Throughout our adult lives there is a decline in peripheral hearing, auditory processing and elements of cognition that support listening ability. Audiometry provides no information about the status of auditory processing and cognition, and older adults often struggle with complex listening situations, such as speech in noise perception, even if their peripheral hearing appears normal. Hearing aids can address some aspects of peripheral hearing impairment and improve signal-to-noise ratios. However, they cannot directly enhance central processes and may introduce distortion to sound that might act to undermine listening ability. This review paper highlights the need to consider the distortion introduced by hearing aids, specifically when considering normally-ageing older adults. We focus on patients with age-related hearing loss because they represent the vast majority of the population attending audiology clinics. We believe that it is important to recognize that the combination of peripheral and central, auditory and cognitive decline make older adults some of the most complex patients seen in audiology services, so they should not be treated as “standard” despite the high prevalence of age-related hearing loss. We argue that a primary concern should be to avoid hearing aid settings that introduce distortion to speech envelope cues, which is not a new concept. The primary cause of distortion is the speed and range of change to hearing aid amplification . We argue that slow-acting compression should be considered as a default for some users and that other advanced features should be reconsidered as they may also introduce distortion that some users may not be able to tolerate. We discuss how this can be incorporated into a pragmatic approach to hearing aid fitting that does not require increased loading on audiology services. In this review paper, we highlight the importance of recognizing the effects of normal ageing on hearing aid fitting because it has a considerable impact on an individual’s understanding of speech and ability to benefit from hearing aids. Auditory processing and cognition decline throughout early, middle and late adult life and undermine our ability to hear in all types of listening situations. “Normal ageing” refers to non-pathological changes in cognition and auditory ability with age . We do nWe first provide a brief review of age-related change to central auditory processing and how this alters dependence on different elements of speech (Section 2). We then offer a short review of the basic concepts of cognitive change with age (Section 3), and how a decline in some elements of cognition also alters speech perception, particularly undermining listening in more challenging circumstances (Section 4). This understanding then enables us to determine how hearing aid parameters and fitting procedures might affect older adults’ listening ability. In Section 5, we derive a set of evidence-based principles for fitting hearing aids to older adults, and assess specific hearing aid parameters against these principles. We review evidence for an association between some elements of cognition and the benefit, or increased impairment, that may be caused by hearing aid processing strategies. We particularly focus on evidence that addresses the benefit, or harm, caused by fast or slow-acting compression speeds for those with different degrees of cognition. We also assess why the evidence may not always appear consistent. We then offer a discussion of how one might determine practical fitting guidelines for audiologists who predominantly see older adults in clinic (Section 6). Finally, we discuss gaps in the current evidence-base and what further research might be needed (Section 7).The central auditory nervous system (referred to simply as the “auditory system” in subsequent text) is a uniquely complex sensory network, engaging peripheral sensory organs, multiple processing layers in the brainstem, the auditory cortex and wider cortex, culminating in conscious perception and understanding, as well as extensive “top-down” control. The processing of different aspects of speech is distributed across the auditory system. For example, some neurons are tuned to overall amplitude modulation from lower to higher levels of the system  and otheAge-related changes to the underlying neural infrastructure cause progressive “central” auditory deficits with increasing age , 12–17. Temporal information in speech cues can be differentiated across a number of frequency bands : informaComparisons between young and old listeners with matched normal hearing, intelligence and education suggest that speech perception declines with age, demonstrating a greater effect than can be predicted by hearing thresholds , 42–44. “Cognition” refers to the processes of acquiring, retaining and using knowledge  and has Several theories have been proposed to describe the process of decline in some cognitive abilities. The processing-speed theory  suggestsOne way to categorize the basic concepts of fluid and crystallized intelligence into further subtypes of cognition, particularly useful in relating specific processes to speech perception, is provided by the Cattell-Horn-Carroll model , 73 Fig. The modNote that ongoing refinements to the model introduce further broad and narrow domains beyond those shown here . Episodir = 0.39), inhibition (r = 0.34), WM (r = 0.28), and episodic memory (r = 0.26). These are all narrow cognitive domains that deteriorate throughout adulthood  with short time constants, or fast-acting compression (FAC), was employed to enable exaggeration of quieter syllables or phonemes within words by quickly applying greater gain, so is often referred to as “syllabic compression.” This type of compression is based on the fact that some elements of speech may be inaccessible to a hearing-impaired listener, typically high-pitched fricatives for those with a high-frequency hearing loss. FAC aims to restore normal loudness perception across the frequency range . HearingFAC can be interpreted as contravening many of the principles suggested above for individuals with reduced degrees of cognitive function. In general terms, FAC has the effect of “flattening” ENV, whereas ENV is preserved by SAC  150, 15. FAC mayThere are a considerable number of studies that compare the outcomes of using hearing aids with FAC and SAC and relate it to individuals’ cognitive scores. A seminal set of studies by Gatehouse et al. , 176 comIt is difficult to compare studies because of the different paradigms used for testing speech and cognition, as discussed in Section 4. This is further confounded by variable application of algorithms, the number of channels employed in commercial and research hearing aids, and situations that may not be representative of a user’s daily experience . StudiesThe compression ratio defines the range of gain applied within a hearing aid channel. A higher compression ratio increases the range of input levels that, after amplification, are audible without being uncomfortably loud and should improve speech intelligibility in quiet, but will reduce intelligibility in background noise , 171. ThNoise reduction algorithms aim to reduce the level of non-speech sounds and increase comfort. A meta-analysis found that noise reduction does not consistently improve speech intelligibility, but is moderately beneficial for sound quality and comfort . Noise rHearing aids, by their nature, alter a sound signal and inherently introduce some form of distortion relative to the original. Other features manipulate the sound, including frequency-dependent gain, directional microphones, feedback management, frequency lowering, expansion and wind-noise reduction. Any hearing aid processing that distorts ENV may impair speech perception and this may be especially detrimental to those with lower degrees of cognition . HoweverThere is some evidence that frequency-lowering, or frequency compression, can benefit those with higher WM scores but it might act to undermine intelligibility in those with lower WM scores . A meta-One dimension of hearing aid setting that has well-established benefits and consistently positive outcomes is the use of directionality to improve signal-to-noise ratio  so it isThis review is focused on hearing aid parameters and their effect on aided outcomes for older adults with cognitive change related to normal ageing. Whilst not a subject of this review, we should be cognizant of the fact that hearing care for older adults must include a wider appreciation of their needs including physical and listening comfort, psychological, social, behavioral and environmental considerations, and these have implications on hearing aid settings, acceptance and outcomes . For exaThe preceding sections of this paper have reviewed the literature to determine how age-related changes to cognitive domains and auditory processing alter speech perception and, in particular, an individual’s relative dependence on different speech cues that might be disrupted by different approaches to hearing aid processing. In this section, we aim to apply the evidence to the clinical hearing aid fitting process in order to provide pragmatic guidance to clinicians.As part of a patient-centered care model  the audiHowever, the research is broadly consistent in a number of ways. First, older adults are more likely dependent on ENV for understanding speech. FAC causes distortion to ENV that can undermine speech perception, whilst emphasizing elements of TFS that cannot be utilized by many older hearing aid users, and might disrupt binaural inputs. Second, hearing aid users tend to prefer SAC on average, although individuals have different preferences. FAC is likely better in quiet for those with good cognitive processes related to hearing, but likely degrades speech intelligibility and the acceptability of hearing aids for those with lower degrees of cognition. Third, the variation in cognitive processes between individuals increases with age, so we cannot know which specific settings offer the most benefit for an individual, nor whether objective benefit will be aligned with their preference.The combination of peripheral and central auditory decline therefore means that older adults represent some of the most complex patients, as well as the most numerous. Consequently, age-related hearing loss should never be treated as “standard care” simply because of its high prevalence. Determining the correct hearing aid strategy for an individual hearing aid user is therefore a major challenge. One might think that it would be useful to undertake tests of cognition or TFS sensitivity in clinic. However, it is uncertain that a test score could usefully indicate a