Hearing in Adults, published in 1995,contains the fullest report of the United Kingdom’s Medical Research CouncilNational Study of Hearing. It was designed to determine the prevalence anddistribution in Great Britain of audiometrically measured hearing loss as afunction of age, gender, occupation, and noise exposure. The study’s size,quality, and breadth made it unique when it was done in the 1980s. Thesequalities remain, and its data are still the primary U.K. source for theprevalence of auditory problems. However, only 550 copies were printed, and thebook is essentially unobtainable today. We describe here a fully searchable,open-access, digital (PDF) “reprinting” of Hearing in Adults,summarizing the study’s design and the book’s contents, together with a briefcommentary in the light of subsequent developments.The 1011-page book,  The Medical Research Council’s (MRC) “National Study of Hearing” (NSH) was a group ofmajor epidemiological studies of the prevalence and distribution of hearing problemsof adults in England, Scotland, and Wales. It was conducted by the former MRCInstitute of Hearing Research (MRC IHR) in the 1980s. The NSH gave the UnitedKingdom its first stratified and precise quantification of degrees of severity ofhearing loss in a designed study and related these to demographic and pathologicaldeterminants. Its scale and type of measurement have never been repeated in theUnited Kingdom; its data and analysis framework are still used to determineprevalences and derive population numbers e.g., . The curHearing in Adults (hereafterHiA). This book . These goals wereimplemented strategically through six key design features. Given the number of mainvariables supported and the requirement for narrow confidence intervals across thewide age range, a large sample size was needed. The six design features were asfollows: A structured two-tier design to reconcile population reach withclinical/laboratory precision of measurement. The first tier was apostal survey; the second tier was auditory and clinical assessment atfour specially equipped hospital-based research clinics with qualifiedotorhinolaryngolical (ORL) and audiological staff.A double basis of accessing the population, via two sampling frames:individuals from the electoral register and then from households, withcross-checking of the two sets of estimates.Repeated postal reminders, then domiciliary visits to ensure remarkablyhigh response rates and hence reduce attendance bias.Calibration of equipment and detailed analyses of calibration results bycenter, tester, and frequency to determine which effects were largeenough to be worth adjusting for.Initial stratification of first tier responses for efficient gearing ofclinical testing, then poststratification for populationprojections.A broad range of clinical and demographic data to be acquired, includinga rigorous structured protocol for eliciting and calculating lifetimenoise immission.The NSH was designed to determine the prevalence and characteristics of both measuredhearing impairment and self-reported hearing disability in adults (18–80 years) as afunction of severity, age, gender, occupational group, and occupational noiseexposure  and to maintainaudiometric calibration and fixed procedures.HiA OnlineAppendix 1) was informed by related earlier work by In the first tier, a postal questionnaire on hearing, tinnitus, and demographics wassent to 48,313 adults selected at random from the electoral registers. The overallresponse rate was 80%. The questionnaire (reported in HiA Online Appendix 4), otologicalexamination and clinical interview. The sample was initially stratified by age,self-reported hearing, and whether they possessed a hearing aid . For efficiency and precise estimation of means and variances, thestratum with self-reported hearing disability was sampled more densely than thosewith no reported hearing problem. For example, all those who reported in Tier 1 thatthey used a hearing aid were contacted to take part in Tier 2, whereas only about 1in 25 people who reported no hearing problem whatsoever were contacted. The finalTier B sample contained 2,578 individuals with complete audiograms at the usualoctave-spaced frequencies up to 8 kHz for each ear but additionally including 3, 6,and 12 kHz. There were 2,208 otoscopic examinations. The data were poststratifiedfor calculating prevalences, according to location, age band, gender, andself-reported hearing.In the second tier, a reduced sample drawn from those who responded to Tier 1 wasinvited to one of the four clinics of MRC IHR for an audiological assessment, adetailed questionnaire (see https://acorn.caci.co.uk/what-is-acorn). This was a widely usedsurrogate residential marker for socioeconomic status. This study also had atwo-tier design, with a postal questionnaire followed by a home visit forabbreviated clinical assessment.A complementary two-stage study was also conducted on 6,650 addresses to check thenational representativeness of the main study sample. The addresses were chosen fromthe U.K. Postal Address File, which was the most complete postcode database in theUnited Kingdom at the time, also being stratified by health region and by the CACIAcorn housing type .Tinnitus was defined as having prolonged sustained tinnitus,lasting more than 5 min: “Nowadays, do you get noises in your head or ears?” “Dothese noises usually last longer than 5 minutes” .Hearing-aid possession was “yes” to “Have you ever had ahearing aid?” Further definitions were as follows: for audiometry,standard across-frequency averages were calculated on audiograms, with a pragmatic boundary for conductive hearingloss was taken as an air-bone gap ≥15 dB when averaged over 0.5, 1, and 2 kHz. Occupational groups were basedon head-of-household information collected at the clinical interview rather than theself-report data. They were coded in accordance with the recommended RegistrarGeneral’s Classification of Occupations at the time . Noise emission was defined interms of the equivalent continuous sound level (Leq) fora 50-year working lifetime; no noise was ≤80 dB(A). The 80-dBcutoff was used to identify individuals with no noise exposure in the screened data.Higher bands were also defined, but these were only used in associated papers. This led to another major product ofthe study: a parsimonious four-term demographic model for predicting the probabilityof a hearing loss in October 2017. The British Library’s (BL) digitization department undertook thetask of scanning HiA. Photographic reproduction was brieflyconsidered, but pilot work showed that scanning was preferred as generallydelivering more consistently high quality. The digital version was thus created byscanning each page of a copy of HiA and then converting to PDF. Dueto an oversight on our part, the opening material  was not scanned by the BL. This was therefore done by one of us(Akeroyd) at the University of Nottingham and then added to the PDFs. The BL scan isfully text searchable so that any table, section, or page can be accessed rapidly.It is easy to find key words in the text chapters, which enables a high degree ofaccess to the data in a relatively raw form.Online Chapters 1 and 2 give an overview and describe the methods; Online Chapters 3,4, and 5 report, respectively, the prevalence, distribution, and type of hearingimpairment; Online Chapters 6, 7, and 8 report, respectively, hearing impairment byage, social classification, and regional districts current in the mid-1980s; andOnline Chapters 9 and 10 cover self-reported hearing impairment.For the overall prevalence of hearing loss (four-frequency average) inthe better ear across age, gender, and occupational group, see TableB5124-1 (online p. 46).For the prevalence of hearing loss up to 95 dB for those aged 80+, seeTable 8.1 (online p. 822).For medico-legal purposes, see the tables in Online Chapter 4 for decadebands giving audiometric averages and distributions for each of theeight test frequencies, stratified by gender, and manual/nonmanualoccupational group. Online Chapter 6 is also useful, giving data insingle-year bands of three- and four- frequency averages by gender alongwith their distribution in percentiles.A first-time reader may be somewhat daunted by the amount of data and the number oftables. As an orientation, it is therefore useful to give examples of some tablesthat are most useful for answering particular questions: In more detail, Online Chapter 3 reports the cumulative prevalence of differentdegrees of hearing impairment (0 to 95 dB in 5- or 10-dB steps) for each ear andfrequency (plus frequency average) as a function of age-group (decades), gender, andoccupational group . There is a table for every combination ofage , gender , occupational group , audiogram , and ears (better or worse). Online Chapter 4reports the distribution of hearing threshold levels  for the same combinations ofclassifications, along with new classifications of everyone or “normal” ears  only, and better, worse, left, and rightears. The plots on pp. 357–358 illustrate the mean hearing losses by gender anddecade for the better and worse ears, also left, right, and overall.Online Chapter 5 reports prevalences classified by conductive loss, sensorineuralloss, or normal hearing with factorial tables by age, gender, and occupationalgroup. Online Chapter 6 provides numerical estimates of the percentiles of thedistribution of hearing impairment year-by-year then models the percentiles of thehearing threshold distribution using a smoothing window within the regression, as afunction of age, gender, and type of population. Note that this is the only chapterthat reports modelled data; all other chapters use estimates from the data that arenot smoothed or modeled in any way. The tables are structured by age, gender,otologically typical or otologically screened , conductive or sensorineural hearing loss, and ear.Appendices reproducing the questionnaires andprotocols, together with a Foreword by Mark Haggard and a Preface by AdrianDavis.Online Chapter 7 presents the distribution of hearing impairment as a function of afull social class coding according to head of household. The tables reportcombinations of age, gender, and particular ear. Online Chapter 8 projects the datato estimate the number of people at different levels of severity, for localauthority and health regions and districts in Great Britain, as at 1992. The numberswere derived using census figures for the population and its age structure; theyhave been recalculated since e.g., . FinallyHiA makes the data andconclusions as widely available as modern technology allows. In doing so, ithighlights the clearest weakness in the NSH as a project, namely, its dissemination.Just 550 copies of HiA were printed, and so there was a generalfailure to secure the justified broad distribution and promotion of the study.The accompanying digital reprinting of Timeliness is high on the list of desirable properties for science, so it may beasked why we are now republishing research prioritized and conceived in the 1970sand executed in the 1980s. We argue that the NSH’s continued relevance is rooted inthe scale of the study and the quality and breadth of its data. The quality is dueto