoing research to refine intervention content, delineate subgroup-specific effects, and leverage emerging technologies—such as artificial intelligence and real-time feedback systems—to optimize therapeutic outcomes.

Supplementary Materials

The online-only Data Supplement is available with this article at https://doi.org/10.7874/jao.2025.00591.

Supplementary Table 1.

Comprehensive search strategies and keywords used in electronic database searc

jao-2025-00591-Supplementary-Table-1.pdf

Supplementary Table 2.

Standardized meta-analysis model inputs for the pediatric group

jao-2025-00591-Supplementary-Table-2.pdf

Supplementary Table 3.

Standardized meta-analysis model inputs for the adult and older adult group

jao-2025-00591-Supplementary-Table-3.pdf

Notes

Conflicts of Interest

The authors have no financial conflicts of interest.

Author Contributions

Conceptualization: Woojae Han. Data curation: Sangmin Park, Sunmi Ma, Jieun Joo. Formal analysis: Sangmin Park. Funding acquisition: Seunghee Ha. Methodology: Sangmin Park, Woojae Han. Project administration: Woojae Han. Validation: Tae-Jin Yoon. Writing—original draft: Sangmin Park, Woojae Han. Writing—review & editing: Woojae Han. Approval of final manuscript: all authors.

Funding Statement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2025S1A5C3A02005633).

Acknowledgments

None

References

1. World Health Organization. Deafness and hearing loss [Internet] Geneva: World Health Organization; 2025. [cited 2025 Aug 31]. Available from: https://www.who.int/news-room/fact-sheets/detail/deafness-and-hearing-loss.

2. Ferguson M, Maidment D, Henshaw H, Heffernan E. Evidence-based interventions for adult aural rehabilitation: that was then, this is now. Semin Hear 2019;40:68–84.

3. Henshaw H, Ferguson MA. Efficacy of individual computer-based auditory training for people with hearing loss: a systematic review of the evidence. PLoS One 2013;8:e62836.

4. Barnett M, Hixon B, Okwiri N, Irungu C, Ayugi J, Thompson R, et al. Factors involved in access and utilization of adult hearing healthcare: a systematic review. Laryngoscope 2017;127:1187–94.

5. Karah H, Karawani H. Auditory perceptual exercises in adults adapting to the use of hearing aids. Front Psychol 2022;13:832100.

6. Kim MS, Kim KH, Choe G, Park YH. Comparative effectiveness of personal sound amplification products versus hearing aids for unilateral hearing loss: a prospective randomized crossover trial. J Korean Med Sci 2024;39:e179.

7. Laird E, Sucher C, Nakano K, Ferguson M. Systematic review of patient and service outcome measures of remote digital technologies for cochlear implant and hearing aid users. Front Audiol Otol 2024;2:1403814.

8. Falkenberg ES. Holistic aural rehabilitation: a challenge. Scand J Disabil Res 2007;9:78–90.

9. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71.

10. Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ 2019;366:l4898.

11. Sterne JA, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 2016;355:i4919.

12. Tye-Murray N, Spehar B, Sommers M, Mauzé E, Barcroft J, Grantham H. Teaching children with hearing loss to recognize speech: gains made with computer-based auditory and/or speechreading training. Ear Hear 2022;43:181–91.

13. Koprowska A, Wendt D, Serman M, Dau T, Marozeau J. The effect of auditory training on listening effort in hearing-aid users: insights from a pupillometry study. Int J Audiol 2025;64:59–69.

14. Koprowska A, Marozeau J, Dau T, Serman M. The effect of phoneme-based auditory training on speech intelligibility in hearing-aid users. Int J Audiol 2023;62:1048–58.

15. Reis M, McMahon CM, Távora-Vieira D, Humburg P, Boisvert I. Effectiveness of computer-based auditory training for adult cochlear implant users: a randomized crossover study. Trends Hear 2021;25:23312165211025938.

16. Saunders GH, Smith SL, Chisolm TH, Frederick MT, McArdle RA, Wilson RH. A randomized control trial: supplementing hearing aid use with listening and communication enhancement (LACE) auditory training. Ear Hear 2016;37:381–96.