specific course of action, nor which cognitive tests should be used. Verbally-delivered cognitive tests are affected by hearing loss and there is no well-established test that has been shown to be unaffected by sensory impairment , 221. ItWe therefore propose a pragmatic approach to hearing aid setting that could be implemented within typical current fitting appointments. The principles above can be employed to ensure that relevant factors are considered for older adults, which we define nominally as those over 55 years of age in line with the English NHS definition of age-related hearing loss. We believe the following statements concerning hearing aid settings for older adults follow directly from the evidence:All factors that introduce distortion to ENV should be explicitly considered in hearing aid fittings. This should primarily include compression speed and compression ratio, but also noise reduction, frequency lowering and other advanced features.Compression speed and compression ratio are primary determinants of the degree of distortion introduced to ENV. This indicates a need for hearing aid manufacturers to publish compression speeds as part of their standard product information, and provide products that allow clinicians to change compression speed, or offer adaptive compression speed algorithms that can be selected appropriately for each individual.SAC should be considered as the default setting for older adults and should be employed in noisy environments for all hearing aid users. However, recognizing the variation in preference between individuals, both SAC and FAC approaches can be provided in separate hearing aid programs and the audiologist can employ validation techniques to assess which is best set as the default program. There is no good reason that hearing aids should default to FAC for older adults.If FAC is used, the compression ratio should be reduced to levels that avoid ENV distortion. There is no clear evidence that suggests a specific value, so it is difficult to provide robust guidance. Our own clinical experience and discussions with hearing aid manufacturers suggests a value as low as 1.5. This is, admittedly, anecdotal but there is some evidence to suggest that linear aids are preferred over WDRC aids with FAC and a compression ratio of 2.0 when subjectively rating the quality of aided speech . Users aDirectionality is always beneficial to improve the signal-to-noise ratio. This might also include a consideration of ear-molds in place of open-fittings, because the latter reduces directional benefit , 225. AlNoise reduction is likely best set to moderate, although this depends on each hearing aid manufacturer’s approach and the evidence base is not strong. Strong noise reduction may well impair speech perception, especially for those with lower degrees of cognition. However, the user may be offered options or multiple programs because some may prefer stronger noise reduction in some situations.Other advanced hearing aid features, such as frequency lowering, may also distort the signal in ways that further impair speech intelligibility for those with reduced abilities in some cognitive domains. The evidence is generally weak, so these should be considered as options for each individual.Unilateral aiding should be considered where binaural interference is suspected. This is easily achieved in clinic by comparisons of speech intelligibility and listening comfort with bilateral hearing aids versus the left and right hearing aid working unilaterally. In some cases, clinicians may find that the individual’s speech intelligibility is significantly better when aiding only one of the ears, and intelligibility may be impaired or the sound distorted whenever gain is applied to the other ear.One should recognize that any recommendation regarding hearing aid parameters cannot be prescriptive given the current state of knowledge and considering the wide variability in individual needs. This implies that there must be some process of ensuring that hearing aid settings are optimal, or at least acceptable, for each individual. Overall, we believe that a full consideration of hearing aid parameters needs to be combined with the over-riding principles of patient centered care. This engenders a need to balance the key elements of the hearing aid fitting process, including verification, validation and counselling. “Verification” is the process of matching hearing aid gain to a prescribed target using real ear measurements (REMs). “Validation” should aim to provide evidence that all hearing aid settings are suitable for an individual. This may include simple tests of loudness discomfort and speech intelligibility, more advanced techniques such as speech mapping, paired comparison approaches , or ques9. Conducting verification and matching gain to a prescription target does not, in itself, make a good hearing aid fitting. The verification process is solely aimed at setting individualized hearing aid gain and does not encourage a consideration of the other parameters highlighted in this review. For example, setting the gain to a prescription target for 50, 65, and 80 dB input levels may lead to high compression ratios where FAC is used, causing inappropriate ENV distortion. Verification is an important step that may offer a large  or small10. The only clinical process that can evaluate overall hearing aid settings and their suitability for an individual is validation . Accordi11. Hearing aids cannot overcome all of the peripheral and central auditory deficits discussed in this review, so wider considerations should be addressed to achieve the optimum outcome in the perception of the individual user. Audiologists must, of course, consider other non-auditory factors. Informational counselling regarding central auditory decline should aim to set reasonable expectations for the hearing aid user and their families or careers , 237 andResearch studies use a wide array of both cognitive and listening tasks, so the associations observed between them are variable. Although WM tasks predominate in many studies, it is not the only domain of cognition that is relevant  and we aWhilst there is variation in the evidence, it appears to us that the balance of evidence suggests that slow-acting compression may be the best default position for most older adults along with other cautious settings for compression ratios and noise reduction, although accepting there will be individual variations. However, further research should seek to confirm the size of the effect. Furthermore, most research on the effect of hearing aid settings considers one parameter in isolation whilst other parameters are held constant. This is unlikely to reflect the overall function of commercial hearing aids and assess the interaction between different hearing aid features. Recent work has demonstrated the interactions between compression speed and other settings, such as noise reduction and directionality , 210, sohttps://osf.io/fdzeh. The SHAOA (Setting Hearing Aids for Older Adults) study has been approved by the UK Health Research Authority and National Health Service (NHS) Research Ethics Committee (IRAS ID 313159), and it has been adopted onto the NHS National Institute for Health Research (NIHR) portfolio. Finally, in suggesting this approach, we make an implicit assumption that audiologists may not consider all of the factors that have been highlighted here, which we have not evidenced. Accordingly, we will also complete an online survey of UK clinicians to evaluate this, under University of Manchester ethics approval.In this paper we have proposed an approach to setting hearing aids for older adults. Whilst this may be derived from the balance of evidence, it is not specifically validated. We have therefore designed a randomized control trial based on the principles discussed in this paper, pre-registered on the Center for Open Science’s Open Science Framework (OSF), at RW conducted an initial long-form literature review which was reviewed with comments and changes from HD and AH. RW wrote the draft of this paper with comments and revisions from HD and AH. RW is Principal Investigator for ongoing research with HD and AH as academic supervisors. All authors contributed to the article and approved the submitted version.RW is funded by the NHS National School of Healthcare Science (NSHCS) as part of the NHS Higher Scientific Specialist Training (HSST) scheme, supporting work at the Royal Berkshire NHS Foundation Trust. HD and AH are supported by the NHS National Institute for Health Research (NIHR) Manchester Biomedical Research Centre.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The ageing population in China has led to a significant increase in the number of older persons with disabilities. These individuals face substantial challenges in accessing adequate activities of daily living (ADL) assistance. Unmet ADL needs among this population can result in severe health consequences and strain an already burdened care system. This study aims to identify the factors influencing unmet ADL needs of the oldest old (those aged 80 and above) with disabilities using six machine learning methods.Drawing from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) 2017–2018 data, we employed six machine learning methods to predict unmet ADL needs among the oldest old with disabilities. The predictive effects of various factors on unmet ADL needs were explored using Shapley Additive exPlanations (SHAP).The Random Forest model showed the highest prediction accuracy among the six machine learning methods tested. SHAP analysis based on the Random Forest model revealed that factors such as household registration, disability class, economic rank, self-rated health, caregiver willingness, perceived control, economic satisfaction, pension, educational attainment, financial support given to children, living arrangement, number of children, and primary caregiver played significant roles in the unmet ADL needs of the oldest old with disabilities.Our study highlights the importance of socioeconomic factors , health status , and caregiving relationship factors  in reducing unmet ADL needs among the oldest old with disabilities in China. Government interventions aimed at bridging the urban–rural divide, targeting groups with deteriorating health status, and enhancing caregiver skills are essential for ensuring the well-being of this vulnerable population. These findings can inform policy decisions and interventions to better address the unmet ADL needs among the oldest old with disabilities. According to the 2021 seventh census, 264 million people, or 18.7% of China’s total population, are aged 60 or aboveIn comparison to the considerable demand for