the profound multidisciplinary professional care taken in its design, protocols,execution, and analysis. This level of care required substantial resources; thus,the field of hearing arguably owes a permanent debt of gratitude to the U.K. MedicalResearch Council, and the English, Welsh, and Scottish Health Departments. In thelate 1970s and early 1980s, their funding of MRC IHR (see Appendix) enabled it tobuild up a team of applied scientists with the necessary multidisciplinaryknowledge, ensured it had the breathing space for a profound consideration ofmethodological and logistical issues, and allowed piloting to work out exactly whatneeded to be done and how, all with the purpose of giving the requisitegeneralizability and precision. This marriage of research resources and hospitalresources was crucial, and is usually hard to achieve. It is perhaps unlikely thatsuch a harmonious conjunction of resource, expertise, purpose, and team structurewould occur again in the foreseeable future. The NSH may remain unequaled in itsexperimental care.use, the simple answeris yes, as evidenced by the fact that it was one of seven data sets used todetermine the current ISO standard for the statistical distribution of hearingthresholds related to age and gender (ISO 7029:2017). Almost 90% of theHiA median thresholds for the combinations of Frequency × AgeBand × Gender  are within ±5 dB of the corresponding ISO values,though the differences reach up to 10 dB for some of the 8-kHz data or for the 71 to80 age band. In terms of purpose, the answer is more complicatedbecause a study like HiA is unlikely ever to be replicated at thesame scale and quality as the NSH and because the population, with its health andlife, has moved on. Certainly most of the empirical methods are still used;someone’s hearing is still established subjectively by self-report questionnaire andobjectively by pure-tone audiometry. Stratification questions similar to “Do youfind it very difficult to follow a conversation if there is a background noise, egTV, radio, children playing?” are still used routinely in survey or cohort work, but forthe population in total, having many more older people will have made the populationaverage hearing level worse. The life expectancy at age 65 years has increased from13 and 17 years  to 19 and 21 years . ThemagThird, the growth of obesity and diabetes is a major change in population healtharound the world. There is now consistent evidence from large cohort studies of anassociation of diabetes with hearing loss e.g., , althougHiA waspublished and about 40 years since the project was started, much scientific andpublic comment on the prevalence of hearing loss  is,ultimately, traceable to its data.Against this reservation about the possible incompleteness of the projection modelinto the indefinite future and to all populations must be placed the severalfavorable considerations discussed earlier, of which the main two are (a) thecontinuity of standards in the audiological test measures plus relevantquestionnaire items and (b) the uniquely comprehensive design and sampling,otological screening, and attention to measurements. These give the NSH a continuingimportance and relevance. It remains a primary source of formal control data anddetailed distributions of audiological level by age, gender, occupation, and noiseexposure. Thus, despite it being nearly 25 years since https://www.nottingham.ac.uk/mrcihr/index.aspx for a finaloverview.The MRC Institute of Hearing Research was founded in 1977 following the advocacy oftwo members of the Wilson Government of the United Kingdom: Jack Ashley(Parliamentary Private Secretary) and Barbara Castle . It was an intramural unit of the Medical Research Council,which was set up to conduct and coordinate multidisciplinary research in hearing.The NSH was one of its primary projects; the need for multicenter studies set therequirement for the multicenter structure of IHR that continued throughout itshistory. The Institute closed in 2018. See Click here for additional data file.Supplemental material, TIA887614 Supplemental Material for Hearing in Adults: ADigital Reprint of the Main Report From the MRC National Study of Hearing byMichael A. Akeroyd, George G. Browning, Adrian C. Davis and Mark P. Haggard inTrends in Hearing


Improvement of speech perception in quiet is an important goal of hearing aid provision. In practice, results are highly variable. The aim of this study was to investigate the relationship between type and extent of hearing loss (audiogram type), maximum word recognition score, and aided speech perception.max) and the monosyllabic speech recognition score with hearing aids, WRS65(HA) were analyzed for 10 different standard audiogram types.Pure tone and speech audiometric data of 740 ears in 370 patients were reviewed. All subjects visited our hearing center for hearing aid evaluation between 2012 and 2017. The maximum word recognition score (WRS65(HA) with hearing aids for different degrees of hearing loss is, within error boundaries, comparable to previous investigations and shows a difference of 10–20 percentage points to the WRSmax. This difference tends to be larger for flat and moderately sloping audiograms compared to steep-sloping audiograms. The ratio WRS65(HA)/WRSmax can be interpreted as an efficiency factor for hearing aid provision, since it relates speech recognition with hearing aids to the maximally achievable information carrying capacity of the hearing impaired.The WRSThe expectation regarding hearing aid provision has to be adjusted according to maximum word recognition score, the derived quality measures, degree of hearing loss, and audiogram type. Hearing loss is one of the five most frequent disorders with a substantial impact on quality of life . In Germ65(HA), for moderate and severe hearing loss is on average 20 percentage points below the maximum word recognition score (WRSmax), as measured in the speech audiogram with headphones. For a sample of n = 181 individuals provided with hearing aids, a statistical correlation was found between the mean of the hearing thresholds at 0.5, 1, 2 and 4 kHz  and the WRSmax or WRS65(HA) was found. This can be described by the following equations.A previous study  investigDeutsches Institut für Normung, DIN) EN 60118-15 and is intended to represent typical audiograms of hearing aid users. This DIN norm requires a realistic characterization of the hearing aids and the hearing aid setting. It therefore makes sense to apply these standard audiograms to clinical issues associated with hearing aid provision. All standard audiograms shown in Fig. N-type, with a maximum decay of 20 dB per octave) and with strong (S-type with maximum decay of at least 25 dB per octave) frequency dependence. These types were subdivided into seven or three subtypes depending on the degree of hearing loss (N1–N7 and S1–S3).In other studies with hearing aid users, comparable values were found for the parameters mentclasspt{minimat}β0andβ1. For furThe aim of the present study was to investigate speech recognition with and without a hearing aid as a function of the extent and the frequency course of hearing loss for a large population of hearing aid users. In addition, the authors investigated the extent to which the earlier findings  also appIn this retrospective study, 2357 hearing aid examinations were evaluated; these were performed between August 2012 and September 2017 in the Erlangen ENT Clinic, Germany. Bilateral hearing aid users with at least 3 months of hearing aid experience, German as mother tongue and a minimum age of 18 years were included. The exclusion criteria included abnormal otoscopic results, a mean air–bone gap at 0.5, 1, 2 and 4 kHz of more than 5 dB, an asymmetry of 4FPTA on both sides of more than 20 dB and any technical defects in the hearing aids. The data from a total of 740 ears from 370 users  aged 21 to–98 years  remained.65).Pure-tone air-conduction thresholds were measured for frequencies between 0.125 and 8 kHz and bone-conduction thresholds between 0.25 and 6 kHz. The Freiburg monosyllable test was used to measure speech recognition. The measurements in quiet were performed with monaural presentation using headphones, initially at 65 dB SPL . The uncomfortable loudness level (UCL) corresponds to the lowest speech presentation level that is no longer tolerated. In addition to WRSSPL for the left and right ear separately; the contralateral side was adequately blocked with earplugs.The hearing aid check included a visual inspection and feedback provocation of oscillation. In addition, qualified personnel (hearing aid acousticians) checked whether the type and model of hearing aid provided were appropriate for the individual’s hearing loss. The amplification was checked by measurement in situ. The speech test with hearing aid was conducted in free field at 65 dB1–N7 and S1–S3 according to Bisgaard [For all patients, the audiometric data of the 740 ears were analyzed for each side separately. Cases were classified according to their hearing-loss characteristics into the 10 audiogram types Nmax and WRS65(HA) the differenceFor comparison of WRSmax that can be amplified by the hearing aid to give a speech perception of 65 dB SPL. It can be interpreted as the speech-audiometric efficiency factor of the hearing aid in question.The quotient Q stands for the proportion of the WRSmax or WRS65(HA), as a function of hearing loss, 4FPTA, was performed in a manner analogous to that described by Hoppe et al. [Logistical regression analysis of speech recognition, WRSe et al. . The nonn) are shown to the right of the curves.The 10 standard audiogram types, according to Bisgaard [Table Fig. 1, N2 and S1) all hearing aid users achieved a WRS65(HA) greater than 50%. For moderate hearing loss (N3 and S2), this was achieved in 75% of the cases. Of the users with severe hearing loss—groups N4 and N5, as well as S3—only a quarter had speech recognition scores above 50%. For the groups N6 and N7, with profound hearing loss up to deafness, this 50% score was observed in only a few isolated cases: four out of 71 in the N6 group and one out of 80 in the N7 group. As shown in Fig. For mild hearing loss N1, N and S1 amax for the individual groups is shown in Fig. max is approximated by the WRS65(HA). Fig. max greater than zero. For example, for the N6-type group, WRSmax above zero was found in 60 of 71 cases. The corresponding results for the other groups are stated above the border of Fig. J, the standardized test statistic z and the corresponding p value are: J = 36468, z = −11.7 and p < 0.001 for N‑type audiograms and J = 1020, z = −5.8 and p < 0.001 for S‑type audiograms.Fig. max and light grey for WRS65(HA). The results of the logistical regression of the WRSmax or WRS65(HA) are shown separately for N‑type and S‑type hearing-loss audiograms. The regression calculation was performed for 618 N-type cases (ears) and for 122 S‑type cases. While the curves for WRSmax of the N‑type groups lie within the 95% confidence interval, the fit of WRSmax for the S‑type groups lies below the 95% confidence.Fig. 65(HA) are largely within the 95% confidence interval, with a tendency toward better values for the S‑type