Abstract
Digital interventions are increasingly used to support hearing aid users; however, evidence for first-time hearing aid users remains unclear. This systematic review and meta-analysis evaluated the efficacy and effectiveness of digital interventions to improve outcomes for first-time hearing aid users. The protocol was pre-registered (PROSPERO; CRD420251125785) and conducted in accordance with PRISMA 2020. PubMed, Scopus, and Web of Science were searched (January 2026). Eligible studies included randomized controlled trials, controlled clinical trials, and quasi-experimental studies evaluating internet-, app-, or web-based interventions. Outcomes were grouped into six domains: hearing aid use, benefit and satisfaction, hearing and communication, knowledge, skills and self-management, speech-in-noise performance, and psychosocial and emotional adjustment. Risk of bias was assessed using RoB 2 and ROBINS-I, and certainty of evidence using GRADE. Random-effects meta-analyses were conducted where ≥3 randomized trials reported comparable outcomes. Eleven publications (nine trials) were included. Most interventions focused on education, self-management, and counseling, with few targeting perceptual training. The most consistent improvements were observed in knowledge, skills and self-management (moderate-certainty). Evidence for hearing aid use, benefit and satisfaction, hearing and communication, and psychosocial and emotional adjustment was limited and inconsistent (low-certainty), while speech-in-noise evidence was of very low certainty. Meta-analyses of hearing aid use and IOI-HA outcomes showed no significant pooled effects. Digital interventions show the most consistent evidence for improving knowledge, skills, and self-management. Evidence for other outcomes remains limited and inconsistent. Clinicians may consider digital educational programs complementing standard care. Future research should prioritize larger, pre-registered trials with broader interventions and standardized outcomes.
Introduction
Acquired adult-onset hearing loss is a highly prevalent long-term condition, with nearly 430 million adults globally experiencing a disabling hearing loss (World Health Organization, 2025). Although hearing aids are the primary clinical intervention for managing hearing loss, up to 40% of adults fitted with hearing aids report inconsistent use or limited benefit (Barker et al., 2016). For many individuals, the early period following hearing aid fitting involves a complex adjustment process (Dawes et al., 2014; Ferguson et al., 2016b). First-time hearing aid users often encounter practical challenges such as device handling and maintenance, as well as perceptual difficulties related to sound quality and acclimatization to amplified sound (Dawes et al., 2014; McCormack & Fortnum, 2013; Wentzel et al., 2025). In addition, psychosocial factors, including expectation management, communication confidence, and adaptation to wearing hearing aids in daily life, may further influence successful hearing aid use and outcomes (Dawes et al., 2014; Ferguson et al., 2016b; McCormack & Fortnum, 2013; Wentzel et al., 2025). These ongoing challenges indicate that amplification alone is often insufficient to support optimal hearing-related and psychosocial outcomes, emphasizing the need for comprehensive approaches to audiological rehabilitation (Ferguson et al., 2019). Conceptually, comprehensive audiological rehabilitation is grounded in four core components, including sensory management, instruction, perceptual training, and counseling (Ferguson et al., 2019). In parallel with this broader rehabilitation framework, there has been a growing emphasis on person-centered and self-management approaches, which aim to empower individuals to take an active role in their hearing healthcare (Ferguson et al., 2019). Within this context, digital interventions, defined as structured programs delivered via web-based or mobile platforms, such as educational modules, auditory training, and self-management tools, have emerged as promising approaches to provide scalable, accessible, and cost-effective support for hearing aid users (Beukes et al., 2019; Paglialonga et al., 2018).
Despite the rapid growth of digital interventions in audiology, existing evidence offers limited insight into their efficacy and effectiveness for first-time hearing aid users specifically. For example, a Cochrane review evaluating interventions to promote hearing aid use in adults found only low- to very low-quality evidence for self-management and delivery system interventions and did not differentiate between first-time and experienced users (Barker et al., 2016). Similarly, a broader systematic review of internet-based interventions for adults with hearing loss, tinnitus, and vestibular disorders (Beukes et al., 2019) included some studies involving first-time hearing aid users but did not focus exclusively on this group. The authors reported substantial heterogeneity and called for reviews targeting distinct populations or conditions (Beukes et al., 2019). More recently, a mixed-methods systematic review examining engagement with digital interventions (Ravichandran et al., 2025) identified multiple factors influencing user engagement but did not assess the efficacy and effectiveness of these interventions. The authors emphasized the need for targeted research assessing outcomes directly, particularly for populations with specific needs, such as first-time hearing aid users (Ravichandran et al., 2025). While some interventions have shown positive outcomes among experienced users, it remains unclear whether these results generalize to individuals at the start of their hearing aid journey. For example, Thorén et al. (2015) reported improvements in communication outcomes following online rehabilitation for experienced users yet acknowledged that these findings may not generalize to individuals fitted with hearing aids for the first time. Similarly, a state-of-the-art review of eHealth across the adult hearing aid journey (Paglialonga et al., 2018) highlighted the growth of digital solutions across the hearing aid pathway but noted a lack of high-quality clinical evidence supporting their use in standard care.