17. Humes LE, Skinner KG, Kinney DL, Rogers SE, Main AK, Quigley TM. Clinical effectiveness of an at-home auditory training program: a randomized controlled trial. Ear Hear 2019;40:1043–60.

18. Moradi S, Wahlin A, Hällgren M, Rönnberg J, Lidestam B. The efficacy of short-term gated audiovisual speech training for improving auditory sentence identification in noise in elderly hearing aid users. Front Psychol 2017;8:368.

19. Dornhoffer JR, Shannon C, Hernandez-Herrara GA, Schvartz-Leyzac KC, Dubno JR, McRackan TR. When to start computer-based auditory training after cochlear implantation: effects on quality of life and speech recognition. Otol Neurotol 2024;45:1023–9.

20. Muck S, Magele A, Wirthner B, Schoerg P, Sprinzl GM. Effects of auditory training on speech recognition in children with single-sided deafness and cochlea implants using a direct streaming device: a pilot study. J Pers Med 2023;13:1688.

21. Reynard P, Attina V, Idriss S, Hermann R, Barilly C, Veuillet E, et al. Effect of serious gaming on speech-in-noise intelligibility in adult cochlear implantees: a randomized controlled study. J Clin Med 2022;11:2880.

22. Yu L, Rao A, Zhang Y, Burton PC, Rishiq D, Abrams H. Neuromodulatory effects of auditory training and hearing aid use on audiovisual speech perception in elderly individuals. Front Aging Neurosci 2017;9:30.

23. Lai CY, Ng PS, Chan AHD, Wong FCK. Effects of auditory training in older adults. J Speech Lang Hear Res 2023;66:4137–49.

24. Zhang H, Ma W, Ding H, Zhang Y. Sustainable benefits of high variability phonetic training in Mandarin-speaking kindergarteners with cochlear implants: evidence from categorical perception of lexical tones. Ear Hear 2023;44:990–1006.

25. Sato T, Yabushita T, Sakamoto S, Katori Y, Kawase T. In-home auditory training using audiovisual stimuli on a tablet computer: feasibility and preliminary results. Auris Nasus Larynx 2020;47:348–52.

26. Smith SL, Saunders GH, Chisolm TH, Frederick M, Bailey BA. Examination of individual differences in outcomes from a randomized controlled clinical trial comparing formal and informal individual auditory training programs. J Speech Lang Hear Res 2016;59:876–86.

27. Miller S, Zhang Y, Nelson P. Neural correlates of phonetic learning in postlingually deafened cochlear implant listeners. Ear Hear 2016;37:514–28.

28. Kerneis S, Galvin JJ 3rd, Borel S, Baqué J, Fu QJ, Bakhos D. Preliminary evaluation of computer-assisted home training for French cochlear implant recipients. PLoS One 2023;18:e0285154.

29. Sullivan JR, Thibodeau LM, Assmann PF. Auditory training of speech recognition with interrupted and continuous noise maskers by children with hearing impairment. J Acoust Soc Am 2013;133:495–501.

30. Barcroft J, Sommers MS, Tye-Murray N, Mauzé E, Schroy C, Spehar B. Tailoring auditory training to patient needs with single and multiple talkers: transfer-appropriate gains on a four-choice discrimination test. Int J Audiol 2011;50:802–8.

31. Miller SE, Zhang Y, Nelson PB. Efficacy of multiple-talker phonetic identification training in postlingually deafened cochlear implant listeners. J Speech Lang Hear Res 2016;59:90–8.

32. Hsieh DL, Liu TC. Effect of computer-assisted speech training on speech recognition and subjective benefits for hearing aid users with severe to profound prelingual hearing loss. Commun Disord Deaf Stud Hearing Aids 2015;3:144.

33. Fu QJ, Galvin J, Wang X, Nogaki G. Effects of auditory training on adult cochlear implant patients: a preliminary report. Cochlear Implants Int 2004;5(Suppl 1):84–90.