groups (severe hearing loss) compared with N‑type groups (mild to moderate hearing loss).A different picture emerges for speech recognition with hearing aids: The two regression functions for the WRSThe aim of this work was to investigate the correlation between the pure-tone and speech-audiometric measures as assessed during hearing aid evaluation. The focus was on: (i) understanding speech in quiet, (ii) the improvement through a hearing aid as the principal effect of hearing-aid provision and (iii) the relationship to maximum monosyllable recognition. Extending the scope of previous work , 8, the 65, with or without a hearing aid, is primarily determined by the 4FPTA. For the WRS65(HA), the type of audiogram provides additional information  decays monotonically, in both N and S audiogram types, with increasing 4FPTA. However, the regression function for the hearing aids in patients with S‑type audiograms is above the regression function for those with N‑type audiograms. In particular, a comparison of the N3 and S2 groups—with nearly equal 4FPTA and approximately equal age distribution—shows that the WRS65(HA) for the S‑type audiograms is 15 percentage points above the WRS65(HA) for the N‑type audiograms. The results of the logistical regression support this finding: In low to moderate hearing loss, good speech recognition can be achieved with hearing aids, especially in cases where the audiogram is steep. While in the S groups the steep drop in the audiogram in the headphone measurement of WRSmax obviously leads to poorer results, the provision of a hearing aid compensates better for the frequency-specific attenuation component of hearing loss.WRSsee Fig. b. WRS65 to WRSmax, as shown in Fig. In the N groups, the frequency-independent amplification in the WRSmax of the S group can be compensated for by the advantages associated with the open-fit design [A further explanation could be the increasing availability of open-fit hearing aids in the last few years, for which the S‑type audiograms are well suited in respect of the tonal-audiometric prerequisites . An initt design , 20.Fig. max and WRS65(HA) against the background of the speech audiometric evaluation of a hearing aid provision. The Guideline for Hearing Aids of the German Joint Federal Committee (Gemeinsamer Bundesausschuss) [65(HA) over WRS65 of at least 20 percentage points. It also calls for WRS65(HA) to converge with the WRSmax as closely as possible, even if this is often not achieved [max and WRS65(HA) below 20 percentage points for the majority of hearing aids provided. For these areas, the known floor and ceiling effects of the language test used will necessarily limit the difference, and thus its diagnostic value.Another aspect of the present work was the further description of the relationship between WRSachieved , 15, 21.achieved , 21, 26.max = 0% is of little practical relevance here. In these cases alternative speech tests should be considered. If this is not possible, then speech audiometry is in any case not an appropriate method for assessing hearing aid provision.For mild to moderate hearing loss, most hearing aids can achieve an efficiency factor greater than 3/4. From a moderate degree of hearing loss upwards (4FPTA >60 dB) this falls to 1/2. The fact that the efficiency factor is not defined for the case of WRSmax and WRS65(HA) are identical. The difference is zero and the efficiency factor one. Relevant differences only arise if the WRSmax is not achieved. The efficiency Q quantifies the actually attained proportion of the greatest possible speech recognition (information-carrying capacity [Table capacity ) and canThe results presented here, obtained at a specialized ENT clinic with an associated hearing-aid and cochlear-implant centre, are confirmed by other work , 19, 21 65(HA), and maximum word recognition score, WRSmax measured with headphones, provides additional information on the speech-audiometric efficacy of the hearing aid.The ratio between speech understanding with the hearing aid, WRSThe efficiency of a hearing aid provision is on average higher with strongly frequency-dependent S-type audiograms than with the flatter N-type audiograms.For hearing losses below 60 dB HL, the efficiency is close to one; above 60 dB HL, on average, values of only 1/2 are achieved.


Supplemental Digital Content is available in the text. oSo). Unfortunately, presentation of identical stimuli to each ear inhibits detection of unilateral sensorineural hearing loss (SNHL), and neither diotic nor monaural presentation sensitively detects conductive hearing loss (CHL). After an earlier finding of enhanced sensitivity in normally hearing listeners, this study tested the hypothesis that interaural antiphasic digit presentation (NoSπ) would improve sensitivity to hearing loss caused by unilateral or asymmetric SNHL, symmetric SNHL, or CHL.The digits-in-noise test (DIN) has become increasingly popular as a consumer-based method to screen for hearing loss. Current versions of all DINs either test ears monaurally or present identical stimuli binaurally  with various levels of hearing based on a 4-frequency pure-tone average (PTA) at 0.5, 1, 2, and 4 kHz. The study sample was comprised of listeners with normal hearing , symmetric SNHL , unilateral or asymmetric SNHL , and CHL . Antiphasic and diotic speech reception thresholds (SRTs) were compared using a repeated-measures design.r > 0.89). Area under the receiver operating characteristics curve for detection of hearing loss (>25 dB HL) was higher for antiphasic DIN (0.94) than for diotic DIN (0.77) presentation. After correcting for age, PTA of listeners with normal hearing or symmetric SNHL was more strongly correlated with antiphasic  than diotic  SRTs. Slope of fitted regression lines predicting SRT from PTA was significantly steeper for antiphasic than diotic DIN. For listeners with normal hearing or CHL, antiphasic SRTs were more strongly correlated with PTA  than diotic SRTs . Slope of the regression line with PTA was also significantly steeper for antiphasic than diotic DIN. The severity of asymmetric hearing loss (poorer ear PTA) was unrelated to SRT. No effect of self-reported English competence on either antiphasic or diotic DIN among the mixed first-language participants was observed.Antiphasic DIN was significantly more sensitive to all three forms of hearing loss than the diotic DIN. SRT test–retest reliability was high for all tests (intraclass correlation coefficient Antiphasic digit presentation markedly improved the sensitivity of the DIN test to detect SNHL, either symmetric or asymmetric, while keeping test duration to a minimum by testing binaurally. In addition, the antiphasic DIN was able to detect CHL, a shortcoming of previous monaural or binaurally diotic DIN versions. The antiphasic DIN is thus a powerful tool for population-based screening. This enhanced functionality combined with smartphone delivery could make the antiphasic DIN suitable as a primary screen that is accessible to a large global audience. Hearing loss presents a significant global health burden as the fourth leading contributor to years lived with disability . MountinPoor awareness of hearing loss and existing models of clinic-based adult screening among the lay public also contribute to hearing healthcare inaccessibility . In effor = 0.77) it demonstrated sensitivity and specificity of more than 90% to detect SNHL . On the other hand, global access to smartphones by adults is estimated to be 80% by the year 2020, providing a modern-day alternative . WhereasThere has been a growing interest in increasing the efficiency and sensitivity of existing DINs using various test modifications. Using a fixed-SNR procedure, oSπ) was shown to improve DIN SRTs in normal-hearing listeners  or present the test stimuli binaurally and identically to each ear (homophasic or diotic). This binaural DIN setup allows for rapid testing in approximately 3 min, whereas sequential testing of each ear doubles test time and may thus reduce uptake and completion. Using diotic presentation may, however, preclude detection of unilateral or asymmetric SNHL. These listeners may pass the diotic DIN test because performance is largely based on the functionally better ear . Furtheristeners .oSo), only slight SNR variations were observed across a range of interaural level differences. However, in the antiphasic condition (NoSπ), SNRs became worse with increasing interaural level differences.Sensitivity differences between diotic and antiphasic auditory stimulus presentations are commonly known as the binaural masking level difference . Before oSo) presentation was small (≅1 dB). However, the use of antiphasic digits (NoSπ) provided a further ≅5 dB advantage. Listeners with unilateral SNHL or CHL are not expected to have full access to the antiphasic advantage due to subtle timing irregularities caused by peripheral hearing loss, either sensorineural . All eligible participants were informed on the study aims and procedures and provided consent before participation.oSo) or were phase inverted between the two ears . To prevent possible learning of the masking noise  earbuds in a quiet, office-like room. The first training test used antiphasic presentation. The remaining four DIN tests alternated between antiphasic and diotic DIN, with a test and retest for each participant. The test order was therefore: (1) antiphasic training list, (2) antiphasic test, (3) diotic test, (4) antiphasic retest, and (5) diotic retest.f = 0.25), with 80% statistical power at 2-tailed significance level of 0.05, to test both hypotheses. The sample of 23 listeners with CHL was subsequently added.Statistical analysis was done using the Statistical Package for the Social Sciences (IBM SPSS v25.0). A sample size of 122 listeners  would provide a medium effect size (Cohen’s t test. Intraclass correlation coefficients (ICC) were calculated and were based on a mean rating of the number of observations  of both diotic and antiphasic test conditions, absolute agreement, and a two-way mixed-effects model. In addition, measurement error between test-retest for diotic and antiphasic presentation was calculated by determining quadratic mean (√2) of within-subject SDs for the test–retest measures. All subsequent analyses were conducted by averaging the test and retest SRT values for the diotic and antiphasic DIN. Associations between poorer ear PTA and SRT were examined using Pearson’s partial correlation. ROC curves were calculated to determine the sensitivity and specificity of the DIN tests for different cutoff values, to detect mild hearing loss and worse (PTA > 25 dB HL) and moderate hearing loss and worse (PTA > 40 dB HL). SRT cutoff values corresponding to reasonably high sensitivity and specificity were chosen while demonstrating the trade-off between sensitivity and specificity .The effect of test condition  and hearing loss category  on the SRT was assessed using repeated-measures analysis of variance. Post hoc comparisons used Bonferroni adjustment for multiple comparisons. In cases where sphericity was violated, Greenhouse-Geisser corrections were applied. Analysis of covariance was used to determine the effects of age and English-speaking