This lack of targeted evidence is particularly concerning given the importance of the early post-fitting period for long-term success (Ferguson et al., 2016b), during which first-time hearing aid users commonly encounter specific challenges including acclimatization, device handling, expectation management, and psychosocial adjustment (Ferguson et al., 2019; Meijerink et al., 2020). Addressing this vulnerability requires interventions that are introduced early in the rehabilitation pathway and specifically target the foundational skills needed for successful hearing aid use. Evidence suggests that early educational interventions can strengthen key foundations of self-management, including knowledge and self-efficacy, thereby enhancing engagement with hearing rehabilitation (Gomez & Ferguson, 2020). For instance, C2Hear Reusable Learning Objects (RLOs), when delivered at the hearing assessment appointment, significantly improved self-efficacy and knowledge even before hearing aid fitting (Gomez & Ferguson, 2020). These RLOs incorporate animations, demonstrations, quizzes, and patient testimonials, elements grounded in vicarious and mastery experiences, which are among the strongest contributors to self-efficacy (Gomez & Ferguson, 2020). Early access to such interventions may therefore help first-time hearing aid users feel more confident and better equipped for hearing aid use, positively influencing adherence and benefit (Gomez & Ferguson, 2020). Although not exclusive to first-time hearing aid users, digital interventions like the SUpport PRogram (SUPR) have demonstrated improvement in long-term hearing aid satisfaction and self-efficacy among older adults (Meijerink et al., 2020). These findings, alongside promising outcomes from early-stage interventions like C2Hear (Gomez & Ferguson, 2020), suggest that digital tools may be particularly valuable during the early post-fitting adaptation period, when users are establishing consistent hearing aid usage patterns. However, there remains no systematic synthesis focused specifically on their efficacy and effectiveness for first-time hearing aid users.
The overarching research question was: What is the evidence for the efficacy and effectiveness of digital interventions in improving hearing aid outcomes among first-time adult hearing aid users? By focusing on first-time hearing aid users, this review addresses a critical gap in the literature by targeting a formative stage in the rehabilitation process when acclimatization challenges, handling difficulties, and unmet expectations can increase the likelihood of reduced adherence and long-term benefit (Ferguson et al., 2019; Meijerink et al., 2020). The findings will inform evidence-based clinical practice and support the development of timely, scalable digital interventions tailored to the needs of first-time hearing aid users.
Method
This systematic review was conducted in accordance with the Joanna Briggs Institute (JBI) Reviewer Manual for systematic reviews and is reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines (Page et al., 2021) (Supplementary Material 1). PRISMA 2020 guidelines provide a standardized framework to ensure transparent and complete reporting of systematic reviews (Page et al., 2021). The protocol was pre-registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251125785). As this study involved secondary analysis of published data and did not include human participants, ethical approval was not required.
Search Strategy
The primary author (MK) conducted a comprehensive literature search across three electronic databases: PubMed, Scopus, and Web of Science. The search strategy was informed by the Population-Concept-Context (PCC) framework and included keywords related to (1) the population of first-time hearing aid users, (2) the concept of digital or internet-based interventions, and (3) the context of hearing aid rehabilitation, support, or acclimatization. The search terms used were: (“new hearing aid user*” OR “first-time hearing aid user*”) AND (“digital” OR “internet-based” OR “internet” OR “web-based” OR “app-based” OR “online” OR “eHealth” OR “mHealth” OR “mobile”) AND (“rehabilitation” OR “support” OR “acclimatization” OR “intervention”). Searches were limited to studies published in English. No date restrictions were applied. The adult population criterion was operationalized during eligibility screening rather than through database search filters. The initial search was conducted on 22 August 2025, and the final search update was completed on 16 January 2026. In addition, the reference lists of all included studies were manually screened to identify any additional eligible studies.
Eligibility Criteria
Eligibility Criteria
Study Selection
All records retrieved from the database searches were imported into Covidence systematic review software (Covidence: Veritas Health Innovation, n.d.) and duplicate records were removed. Title and abstract screening was conducted independently and in a blinded manner by the primary author (MK) and a second reviewer (PP) against the predefined eligibility criteria (Table 1), with decisions compared within the Covidence platform after completion. All disagreements were resolved through discussion and consensus, and the agreed interpretation of the eligibility criterion was applied consistently to all remaining assessments.
Data Extraction
Data extraction was conducted by the primary author (MK) using a standardized data extraction form developed in Google Sheets. Extracted data included study identification details, study design, participant characteristics, description of the digital intervention, comparator(s), measures of adherence or use, and outcome measures. To ensure accuracy and completeness of the extracted data, a second reviewer (PP) independently cross-checked a random 40% sample of the extracted studies. Minor discrepancies in the level of detail extracted were identified and resolved through discussion. No substantive inconsistencies in outcome data were observed.
Data Synthesis
Study-Level Classification and Unit-of-Analysis Decisions
Studies were classified as evaluating efficacy or effectiveness using predefined criteria adapted from Gartlehner et al.’s (2006) framework distinguishing explanatory (efficacy) and pragmatic (effectiveness) trials. This framework considers key design features influencing external validity, including clinical setting, eligibility criteria, outcomes, intervention delivery, sample size, and use of intention-to-treat analysis (Gartlehner et al., 2006). Trials were categorized as efficacy when conducted under controlled laboratory conditions or designed as pilot or feasibility studies, and as effectiveness when embedded in routine clinical care, including broadly representative populations and patient-centered outcomes. Recognizing that explanatory and pragmatic features lie on a continuum, classification reflected the overall balance of methodological characteristics rather than strict dichotomization. For example, studies conducted in routine clinical settings with broad inclusion criteria but incorporating some controlled elements (e.g., structured intervention delivery) were classified as effectiveness trials based on their overall pragmatic orientation.
Where multiple studies arose from the same underlying trial, these were treated as a single unit of evidence for the purposes of evidence synthesis and interpretation to avoid unit-of-analysis errors and artificial inflation of precision. Linked studies were presented as separate rows in tables to ensure completeness of reported outcomes; however, conclusions were framed around the number of independent trials (n = 9) rather than the number of studies (n = 11).
