Deaf and hard-of-hearing (DHH) individuals using cochlear implants (CIs) often have regular jobs or enroll in mainstream education where they face complex social challenges. While first HCI interventions targeted this group's communication skills, or compensated for limited sound perception, we instead focused on experiential aspects like fatigue and feeling different from others. We moved beyond individual-focused design by engaging interaction-partners to share responsibility for overcoming social barriers. This work identifies generative, intermediate-level design knowledge, addressing common interaction-level challenges. A design-oriented, thematic analysis of interviews with 14 CI users revealed four subsequent themes: invisible, shifting hearing demands; misunderstandings and social impact; strategies for managing interaction barriers; and emotional, relational costs. Mapping these themes to HCI concepts like seamfulness, social translucence, and proxemics highlights open-ended, concrete design opportunities that support socializing beyond functional access. Framing interaction success as shared responsibility broadens inclusive design discourse for DHH populations and wider disability design spaces.

OBJECTIVES: The pupil dilation response is often used as a physiological measure of listening effort. One way to manipulate listening effort is to manipulate intelligibility. Only a few studies assessed the relationship between intelligibility and the pupil dilation response in cochlear implant (CI) users. Those studies did not consistently replicate the effects of intelligibility on the pupil dilation response evoked by sentence recognition in noise as observed in individuals with typical hearing or hard of hearing. Therefore, this study examined the effects of intelligibility on the pupil dilation response in CI users using several types of speech material. The type of masker is also known to influence listening effort as measured by pupillometry in individuals with typical hearing and hard of hearing. To our knowledge, this is not yet investigated in CI users. Therefore, this was also assessed in the current study. Finally, to account for subjective experiences, ratings of listening effort, difficulty, performance, and tendency of giving up were assessed. DESIGN: Twenty-eight postlingually deafened adult unilateral or bimodal CI users participated. Their ages ranged from 41 to 71 yrs old (mean = 58.4). A 3 × 3 within-subjects design was used with 3 intelligibility conditions (quiet, 50%, and 20% intelligibility in continuous noise) and 3 types of speech material (digit triplets, consonant-vowel-consonant [CVC] words, everyday sentences). Linear mixed model analyses assessed the effects of speech material and intelligibility condition on the mean pupil dilation (MPD), peak pupil dilation (PPD), and baseline pupil size (BPS). A paired sample t test was used to compare the effect of masker type (continuous noise versus a single interfering speaker) on these pupil measures for 50% sentence intelligibility. For all conditions, participants rated their experienced listening effort, difficulty, performance, and tendency of giving up. RESULTS: In the main analysis (N = 23), MPD, PPD, and BPS differed between the speech materials, but these measures did not depend on speech intelligibility. CVC words elicited the lowest MPDs and PPDs, followed by digit triplets and everyday sentences, with the latter showing the most pronounced pupil responses. The BPS was larger for sentences compared with CVC words and digit triplets. CVC words and sentences were rated as the most effortful and difficult, with the lowest self-perceived performance, and evoking the highest tendency to give up. Self-perceived performance was furthermore influenced by intelligibility (quiet > 50% > 20%). The other subjective ratings, such as listening effort, decreased with increasing intelligibility. A separate analysis on the data for the digit triplet material, including all CI users (n = 28), showed an intelligibility effect on the PPD. Finally, the analysis (N = 15) of the effect of masker type showed that PPDs and BPSs were larger for sentences masked with an interfering speaker compared with continuous noise. CONCLUSIONS: The intelligibility conditions in this study did not result in any measurable differences in listening effort, as indicated by the pupil dilation responses of unilateral or bimodal postlingually deafened CI users for everyday sentences or CVC words. A main effect of intelligibility condition on PPD was only found for digit triplets. Speculatively, this may be because the relative simplicity and low cognitive load evoked by this speech material allowed intelligibility effects to become apparent in this specific group of listeners. Subjective ratings indicated greater listening effort, difficulty, and a tendency to give up at lower intelligibility levels. When sentences were masked with an interfering speaker, both PPD and subjective listening effort increased compared with masking with continuous noise. These findings suggest that manipulating masker type can alter the pupil dilation response and perceived listening effort in CI users, even when using everyday sentences.