competence on the diotic and antiphasic SRT. General linear regression was used to test whether the slope of the relation between PTA and SRT differed between antiphasic and diotic testing. The effect of test repetition on antiphasic SRT was investigated using a paired sample Listeners with normal hearing had lower SRTs than those with hearing loss using both diotic and antiphasic testing Fig. . Howeverp < 0.001). The correlation was, however, stronger for antiphasic . For listeners with either normal-hearing or symmetric SNHL, poorer ear PTA was significantly (p < 0.001) correlated with both antiphasic  and diotic  SRTs  = 7.79.14, p < 0.001). Antiphasic SRTs of listeners with normal hearing or CHL were more strongly correlated to poorer ear PTA  than diotic SRTs . The slope of the fitted regression was also significantly steeper for antiphasic compared with diotic SRTs , indicative of greater sensitivity of the antiphasic DIN. The severity of unilateral or asymmetric SNHL (poorer ear PTA) was unrelated to SRT. For the diotic DIN, there was substantial overlap between the SRTs of normal-hearing listeners and those in each of the three hearing loss groups . Similarly, diotic test and retest showed no significant SRT difference (p = 0.6). SRT test–retest reliability was high for listeners with normal hearing or SNHL for both diotic DIN  and antiphasic DIN . Listeners with CHL had high test–retest reliability for antiphasic DIN, with ICC of 0.88 , but had poorer ICC of 0.61 for homophasic DIN . Diotic DIN had lower measurement error  than the antiphasic DIN  for the whole sample, but the variance between listeners was much higher for the antiphasic DIN than for the diotic DIN  across hearing categories after the presentation of the initial antiphasic training list (p = 0.16) was found between the two groups for either the diotic DIN  or the antiphasic DIN .The effect of competence in the English language on SRT was assessed by dividing listeners into high competence  and lower competence  groups. Controlling for poorer ear PTA and age, no significant SRT difference (http://links.lww.com/EANDH/A559) but because of interaural summation and unmasking effects that interaction is complex  because the SRT improvement is larger compared with the NπSo condition , but in most cases (20/23) were still within the normal-hearing range. Earlier studies demonstrated that antiphasic processing is disrupted by acute CHL that both attenuates and delays sound passing through the ear . ChronicListeners with normal hearing and SNHL had a small training effect between the antiphasic training list and test condition. There were no significant SRT differences between the diotic DIN and antiphasic DIN test and retest measurements. Similar findings were reported by The high sensitivity of a 3-min antiphasic DIN to detect hearing loss of various types, symmetries, and degrees holds significant potential for population-based screening. CHL, in the form of otitis media, is typically more prevalent among underserved, remote, and poor populations than other forms of hearing loss  but is nA smartphone platform of test delivery has proved a successful method of screening, allowing for directed referrals from cloud-based data management platforms , therebyIn conclusion, antiphasic SRTs correlated significantly better to poorer ear PTA than diotic SRTs. As a result, antiphasic presentation markedly improved sensitivity to detect SNHL and CHL, either symmetric or asymmetric, making it a powerful tool for population-based screening.The authors thank all the participants of this study, Steve Biko Academic Hospital, and all participating private practices for their assistance with data collection. The authors thank Li Lin for assistance with data analysis.


The main objective of this study was to explore the impact of hearing impairment on psychological distress and subjective well-being in older adults with hearing impairment.The study with cross sectional research design was conducted in three public sector hospitals of Lahore, from February 2017 to June 2017. Participants of the study were adults aged 50-90 years and with hearing impairment, selected through non-probability sampling technique. Demographic Information sheet, Kessler psychological distress scale by Kessler, Mroczek. in 1992 and Satisfaction with life scale by Diener, Emmons, Larsen, Griffin in 1985 were used for data collection. SPSS 21 was used to analyze the data.p<0.01). One-way analysis of variance revealed insignificant differences of psychological distress and subjective well-being across three levels of hearing impairment.There were 200 participants with age ranged from 53 to 89 years . Of the total, 100 (50%) subjects were men and 100 (50%) were women. Significant gender differences were found in psychological distress, with men reflecting more symptoms of psychological distress (p<0.01), whereas non-significant gender differences were found in case of subjective well-being (p>0.05). Moreover, psychological distress was observed as a predictor of subjective well-being (Early diagnosis and rehabilitation of age-related hearing loss improves the overall quality of life of older adults living with hearing impairment. Hearing impairment is described as the partial or total loss of hearing ability. On the basis of the severity of the problem hearing impairment can be classified as mild, moderate, severe and profound. Age related hearing impairment is a very common disorder in older adulthood. It is considered as third most prevalent chronic health condition in people over 65 years of age.3Hearing impairment in aging is substantially associated with disability, increased risk of incident morbidity, poor self-perceived health,7Psychological distress is defined as the condition of emotional disturbance with feelings of anxiety , depression . People may experience psychological distress while coping with the stressful, disturbing or harmful circumstances in their daily life.12Subjective well-being is how a person evaluates his/her life cognitively and emotionally as a whole, it basically includes cognitive judgments concerning life satisfaction and emotional reactions to life events that may be positive or negative.16Current study was aimed to gauge the impact of age related hearing impairment on psychological distress and subjective well-being in older adults. Gender differences in psychological distress and subjective well-being were studied. Additionally, predictive relationship between psychological distress and subjective well-being and difference in both variables were investigated.The cross sectional study was conducted in Lahore, from February 2017 to June 2017. The study sample comprised of 200 older adults 53 to 89 years old with hearing impairment, among the participants 100 (50%) were men and 100 (50%) were women. Non-probability purposive sampling technique was employed to select the sample. The clinical diagnosis of hearing impairment was carried by the physicians using audiometry. People with hearing impairment but less than 50 years of age were excluded from the study.A brief demographic form along with Kessler Psychological Distress Scale (K10) by Kessler and Satisfaction with Life scale (SWLS) developed by Diener and his colleagues, was used for data collection. Kessler Psychological Distress Scale (K10), was used to measure the mental condition of the participants. Scale consisted of 10 items graded on likert scale of five points . K10 was proved to be a better predictor of non specific psychological distress, anxiety and depression and is widely used as a global measure of psychological distress. The scale has good reliability, ranges from 0.89 to 0.91.17Subjective well-being of the participants was assessed by the Satisfaction with Life Scale (SWLS). This is a short form 5 item scale, responses were rated on 7 point likert scale (1 = strongly agree to 7 = strongly disagree). It is widely used scale for measuring life satisfaction having good psychometric properties. The reliability of scale was reported by authors as 0.87.18Prior to data collection informed consent was obtained from the participants after elaborating the purpose of the study, they were assured about the confidentiality of their personal information. Urdu versions of Kessler Psychological Distress Scale (K10) and Satisfaction with Life Scale (SWLS) were administered to collect data about study variables. Personal demographics of patients were obtained on separate sheet prepared to collect information regarding age, gender, marital status, family system, socio-economic status and necessary details about their problem. SPSS 21 version was used for data analysis. Analysis of the basic variables was done by using descriptive statistics. Gender differences among two study variables were studied by using independent sample t-test. Linear regression analysis was used to find out whether psychological distress is a predictor of subjective well-being. One-way analysis of variance was used to find out if there are any differences among psychological distress and subjective wellbeing among different levels of hearing impairment in older adults. Ethical clearance was obtained from the ethical and research committee of the Lahore College for Women University, Lahore with IRB number 138 and issue date of 13-01-20.Of the 200 participants 100 (50%) subjects were men and 100 (50%) were women. Overall mean age was 65.92±9.7. Majority 138(69%) participants were living in nuclear family system. Most of the participants 139(69.5%) were married, 123(61.5%) belonged to middle class. Education statistics showed that 105(52.5%) participants were educated and 95(47.5%) were uneducated. Majority 101(50%) were having moderate hearing disability, 71(33.5%) with mild, 22(11%) with severe and 6(3%) were dealing with profound hearing impairment.Gender differences in psychological distress and subjective well-being in both genders were studied. Psychological distress was reported to be higher in males (p<0.05) as compared to females. But no gender differences were found in subjective well-being (p>0.05) .Linear regression analysis was used to find out the predictive relationship between psychological distress and subjective well-being in adults with hearing impairment. Results indicate that psychological distress was significant predictor of subjective well-being (p<0.01) .One-way analysis of variance was employed to test if there are any differences in perceived psychological distress and subjective well-being among different levels of hearing impairment. Results revealed that there were no significant differences found for both variables in different levels of hearing impairment (p>0.05) .Hearing impairment is the most common sensory disability in older adult. Review of the previous literature suggests that hearing impairment is negatively associated with the mental health and the quality of life of adults.Gender differences in subjective well-being and psychological distress in adults with hearing impairment were explored in the study. No gender differences were found in case of subjective well-being, but for psychological distress men scored significantly higher as compared to