care, the supply of long-term care in China is significantly insufficient, leading to a large number of older persons with unmet ADL needs. Institutional stagnation and the influence of Confucian culture have resulted in informal care provided by families remaining the primary source for addressing the care needs of older persons with disabilities , 8. HoweIdentifying the factors affecting unmet ADL needs is crucial for improving the care system and maintaining the health of older individuals with disabilities. On one hand, unmet needs are a key concern in the development of new care systems . They sePrevious studies have analyzed the factors affecting unmet ADL needs, demonstrating that low educational status, low income, absence of a spouse, living alone, and ADL disabilities are associated with unmet ADL needs . Some reWhile previous studies offer important findings, there are still some gaps that require additional investigation. Firstly, there is a lack of attention to the Chinese context. With a few exceptions mentioned above, the majority of studies are based on Western settings . China aAs an important branch of artificial intelligence, machine learning offers superior predictive power compared to traditional linear models . MachineUnmet ADL needs for the oldest old with disabilities essentially constitute a prediction problem, and the application of machine learning is both necessary and feasible. Identifying the factors that affect unmet ADL needs for the oldest old with disabilities involves determining which variables can accurately predict unmet needs. In this regard, machine learning methods with superior predictive power are more suitable than traditional linear models for analyzing the factors affecting unmet ADL needs among the oldest old with disabilities.However, to the best of our knowledge, there are no studies that have employed machine learning to analyze the influencing factors affecting unmet ADL needs among the oldest old with disabilities in China. In this study, we utilized six machine learning methods—Naïve Bayes, Logistic Regression, Decision Tree, K-Nearest Neighbors (KNN), Random Forest, and Gradient Boosting—to identify the factors influencing unmet ADL needs among the oldest old with disabilities in China. Naïve Bayes is a probabilistic statistical classifier based on Bayes’ theorem, which assumes that features are independent of each other. Logistic Regression is a widely used linear model for binary classification problems, which predicts outcomes by fitting the relationship between features and probabilities. Decision Tree is a feature-based tree-like structure that classifies or predicts instances through a series of decision conditions. KNN model determines the category of a new sample by measuring the distance between different samples. Random Forest is an ensemble learning method that combines the predictions of multiple decision trees to improve model accuracy. Gradient Boosting is an iterative ensemble learning method that builds a powerful predictive model by progressively optimizing the prediction results. By comparing the performance of these methods, we aim to determine the most effective approach for analyzing the influencing factors affecting unmet ADL needs in this population. Our findings will contribute to a better understanding of the key factors that impact unmet ADL needs, thereby informing the government’s formulation of appropriate public policies and the enhancement of caregiver knowledge and skills.2.2.1.The data for this study were obtained from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The survey was organized and executed by the Centre for Healthy Ageing and Development Research at Peking University and the National Development Research Institute. The CLHLS started with a baseline survey in 1998 and has conducted follow-up surveys in 2000, 2002, 2005, 2008, 2012, 2014, and 2017–2018. All participants signed a written informed document and agreed to participate in the survey project. The CLHLS is well-representative, covering 23 provinces in China, with 15,874 older persons aged 65 and over interviewed in the most recent follow-up survey (2017–2018).Using the 2017–2018 CLHLS data, a total of 2,436 oldest old aged 80 and above with disability were selected for this study. Following studies using the CLHLS, we considered older persons with disabilities as individuals who required assistance in their daily living activities for more than 3 months . CLHLS a2.2.Unmet ADL needs were measured by participants’ self-response to the question, “Do you think you currently get enough help with these six daily activities of bathing, dressing, going to the toilet, indoor activities, continence, and eating to meet your needs?” Participants’ responses were categorized as “completely satisfied,” “average,” and “not satisfied.” In line with existing studies , 36, we 2.3.Multiple dimensions influence unmet ADL needs in older persons. Drawing from existing studies and considering data availability , 36, thiDemographic characteristic variables included gender, age, and marital status. Gender is categorized as male or female. Age represents the participant’s actual age. Marital status is divided into two categories: married (including married or partnered) and unmarried .Regarding socioeconomic characteristics, we examined household registration, educational attainment, pension, economic satisfaction, and economic rank variables. Household registration is categorized as urban or rural. Educational attainment is divided into primary school and below or junior high school and above. Pension is classified as either yes or no. Economic satisfaction is assessed based on whether the respondent feels their financial resources are sufficient, with yes or no responses. Economic rank represents the respondent’s economic status within their local area, spanning five levels from very poor to very rich.Health status variables encompassed self-rated health and disability class. Self-rated health refers to the participant’s self-assessment of their health status on a 5-point scale, ranging from very unhealthy to very healthy. Disability class indicates the severity of the participant’s disability: assistance required for 1–2 ADL tasks indicates low-level disability; 3–4 ADL tasks, medium-level disability; and 5–6 ADL tasks, high-level disability.For the family relationship characteristic variables, we considered the number of children, financial support given to children, financial support received from children, and living arrangement. The number of children refers to the total number of children the participant has. Giving financial support to children denotes whether the participant provided financial support to their children in the past year, with yes or no responses. Receiving financial support from children indicates whether the participant received financial support from their children in the past year, also with yes or no responses. Living arrangement is represented by a dummy variable, divided into two categories: living with children and not living with children.Regarding caregiving relationship characteristics, we selected three variables: perceived control, primary caregiver, and caregiver willingness. Perceived control refers whether the participants believe they have influence over their personal matters, with yes or no responses. Primary caregivers are categorized into three groups: spouse, children, and other. Caregiver willingness pertains to the primary caregiver’s willingness to provide care, with responses being yes or no.2.4.In this study, we applied six machine learning methods to predict unmet ADL needs among the oldest old with disabilities: Naïve Bayes, Logistic Regression, Decision Tree, KNN, Random Forest, and Gradient Boosting.Naïve Bayes is a widely used classification model based on Bayesian probability theory. It calculates the conditional probabilities of different independent features to classify categories. Though effective and capable of handling multi-category problems with small data amounts, Naïve Bayes is sensitive to data input methods.Logistic Regression, a special case of a generalized linear model, transforms linear regression values between  by leveraging a sigmoid equation. This process turns continuous variable regression into a dichotomous task by setting a threshold.Decision Tree utilize a tree structure, offering a simple and efficient classification method commonly used across various applications.KNN, one of the simplest machine learning methods, classifies samples by calculating the distance between the sample and the training data points in the feature space. The sample’s class is determined by the majority class among the K “nearest neighbor” points. KNN is highly accurate and requires no assumptions about data distribution; however, its computational complexity increases with larger datasets due to its reliance on distance calculations.Random Forest is a typical ensemble learning method based on Bagging, suitable for addressing classification and regression problems. By constructing multiple Decision Trees, the model enhances information gain, reducing interference caused by noisy data. The random forest output is determined by the majority of Decision Tree outputs.Gradient Boosting model combines multiple weak models to create more powerful and accurate ones. Gradient Boosting improves prediction accuracy by iteratively enhancing the estimation of weak models.By utilizing these six machine learning methods, this study aims to identify the most effective method for predicting factors influencing unmet ADL needs among the oldest old with disabilities in China. The results can contribute to the development of public policies and the improvement of caregiver knowledge and skills.2.5.Machine learning shows impressive predictive capabilities; however, its prediction process often operates as a black box, leading to limited interpretability of the outcomes , 40. In Owing to its robust interpretability and visual representation, the SHAP framework has been widely adopted within the machine learning domain. This explanatory model, which aligns with human intuition, has gained increasing popularity in recent years for explaining machine learning models associated with medical diagnoses, social behaviors, and other complex phenomena .2.6.t-test, with results presented as mean ± standard deviation. Categorical variables are compared via a chi-square test, and the results are reported as the number and percentage. Statistical significance was determined using a two-tailed p-value of less than 0.05, indicating that the probability of obtaining the observed results by chance alone is less than 5%.In training the machine