Modeling psychophysical auditory detection has proven to be difficult, as with existing neural models and detection models, we were unable to adjust the slope of the psychometric curve accurately. In machine learning, the softmax function is an excellent tool to assign probabilities to model outputs. Incorporating this function into psychophysical detection models can enhance the precision of the auditory detection model. This study extended Hamacher’s detection model by integrating a softmax function, providing additional control over the slope of psychometric curves.•Using computational simulations of both normal and electric hearing, we applied this enhanced model to two psychophysical tasks: masker-probe detection and amplitude modulation detection.•The outcomes demonstrated that the normal hearing model aligned closely with expected performance, with predictable shifts in psychometric curves as the noise and slope parameters varied. In addition, with the electric hearing model, the new detection model could now reach lower asymptotes in the psychometric curve than with Hamacher’s detection model.•These findings suggest that incorporating the softmax function provides a flexible tool for modeling auditory psychophysical data. This tool has potential applications for in silico evaluation of speech coding strategies for cochlear implants.

Introduction: Cochlear implantation (CI) is the standard treatment for severe-to-profound sensorineural hearing loss, but CI users often struggle with speech understanding in noisy environments. The Dutch/Flemish Matrix test is frequently used to evaluate speech-in-noise performance due to its assumed immunity to learning effects. However, studies challenge this assumption, revealing significant learning effects that can confound research outcomes. In this study, we modeled the learning curves of the Dutch/Flemish Matrix test to assess the influence of both between-session and between-test effects. We hypothesized that a exponential model would describe the learning effects more accurately than a linear model. Methods: The perceptual learning effects associated with the Dutch/Flemish Matrix test were assessed in 17 bimodal CI users. All participants performed the Matrix speech-in-noise tests across four sessions, with 13 randomized tests per session. The tests were conducted in a soundproof booth with an eight-speaker babble noise. The outcome parameter was the speech recognition threshold and was analyzed with a linear mixed model to account for confounders. Results: The results showed a statistically significant learning effect between sessions that added up to a speech intelligibility increase of 1.3 dB signal-to-noise ratio (SNR) (equivalent to ∼10% word score) between the first and second sessions, 0.86 dB SNR (∼7%) between the second and third sessions and 0.67 dB SNR (∼5%) between the third and fourth sessions. In addition, a statistically significant within-session learning effect (i.e., between tests) was observed with a linear slope of −0.11 dB SNR/test (∼0.9% word score/test), which accumulates to a total of 1.7 dB SNR (13%) between session start and end. The between-session learning curve was described more accurately with an exponential fit than with a linear fit. The between-test learning curve can be described equally well with a linear and an exponential fit. Conclusion: A robust between-test learning effect was observed, which could be accurately modeled using either a linear or exponential learning curve. Additionally, a between-session learning effect was evident and was best described by an exponential learning curve. This study provides an important handle for correcting these learning effects in future studies.

Objective and Design: With this cross-sectional study, we aimed to assess whether cochlear implant (CI) users have different occupational well-being than individuals with hearing loss (HL) without CI (HL group) and those with typical hearing (TH). We used validated questionnaires to assess all outcomes. Study sample: We included 98 CI users (mean age 51 y), 52 HL group participants (mean age 49 y) and 54 TH group participants (mean age 46 y). Results: Capabilities, physical and psychosocial working conditions were similar overall across the three groups. However, compared to the HL group, the CI group had significantly better outcomes on a range of variables, reporting fewer psychosomatic symptoms, better health, higher acceptance of their HL, better verbal coping strategies, fewer interruptions during work, and lower perceived noise level. There were no variables indicating that CI users performed worse than their peers from the HL group. Conclusions: Overall, CI users show occupational well-being and capabilities comparable to those of other groups. However, CI users appear to be more advanced in their progress towards acceptance of their HL, use of verbal coping strategies, are better adjusted at work, and report better health than individuals with HL without a CI.