Narrative Synthesis
Narrative synthesis was conducted in accordance with the Synthesis Without Meta-analysis (SWiM) reporting guidelines (Campbell et al., 2020). The formal synthesis was conducted by the primary author (MK) and cross-checked by all co-authors. All extracted outcomes were grouped into six predefined conceptual domains: (1) hearing aid use, (2) hearing aid benefit and satisfaction, (3) hearing and communication outcomes, (4) knowledge, skills and self-management, (5) speech-in-noise performance, and (6) psychosocial and emotional adjustment. Within each domain, studies were summarized in a structured narrative synthesis, ordered from newest to oldest, and including mean differences and standardized effect sizes, where available. Due to heterogeneity in outcome measures and reporting, results were synthesized narratively based on direction of effect, magnitude of reported effects, and statistical significance. For Randomized Controlled Trials (RCTs), direction of effect reflected whether outcomes favored the intervention or comparator group; for single-arm pre–post studies, direction of effect reflected change from baseline to follow-up. Inconsistency across studies was characterized narratively by examining variation in the direction, magnitude, and statistical significance of reported effects within each domain. Pre–post study designs were interpreted with caution, as observed changes may reflect hearing aid acclimatization rather than the specific effects of the intervention.
Quantitative Synthesis
Where at least three RCT studies reported comparable outcome measures, meta-analyses were conducted using RStudio (Version 2026.01.1+403; Posit Software). Four outcomes met these criteria: hearing aid use measured using objective data logging (hours/day), International Outcome Inventory for Hearing Aids (IOI-HA) hearing aid use, IOI-HA satisfaction, and IOI-HA quality of life. Several studies reported outcomes using the IOI-HA; however, reporting varied across studies, with some presenting total scores and others reporting individual items or subdomains. To enable cross-study comparison and quantitative synthesis of specific IOI-HA outcomes, corresponding authors were contacted via email to obtain individual IOI-HA item scores where these were not explicitly reported. Two corresponding authors were contacted and both of them responded within one month. The additional data provided were incorporated into the meta-analysis to ensure consistency in outcome reporting. No imputation was required for missing data. Random-effects models were used to account for potential between-study variability. Mean differences (MDs) with 95% confidence intervals (CIs) were calculated for all outcomes. Statistical heterogeneity was assessed using the I2 statistic and τ2. Sensitivity analyses were conducted using a leave-one-out approach to assess the robustness of pooled estimates.
Risk of Bias
Risk of bias assessments were conducted by the primary author (MK) using the revised Cochrane Risk of Bias tool for randomized trials (RoB2) and the Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) tool (Sterne et al., 2016, 2019). Both tools assess risk of bias across multiple domains using structured signaling questions to guide domain-level judgments, resulting in an overall risk of bias rating for each study (Sterne et al., 2016, 2019). A second reviewer (PP) also completed risk of bias assessments of a random 40% sample of the 11 included studies to ensure consistency and accuracy. All disagreements were resolved through discussion and consensus, and the agreed interpretative approach was applied consistently across all included studies.
Certainty of Evidence
The certainty of evidence for each outcome domain was assessed independently by two reviewers (MK and PP) using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach as recommended by the GRADE guidelines (Guyatt et al., 2008). Certainty was evaluated across five GRADE domains: risk of bias, inconsistency, indirectness, imprecision, and other considerations (e.g., publication bias). RCTs were initially rated as high-certainty evidence and were downgraded where concerns were identified. Where outcome domains included non-randomized or single-arm pre-post studies, certainty ratings were determined based on the overall body of evidence contributing to that domain. Certainty ratings were assigned for each of the six predefined outcome domains. Additional service-level and engagement outcomes were reported in a small number of studies; however, these were heterogeneous and not central to the predefined outcome domains and were therefore not included in the GRADE certainty assessment.
Results
Study Selection
The database searches identified a total of 436 records, including 387 from Scopus, 25 from Web of Science, and 24 from PubMed. After removal of 46 duplicate records (45 identified by Covidence and 1 identified manually), 390 records remained for title and abstract screening. Inter-rater agreement for title and abstract screening was 97.2% (11 conflicts out of 390 records), with all discrepancies resolved through discussion and consensus. Of these, 375 records were excluded based on title and abstract review. The main reasons for exclusion included ineligible populations (e.g., not first-time hearing aid users), absence of a digital intervention, and ineligible study designs (e.g., reviews and qualitative studies).
Fifteen full-text publications were subsequently assessed for eligibility. Inter-rater agreement for full-text eligibility assessment was 66.7%, reflecting five disagreements among the 15 publications assessed. Given the small number of full-text articles, this corresponds to a limited number of conflicts rather than poor agreement. Disagreements were resolved through discussion and primarily arose from ambiguity in determining first-time hearing aid user status when this was inferred rather than explicitly defined. In such cases, inference was based on contextual indicators including timing relative to initial fitting, and descriptions of participant experience (e.g., newly fitted users). These predefined criteria were applied consistently to guide inclusion decisions. Four studies were excluded at the full-text stage due to incorrect study design (n = 1) or an ineligible patient population (n = 3). No additional studies were identified through reference list screening in January 2026. In total, 11 publications met the inclusion criteria; however, these studies represent 9 independent trials, as three studies reported outcomes from the same underlying RCT (Ferguson et al., 2015, Ferguson et al., 2016a; Maidment et al., 2016) (Figure 1). PRISMA flow diagram summarizing the study selection process, including records identified, screened, assessed for eligibility, and included in the systematic review
Study Characteristics
Study Design and Participant Characteristics of Included Studies (n = 11 Publications; 9 Independent Trials)
Note. USA = United States of America; UK = United Kingdom; RCT = randomized controlled trial; NR = not reported; PTA = pure-tone average; PC = Personal Computer.
aOverall sample characteristics are reported in pre-post designs or where group-specific data were unavailable.
bParticipant characteristics are reported at the outcome evaluation when multiple time points were available.
cThree studies originate from the same underlying trial but are presented as separate rows, as they report different outcome measures, sample sizes, and/or analyses.