Article information Continued

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

PICOS	Inclusion criteria
Participant	Individuals with at least a mild degree of hearing loss (age ≥2 years)
Intervention	Self-directed auditory rehabilitation (excluding non-speech auditory training)
Control	Studies that compared post-training outcomes with pre-training outcomes in a repeated-measures design or with those from an untrained control group
Outcome	Behavioral or objective auditory tests, or patient-reported functional or quality-of-life outcomes
Study	Randomized controlled trials, non-randomized controlled trials, cohort studies with control groups, and repeated-measures designs

ID	Bias arising from the randomization process	Bias due to deviations from intended interventions	Bias due to missing outcome data	Bias in measurement of the outcome	Bias in selection of the reported result
Tye-Murray, 2022 [12]	2	1	1	1	1
Reis, 2021 [15]	2	1	1	2	1
Saunders, 2016 [16]	1	1	1	2	1
Humes, 2019 [17]	1	1	1	1	1
Moradi, 2017 [18]	2	1	1	1	1
Reynard, 2022 [21]	1	1	1	2	1
Zhang, 2023 [24]	2	1	1	1	1
Smith, 2016 [26]	1	1	1	1	1
Sullivan, 2013 [29]	1	2	2	1	2
Barcroft, 2011 [30]	1	1	1	1	1

ID	Confounding	Selection of participants	Classification of interventions	Deviations from interventions	Missing data	Measurement of outcomes	Selection of reported result
Koprowska, 2025 [13]	2	2	1	1	1	1	1
Koprowska, 2023 [14]	2	1	1	1	1	1	1
Dornhoffer, 2024 [19]	3	2	1	1	1	1	1
Muck, 2023 [20]	3	3	1	1	1	3	3
Yu, 2017 [22]	4	4	1	2	4	3	3
Lai, 2023 [23]	2	2	1	1	2	2	2
Sato, 2020 [25]	3	3	1	1	2	2	2
Miller, 2016(a) [27]	2	2	1	1	1	1	1
Kerneis, 2023 [28]	2	2	1	2	2	1	2
Miller, 2016(b) [31]	2	2	1	1	1	1	1
Hsieh, 2015 [32]	2	2	1	2	2	1	1
Fu, 2004 [33]	3	3	1	2	2	1	1

Table 4

Summary of characteristics of included studies on self-directed auditory rehabilitation