As more deaf and hard of hearing (DHH) students attend mainstream schools, understanding how physical and social environments can support their social inclusion becomes increasingly critical. Limited access to informal, unstructured peer interactions like those occurring during recess – important contexts for developing a social life at school – is a key challenge. This study makes three main contributions: (1) Synthesizing interdisciplinary research on DHH students' individual capabilities relevant to social participation through a narrative review, framed within school contexts using affordance theory. (2) Developing a novel affordance-based, conceptual framework that shows how DHH students’ opportunities for social participation arise from dynamic interactions between capabilities and school environment. (3) Creating a practical tool to support school evaluation and intervention planning by stakeholders without extensive DHH experience, and guiding future DHH affordance research. Findings demonstrate how DHH sensory, cognitive, and psychological capabilities interact with situational and environmental factors, including built spaces, group dynamics, and stigma. The framework also emphasizes how social experiences can, in turn, shape DHH capabilities over time. Supporting practical implementation, a DHH capability-environment matrix tool was developed, providing a visual means to map affordance relationships and systematically identify school barriers to social interaction. By reframing DHH inclusion through an affordance lens, this work shifts focus from individual limitations to systemic and environmental contributors to exclusion, situating deafness within a broader spectrum of diversity. The paper concludes with implications for advancing affordance research in environmental psychology and outlines directions for further development and evaluation of the matrix in school settings.

Introduction: Computational modeling of cochlear implant stimulation has a long history, but its development has mostly been restricted to generic models, with patient-specific modeling being relatively rare, in spite of its potential applications in both research and clinical practice. Areas covered: The present state of computational cochlear implant models is discussed in relation to patient-specific modeling. From three-dimensional geometries derived from clinical imaging to full end-to-end models of the electrically stimulated peripheral auditory system, computational cochlear implant models have progressed to the point where they can meaningfully simulate responses to complex (speech) stimuli. Expert opinion: The development of patient-specific models that could be used to study the underlying mechanisms of cochlear implant functioning and ultimately be applied to make clinical diagnoses and recommendations, is within reach. However, there are still obstacles to overcome; the most immediate of these is the issue of auditory neural health, which is currently impossible to definitively assess in a living subject, yet has profound effects on electrical stimulation.

Objective: To determine correlations between speech recognition thresholds (SRTs) for everyday sentences compared to Matrix sentences and digits-in-noise (DIN) triplets. Design: Comparative analysis of SRTs across three speech materials in both cochlear implant (CI) users and typical hearing (TH) listeners, using linear regression and analysis of covariance. Study Sample: 18 experienced CI users (mean age 63 ± 5 years) and 18 age-equivalent TH listeners (mean age 62 ± 12 years), all naive to the test materials. Results: SRTs of Matrix sentences and everyday sentences correlated significantly (R²: 0.81 for CI, 0.71 for TH), as did SRTs of DIN triplets and everyday sentences (R²: 0.42 for CI, 0.28 for TH). Regression slopes did not differ significantly between CI and TH groups in either comparison. However, intercepts differed significantly between the CI (−2.65) and TH (−6.70) groups for the DIN triplets, but not for the Matrix sentences. Slopes for the DIN triplets deviated significantly from unity for both groups. Conclusions: Dutch/Flemish Matrix sentence SRTs closely correlate with everyday sentence SRTs for both CI users and TH listeners, establishing it as a reliable alternative for repeated assessment. DIN triplet SRTs showed weaker correlations with everyday sentences and with significant intercept differences between groups.

Objective and design: This cross-sectional study aimed to compare occupational performance of cochlear implant (CI) users to that of adults with hearing impairment without CI and those with normal hearing (NH). We used the Amsterdam Checklist for Hearing and Work to assess job characteristics, hearing activities, need for recovery and other outcomes. Study sample: We included 204 adults: 98 CI users (mean age 51), 52 participants with hearing impairment, without CI (HI group, mean age 49) and 54 participants with NH (NH group, mean age 46). Results: Job characteristics were similar between the groups, but the CI and HI groups were significantly more likely to report (effortful) communication in noise compared to the NH group. Need for recovery was significantly higher in the HI than in the NH group, but the CI and NH groups showed no significant difference. The CI group needed less guidance in managing their hearing loss in the workplace than the HI group did. Conclusions: The relatively favourable outcomes for CI users in need for recovery and reduced need for guidance at work may be due to the extensive training and counselling they received as part of their rehabilitation program.