Across 11 publications, seven included a formal sample size justification or power calculation, whereas four did not provide any justification for the chosen sample size. Sample sizes varied substantially across studies, ranging from 10 to 343 participants. Participants were predominantly older adults, with mean ages ranging from approximately 60 to 76 years. Where reported, age ranges ranged from early adulthood to advanced age (approximately 20 to 94 years). Sex distribution was generally balanced across intervention and control groups. Better-ear pure-tone average (PTA) thresholds, reported in seven studies, were consistent with mild-to-moderate hearing loss, with mean values typically between 24 and 45 dB HL. Digital literacy or access to technology was explicitly described in 9 publications, including 4 studies where it was specified as an eligibility criterion and 5 studies where it was reported based on self-report or participant characteristics. Participants were generally required to have basic to high levels of digital competence, including access to a smartphone, computer, email, or internet, depending on the intervention modality.
Digital Interventions
Characteristics of Digital Hearing Interventions, Comparators, and Intervention Adherence Across Included Studies (n = 11 Publications; 9 Independent Trials)
Note. COSI = Client Oriented Scale of Improvement; HA = hearing aid; IDA = Ida Institute; mHealth = mobile health; PC = personal computer; SD = standard deviation; SNR = signal-to-noise ratio; NR = not reported.
aThree studies originate from the same underlying trial but are presented as separate rows, as they report different outcome measures, sample sizes, and/or analyses.
bAdherence and usage were reported using study-defined metrics (e.g., self-report, logs, per-protocol criteria), which varied across studies.
Only two of the 11 publications investigated audiovisual training, both of which targeted perceptual learning (Abrams et al., 2015; Rao et al., 2017). The remaining studies primarily focused on educational interventions related to hearing loss, hearing aids, communication strategies, and psychosocial aspects. With respect to timing and duration, most interventions were delivered exclusively post-fitting, one intervention was delivered pre-fitting (Gomez & Ferguson, 2020), and one intervention included both at-fitting and post-fitting components (Vassou et al., 2024). Intervention duration ranged from three weeks to 24 weeks.
Across the 11 publications, six interventions were self-guided, two interventions were clinician-guided, and three interventions were minimally guided. Prescribed dose and intensity differed substantially by intervention type. For example, educational and multimedia interventions generally involved brief video-based content, with total prescribed exposure ranging from approximately 40 to 60 minutes, whereas the auditory training intervention required higher engagement, prescribing ≥30 minutes per day, five days per week over three to four weeks. Personalization features were included in most studies, most commonly through user-selected content, goal-oriented frameworks, or adaptive task difficulty.
Comparators varied across studies. Seven studies included a usual care comparator (standard hearing aid fitting), one study used a printed educational booklet, one study used an audiobook/listening-practice control, and two studies employed a single-arm pre-post design without a comparator. Although some comparator conditions involved digitally delivered content (e.g., audiobooks), these were not considered digital interventions as they did not constitute structured rehabilitation programs targeting hearing-related outcomes. For example, in Rao et al. (2017), the intervention was an adaptive auditory training program, whereas the audiobook condition involved passive listening used as a control. Adherence and/or usage metrics were reported in eight studies, using study-defined measures, for example system-recorded access data or self-report usage logs. Direct comparison of adherence across studies was limited by heterogeneity in reporting methods and definition.
Outcome Measures
Outcome Measures and Direction of Effects of Digital Interventions for First-Time Hearing Aid Users
Note. Outcome measures are listed exactly as reported in the original studies and are classified as primary/main or secondary/alternative according to authors’ descriptions or emphasis in the methods and results. Only outcomes that were statistically tested at the group level are included. Outcomes reported descriptively only, not statistically tested, or analyzed solely at the individual-item level are not presented.
aSeveral studies did not explicitly specify primary outcomes. In these cases, outcomes were classified as primary/main based on authors’ stated aims, methods emphasis, and/or placement and emphasis in the Results.
bDirection of effects is indicated as follows: (+) and (−) indicate the direction of statistically significant effects, and ns indicates non-significant findings. For randomized and non-randomized controlled studies, (+) indicates that the intervention group was favored and (−) that the comparator group was favored. For pre–post (single-group) studies, (+) indicates a statistically significant improvement from baseline to follow-up and (−) indicates a statistically significant deterioration from baseline to follow-up.
cEffect sizes are reported only for statistically significant outcomes and only where explicitly provided in the original studies.
dThree studies originate from the same underlying trial but are presented as separate rows, as they report different outcome measures, sample sizes, and/or analyses.
eRao et al. (2017) reported additional electrophysiological and selective-attention outcomes (ERP measures), which were not extracted as they fall outside the audiological and functional outcome scope of this review.
fIndividual IOI-HA data obtained through correspondence with study authors.