women. In old age most of the people consider age related hearing impairment as the part of normal aging process. That is the main reason of not having a major impact of the problem on their subjective well-being. Current findings are in line with the previous literature, where hearing loss was found to be associated with psychological distress in both men and women, but slightly more depressive symptoms were observed in men than it may affect women. It may be due to the reason that men experience an additional source of psychological distress due to the fact that they usually face the societal pressure of being the bread-winner for the family, and the disability hamper their daily life functioning to a greater extent.Results of the study revealed that psychological distress is a predictor of subjective well-being among older adults with hearing impairment. These findings correspond with the existing literature suggesting that hearing loss actually cuts off the person facing problem form other people of society. People facing problems in communication with others may experience withdrawal from social interactions, feeling of being excluded, poor quality of life and loneliness that lead to the feeling of depression and having higher rate of psychological distress.10A study intended to explore the quality of life of people having hearing loss proved that hearing impairment was positively associated with psychological distress, where people experiencing more psychological distress tend to have decreased overall quality of life.9Subjective wellbeing and psychological distress in older adults dealing with different levels of hearing impairment was studied. Present study provided evidence that no significant differences were found in both variables among varying levels of hearing impairment. It is evident from the literature that problem in high or medium frequency hearing has nearly no impact on mental health if low frequency hearing was not affected.This study will provide an important insight for health care practitioners to introduce new plans and policies to figure out the issue at initial level and to prevent mental health problems and improve the well-being of adult population with hearing impairment. As the age related hearing impairment is slightly unnoticeable disability, so it can be easily neglected by the people, especially if they are having any other major health related problems. This situation necessitate the formulation of effective framework for the timely identification of the problem and to ensure the availability of proper hearing aids and other assistive techniques to the people already having or at risk of hearing loss. It is recommended that professionals working with this population should carry out screening for psychological distress along with the physical monitoring of hearing loss. Social support is an important aspect regarding the management and rehabilitation of older adults with hearing impairment.Sample of research comprised of participants from few public sector hospitals of only one city, it was mainly due to lack of resources. Psychological impact of the hearing impairment may vary in different areas or countries. To resolve the concerns related to external validity studies should include multiple public and private sector institutes form different areas of Pakistan. Future researches are needed to elucidate the relationship of hearing impairment and mental health involving more personal and environmental factors more importantly.Gender appear to be a variant in Psychological distress reflecting high distress in men with the said condition however for the subjective well-being there were no gender differences observed. Moreover, psychological distress was found to be a predictor of subjective well-being in adults with hearing impairment and no significant differences in psychological distress and subjective well-being were found in different levels of hearing impairment.YN: Conceived, designed and did statistical analysis & editing of manuscript. She is also responsible and accountable for the accuracy or integrity of the work.BE: Supervised research.AM: Did review and final approval of manuscript.


For distinguished parameter regimes corresponding to chemotaxis-dominated cell movement and low branching rates, both continuum models reduce at leading order to identical PDEs within the domain interior. Numerical and analytical results confirm that pointwise differences between solutions to the two continuum models are small if these conditions hold, and demonstrate how perturbation methods can be used to determine when a phenomenological model provides a good approximation to a more detailed coarse-grained system for the same biological process.Although discrete approaches are increasingly employed to model biological phenomena, it remains unclear how complex, population-level behaviours in such frameworks arise from the rules used to represent interactions between individuals. Discrete-to-continuum approaches, which are used to derive systems of coarse-grained equations describing the mean-field dynamics of a microscopic model, can provide insight into such emergent behaviour. Coarse-grained models often contain nonlinear terms that depend on the microscopic rules of the discrete framework, however, and such nonlinearities can make a model difficult to mathematically analyse. By contrast, models developed using phenomenological approaches are typically easier to investigate but have a more obscure connection to the underlying microscopic system. To our knowledge, there has been little work done to compare solutions of phenomenological and coarse-grained models. Here we address this problem in the context of angiogenesis (the creation of new blood vessels from existing vasculature). We compare asymptotic solutions of a classical, phenomenological “snail-trail” model for angiogenesis to solutions of a nonlinear system of partial differential equations (PDEs) derived via a systematic coarse-graining procedure :012410, 2017. The online version contains supplementary material available at 10.1007/s00285-021-01570-w. Continuum and discrete approaches are widely used to develop theoretical models for biological systems. In the former framework, one approximates quantities of interest using continuous variables and measures their evolution in space and/or time via differential equations. By contrast, discrete approaches describe the behaviour of individual “agents” (such as cells or molecules) in simulations , we still have a poor understanding of how different parameter values and agent interaction rules affect their solutions over large spatial and temporal scales. Kursawe et al. , for exaCoarse-grained macroscopic partial differential equations (PDEs) represent a possible candidate for this framework. They are constructed from discrete-to-continuum derivations, rather than from phenomenological arguments, and describe how the average distribution of agents in a discrete model evolves over time and space  compartment-based models  and E the column averaged tip and stalk cell densities, respectively, at location C the column averaged concentration of a generic TAF that regulates the cell dynamics. The system is closed by imposing no-flux boundary conditions for the tip cells . We assume that the source of TAF is located at G(x) and H(x) represent the tip and stalk cell densities at time D, The coarse-grained PDE describes the P–ABM’s average distribution of tip and stalk cells over time and space. Although the full system of equations is formulated in 2D, it may be reduced to one spatial variable by column averaging the dependent variables, making a mean-field approximation, and non-dimensionalising the equations with appropriate length and time scales. The resulting 1D coarse-grained system can be written in Cartesian coordinates as follows: we denote by In Eq. , the expy et al. , we chooC by setting Equation  describen to Eq.  in this n to Eq. , is \docN, E, C, D, The second continuum angiogenesis model that we investigate is based on the classical “snail-trail” framework. Its defining feature is that the stalk cell density increases at a rate proportional to the magnitude of net tip cell flux, which models the experimental observation that stalk cells proliferate along the path of tip cells . We . We N as t as t\docmentclass2pt{minimAlthough the P–PDE has a different stalk cell evolution equation than the ST–PDE and contains additional nonlinear terms, Pillay et al.  found thIn this article, we compare the behaviour of solutions to the ST–PDE and P–PDE in order to determine when they will be in good agreement. In Sect. mutatis mutandis, and is presented in Appendix The procedure we use to reduce the ST–PDE and P–PDE to their dominant, leading order dynamics is presented below. For clarity, the details are shown only for the ST–PDE: the analysis for the P–PDE follows All parameter values in the ST–PDE are equal to their counterparts in the P–PDE.The initial and boundary conditions for the ST–PDE and P–PDE are identical.After substituting equation (x in terms of the new independent variables. Equations ((A3)Tip cell movement is dominated by chemotaxis and the branching rate is sufficiently small so that Assumption (A3) is motivated by research that suggests chemotaxis up TAF gradients is the dominant mechanism by which tip cells migrate  then thenAll mentclasspt{minimamentclasspt{minimaquations –22) in  in All pquations : (A3)TipWe will also assume for the remainder of this section that the ratio U of the formWith into Eq. , and equmentclass2pt{minimX and Figure entclass1pt{minimaentclass1pt{minimaCrucially, we show in Appendix X).We have validated these conclusions with numerical results. Figure The ST–PDE and P–PDE tip cell solutions appear to travel with similar speeds in Fig. The ST–PDE tip cell solutions appear to be indistinguishable from those of the P–PDE. We investigated this further by computing the largest pointwise difference between the ST–PDE and P–PDE tip cell solutions over the spatial domain and normalising that value by the maximum tip cell density at each time point , and hez into one in terms of the unscaled variable X: if we redefine the wave speed as To our knowledge, there is no closed-form solution to the boundary value problem given by Eq.  that is entclass1pt{minimaWe observe in Fig. d by Eq. .At this point, we have only presented self-similar solutions to the leading order inner tip cell density in the case where A is a constant such that A is uniquely determined by solving the ODE, satisfying the two boundary conditions, and enforcing the constraint that the solution must be non-negative. This sets When d by Eq. . This isIn this article, we have analysed two continuum models for angiogenesis: the snail-trail and Pillay PDE systems. The P–PDE is a nonlinear mean-field model that describes the coarse-grained behaviour of a discrete, rule-based ABM  reveal that stalk cell solutions of the ST–PDE and P–PDE are different to each other near the left-hand boundary. Thus, one extension of our analysis is to identify potential boundary layers in the leading order ST–PDE and P–PDE solutions, and match them to the dynamics derived