Objective: Measuring listening effort using pupillometry is challenging in cochlear implant (CI) users. We assess three validated speech tests (Matrix, LIST, and DIN) to identify the optimal speech material for measuring peak-pupil-dilation (PPD) in CI users as a function of signal-to-noise ratio (SNR). Design: Speech tests were administered in quiet and two noisy conditions, namely at the speech recognition threshold (0 dB re SRT), i.e. the SNR where speech intelligibility (SI) was 50%, and at a more favourable SNR of +6 dB re SRT. PPDs and subjective ratings of effort were obtained. Study sample: Eighteen unilaterally implanted CI users. Results: LIST sentences revealed significantly different PPDs between +6 and 0 dB re SRT and DIN triplets between quiet and +6 dB re SRT. PPDs obtained with the Matrix test were independent of SNR and yielded large PPDs and high subjective ratings even in quiet. Conclusions: PPD is a sensitive measure for listening effort when processing LIST sentences near 0 dB re SRT and when processing DIN triplets at more favourable listening conditions around +6 dB re SRT. PPDs obtained with the Matrix test were insensitive to SNR, likely because it is demanding for CI users even in quiet.

Many speech coding strategies have been developed over the years, but comparing them has been convoluted due to the difficulty in disentangling brand-specific and patient-specific factors from strategy-specific factors that contribute to speech understanding. Here, we present a comparison with a ‘virtual’ patient, by comparing two strategies from two different manufacturers, Advanced Combination Encoder (ACE) versus HiResolution Fidelity 120 (F120), running on two different implant systems in a computational model with the same anatomy and neural properties. We fitted both strategies to an expected T-level and C- or M-level based on the spike rate for each electrode contact’s allocated frequency (center electrode frequency) of the respective array. This paper highlights neural and electrical differences due to brand-specific characteristics such as pulse rate/channel, recruitment of adjacent electrodes, and presence of subthreshold pulses or interphase gaps. These differences lead to considerably different recruitment patterns of nerve fibers, while achieving the same total spike rates, i.e., loudness percepts. Also, loudness growth curves differ significantly between brands. The model is able to demonstrate considerable electrical and neural differences in the way loudness growth is achieved in CIs from different manufacturers.

Devising a psychophysical test to assess spectral resolution has not been easy. Two tests that have been used previously are the spectral ripple test and the spectral-temporally modulated ripple test (SMRT). Over time, questions have been raised about the validity of these tests. We introduce a new computational electric hearing (with a cochlear implant, CI) model that can simulate how sound is transferred through a speech processor and is received by the cochlear nerve fibers. With this electric hearing model and a normal hearing model, we investigated whether the known limitations of these tests can be detected. For the spectral ripple test, we could show the limitations in the output of the CI, the information conveyed to the cochlear nerve, to estimate the threshold, and show the benefit of current steering. In addition, we reproduced the aliasing effect with normal hearing in the SMRT, as well as the reduced ripple resolution in CI users. Our computational modeling framework can serve as a first-step assessment of the validity of new psychophysical tests. Moreover, it could be used to test new speech coding strategies.

Objective: To assess the impact of cochlear implantation (CI) and speech perception outcomes on the quality of life (QoL) of adult CI users and their communication partners (CP) one-year post-implantation. Design: This research is part of a prospective multicenter study in The Netherlands, called SMILE (Societal Merit of Intervention for hearing Loss Evaluation). Study sample: Eighty adult CI users completed speech perception testing and the Nijmegen Cochear Implant Questionnaire (NCIQ). Fifty-four CPs completed the Hearing Impairment Impact–Significant Other Profile (HII-SOP). Results: CI resulted in a large improvement in the QoL of both users and CPs. Despite this, some users still reported difficulties in the NCIQ sub-domains Social Interactions, Activity Limitations and Self-esteem. Similarly, some CPs still reported moderate and severe third-party disability on the HII-SOP. Additionally, the correlation between speech perception results and self-reported QoL was weak to negligible for both groups. Conclusions: Speech perception in quiet is not an accurate measure of real-life success with a CI. A subset of CI users and CPs still experience substantial QoL challenges regardless of speech perception performance. To improve counselling and intervention, QoL measures should be a standard part of the CI care pathway for CI users and their CPs.