Evidence landscape of digital interventions for first-time hearing aid users across outcome domains in 11 publications (9 independent trials)
Hearing Aid Use
Four studies assessed hearing aid use using objective data logging or self-reported measures, including the International Outcome Inventory for Hearing Aids (IOI-HA) use items and the Glasgow Hearing Aid Benefit Profile (GHABP) use subscale. Across effectiveness trials, between-group differences in overall hearing aid use were generally not observed. No significant group differences were reported for data-logged use in Lelic et al. (2025), Vassou et al. (2024), or Ferguson et al., 2016a. Similarly, GHABP hearing aid use did not differ significantly between groups in Ferguson et al., 2016a. However, subgroup analysis indicated significantly greater hearing aid use among suboptimal users (<70% baseline use) in the intervention group (d = 0.83). In Meijerink et al. (2020), IOI-HA hearing aid use scores favored the intervention group, although hearing aid use patterns did not differ significantly. Although overall use time did not differ between groups, Lelic et al. (2025) reported differences in sound environment exposure, with intervention participants demonstrating reduced exposure to low sound levels and increased exposure to medium sound levels. Overall, digital hearing interventions did not consistently increase overall hearing aid use compared with control conditions, although benefits were observed in specific subgroups and use patterns.
Hearing Aid Benefit and Satisfaction
Across five studies, hearing aid benefit and/or satisfaction were assessed using different self-reported outcome measures, including IOI-HA, the International Outcome Inventory for Alternative Interventions (IOI-AI), the Hearing Aid Rehabilitation Questionnaire (HEARLI-Q), the Client-Oriented Scale of Improvement (COSI), single-item overall satisfaction ratings, satisfaction of hearing aid use, the Satisfaction with Amplification in Daily Life (SADL), and GHABP benefit and satisfaction subscales. Across effectiveness trials, between-group findings were limited or mixed. Lelic et al. (2025) reported significantly greater improvements favoring the intervention group for IOI-HA total scores, HEARLI-Q satisfaction, and COSI degree of change and final ability, although no difference was observed for a single-item overall satisfaction rating. Meijerink et al. (2020) reported greater IOI-HA satisfaction in the intervention group; however, several IOI-AI domains favored the control group, while others were non-significant. No significant group differences were observed for satisfaction outcomes in Vassou et al. (2024) or for SADL, IOI-HA total scores, GHABP benefit, or GHABP satisfaction in Ferguson et al., 2016a. In the pre–post investigation by Arnold et al. (2022), COSI outcomes were reported descriptively with most participants indicating improvement, although statistically significant pre–post effects were not identified. Overall, digital hearing interventions demonstrated potential to improve hearing aid benefit and satisfaction in some studies; however, effects were not consistently observed across measures or study designs.
Hearing and Communication Outcomes
Five studies evaluated hearing and communication outcomes using instruments including the Hearing Handicap Inventory (HHI/HHIE/HHIE-S), the Communication Profile for the Hearing Impaired (CPHI), GHABP disability subscales, and the Social Participation Restrictions Questionnaire (SPaRQ).
In effectiveness trials, between-group effects were generally limited. Vassou et al. (2024) reported no group difference for HHI overall. Within the CPHI, non-verbal strategies favored the intervention group, whereas verbal strategies favored the control group. Similarly, Meijerink et al. (2020) found no significant between-group differences across CPHI domains or hearing disability subdomains. Ferguson et al., 2016a also reported no group differences for HHIE overall or GHABP residual disability.
In contrast, within-group improvements were observed in efficacy-type pre–post investigations. Arnold et al. (2022) reported significant improvement in HHIE-S scores. Ferguson et al. (2021) observed large improvements from baseline to follow-up across HHIE overall (d = 1.7), emotional (d = 1.2), and situational (d = 1.7) domains, as well as GHABP hearing disability (d = 1.7) and SPaRQ behavior (d = 1.6) and perception (d = 1.8). Overall, improvements in hearing-related disability and communication outcomes were more consistently observed in pre–post investigations than in controlled effectiveness trials.
Knowledge, Skills, and Self-Management
Seven studies (four independent trials) assessed knowledge, skills, and self-management using measures including the Telephone Use Questionnaire (TAQ), Measure of Audiologic Rehabilitation Self-Efficacy for Hearing Aids (MARS-HA), University of Rhode Island Change Assessment for Hearing Loss (URICA-HL), Ida Line Tool, Practical Hearing Aid Skills Test (PHAST), Patient Activation Measure (PAM), and the Hearing Aid and Communication Knowledge questionnaire (HACK). In pre–post investigations, significant improvements from baseline to follow-up were observed for TAQ (Arnold et al., 2022), MARS-HA domains (d = 0.5–1.1), and HACK domains (d = 0.8–1.3) in Ferguson et al. (2021).
Across effectiveness trials, several studies demonstrated improvements favoring the intervention group. Gomez and Ferguson (2020) reported significant improvements in HACK overall (d = 1.38), practical (d = 1.6), and psychosocial (d = 0.97) domains, as well as MARS-HA overall and handling subdomains. Improvements favoring the intervention group were also observed in Meijerink et al. (2020) for MARS-HA advanced handling and URICA-HL action stage, although other readiness domains were non-significant. In the RCT reported across three publications (Ferguson et al., 2015, Ferguson et al., 2016a; Maidment et al., 2016), significant improvements favoring the intervention group were consistently reported for HACK overall (d = 0.93–0.94), practical (d = 0.86–0.88), and psychosocial knowledge (d = 0.65–0.68). Ferguson et al., 2016a also reported improvements in PHAST overall performance and selected practical handling tasks, while PAM activation was non-significant. Overall, digital hearing interventions consistently improved hearing aid knowledge and practical skills, although broader self-management constructs such as readiness and activation showed more variable results.
Speech-in-Noise
Three studies assessed speech-in-noise performance using objective measures including the Quick Speech-in-Noise Test (QuickSIN), Hearing in Noise Test (HINT), and Words-in-Noise Test (WIN).