in Sect. The approach taken in this paper may be generalised to study the relationship between the ST–PDE, P–PDE, and other nonlinear continuum models for angiogenesis. As a particular example, we cite a coarse-grained system from Bonilla et al. , which hAlthough we identified parameter regimes for which two continuum models are expected to be in good agreement with each other, one open question we did not address in this work is when the continuum models will also closely approximate solutions of discrete models for angiogenesis (which are closer representations of the true biology). Some insight into this question may be gained by considering the derivation of the P–PDE, since this continuum model describes the mean-field behaviour of an ABM and has the same leading order solution as the ST–PDE. In particular, mean-field models such as the P–PDE are appropriate representations of discrete models when spatial correlations between agents can be neglected. In the case of on-lattice ABMs, for instance, this means that the average occupancy of a given lattice site must be independent of the occupancy of its neighbours  angiogenesis data.This raises the question of how one should quantify the degree of agreement between discrete and continuum results. For example, “good agreement” could be characterised by sufficiently small absolute pointwise differences between the discrete and continuum solutions, or by small differences between their wave speeds. Clarifying what it means for discrete and continuum models to be in good agreement may provide insight into new metrics that could indicate both the extent of angiogenic progression and when it would be appropriate to apply simple continuum models to study and analyse in vitro and in vivo approaches.We anticipate that some of our results from this article also hold in a discrete setting due to the relationship between the P–PDE and its underlying ABM. In particular, we anticipate that for parameter regimes in which tip cell branching is rare and cell movement is dominated by chemotaxis, solutions to the two continuum models will be in good agreement with ensemble averages of the P–ABM. If this is true, then this suggests that several summary statistics, such as the number of branches and the average tip cell displacement, could be used to anticipate when discrete solutions would be captured well by continuum models. It would be interesting in future work to evaluate how well such statistics predict the level of similarity between P–ABM and ST–PDE solutions, as this will inform us of when simple phenomenological systems will be good descriptions of more complex discrete angiogenesis data, potentially including those obtained from Supplementary material 1 (pdf 20118 KB)Below is the link to the electronic supplementary material.


Noise-induced hearing loss is 100% preventable if the collaborative stakeholders in the prevention process are fully committed to the process and implement effective measures timely. Audiologists have within their scope of practice the prevention of hearing loss and this needs to be at the forefront of all advocacy campaigns to prevent occupational hearing loss (OHL). In a systematic review by Moroe, Khoza-Shangase, Kanji and Ntlhakana , where lThe South African Mine Health and Safety Council MHSC,  clearly Evidence from numerous studies, which have been conducted to evaluate the effectiveness and efficacy of management of OHL within the South African mining industry, have yielded unfavourable findings, which indicate that significant efforts are still required to successfully manage OHL  recent advances in the management of occupational noise, (2) barriers and/or facilitators to hearing conservation, (3) contextual factors influencing implementation of HCPs, (4) monitoring and evaluation factors in occupational noise, (5) other toxins contributing to OHL and (6) policy and legislation in the management of occupational noise.Published evidence indicates that the prevalence of OHL is high in low- and middle-income (LAMI) countries, such as South Africa. This is a serious indictment as hearing loss is known to represent a heavier burden in LAMI countries than in high-income regions of the world because of the challenges faced by LAMI countries when compared with their developed counterparts. This is particularly concerning in a country of significant socio-economic inequity such as South Africa, where OHL can present a limitation on the kind of employment suitable for a person with a hearing impairment  in South Africa, which, according to the authors, perpetuates a monological ‘excessive noise-hearing loss’ paradigm that has serious implication for the rights of all workers to equal protections and benefits specifically with respect to occupational audiology healthcare. These authors assert that there is a need to harmonise OHS law and expand the scope of hearing protection legislation to include the full range of established and present ototoxic hazards to ensure that all workers receive equal protection and benefits from the law.Findings presented in the paper ‘Chemicals, noise and occupational hearing health in South Africa: A mapping study’ support the aforementioned view. This paper answers the question, ‘what is the nature of knowledge about occupational ototoxic chemicals and/or noise exposure in South Africa?’, with findings clearly indicating that chemical exposures are only just beginning to be recognised as ototoxic in South Africa; therefore, regulations need to consider this as an important aspect of HCPs. The articles ‘Burden of disease: A scoping review of HIV/AIDS and TB in occupational noise-induced hearing loss’ and ‘Middle ear pathologies in adults within the mining industry: A systematic review’ argue that over and above chemical exposure as a compounding factor in OHL, considerations of burden of disease in otology and audiology should be viewed as critical as certain diseases can cause hearing impairment as a primary effect, as a secondary or opportunistic effect, or as a side effect of treatment options for that disease. When an employee is suffering from any such diseases, concomitant exposure to hazardous noise levels can present an even bigger challenge to successful HCPs, if the complex interactions are not taken into consideration in the conception, implementation and monitoring of HCPs. Furthermore, the article ‘Occupational noise and age: A longitudinal study of hearing sensitivity’ reminds the readers of the impact of age as an influencing factor, over and above the aforementioned factors, also in OHL. The focus on the employees is further seen in the article ‘Does occupational noise matter among manufacturing SME workers? Empirical evidence from Magaba, Mbare’, where the authors explore how occupational noise impacts attitudes towards occupational noise exposure, susceptibility to hearing loss and job performance. The article ‘Occupational noise-induced hearing loss in the mining sector in South Africa: Perspectives from occupational health practitioners on how mineworkers are trained’ places the employees in the hands of occupational health personnel (OHPs) by exploring these stakeholders’ perspectives regarding education and training of mineworkers on ONIHL and its impact on mineworkers’ health. Important contextual factors, such as linguistic and cultural diversity considerations, are suggested as critical if efficient training programmes for employees of HCPs are to succeed within the African context.The role of the OHPs, with a special focus on the audiologist, is centralised in HCPs in the articles ‘Secondary data review of a South African platinum mine: Estimating miners’ risk for occupational noise-induced hearing loss’, ‘Classification of audiograms in the prevention of noise-induced hearing loss’ and ‘Feedback-based noise management matrix in action’. Accurate, comprehensive and efficient data capturing, management and use is key to any successful programme implementation and monitoring. Such data management relies on the use of accredited sensitive and valid measures as well as classification and criteria – with the data allowing matrix and models to be utilised in a complex intervention manner to plan, execute and monitor primary preventive programmes such as HCPs. For example, the article ‘Feedback-based noise management matrix in action’ demonstrates a basic static feedback model with its practical applications, such as estimating, monitoring and providing quantitative information to aid miners, mining administrators and policymakers in decision-making around HCPs.The articles entitled ‘Recent advances in HCPs: A systematic review’ and ‘Engineering noise control for mines: Lessons from the world’ offer critical review and analysis of advances that require serious deliberation and consideration because they could be of benefit to LAMI contexts such as Africa, with a goal to learn from developed contexts in order to meet the noise elimination targets. The authors of these papers provide this evidence while interrogating the practicability and implementation possibilities within the South African or African mining industry. These advances are presented with careful consideration of the African context, allowing the readers to apply these in a contextually responsive manner. The article ‘South African hearing conservation programmes in the context of tele-audiology: A scoping review’ takes the importance of contextual relevance to conclusion in this Special Issue by offering strong recommendations about the application of tele-audiology as a service delivery model because of its particular relevance in resource-constrained settings, such as Africa. Because of the significant capacity:demand challenges in LAMI countries and the need for scaling up audiology professions’ management of HCPs as they fall under their scope of practice, the authors of this manuscript suggest careful consideration of tele-audiology as a platform to deliver services in these contexts. Tele-HCPs have been explored as one of the leading recommendations for increasing access to services within LAMI contexts.The above papers have comprehensively addressed issues of policy and law, context, assessment, management, monitoring, as well as challenges and solutions in this first Special Issue on OHL within the African context in the history of the South African audiology profession. Overall, these papers highlight the following key issues: (1) the importance of translation of knowledge, laws and regulations into practice; (2) the value of collaborative work of all stakeholders for HCPs to be successfully implemented within complex interventions, with audiologists centrally placed; (3) the need to keep abreast with recent advances and their implementation where relevant and responsive contextually; (4) the importance of context analysis in programme implementation; and (5) the complex nature of OHL as well as the importance of managing this within a complex intervention framework.The guest editors are deeply grateful to the National Institute for the Humanities and Social Sciences and the Consortium for Advanced Research Training in Africa for the financial support in producing this Special Edition.