learning method, samples were first randomly divided into a training set (70%) and a test set (30%). The optimal parameters for each model were then determined using ten-fold cross-validation in the training set. To optimize the machine learning methods, we used a combination of manual parameter tuning, grid search, and random search techniques. Manual parameter tuning involved adjusting model parameters by hand to achieve the best performance, while grid search and random search involved systematically testing different combinations of parameters to find the best combination. Ten-fold cross-validation was chosen as the method for parameter tuning because it provides a good balance between bias and variance in the estimated performance of the model. Performance of the models was assessed using evaluation metrics such as accuracy, precision, recall, F1 score, and AUROC. These metrics provided important information about the accuracy and reliability of the model’s predictions. Because our outcome variable is binary , the AUROC is a suitable evaluation metric as it measures the model’s ability to correctly distinguish between positive and negative cases. The calculation formula and explanation for the above model evaluation metrics are as follows.1. Accuracy. Accuracy measures the proportion of correctly predicted instances (both true positives and true negatives) out of the total instances.Accuracy = (Number of Correct Predictions) / .2. Precision. Precision represents the ratio of true positive predictions to the total predicted positive instances. It quantifies the model’s ability to avoid false positives.Precision = (True Positives) / .3. Recall. Recall calculates the ratio of true positive predictions to the total actual positive instances. It measures the model’s ability to identify all positive instances.Recall = (True Positives) / .4. F1 score. The F1 score is the harmonic mean of precision and recall. It provides a balanced measure of a model’s performance, especially when dealing with imbalanced datasets.F1 score = 2 *  / .5. AUROC. ROC curves plot the true positive rate  against the false positive rate as the classification threshold changes. AUROC represents the area under this ROC curve and is a good metric for assessing a model’s performance across different threshold values. Higher AUROC values indicate better model performance.Based on these evaluation indicators, we pinpointed the optimal model for predicting unmet ADL needs among the oldest old with disabilities. The optimal model provides the best balance between performance and interpretability. To understand the importance and influence of each variable on unmet ADL needs, we used SHAP to decompose the contribution of each feature to the prediction results based on the optimal model. SHAP is a useful tool for interpreting machine learning methods because it provides insights into the importance and influence of each variable on the outcome, which can help guide decision-making and policy development. The aforementioned data analysis was conducted using Stata (Stata 17 MP) and Python (Python 3.10) software platforms.3.3.1.3.2.3.3.To gain insights into the factors influencing unmet ADL needs among the oldest old with disabilities, we used SHAP to learn how individual variables contributed to the Random Forest model’s prediction. As seen in 4.Aging is indeed a prevalent issue faced by societies worldwide, and the likelihood of disability in older person tends to increase with age , 44. ProExisting studies have extensively explored this issue using linear models . HoweverMachine learning is an important branch of artificial intelligence. In the era of complex big data, machine learning plays an increasingly crucial role in the field of geriatric health due to its powerful predictive capabilities. For example, Xin and Ren analyzed the main factors influencing depression among older persons with disabilities in rural and urban China using the Random Forest model . Lin et Similarly, in this study, the machine learning model achieved impressive results. Six machine learning models - Naive Bayes, Logistic Regression, Decision Tree, KNN, Random Forest, and Gradient Boosting - were employed in the analysis. The AUROC values for all models were greater than 0.65, indicating good prediction performance. Among them, the Random Forest model had the best prediction with an AUROC of 0.752, accuracy of 0.702, recall of 0.660, and precision of 0.735. The strong predictive power of the machine learning models in this study is consistent with the results of previous studies, which have demonstrated the potential of machine learning algorithms in predicting the outcomes of interest in geriatric health research .To further investigate the factors influencing unmet ADL needs among the oldest old with disabilities, this study used SHAP based on the Random Forest model with the optimal predictive performance. The results identified household registration, disability class, economic status, self-rated health, caregiver willingness, perceived control, economic satisfaction, pension, educational attainment, financial support given to children, living arrangement, number of children, and primary caregiver as the factors influencing unmet ADL needs among the oldest old with disabilities, in order of importance. These findings provide valuable insights into the factors that contribute to unmet ADL needs in this population and can guide policymakers and care providers in developing targeted interventions and allocating resources effectively. It is noteworthy that receiving financial support from children, age, gender, and marriage were not significantly associated with unmet ADL needs among older persons with disabilities. Our findings are consistent with some studies, but there are also differences.The association between household registration and unmet ADL needs is consistent with the study by Zhu and Oesterle , who fouThe study by Schure et al. has also found an association between the disability class and unmet ADL needs . IndividIn addition to household registration, the socioeconomic dimension factors of economic rank, economic satisfaction, pension, and educational attainment were all significantly associated with unmet ADL needs. Desai et al. also have found an association between economic status and unmet ADL needs . Zhu’s sApart from objective health and financial status, caregiver willingness and perceived control, which reflect the caregiving patterns of the older persons with disabilities, are important variables in predicting unmet ADL needs. Existing studies also found a significant association between caregiver willingness and unmet needs , 13. CarIn terms of the family relationship, this study found that providing financial support to children was significantly associated with unmet caregiving needs among the oldest old with disabilities. This finding aligns with the intergenerational exchange theory, where providing financial support to children is associated with better caregiving services. In Chen et al.’s study, higher income levels for caregivers also reduced the likelihood of unmet care need . MoreoveInterestingly, this study found weak associations between age, marital status, and gender with unmet ADL needs, which is inconsistent with Chen et al.’s findings . Momtaz Compared to previous studies, this study offers the following advantages: Firstly, it introduces machine learning to analyze factors affecting unmet ADL needs among the oldest old with disabilities. Machine learning models offer stronger predictive power without requiring additional model assumptions, unlike traditional linear models. Secondly, the study combines six machine learning algorithms, including Naïve Bayes, Logistic Regression, Decision Tree, KNN, Random Forest, and Gradient Boosting, to ensure robust results. Among these models, Random Forest demonstrated the most effective predictive performance. Lastly, by combining machine learning with SHAP, this study builds an interpretable model, allowing for a thorough exploration of the importance and influence of different factors on unmet ADL needs among the oldest old with disabilities.However, this study has some limitations that should be acknowledged. Firstly, the context of the study is limited to China, and the findings may not be generalizable to other countries due to the unique cultural, social, and economic characteristics of China. For instance, while household registration is a significant predictor of unmet ADL needs among the oldest old with disabilities in China, it may have limited relevance for other countries due to its unique nature. Secondly, this study focuses on the oldest old with disabilities, which may not reflect the situation of younger older persons with disabilities. While age and marital status were not predictor variables affecting unmet ADL needs among the oldest old with disabilities, this may differ for the younger old group. Lastly, the study did not include all possible factors that may influence unmet ADL needs, and future research should explore additional variables to gain a more comprehensive understanding of the factors affecting unmet ADL needs among the oldest old with disabilities. Despite these limitations, this study provides valuable insights into the factors associated with unmet ADL needs among the oldest old with disabilities, which can inform policies and interventions aimed at improving the quality of life for this vulnerable population.Our study on predicting unmet ADL needs among the oldest old with disabilities in China holds crucial policy implications. Firstly, optimizing resource allocation is paramount to address disparities in access to care and support. The factors of household registration and economic rank were found to be associated with unmet ADL needs. Policymakers must focus on equitable distribution of resources, ensuring that economically disadvantaged and remote regions have adequate support and services available to meet the needs of older persons with disabilities.Secondly, tailored care and support for individuals with different disability classes are essential to address their specific requirements. Customized rehabilitation programs and welfare measures must be implemented to cater to the diverse needs of each disability group. By acknowledging and addressing these unique needs, policymakers can enhance the overall well-being and quality of life for the oldest old with disabilities in China.Thirdly, to bolster the overall support system, policymakers should emphasize the importance of economic security for older adults. Improving pension schemes and providing additional financial aid to those in need can significantly reduce financial burdens and