In pre–post analysis, Arnold et al. (2022) reported significant improvement in QuickSIN scores from baseline to follow-up. In effectiveness trials, Rao et al. (2017) observed significantly greater improvement in HINT performance favoring the intervention group (η2 = 0.48). In contrast, Abrams et al. (2015) reported no significant between-group differences for HINT or WIN. However, a significant dose–response relationship was identified, with greater hours of auditory training associated with improved WIN performance (r = −0.588). Overall, evidence for improvements in speech-in-noise performance following digital hearing interventions was limited and inconsistent.
Psychosocial and Emotional Adjustment
Three studies assessed psychosocial and emotional adjustment using measures including the Hearing Handicap and Disability Inventory emotional domain, CPHI psychosocial subscales, EuroQol-5 Dimension (EQ-5D-3L), and Hospital Anxiety and Depression Scale (HADS). In effectiveness trials, findings were heterogeneous. Vassou et al. (2024) reported improvements favoring the intervention group for several CPHI domains, including attitudes of others, maladaptive behaviors, acceptance of loss, anger, discouragement, and withdrawal, although need for problem awareness favored the control group. Meijerink et al. (2020) observed no group differences across psychosocial domains, and Ferguson et al., 2016a reported no significant between-group differences for EQ-5D-3L or HADS outcomes. Overall, digital hearing interventions demonstrated selective improvements in psychosocial domains in some studies, but findings were inconsistent across measures and trials.
Other Outcomes
Three studies reported additional outcomes including intervention engagement and service-level indicators. Arnold et al. (2022) reported no significant change in Visit-Specific Satisfaction Questionnaire (VSQ-9) scores. Meijerink et al. (2020) found no difference in recommendation of hearing aid dispensing services between groups. Maidment et al. (2016) reported significantly higher Reusable Learning Object (RLO) use in the intervention group. Overall, digital hearing interventions did not consistently influence service-level satisfaction or recommendations, although higher engagement with intervention materials was observed in one study.
Risk of Bias
Summary of Risk of Bias Assessments Using the RoB2, RoB2 for Cluster Randomized Trials and ROBINS-I
aThree studies originate from the same underlying trial but are presented as separate rows, as they report different outcome measures, sample sizes, and/or analyses.
Certainty of Evidence
Summary of Findings and Certainty of Evidence (GRADE)
Note. GRADE = Grading of Recommendations Assessment, Development, and Evaluation.
aAcross 7 studies from 4 independent trials.
bRisk of bias: Downgraded due to self-reported outcomes in unblinded participants, some concerns in allocation concealment, and inclusion of single-arm pre-post studies in some domains.
cInconsistency: Downgraded due to variability in direction and magnitude of effects across studies.
dImprecision (Speech-in-noise): Small total sample size and limited number of contributing trials.
eMultiplicity of outcomes and concentration of evidence within a small number of studies were noted as contextual considerations but did not result in downgrading of the certainty of evidence.
fParticipant counts reflect those assessed for each outcome and are not unique participants, as individuals within the same studies contributed data to multiple domains.
Meta-Analysis
Meta-analyses were conducted for outcomes reported by at least three RCTs using comparable measures. Four outcomes met these criteria: hearing aid use measured using data logging, IOI-HA hearing aid use, IOI-HA satisfaction, and IOI-HA quality of life. Forest plots are shown in Figure 3. Across all analyses, pooled estimates showed no statistically significant differences between digital intervention and control groups. Effect sizes were small and confidence intervals crossed the null in all cases. Statistical heterogeneity was low to moderate across outcomes. For data logging hearing aid use, heterogeneity was moderate (I2 = 40.1%; τ2 = 0.99), whereas heterogeneity was negligible for IOI-HA hearing aid use, satisfaction, and quality of life (all I2 = 0.0%; τ2 = 0.0). Given that only three studies contributed to each analysis, heterogeneity estimates should be interpreted with caution. Leave-one-out sensitivity analyses indicated that pooled estimates were stable, with all analyses remaining non-significant and confidence intervals consistently crossing zero, supporting the robustness of the primary findings (Supplementary Material 5). Although pooled effects were small and not statistically significant, and confidence intervals crossed the null, clinically meaningful effects cannot be excluded, particularly given the modest sample sizes across studies. Forest plots of meta-analyses for selected hearing aid outcomes. (A) Hearing aid use (data logging). (B) IOI-HA hearing aid use. (C) IOI-HA satisfaction. (D) IOI-HA quality of life. Pooled effects were estimated using random-effects models. Squares represent individual study estimates weighted by inverse variance, horizontal lines indicate 95% confidence intervals, and diamonds represent pooled estimates. Positive mean differences (MD) indicate outcomes favoring the digital intervention group, whereas negative mean differences indicate outcomes favoring the control group
Discussion
The systematic synthesis of evidence from nine independent trials across 11 publications demonstrated a clear gradient in the certainty and consistency of digital intervention effects across outcome domains. Digital interventions most consistently improved hearing aid-related knowledge, skills, and self-management, supported by moderate-certainty evidence for the estimated intervention effect. Effects on hearing aid use, hearing aid benefit and satisfaction, hearing and communication outcomes, and psychosocial and emotional adjustment were limited and inconsistent, supported by low-certainty evidence. Evidence for speech-in-noise outcomes was of very low certainty, reflecting the small number of contributing studies, heterogeneous outcome measures, and risk of bias concerns. These findings suggest that digital interventions consistently supported knowledge and self-efficacy development, but that translating these gains into sustained changes in hearing aid use and psychosocial outcomes remains an open question.