Patients whose audiogram indicated profound hearing loss were 3.89 times more likely to have vestibular dysfunction than those whose audiogram shape indicated low-frequency hearing loss . Patients who had saccule dysfunction were 0.11 times as likely to have hearing recovery than those who had normal saccule function . When adjusted for sex and age, patients who had saccule dysfunction were 0.07 times as likely to have hearing recovery than those who had normal saccule function . Abnormal results following cVEMP testing may be a potential predictive factor for poor hearing recovery.Sudden sensorineural hearing loss (SSNHL) patients with vertigo have a poorer prognosis. However, the factors associated with hearing recovery remain uncertain. This retrospective study was to evaluate the association between hearing characteristics/hearing recovery and the patterns of vestibulocochlear lesions in SSNHL patients with vertigo. Patients were classified into groups according to the patterns of vestibular dysfunction. We not only compared hearing characteristics and prognosis among subgroups but also determined the potential association between vestibular lesion location and hearing recovery. The shapes of the audiogram differed significantly between patients with normal vestibular function and patients with vestibular dysfunction ( Sudden sensorineural hearing loss (SSNHL) is a disease that is characterized by rapid-onset sensorineural hearing loss of more than 30 dB in at least 3 contiguous audiometric frequencies within 72 h . The incDue to the close anatomical and phylogenetic association between the cochlea and the vestibular organs, impairment of cochlear function could cause not only SSNHL, but also vestibular disturbance , 7. ApprRecently, some studies have used vestibular function testing to determine the etiology of SSNHL, such as the caloric test, cervical vestibular-evoked myogenic potential (cVEMP), and ocular vestibular-evoked myogenic potential (oVEMP) , 20. TheThis retrospective study was approved by the regional ethical standards committee in the First Affiliated Hospital of Zhengzhou University. According to Siegel' criteria of hearing recovery and guideline for sudden hearing loss issued by Chinese Society of Otorhinolaryngology Head and Neck Surgery in 2015 , 25, a hWe reviewed the clinical records of new, consecutive patients with SSNHL with vertigo visiting the otolaryngological department at the First Affiliated Hospital of Zhengzhou University between January 2016 and December 2018. All included patients went to see a otolaryngologist and received treatment in the otolaryngology inpatient clinic. All patients had detailed history taken and underwent a series of tests, including physical examination, neurotological examination, imaging, hearing, and vestibular testing. Eye movements were observed by means of an infrared charge-coupled device camera and recorded by electronystagmography . Hearing and vestibular tests were performed within 10 days after onset of symptoms. All studied patients received the same treatment plan which was recommended by Chinese Society of Otorhinolaryngology Head and Neck Surgery . The detCaloric nystagmus was recorded in a darkened room by using electronystagmography . Patients lay in the supine position and kept the lateral semicircular canal in a vertical site. We, respectively, used a constant flow of air at alternating temperatures of 30 and 44°C to irrigate the external auditory canal for 30 s. We used maximal slow phase eye velocity for calculating Canal paresis (CP). We defined an abnormal caloric response by the following criteria: CP percentage >20% , 27.We used surface electrode standing on the upper half of each sternocleidomastoid muscle (SCM), reference electrode placed on the side of the upper sternum and a ground electrode on the chin to record the Electromyographic (EMG) activity. During the recording period, patients stayed in the supine position and were guided to keep their heads raised to shrink the SCM. With the use of Neuropack R, the EMG signal from the stimulated side was amplified and bandpass-filtered . The stimulation and analysis time were, respectively, 5 Hz and 100 ms. Short tone bursts of 500 Hz , rise/fall time 1 ms, plateau time 2 ms) were also presented. We assessed the latencies and amplitudes of the first positive–negative peaks (p13–n23) of the cVEMP, which were evaluated from the average of two runs. The p13–n23 amplitude on the unaffected side was regarded as Au, and that on the affected side was as Aa. With regard to the assessment of amplitude, the asymmetry ratio for the p13–n23 amplitude (cVEMP AR) was calculated and regarded as 100 [(Au–Aa)/(Aa + Au)]. Based on the data from normal individuals, 34% was the upper limit of the cVEMP AR . If reprn = 50) by Neuropack R. A hand-held 4810 Mini-shaker  with a short rod placed perpendicularly on the forehead at the hairline transferred a BCV stimuli with a 4 ms tone bursts of 500 Hz frequency, in which rise/fall time was 1 ms and plateau time was 2 ms. The peak driving voltage was 80 V and peak force was 128 dB re 1 lN. The applied stimuli and analysis time window were, respectively, 3 times per second and 50 ms. The means of two sets of 50 stimuli each were calculated. We conducted the consecutive runs to affirm the reproducibility of the oVEMP responses. The first negative peak (nI) latency, the subsequent positive peak (pI) latency, and the amplitude between nI and pI were determined from the means of two runs. The nI–pI amplitude on the unaffected side was defined as Au, and that on the affected side was as Aa. With regard to the assessment of amplitude, the asymmetry ratio for nI–pI amplitude (oVEMP AR) was calculated and regarded as 100 [(Au–Aa)/(Aa + Au)]. We used responses recorded from the eye contralateral to the stimulation site to determine the oVEMP AR. Based on the results from normal individuals, 27.3 for the oVEMPs to BCV was the upper limit of normal oVEMP AR (Patients stayed in the supine position and were guided to keep their heads supported by a pillow. We placed surface EMG electrodes on the skin 1 cm below (active) and 3 cm below (indifferent) the center of every lower eyelid, and placed ground electrode on the chin. During the testing period, individuals looked up about 30 degrees straight ahead and held their focus on a small dot approximately 1 m from their eyes. The signals were magnified by an amplifier with the bandwidth of 0.5–500 Hz. The unadjusted signals were averaged  was calculated with the thresholds at 0.25, 0.5, 1, 2, and 4 kHz.t-test or ANOVA; those that were distributed non-normally were compared by the Wilcoxon signed-rank test. A logistic regression analysis was conducted, and odds ratios (ORs) were calculated for hearing threshold and type of audiogram variables to determine which variables predicted vestibular dysfunction. A multivariable logistic regression analysis, in which age, sex, and patterns of vestibular dysfunction, such as saccule, utricle and lateral semicircular canal, were included as covariates, was used to assess the association between these independent factors and the prognostic effect in SSNHL patients with vertigo. The binary outcome for the logistic regression referred to prognostic effect (effective or ineffective). The 15 dB HL improvement in the PTA was defined as effective. The logistic regression analysis was performed with two models, an unadjusted analysis model and an adjusted analysis model that was adjusted for age and sex. ORs and 95% confidence intervals were calculated according to model-variable coefficients and standard errors, respectively. All p-values of <0.05 were considered to indicate statistical significance.SPSS software  was used for statistical analyses. For categorical data, frequencies and percentages were calculated to describe the distributions of subgroups among patients according to sex, tinnitus, aural fullness, location of damaged ear, history of diabetes or hypertension, characteristics of the audiogram, duration of vertigo, presence of positional nystagmus, and prognosis effect (recovery). Categorical data were compared with a chi-squared test or Fisher's exact test if appropriate. Means (± SD) were used to summarize the average levels of quantitative data, such as age, time between onset of hearing loss and treatment, and hearing threshold. The Shapiro-Wilk test was used to examine whether the measured values could be approximated by a normal distribution. Quantitative data that were distributed normally were compared by two-sample During the study period, 232 SSNHL patients who also complained of vertigo were included. Among these patients, 156 patients met the inclusion criteria, and 76 were excluded according to the exclusion criteria (detailed data in p = 0.006 and p = 0.001)  .p = 0.047). Age, sex, initial PTA of the affected ear, aural fullness and tinnitus were not significantly associated with the presence or absence of vestibular dysfunction . After treatment for 2 weeks, hearing recovery differed significantly in these subgroups (p = 0.001). The