Objectives: Cochlear implants (CIs) are the primary treatment for severe-to-profound hearing loss. For CI users, speech intelligibility (SI) is often excellent in quiet yet degrades dramatically in background noise. Scientific and clinical testing of the effects of noise on SI is routinely performed with speech-in-noise tests. The sensitivity of these tests to signal to noise ratio depends on the slope of their psychometric curve. This slope is not always known for CI users, and direct comparisons between typical hearing (TH) listeners and CI users are lacking. Design: We present a comparative study of a digit test (DIN), a Matrix sentence test, and an everyday sentence test (LIST) for a group of CI users and TH listeners, with use of word (digit) and sentence (triplet) scoring in the free field. We report descriptive statistics and effect size measures of the psychometric slope and the speech reception threshold (SRT) for each speech test. Results: For CI users, the slopes of the psychometric curve were significantly shallower and SRTs significantly higher than those of TH listeners. The shallowest slope was seen with the Matrix test. However, the small variances of the slope and the SRT resulted in effect size estimates that fell between those of the other two tests. The DIN test was associated with steeply sloped psychometric curves with low variance. The scoring method did not substantially affect slopes and SRTs for the DIN test and LIST sentences, but word scoring resulted in shallow slopes and substantially worse SRTs for CI users. Conclusions: The DIN test stood out in this study as an attractive speech-in-noise test for CI users, with steep slopes and low variance in slopes and SRTs among participants. Digit and keyword scoring appear to be viable options for the DIN test and LIST sentences, respectively, potentially increasing the number of available test items. For the Matrix test, sentence scoring yielded shallow slopes and deteriorated SI, especially for the CI group. We recommend word scoring for the Dutch-Flemish Matrix test.

Objectives: – Cochlear implantation is the standard of care for severe-to-profound hearing loss in the Netherlands. Cochlear implants (CIs) generally perform well in quiet conditions, but speech understanding in an environment with reverberations remains difficult. This study aimed to minimize the amount of reverberation present in a speech signal by using novel artificial-intelligence-based algorithms created for use in CIs. Design: – A prospective crossover study was performed, which included 15 CI users, with each participant being their own control. Two versions of the algorithm were tested: one version that focused on late reverberations (DNN-WPE) and another version that additionally minimized early reverberation with a post-filter (DNN-WPEPF). These two algorithms were tested by performing speech intelligibility tests with percentage correct as the outcome measure. The Flemish/Dutch Matrix test was used for speech intelligibility testing. Six different conditions were measured: clean speech (no reverberation), clean speech processed with both algorithms, reverberated speech, and reverberated speech processed by both algorithms. In addition, subjective ratings were performed to assess how the participant perceived the processed sound. These subjective ratings were performed by pairwise comparisons of the aforementioned conditions regarding listening effort, naturalness, and speech intelligibility. Results: – The speech intelligibility scores revealed a statistically significant average improvement of 11% when reverberated speech was processed with DNN-WPE (p < 0.001) and 17% when processed with DNN-WPEPF (p < 0.001). Moreover, the benefit of DNN-WPEPF was significantly greater than the benefit of DNN-WPE (p = 0.018). Both algorithms did not significantly affect speech intelligibility when no reverberation was present (p > 0.05). The outcomes of the three subjective ratings complement the speech intelligibility scores. Speech dereverberated with either algorithm was significantly preferred over reverberated speech for all three outcomes (listening effort, naturalness, and speech intelligibility). Moreover, speech dereverberated with DNN-WPEPF was significantly preferred over speech dereverberated with DNN-WPE. Conclusions: – This study revealed that the DNN-WPE and DNN-WPEPF dereverberation algorithms had benefits for CI users regarding speech intelligibility and subjective ratings. These algorithms did not affect the clean speech, showing that they can be switched on in quiet situations without background noise. Further developments are required to implement the algorithms in real time on the CI processor, and more research is needed to assess them under more realistic listening conditions.