An important consideration when interpreting these findings is the type and content of digital interventions evaluated across studies. Most interventions were primarily educational, focusing on self-management and counseling, with limited emphasis on audiovisual training targeting perceptual learning and speech-in-noise processing. This imbalance likely contributed to the observed pattern of outcomes. Educational approaches are well suited to improving knowledge, skills, and self-efficacy, whereas outcomes such as hearing aid use, speech-in-noise performance, and psychosocial adjustment are influenced by more complex behavioral and perceptual factors. These findings suggest that the effectiveness of digital interventions is closely tied to their underlying content and mechanisms of action, and that future intervention development should more deliberately align intervention components with the specific outcomes they aim to influence (Ferguson et al., 2019). For example, educational and counseling-based interventions may be better suited to improving self-management and hearing aid skills, whereas speech-in-noise performance may require auditory or audiovisual training approaches, and psychosocial adjustment may benefit more from intensive behavioral or social support interventions.
Consistent with this, the strongest evidence across studies was observed in the domain of knowledge, skills and self-management. Digital interventions consistently improved participants’ understanding of hearing aids, device handling skills, and confidence in managing their devices, although broader self-management constructs such as readiness for change and patient activation showed more variable results. This pattern is consistent with the predominantly educational focus of many digital interventions, as also noted in a broader review of eHealth services for hearing aid users (Paglialonga et al., 2018). The multimedia format of educational digital interventions, such as C2Hear, may also facilitate procedural learning, particularly for device handling tasks that are difficult to convey through written instructions alone (Ferguson et al., 2016a). Evidence from the SUPR intervention further suggests that improvements in self-efficacy may be sustained over time and may extend to more advanced hearing aid handling skills (Meijerink et al., 2020).
Knowledge and self-efficacy have been identified as key modifiable predictors of successful hearing aid self-management (Convery et al., 2019). Improvements in these domains may therefore represent an important mechanism through which digital interventions support users in developing the confidence and skills needed to manage their hearing aids effectively. Digital interventions may also be beneficial earlier in the rehabilitation pathway: Gomez and Ferguson (2020) demonstrated that exposure to C2Hear significantly improved self-efficacy prior to the fitting appointment, suggesting that digital tools delivered early in the hearing aid journey may help prepare individuals for hearing aid adoption and support the development of hearing aid management skills. However, much of the evidence in this domain originates from a small number of related studies evaluating the C2Hear programme specifically (Ferguson et al., 2015, Ferguson et al., 2016a; Maidment et al., 2016), and the moderate certainty of evidence is best understood as applying to this type of multimedia educational intervention rather than to digital interventions broadly. Whether comparable effects would be observed with other platforms, such as app-based counseling tools, motivational programs, or telehealth-delivered support, remains to be established.
Digital interventions did not consistently translate into improvements in hearing aid use, benefit, or satisfaction across studies, a finding reinforced by the meta-analyses of objectively measured hearing aid use and IOI-HA outcomes, which showed no significant pooled effects. This is consistent with the Cochrane review by Barker et al. (2016), which reported low- to very low-quality evidence for interventions designed to promote hearing aid use, with generally small and uncertain effects across behavioral and patient-reported outcomes. Hearing aid use, benefit, and satisfaction are influenced by multiple audiological and non-audiological factors (Mothemela et al., 2023), which may explain why time-limited digital interventions have not demonstrated consistent effects on these outcomes. The lack of significant effects may also reflect limited variability in intervention timing, with most delivered post-fitting. In addition, substantial heterogeneity also existed across studies in adherence reporting, intervention duration, prescribed dose, degree of clinician involvement, and engagement strategies. Intervention duration ranged widely from 3 to 24 weeks, while prescribed dose varied from brief educational modules to intensive auditory training programmes requiring regular daily engagement. The degree of clinician involvement also differed considerably, ranging from entirely self-guided interventions to clinician-guided counseling and remote follow-up support. Engagement strategies included quizzes, adaptive tasks, reminders, personalised listening goals, and communication-partner involvement. Adherence reporting was inconsistent across studies, although some interventions demonstrated reduced engagement over time. These differences likely influenced intervention exposure, participant engagement, and the outcomes most likely to be affected.
Nevertheless, some evidence suggests that digital interventions may benefit specific subgroups or on specific dimensions of hearing aid use. Ferguson et al., 2016a reported greater improvements in hearing aid use among participants classified as suboptimal users at baseline, and Meijerink et al. (2020) observed short-term gains following the SUPR intervention, though these were not sustained at longer follow-up, highlighting the potential need for ongoing support to maintain intervention effects. In addition, Lelic et al. (2025) reported differences in sound environment exposure despite similar overall use time, suggesting that digital interventions may influence how hearing aids are used rather than simply increasing total hours of wear. Similarly, evidence for improvements in hearing aid benefit and satisfaction was mixed. Although some trials reported positive effects favoring digital interventions (Lelic et al., 2025; Meijerink et al., 2020), several studies found no significant differences between intervention and control groups (Ferguson et al., 2016a; Vassou et al., 2024). These mixed findings may partly reflect the multifactorial nature of hearing aid benefit and satisfaction as well as the wide range of outcome measures used (Mothemela et al., 2023).
Evidence for improvements in hearing and communication outcomes was also limited and inconsistent, with significant improvements primarily observed in pre–post investigations (Arnold et al., 2022; Ferguson et al., 2021). In the absence of control groups, improvements observed in single-arm pre-post studies cannot be attributed to the digital interventions. Equivalent or greater improvements in communication outcomes are well-documented in first-time hearing aid users who receive no structured intervention beyond standard fitting, consistent with established patterns of auditory acclimatization over the first weeks and months of device use (Dawes et al., 2014; Wentzel et al., 2025). These within-group changes, including adaptation to amplified sound, increasing familiarity with device handling, and the gradual development of communication strategies, represent a natural trajectory of hearing aid adjustment rather than evidence of intervention efficacy. Accordingly, findings from pre-post designs in this domain should be interpreted as largely reflecting feasibility and acceptability rather than causal effectiveness.