enable older individuals to better cope with their ADL requirements. This approach will foster a more dignified and supportive environment for the oldest old with disabilities.In conclusion, addressing unmet ADL needs among the oldest old with disabilities in China requires a multifaceted approach. Policymakers must optimize resource allocation, provide tailored care and support, and strengthen economic security to enhance the well-being and quality of life of this vulnerable population. By implementing these policy measures, the government can create a more inclusive and supportive society for the oldest old with disabilities, fostering their independence and overall happiness in their later years.5.This study employed six machine learning methods to predict unmet ADL needs among the oldest old with disabilities in China, with the Random Forest algorithm demonstrating the highest prediction accuracy. The analysis identified critical factors influencing unmet ADL needs, emphasizing the importance of addressing socioeconomic disparities, health status, and caregiving relationship factors. To alleviate unmet ADL needs, our findings suggest that government interventions should focus on bridging the urban–rural divide, supporting those with deteriorating health status, and enhancing caregiver skills and resources. The study’s results can guide policymakers and stakeholders in designing and implementing effective interventions to improve the well-being and quality of life for the oldest old with disabilities in China. Furthermore, the machine learning approach showcased in this study can be adapted and utilized in other countries and regions to better understand and address the unmet ADL needs of their ageing populations.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.The ethics committee of the Institutional Review Board, Duke University (Pro00062871), and the Biomedical Ethics Committee, Peking University (IRB00001052–13074) approved all the procedures. All methods were performed in accordance with the relevant guidelines and regulations. Informed consent was obtained from both the literate participants and the legal guardian/next of kin of illiterate participants.KW: Writing – original draft, Writing – review & editing, Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Software, Validation, Visualization. JZ: Writing – original draft, Writing – review & editing, Visualization. JH: Writing – original draft, Writing – review & editing, Methodology. DL: Writing – review & editing, Visualization. YL: Writing – review & editing, Conceptualization, Formal Analysis, Funding acquisition, Project administration, Supervision.The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Sibling relationships, one of the most extended relationships in life, contribute to an individual’s social and emotional development. However, this relationship may be influenced if one sibling has a hearing loss.This study explored the influence of a hearing loss on the sibling relationship by gaining the perspectives of the sibling with normal hearing.Adopting a phenomenological research design, semi-structured online interviews were conducted using Zoom and WhatsApp with nine participants who have siblings with hearing loss.Hearing loss may significantly impact the normal hearing sibling’s quality of life, affecting their psychological and social well-being, familial and peer relationships and overall experiences. Personal development, independence, maturity and closer sibling bonds were some of the positive influences reported by the participants. Attendance to aural rehabilitation therapy sessions, knowledge of hearing loss, personalities and household living arrangements positively influenced the relationship between siblings. The lack of attendance to aural rehabilitation sessions resulted in communication difficulties between siblings.There is a need to include siblings in aural rehabilitation and family engagements related to the child with hearing loss to provide a holistic and more effective rehabilitation and adjustment process.This study aimed to improve family-centred intervention as it is focussing on the siblings’ perspectives of the hearing loss. Furthermore, previous studies have generally focussed on adults and not much research has been conducted surrounding the sibling relationship. According to the World Health Organization . The six-step analysis process developed by Braun and Clarke  was follBefore the main study, the researchers conducted a pilot study with two individuals (aged 18–25 years). The results obtained from the pilot study indicated that the data collection tool had to be amended. Two researchers had to record the interview at the same time in the event of internet connectivity problems.The chosen methodology allowed the researchers to collect data within the appropriate context regarding the cultural and linguistic variables Leung, . This waConstruct validity was ensured in the study through the pilot study, to allow for the researcher to be cognisant of any changes that needed to be made while conducting the interview. The tool was adapted from Eichengreen and Zaidman-Zait , furtherDuring data analysis, the researchers engaged with each other to reduce bias; the transcriptions were swapped between the researchers, and a cross-check was conducted. The researchers also ensured reliability and validity through respondent validation. As the participants were either in employment or currently attending high school and tertiary institutions, their interview transcriptions were sent to each participant to allow the participant to comment on its accuracy  explaining to me and also my grandmother saying, “You the one who’s supposed to be there for her, she’s your sister, if not who’s going to be there for her and what not”. I feel I had to think that through, and you know get used to that.’Hence the participant’s familial support greatly assisted in moulding her relationship with her sibling. However, Susi expressed:‘I feel maybe if my mother had explained to me that she is deaf right now and she has to go to a totally different school, that was never explained to me at that time because a lot of attention was going towards her.’From the above response, the effect of the family on the sibling relationship is evident as parents’ failure to apply equitable rules in the family towards their children may give rise to grievances raised by the normal hearing siblings about unfairness  and visual aids to communicate with his sibling:‘Sometimes we talk to him using WhatsApp, but the problem is we can only chat using English because he can’t write in isiZulu. My family knows sign language; they are about five of them that can communicate with him fluently. Another way of communicating with him is by showing him something or writing something down on paper; in that way, he is able to understand and respond back.’However, Andrew further mentions that when he wants to confide in his sibling, communication breakdown sometimes occurs, negatively impacting their relationship:‘There will be a time where I want to communicate with him as someone who is also a male, but you find that you cannot just talk to him because you end up speaking to yourself, sometimes you try to explain things to him using sign language, but you see that he will be just agreeing so that he will not disappoint you.’Natasha expressed that her sibling uses total communication, which helped their relationship, as he can relate to the hearing community and the deaf community. ‘… he uses total communication, so he’s able to associate with both worlds, you know, the deaf world and the hearing world. I think that really helped him’.However, Natasha also commented that because her sibling uses sign language, he experiences difficulties understanding colloquial language, requiring her to serve as an interpreter for him in such situations.‘If we were having big group conversations, you know, I used to interpret quite a lot or explain situations to him a lot. In the deaf culture, certain things they don’t really understand like slang, for example. Like Indian people use a lot of slang, so like Indian boys and things like that use a lot of slang, so sometimes he didn’t understand those things, because it wasn’t part of their vocabulary. So that was the thing that stood out because I kind of grew up in this whole environment I think I understood him the most.’Participants indicated that they began to develop a more profound knowledge of their sibling’s hearing loss as time progressed, resulting in more communication and interaction. Hence, an increase in time drastically improved the sibling relationship as it resulted in most participants developing a stronger bond. Natasha states that she has become more accepting of her responsibilities towards her brother as she matured: ‘It is just something that they, you know, and you have to do, or you are not forced to do it, but you do it’.It is, thus, evident that the participants feel like with growth came maturity and a newfound appreciation for their role in their sibling’s life.A lack of knowledge about their sibling’s hearing loss resulted in the participants being left out during crucial milestones in their siblings’ life, as expressed by Susi:‘I feel maybe if my mother had explained to me that she is deaf right now and she has to go to a totally different school, that was never explained to me at that time because a lot of attention was going towards her. Yeah, I was never really part of that happening at that particular moment. I wasn’t a part of the school process, the cochlear and how the hearing aids are supposed to work.’Ntokozo expressed that his mother has been instrumental in providing the necessary knowledge to him and has been the primary influence in him understanding his sibling better:‘My mom told me everything I wanted to know. I think so because of her, I was able to understand my brother better.’Natasha expressed that being knowledgeable about her sibling’s hearing loss was not of utmost importance to her as she was the younger sibling; hence, it did not affect her relationship with her sibling.