Study (yr)	Study design	Country	Device type	Sample size (interv/control)	Age (yr) (mean±SD)	SDAR type	Intervention description	Control description	Main outcomes	Key results	Follow-up
Tye-Murray (2022) [12]	RCT, cross-over	USA	CI, HA, Bimodal	96/0	8.4±1.9	Gamified AT	Auditory training (word/sentence tasks)	AV training	Speech & speechreading assessment	Significant improvements, mixed modality> pure modality	Immediate
Koprowska (2025) [13]	Controlled trial	Denmark	HA	10/9	71.7±5.1/69.4±5.5	AT	Phoneme training (schooLo)	Audiobook listening	Speech intelligibility at SNR50/80	Training group improvement (t=−2.87, p<0.05)	2 weeks
Koprowska (2023) [14]	Controlled trial	Denmark	HA	10/10	71.7±24.8/69.4±34.5	AT	Phoneme training (schooLo)	Audiobook listening	Phoneme, sentence clarity	Training group improvement in C1/V/C2 tasks	3 months
Reis (2021) [15]	Cross-over RCT	USA	CI	13/13	63.2±10.7	AT	Computer-based speech training	Computer-based visual training	Sentence, word identification	Auditory training improved dB thresholds	6 sessions
Saunders (2016) [16]	RCT	UK	HA	61/55/63/64	67.6–69.3	AT+counseling/education	LACE (DVD/computer)	Placebo/audio book/education	WIN, APHAP, HHI	Largest improvements with LACE	6 months
Humes (2019) [17]	RCT	USA	HA	13/15/15	54–80	AT	Training in noise	Active/passive control	CST, PHAP	Training group improved most, effects persisted	Up to 34 weeks
Moradi (2017) [18]	RCT	Sweden	HA	14/11	70.8±2.9	AT	Consonant/word discrimination	AO HINT	Speech discrimination	Significant improvements after training	1 month
Dornhoffer (2024) [19]	Prospective	USA	CI	43 (early)/22 (late)	64.4±15.7	Mixed/various	Computer-based training (multiple programs)	N/A	CNCw, AzBio sentences	Early users>late users in improvement	3 and 12 months
Muck (2023) [20]	Prospective, pilot	Germany	CI	12/N/A	8.8	Gamified AT	Tiptoi digital game	N/A	WRS, SSQ-P	Speech perception improved	1 month
Reynard (2022) [21]	RCT	France	CI	13/15	48/60	Gamified AT	Serious games (noise, word/phoneme)	No training	Speech-in-noise threshold	Training group improved	5 weeks
Yu (2017) [22]	Case study	USA	HA	1/1	68/52	Gamified AT	ReadMyQuips^™ AV training	HA only	fMRI, MLST-A	ROI activation, functional connectivity improved	Immediate
Lai (2023) [23]	3-arm trial	Singapore	None	20/21/23	66.7±4.6/66.2±5.8/67.3±6.1	AT+counseling/education	LACE auditory training	Active/passive control	QuickSIN, cognitive tasks	Significant improvement in auditory group	Immediate
Zhang (2023) [24]	RCT	China	CI	14/14	4.9±0.1/5.1±0.1	AT	HVPT training	No training	Identification, discrimination	Improved boundaries & between-category scores	10 weeks
Sato (2020) [25]	Single group	Japan	HA, CI	11/N/A	60.2±13.7	AT	Tablet-based AT (words, AV stimuli)	N/A	Intelligibility (trained/untrained)	Significant improvement (trained/untrained)	N/A
Smith (2016) [26]	Retrospective RCT	USA	HA	61/63/69/70	68.6–70.2	AT+counseling/education	LACE-C, LACE-DVD	Books-on-tape, education	WIN, HHIA/E, APHAP	Greatest gains with computer-based AT	Immediate
Miller (2016) [27]	Pre-post	USA	CI	9/5	55.3	AT	Computer-based high variability	N/A	Behavioral, MMN	Phoneme discrimination improved	N/A
Kerneis (2023a) [28]	Controlled trial	France	CI, Bimodal CI	15/16	51.1±15.3/42.5±17.9	AT	CI rehabilitation program	NH control	Consonant, vowel, SRT in noise	CI users improved after training	1 month
Sullivan (2013) [29]	RCT	USA	HA	8 (ATI)/8 (ATC)/8	12±3.6/11±3.6/11±2.8	AT	Auditory & visual training	N/A	HINT, SRT	Improved SRT post intervention	3 months
Barcroft (2011) [30]	RCT	USA	HA	35/34	67±17/64±18	AT	Multi-talker vs. single-talker training	N/A	Iowa Consonant, Build-A-Sentence	Significant in both groups, greater in multi-talker	N/A
Miller (2016b) [31]	Controlled trial	USA	CI	9/5	58.2/65.5	AT	Computer-based multi-talker discrimination	No training	Phoneme perception	Improved post intervention	N/A
Hsieh (2015) [32]	Controlled trial	Taiwan	HA	15/6	15–24/16–30	AT	CAST: computer-assisted speech training	No training	Speech recognition, COSI	Improved in both groups, greater for intervention	12 weeks
Fu (2004) [33]	Prospective	USA	CI	10/N/A	25–60	AT	Computer-based multi-talker AT	N/A	Vowel/consonant/HINT scores	All outcomes improved post intervention	2 weeks

SDAR, self-directed auditory rehabilitation; RCT, randomized controlled trial; CI, cochlear implant; HA, hearing aid; AT, auditory training; ATI, auditory training interrupted; ATC, auditory training continuous; LACE, Listening and Communication Enhancement; HVPT, High Variability Phonetic Training; AV, audiovisual; NH, normal hearing; AO, auditory only; HINT, Hearing in Noise Test; SRT, speech reception/recognition threshold; WIN, Words-in-Noise test; APHAP, Abbreviated Profile of Hearing Aid Performance; HHI, Hearing Handicap Inventory; CST, Connected Speech Test; PHAP, Profile of Hearing Aid Performance; CNCw, Consonant–Nucleus–Consonant words; WRS, word recognition score; SSQ-P, Speech, Spatial, and Qualities of Hearing Scale for Parents; fMRI, functional magnetic resonance imaging; MLST-A, Multimodal Lexical Sentence Test for Adults; QuickSIN, Quick Speech-in-Noise test; MMN, mismatch negativity; COSI, Client-Oriented Scale of Improvement.