Similarly, evidence regarding psychosocial outcomes was also limited and mixed. Psychosocial and emotional adjustment to hearing aid use involves complex processes including identity adaptation, stigma management, and changes in communication behavior (Wallhagen, 2010). While digital interventions may support aspects of hearing aid management, psychosocial and emotional adjustment at least in some users may require more comprehensive behavioral or counseling interventions involving communication partners and social support networks (Barker et al., 2017), elements that were not prominent features in the included interventions. In addition, many of the included interventions were relatively short in duration and primarily self-directed, which may limit their ability to influence longer-term psychosocial adaptation. These outcomes may also be less sensitive to change in the early stages of hearing aid use, further complicating the detection of meaningful effects within typical study timeframes.
Only three studies assessed speech-in-noise performance and findings were limited and inconsistent. Improvements were observed in a pre-post investigation (Arnold et al., 2022) and in one effectiveness trial reporting greater improvements favoring the intervention group (Rao et al., 2017). In contrast, Abrams et al. (2015) found no significant between-group differences in speech-in-noise outcomes. However, a dose-response relationship was identified, with greater hours of auditory training associated with improved performance on the WIN test, suggesting that intervention engagement may influence outcomes. This finding aligns with a recent systematic review highlighting the importance of engagement for the effectiveness of digital interventions (Ravichandran et al., 2025). Moreover, as highlighted in this review, there have been limited efforts to design and evaluate auditory and/or audiovisual training interventions targeting perceptual learning within digital interventions for first-time hearing aid users. This is despite emerging evidence supporting the use of computerized auditory training for individuals with hearing loss (Henshaw & Ferguson, 2013).
A notable finding of this review was the substantial heterogeneity in outcome measures used across studies. This lack of standardization presents a major challenge for synthesizing evidence in this field. Even when similar instruments were used, differences in scoring approaches limited comparability. For example, while the IOI-HA was used in multiple studies, some studies analyzed total scores whereas others focused on individual subscales. The absence of standardized outcome measures for evaluating hearing aid support interventions has been noted in several previous reviews (Barker et al., 2015; Beukes et al., 2019; Ferguson et al., 2019). Development of core outcome sets for hearing aid intervention trials may help improve comparability and facilitate more robust synthesis of evidence in future research.
Several limitations should be considered when interpreting the findings of this review. The number of available trials remains relatively small, and many studies had modest sample sizes, limiting statistical power and precision of effect estimates. Evidence for several outcome domains was derived from only a few studies, which reduces confidence in the consistency and robustness of conclusions. Most RCTs were judged as having some concerns in terms of risk of bias, primarily due to insufficient reporting of allocation concealment, lack of trial registration or pre-specified analysis plans, and reliance on self-reported outcomes in unblinded participants. These limitations introduce potential risks of performance, detection, and selective reporting bias, which may have influenced the observed effects. Non-randomized and pre-post studies were at serious risk of bias due to the absence of control groups and potential confounding, limiting causal inference. In addition, some of the available evidence originates from a small number of research groups, which may limit generalizability across different clinical settings, populations and digital interventions. Follow-up periods were also relatively short in many studies, limiting insight into the longer-term effects of digital interventions.
Conclusion
Digital interventions designed to support first-time adult hearing aid users predominantly focused on education, self-management, and counseling, with limited emphasis on perceptual learning. These studies show the most consistent evidence for improving hearing aid related knowledge, skills and self-management, supported by moderate-certainty evidence. In contrast, evidence for improvements in hearing aid use, benefit and satisfaction, hearing and communication, and psychosocial and emotional adjustment was limited and inconsistent. Clinicians may consider structured digital educational programs, particularly multimedia tools delivered early in the fitting pathway, as a complement to standard hearing aid fitting for new users. Future research should prioritize larger, pre-registered trials evaluating a broader range of digital interventions (e.g., inclusion of auditory and audiovisual training) with longer follow-up periods, behavioral outcomes (e.g., speech in noise), and greater standardization of outcome measures to enable more robust evidence synthesis.
Supplemental Material
Supplemental Material - Digital Interventions for First-Time Hearing Aid Users: A Systematic Review and Meta-Analysis of Efficacy and Effectiveness
Supplemental Material for Digital Interventions for First-Time Hearing Aid Users: A Systematic Review and Meta-Analysis of Efficacy and Effectiveness by Megan Kruger, Preeti Pandey, Vinaya Manchaiah, and De Wet Swanepoel in Trends in Hearing
Footnotes
Acknowledgements
We used ChatGPT (OpenAI, San Francisco, CA, USA) solely to improve the clarity, readability, and grammatical accuracy of the manuscript text. The assistive AI tool did not contribute to the study design, conceptualization, data analysis, interpretation of results, or original drafting of scientific content. All outputs were critically reviewed and edited by the authors, who take full responsibility for the integrity and accuracy of the manuscript.
Ethical Considerations
This systematic review did not involve human participants or the collection of primary data and therefore did not require ethical approval. All data were derived from previously published studies, which were assumed to have obtained appropriate ethical clearance.
Consent to Participate
This study did not involve human participants; therefore, informed consent was not required.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Data Availability Statement
The datasets generated during and/or analyzed during the current study are available from the corresponding author on request.
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References
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