‘To me, it didn’t really matter, and quite honestly, the reasoning behind him getting there, or the degree of his hearing loss and things like that didn’t really matter, he was there, so there wasn’t anything we could really do, unless, and we had to adjust to him and he had to adjust to us in that way, but because I’m the younger sibling, it’s just something that was there already, there wasn’t anything I needed to know extra, you know.’The younger normal hearing child is born into a typical routine, and there is no need to adjust from a previous, different lifestyle like older normal hearing siblings may have to. Therefore, this concurs with Natasha’s statement, suggesting that she joined her family’s natural flow of life. Having a sibling with hearing loss can be confusing and challenging for normal hearing siblings, especially if they have no prior experience dealing with any disability. It is evident that including the older siblings in the intervention of the sibling with the hearing loss leads to better relations.The interactions between siblings play an important role in developing social skills and the cognitive and emotional development of siblings Poole, . HearingIndividuals who transition to adolescence spend less time with their siblings and start to show a lack of respect as expressed by Mandla:‘It has changed. At first, he respected me; now, he doesn’t respect me at all. He thinks he’s big. It doesn’t make me feel sad because it’s part of growing up; he has to grow up, and sometimes he has to be by himself. You know he has to learn a lot of things in life by himself without me being there.’Susi reported a change in her siblings’ behaviour; however, this helped their relationship as they are now able to share a more intimate relationship:‘So much has changed a lot. She has changed, she is very close to teenage-hood now, so we became closer. Because when she was younger, we were never that close. She was closer to her little sister. So now that she is growing, we are becoming closer.’The above statement indicates that the age difference between her and her sibling has impacted their closeness and their relationship and that the transition to adolescence has fostered a more intimate and meaningful relationship. The interactions between siblings may change as the sibling relationship changes over time  because of having a sibling with a hearing loss.When siblings of children with hearing loss are included in intervention and are provided with additional support such as sibling support groups, it increases their quality of life. Some participants mentioned that their siblings attended aural rehabilitation, and they were also involved in their therapy sessions. Natasha expressed that she was fully involved and active in aural rehabilitation therapy:‘Yes, it was family centred intervention also. So there were sessions that not only my family, like my parents and myself, but it was his communication partners that were also involved like my cousins and my aunts, and everybody got involved in it, so it was quite nice in that sense.’Ntokozo mentioned that he does not usually physically attend the aural rehabilitation sessions:‘On those classes, to be honest, I’m 5% involved because when they do them, I’m usually not there so, unless if they want me to compile a video maybe of me teaching him maybe colours or telling him that this is a pen or something like that.’The above statements indicate that a family-centred approach to intervention was followed for some participants and their families. Furthermore, some participants were well informed about hearing loss and its effect on their siblings because they attended aural rehabilitation. Susi mentioned that:‘My mom started a society where we take in deaf kids like we take in the kids. We have activities because what I can tell you is that deaf people love being around other deaf people. Because that’s something they’re not used to. Yeah. That sense of belonging. Yes. And we have sign language classes. We’re trying to get sponsors.We’re trying to get money to build a home where deaf people can stay.’Natasha chose a career in Audiology because she was involved in her sibling’s aural rehabilitation therapy classes and developed an interest in Audiology at a young age:‘Well, I mean, I’m an audiologist. I don’t think I would have thought about it if I didn’t have a hearing-impaired sibling. We’ve had a lot of opportunities I’ve had a lot of because he was very involved in a lot of things while growing up. I got a lot out of it. I also got a lot to understand the deaf culture, which helps me in many ways. Not only at work but just at home and in social settings.’Essentially, this suggests that attending aural rehabilitation classes was considered beneficial and positively influenced these participants and their families. This is because in attempting to become closer and to alleviate some of the challenges experienced by their siblings, the participants ensured that they educated themselves and became involved in their sibling’s rehabilitation process. They were able to understand the different aspects of hearing loss better, and most importantly, they found a way to make a difference in their siblings’ lives and even their communities.Both Andrew and Musa stated that their siblings attended aural rehabilitation. However, they were not involved for various reasons: the siblings attended boarding school and had their sessions there; hence, they could not attend and be involved. Additionally, some participants indicated that either their siblings did not attend therapy or did not know what aural rehabilitation therapy was.In this study, three of the nine participants indicated that they attended aural rehabilitation with their siblings. In Andrew and Musa’s case, the accessibility of these services was an issue. Despite being probed, specific reasons for the lack of knowledge and non-involvement of other participants and their siblings were not disclosed.The opposite was true in this study because participants who did not have enough information about their sibling’s hearing loss did not develop any assumptions. Instead, they believed that nothing was wrong with their sibling. However, this suggests that the parents of children with impairments must keep siblings updated and involved in their sibling’s management/rehabilitation. Therefore, the inclusion of siblings is encouraged for the effective intervention of children with hearing loss, especially when family-centred intervention is considered.Participants indicated that they play vital roles in their hearing-impaired siblings’ lives. They are often asked to help out with the sibling who has a hearing loss or take on extra roles within the household. The findings of this study support this premise as participants reported that they were aware that their siblings received more parental attention, but they believe it to be justified. Participants who were both younger and older than their sibling with hearing loss reported having the responsibility of constantly looking after their siblings, especially when their parents were not around, as they took on the role of a guardian. Although participants understood their parents’ responsibilities, none of them reported feeling the need to be near-perfect or being responsible for compensating for their siblings.Mbali and Sipho indicated that their sibling’s hearing loss does not influence their roles and responsibilities as they are only responsible for household chores and not their siblings:‘Well, mostly normal stuff as a teenager as you know, cleaning all those stuff, house chores.’Findings from this study suggest that roles and responsibilities of the normal hearing sibling vary within households. Hence, an overall increase in familial roles of individuals who are older than their sibling with hearing loss cannot be generalised.Daily functioning: Participants indicated no drastic change in their daily functioning as their sibling’s hearing loss occasionally affects their lives.Susi expressed:‘It didn’t really affect my everyday life besides the fact that I must remind her to wear cochlear implants, and you need to explain things to her; she doesn’t understand.’The participants believe that having a sibling with a hearing loss only had minor effects on their daily functioning. Although they had to make adjustments to accommodate their siblings, they did not indicate any major disadvantages of the hearing loss. Musa, however, indicated that there is a psychological effect on her daily functioning as she often worries about her sibling with a hearing loss being in situations that could cause him harm:‘At some point like especially when I’m on the road. I get to feel like, he doesn’t get to hear the cars and I wonder how he is going to cope with hearing the cars hooting and when people ask him to move out the way, so I don’t know that’s how I think.’Growing up with someone who has a disability of any sort can impact a person’s traits and characteristics. This influence can be both positive and negative and can push individuals to be better or cause difficulties. Participants in this study did not view their siblings as a burden. Andrew reported that his sibling’s hearing loss often affects his daily functioning; however, he did not express any frustration or anger regarding that. Alternatively, other participants reported that they made minor adjustments that did not affect their daily functioning significantly.The findings from the study support a statement by WHO , which sIn an attempt to avoid experiences that are one-sided and only guided by the sibling who has a hearing loss, parents should also be encouraged to attend and participate in activities that interest the normal hearing sibling and not allow the child’s needs with the disability to overshadow those of the normal hearing sibling . Siblings have various perspectives on their connection with each other. Older siblings are more likely to initiate interactions and educate younger siblings, and younger siblings are more likely to be taught and nurtured Ray, .The inclusion in aural rehabilitation classes may be a way to create a healthier bond between individuals with hearing loss, their normal hearing siblings and their parents. According to Ray , it is hIn this study, there were varying living arrangements. Participants did not attend the same school as their siblings. In most cases, the siblings with the hearing loss attended a boarding school for the deaf and only returned home during the weekends; hence, the siblings spent less time together. Participants who did not live in the same household with their siblings suggested that this influenced their relationship, and they identified a significant difference when they started spending more time together, as reported by Ntokozo:‘We were not that close when this whole thing started happening. Another thing is, I wasn’t at home, like, I went to university, you know, stuff like that. So, obviously, there was no close relationship. So that grew along the way while we spent time together, you know, so it grew, and we became close.’Participants believed that spending less time together harmed their relationship and influenced how close they became; alternatively, spending more time improved their relationship. This is evident in Ntokozo’s statement, where he expresses that he started being close to his sibling after they started spending more time together.Participants described their siblings’ personalities or characters differently, and some described them in contrast to their personalities. When asked to describe his sibling’s personality, Ntokozo stated that:‘He has a wild personality, fun, talkative, and he is an imaginator. He is that person that is always full of energy. I can’t even describe the energy, but it’s always on point.’He further expressed that:‘Another reason why I feel him and I are getting along very well is because when he passes that energy to me, I’m able to see that type of energy and reciprocate it.’This suggests that having similar personalities may positively influence a relationship because it becomes easier for people to relate to each other; they start spending more time together, thus creating a closer bond.Susi mentioned that her sister is an introvert, and she does not like going out in public:‘She’s somebody who doesn’t like being around a lot of people. She gets tired of being in public for too long. So, I’m the one who’s supposed to be with her maybe when we are supposed to go to a wedding or some gathering in the family, and she would say, I don’t feel like going there, and I’m the one who’s supposed to stay behind and be with her.’In this case, the sibling’s personality/character meant that she would depend on her sister when dealing with or avoiding social environments in certain situations. The participant’s understanding of her sibling’s character and what she considers uncomfortable further emphasises that having a sibling as a source of support can decrease low self-esteem, depression and loneliness (Crowe et al., Siblings have varied experiences, depending on whether they are the older or younger sibling. Susi described her role caring for her sibling with hearing loss:‘I think it was always just there and also by them explaining to me and also my grandmother “You the one who’s supposed to be there for you, she’s your sister, if not who’s going to be there for her and what not”. I feel I had to think that through, and you know get used to that.’Typically, an older sibling dominates, and the relationship is asymmetrical during childhood, especially when the younger sibling has a hearing loss. In this study, most participants are older than their siblings, which agrees with the statement as participants are dominant in their sibling relationships as they also play a vital role in caring for their young siblings.The time siblings spend with one another might be a good measure of the quality of their relationship. It was discovered that even when one sibling has a disability, there is a significant level of interaction between siblings (Stoneman, In this current study, each system and the themes identified in the various systems have a mutual relationship. Each theme reflects different systems and reveals how they are connected, how they interact with each other and how this influences the sibling relationship. The participants’ initial reaction to their sibling’s diagnosis included feelings of sadness, a sense of hopelessness and disappointment, thus affecting their psychological state. The above themes reflect the microsystem and the mesosystem. The themes of interaction and communication can also be found within the microsystem and the mesosystem.The sibling relationship may also be affected by informal and formal social structures outside the individuals and do not directly influence them. The participants in this study indicated some of the challenges regarding having a sibling with hearing loss, which included playing the interpreter’s role during social gatherings. According to Ray , normal According to Bronfenbrenner’s ecological systems theory, the sibling relationship is influenced by various contexts and the interaction of the factors within various contexts. Each system does not exist independently but is influenced by various systems.The experiences described by participants in this study differed as both positive and negative influences were observed. The effect of communication difficulties was identified throughout the interactions with participants. A common suggestion to alleviate these challenges was to include normal hearing siblings in aural rehabilitation services to develop skills that would enhance their interactions with their siblings with hearing loss. It is hoped that the research findings from this study shed light on improving the aural rehabilitation practices of audiologists and reflect the unique relationship that siblings share if one has a hearing loss.


The adverse event rate after colorectal surgery is up to 20%, with anastomotic leakage representing 2.9%–15.3% of eventsA 56-year-old woman was diagnosed with rectal adenocarcinoma and underwent laparoscopic anterior resection of the rectum with lymph node dissection and colorectal anastomosis. She presented 1 month later with anastomotic leakage complicated by a presacral abscess and a rectovaginal fistula . The coEndoscopic management of a complex colorectal anastomotic leakage using double-pigtail stents and endoscopic vacuum therapy.Video 1The management of adverse events after colorectal surgery requires a multidisciplinary approach. This combined endoscopic treatment was shown to be a good option in this patient with complex colorectal anastomotic leakage. EVT is a useful tool for the management of colorectal anastomotic leakage. Nevertheless, a prospective comparative study between endoscopic treatment and redo surgery is warranted.Endoscopy_UCTN_Code_TTT_1AQ_2AG


To systematically review the existing literature that examines the relationship between cognition, hearing, and language in children using cochlear implants and hearing aids.The review has been registered in Prospero (Registration: CRD 42020203974). The review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis and examined the scientific literature in VHL, MEDLINE, CINAHL, Scopus, WOS, and Embase. It included original observational studies in children using hearing aids and/or cochlear implants who underwent cognitive and auditory and/or language tests. Data were extracted from the studies and their level of evidence was graded with the Oxford Center for Evidence-Based Medicine: Levels of Evidence. Meta-analysis could not be performed due to data heterogeneity. Outcomes are described in narrative and tables synthesis.The systematic search and subsequent full-text evaluation identified 21 studies, conducted in 10 different countries. Altogether, their samples comprised 1,098 individuals, aged 0.16–12.6 years. The studies assessed the following cognitive domains: memory, nonverbal cognition, reasoning, attention, executive functions, language, perceptual-motor function, visuoconstructive ability, processing speed, and phonological processing/phonological memory. Children with hearing loss using cochlear implants and hearing aids scored significantly lower in many cognitive functions than normal hearing (NH) children. Neurocognitive functions were correlated with hearing and language outcomes.Many cognitive tools were used to assess cognitive function in children with hearing devices. Results suggest that children with cochlear implants and hearing aids have cognitive deficits; these outcomes are mainly correlated with vocabulary. This study highlights the need to understand children’s cognitive function and increase the knowledge of the relationship between cognition, language, and hearing in children using cochlear implants and hearing aids. Interventions combining these technological resources with a period of appropriate speech-language-hearing rehabilitation not only enhance auditory input restoration but also promote greater development of auditory, cortical, language, and social skills .There is a consensus in the literature concerning the benefits of hearing devices to the development of auditory and language skills in children with prelingual hearing loss – especially with early interventions, which can enable them to have either a typical development or one near that of their hearing peers . HoweverIt has been recently proposed that neurocognitive functions and their development may be related to auditory and linguistic performance, influencing it in CI and HA users. Therefore, it is considered an underlying factor that could partly explain this population’s variable performance .Neurocognitive functions can be defined as a series of mental processes that involve knowledge acquisition, short-term memory (STM), long-term memory (LTM), working memory (WM), and operational memory, attention, perception, processing, reasoning, visualization, planning, problem-solving, and execution. These skills develop from the earliest years, progressing from the most basic to the most complex ones .Over the past few years, researchers have been engaged in exploring these neurocognitive functions’ roles and their relationship with hearing and language performances. The brain is a highly dynamic organ that depends on connections and experiences; hence, it is theorized that a period of auditory deprivation would have a substantial effect on both proximal areas  and distal areas, which would secondarily affect neurocognitive functions . HoweverData from studies indicate that children using CI and HA perform significantly worse in various cognitive functions . In lineFurthermore, these measures are found to correlate with and be predictors of performance in speech perception measures . TherefoGiven the above, this systematic review aimed to investigate whether there is a relationship between neurocognitive, auditory, and language skills in hearing-impaired children using hearing devices.2.The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) .2.1.Study eligibility criteria were defined according to the PICO acronym  . The revOnly primary studies were considered for inclusion, except for case reports. Secondary research, book chapters, annals, dissertations, theses, and animal models were excluded. Only studies published in Portuguese and English were reviewed, and no restrictions were applied regarding the year of publication.2.2.The review protocol was registered in the International Prospective Register of Systematic Review (PROSPERO) database under the registration number CRD42020203974.2.3.Preliminary research was conducted to test, refine, and validate the strategy and terms adopted. The final strategy was reviewed by the authors.The following databases were searched for potential studies: Virtual Health Library (VHL), Medical Literature Analysis and Retrieval System Online (MEDLINE/PubMed), Cumulative Index to Nursing and Allied Health Literature (CINAHL/EBSCOhost), Scopus, Web of Science (WOS), and EMBASE (Elsevier). CINAHL, WOS, and EMBASE were accessed via the CAPES/MEC Journal Portal.The search terms were previously identified in Portuguese in the Health Science Descriptors (DeCS), and the corresponding vocabulary in English was identified in the Medical Subject Headings (MeSH). The controlled vocabulary in EMBASE (EMTREE) and CIHNAL (CINAHL Headings) was also consulted.The strategies were modeled and adapted, when necessary, to ensure a highly sensitive search. All possible combinations were used between the following index terms, synonyms, and free terms: child preschool, child, hearing loss, deafness, cochlear implants, hearing aids, cognition, neuropsychological tests, executive function, memory, attention, auditory perception, speech perception, language, language development. During the research, the language filter was applied to retrieve only studies published in Portuguese and English. There was no limitation regarding the publication period, and retrieved studies had been published by August 2020.2.4.All records retrieved from the databases were imported into the reference manager EndNote Web to remove duplicates. The resulting records were exported to the Rayyan (web version) systematic review manager  for screTwo reviewers (JV and NE) blindly and independently screened study titles and abstracts. Studies whose abstracts were unavailable were removed. Each record was labeled as “included,” “maybe,” or “excluded.” The reasons for excluding the latter were identified.After such screening, the reviewers’ decisions were unblinded. When they diverged, the conflicting decisions were solved by a third independent reviewer (CF). Then, the selected records were imported to the Zotero reference manager for full-text reading. The CAPES/MEC Journal Portal was used as a primary alternative to retrieve full texts. If they were unavailable in this virtual library, a second attempt was made in ResearchGate. If this also failed, full texts were directly requested from the authors via ResearchGate.After the retrieval, two reviewers (JV and CF) independently screened the full texts. If they diverged, it was solved through consensus and, if necessary, a third evaluator was consulted (ACR).2.5.Two independent researchers (JV and CF) extracted data into a standardized Microsoft Excel spreadsheet to avoid measurement bias. Extracted data were compared, and any discrepancies were solved by discussion. The following data were extracted from each record: title, authors, year of publication, country of the study, study objective, sample size, participant exclusion and inclusion criteria, sex, chronological age, hearing deprivation time, age at the time of intervention, the device used, length of use, study design, and control group (if any). If the authors did not explain the research design, features of the design were noted.Results were described regarding subjective and objective research instruments used for the audiological evaluation; speech, language, and cognitive functions; description of the cognitive domains evaluated; evaluation results; associations between tests; and study limitations.2.6.Studies were evaluated according to the Oxford Center for Evidence-Based Medicine: Levels of Evidence . The lev2.7.Due to outcome measure heterogeneity, it was not possible to conduct a meta-analysis. Therefore, the results were descriptively analyzed, and the summarized data are presented in tables.3.3.1.The initial search identified 7,309 manuscripts. Duplicates were removed, totaling 4,065 records. Another 162 duplicates had not been identified at first and were manually removed. A total of 3,082 records were screened by title and abstract. Of these, 3,006 were excluded for not meeting the inclusion criteria. The full texts of 74 out of the 76 potential records were retrieved and screened for eligibility – 53 of them were excluded because they did not meet the inclusion criteria. Thus, 21 articles were included in the review. The study selection process with all PRISMA 2020 stages ,b is sho3.2.The general study characterization is provided in 3.3.The sample size of the studies ranged from 10 to 176 participants, totaling 1,098 hearing-impaired children who used CI and/or HA. Approximately 53% of the total population were males. Sex data were not available in four studies . Their mThree studies included patients with mild to profound hearing loss , two incRegarding device use, 17 studies included participants who received unimodal auditory stimulation. Among them, four studies  specificIt is important to clarify that the studies by The studies by 3.4.The 21 studies used heterogeneous neuropsychological tests/subtests, and some of them used more than one tool  and outcome measures such as verbal WM, visuospatial WM, perceptual fluid reasoning abilities, and receptive vocabulary . On the 4.HAs enable most children experiencing hearing loss to hear and access speech and surrounding sounds through amplification. From another perspective, CIs restore certain aspects of hearing in children with severe to profound hearing loss who did not benefit from HAs, by providing direct stimulation to the auditory nerve through electrical signals. Despite their distinct characteristics and mechanisms, both have been employed as tools for early intervention in auditory habilitation for children with hearing loss, offering appropriate auditory stimulation, which prevents many detrimental effects of sensory deprivation. Hence, they can develop auditory and linguistic skills and learn alongside their NH peers. While hearing devices have a remarkable effect on children’s development, there is still a large variability in their outcomes that are not quite explained by conventional factors. The current review was designed to enhance our understanding of cognitive functions in children with CI and HA and how these functions interact with or influence their language and auditory abilities.Many studies use cognitive tools to access children with hearing loss. Since this specific population is extremely heterogeneous, it is important to notice the number of different cognitive tools used to assess them in our review. This result highlights the absence of and the need for validated tests to assess this target population.Memory was the most assessed domain. At least 71.4% of the studies assessed some aspect of memory, including auditory memory  and visuThere is no consensus regarding specific memory domain deficits. However, not surprisingly, several studies suggested that hearing-impaired children perform worse on auditory memory tasks and tend to perform on average or above average on visual memory tasks. When it comes to phonological awareness, children with CI tend to have lower ability levels and seem not to catch up with their hearing counterparts even when they receive early implantation. These results reinforce the critical role of auditory experiences in phonological awareness.In addition, a period of deafness in early development may affect the executive functions’ building blocks. Findings with conventional executive function performance measures and parent report measures demonstrated that children with CI and HA have issues with some executive function domains, such as working memory , shiftinOverall results indicate that children with hearing loss have lower scores in many cognitive domains compared to NH peers.Numerous studies have demonstrated close links between hearing, language, and cognitive outcomes. Relationships between hearing data and cognitive function were identified in some studies. Hearing age is associated with sequence memory learning  and execComprehension in challenging environments requires cognitive resources. Language, working memory, and auditory attention have been found to explain speech recognition in children using HA . This knMemory is a common underlying source that is involved in speech perception, language, and speech production. Findings suggest a significant association pattern between memory and speech perception , receptiPhonological awareness has been shown to predict vocabulary , demonstExecutive function is an umbrella term for a set of cognitive abilities that enable us to reason, solve problems, stay focused, have self-control, plan, and think . Results5.Given the above, this systematic review suggests that cognitive functions can be related to hearing and language data. These results emphasize the wide range of assessment tools used to evaluate this specific population, particularly in terms of cognitive function. This provides an overview of the lack of consensus on instruments suitable for assessing CI and HA users. As a result, performance in language, cognitive, and hearing abilities is expected to vary.Despite the variability, available evidence suggests that children with hearing loss perform worse in cognitive function than their hearing counterparts, which may account for variability in other outcomes. A better understanding of how these underlying mechanisms relate to auditory and language abilities can be useful for effective interventions. Our findings shed some light on the importance of individualized cognitive assessment in this specific population and the potential benefits that identifying cognitive risks or underperformance may bring to rehabilitation strategies and intervention monitoring.Further research is required to understand whether specific intervention strategies based on their cognitive function may mitigate any effects on auditory and language ability function. In our study, only children without any other disability besides hearing impairment were included, as this factor could be a confounding variable. However, we acknowledge that including children with conditions that overlap or co-occur with hearing loss could help establish the direct and indirect impact on neuropsychological, language, and auditory development as well as their interaction. Future research should be oriented toward addressing these gaps.The original contributions presented in the study are included in the article/JL contributed to study conceptualization and design, data collection, analysis, interpretation, article drafting and review, and final version approval. CM contributed to data analysis, article writing, and final version approval. NZ-A contributed to study design, data analysis, critical content review, and final version approval. PM contributed to data interpretation, critical content review, and final version approval. AR contributed to study conceptualization and design, data interpretation, critical content review, and final version approval. All authors contributed to the article and approved the submitted version.