percentages of recovery in the C type, CL type, CS type, CUAccording to the patterns of vestibular dysfunction, patients were divided into different subtypes. A total of 24.4% were C, 7.1% were CL, 2.6% were CS, 5.1% were CU, 23.7% were CUL, 7.7% were CUS, and 29.5% were CUSL type. Clinical characteristics, hearing characteristics and prognosis were analyzed in these groups . Among ttype, CUL type, CUS type, and CUSL type patients were 26.8, 63.3, 0.00, 50.0, 43.2, 8.3, and 8.7%, respectively .p = 0.001). Patients who had saccule dysfunction were 0.11 times as likely to recover hearing than those who had normal saccule function . Patients who had utricle dysfunction were 0.49 times as likely to recover hearing than those who had normal utricle function . Sex and lateral semicircular canal dysfunction were not significantly associated with hearing recovery. In model 2, patients who had saccule dysfunction were 0.07 times as likely to recover hearing than those who had normal saccule function . However, utricle dysfunction and lateral semicircular canal dysfunction were not significantly associated with hearing recovery . This result was consistent with a recent meta-analysis, which reported that the pooled hearing recovery in the abnormal cVEMP response group was nearly half that of the recovery in the normal cVEMP response group (Vertigo is a symptom of vestibular dysfunction and has been described as a sensation of motion, most commonly rotational motion . A largese group . Our resOur study may have several limitations. First, it is difficult to maintain homogeneous sample in each subcategory in this retrospective study, which may have caused selection bias and information bias. Second, vestibular tests were not carried out at SSNHL onset, and some patients were admitted to the hospital days later. Vestibular function might have recovered before the vestibular tests were performed. This may have increased the number of patients with normal vestibular function. Third, we did not assess the functions of the anterior and posterior semicircular canals in this study. Those patients who were classified as C type might have also had dysfunction of the anterior and posterior semicircular canals. In addition, before going to the hospital, the patients did not undergo vestibular tests, and thus we did not know if the results would have been abnormal.In conclusion, the percentages of abnormal vestibular responses in SSNHL patients with vertigo were highest in caloric testing, followed by oVEMP and cVEMP. Abnormal cVEMP testing may be a potential predictive examination for poor hearing recovery.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the regional ethical standards committee in the First Affiliated Hospital of Zhengzhou University. The patients/participants provided their written informed consent to participate in this study.YW built the models, analyzed the data, and drafted the manuscript. LW and FY were involved in reviewing the manuscript. LY was the principal investigator and managed the study. All authors read and approved the final manuscript.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.


Diabetic retinopathy (DR), the most common cause of vision loss, is caused by damage to the small blood vessels in the retina. If untreated, it may result in varying degrees of vision loss and even blindness. Since DR is a silent disease that may cause no symptoms or only mild vision problems, annual eye exams are crucial for early detection to improve chances of effective treatment where fundus cameras are used to capture retinal image. However, fundus cameras are too big and heavy to be transported easily and too costly to be purchased by every health clinic, so fundus cameras are an inconvenient tool for widespread screening. Recent technological developments have enabled to use of smartphones in designing small-sized, low-power, and affordable retinal imaging systems to perform DR screening and automated DR detection using image processing methods. In this paper, we investigate the smartphone-based portable retinal imaging systems available on the market and compare their image quality and the automatic DR detection accuracy using a deep learning framework.Based on the results, iNview retinal imaging system has the largest field of view and better image quality compared with iExaminer, D-Eye, and Peek Retina systems. The overall classification accuracy of smartphone-based systems are sorted as 61%, 62%, 69%, and 75% for iExaminer, D-Eye, Peek Retina, and iNview images, respectively. We observed that the network DR detection performance decreases as the field of view of the smartphone-based retinal systems get smaller where iNview is the largest and iExaminer is the smallest.The smartphone-based retina imaging systems can be used as an alternative to the direct ophthalmoscope. However, the field of view of the smartphone-based retina imaging systems plays an important role in determining the automatic DR detection accuracy. The World Health Organization estimates that 347 million people have diabetes worldwide and the number will increase to 552 million by the year 2030. In the United States, more than 9 percent of Americans (29 million) have the disease and 8 million of those are undiagnosed. A diabetic person is at high risk of eye disease including diabetic retinopathy, diabetic macular edema, cataract, and glaucoma. The most common cause of vision loss is the diabetic retinopathy (DR) that is caused by bleeding of the small blood vessels in the retina. If the these bloody retina veins are untreated, it may cause to varying degrees of vision loss and even blindness. In the US, more than 4.4 million people aged 40 and older had DR problem at different stages. Due to the its silent nature, DR may cause no symptoms or only mild vision problems . Since eIn the retina examination, doctors use special optical devices such as an ophthalmoscope, 20D lens, and fundus camera. Due to the easier storage, better image quality, and faster electronic transfer, fundus cameras are widely used to detect eye diseases with their digital imaging features. However, retinal imaging with a fundus camera is a time-consuming and manual process. An expertise is required to capture a retinal image and an expert evaluation report may take a few days to submit. Since fundus cameras are also too big and heavy to be transported easily and too costly to be purchased by every health clinic, fundus cameras are inconvenient tools for widespread screening. In addition, it is very hard to find the equipment and expertise in rural areas that have a high diabetes rate . The neeRecent technological developments have enabled use of smartphones in designing small-sized, low-power, and affordable biomedical imaging devices. These systems are capable of imaging, onboard processing, and wireless communication. Therefore, smartphone-based systems are very popular in several applications ranging from health care to entertainment since they make existing systems small and portable. Since fundus cameras are large-size, heavy-weight, and high-price devices, they are good candidate to be transformed into a portable device to perform fast DR screening. Developing new portable retinal imaging systems using smartphones is an emerging research and technology area that attracts several universities and companies.In the literature, using 20D Lens with a smartphone is one of the early designs to record video on human and rabbit eyes  as shownRusso et al.  developeIn addition, there exist several telemedicine solutions for retinal image analysis for diabetic retinopathy screening . These sKaggle’s competition is one of attempts to attract researchers to present solutions for diabetic retinopathy detection providing the EyePACS retinal images. EyePACS contains 78685 retinal images to assess the DR existence and severity recommendation in different studies. This competition gives opportunity to researchers to design their deep learning networks and try them with a publicly available dataset. It also accelerates the research findings for automatic DR detection and usage of the deep networks for classification based medical research with higher detection performance. Graham is the winner achieving the accuracy score of 0.84957. He first preprocessed the retina images to remove the illumination difference and used a convolutional neural network, SparseConvNet and random forest for classification by augmenting the retina images to increase number of images in training set .With the improvement of computational power and advances in neural network, deep learning algorithms, especially Convolutional Neural Networks (CNNs), have been widely used in different applications including retinal imaging. Rajalakshmi et al.  proposedIn this paper, we first investigate the smartphone-based portable retinal imaging systems available on the market. We compare their image quality to determine if they are suitable for DR detection during a general health screening in urban areas, remote health clinics, nursing homes, pharmacies, schools, and even by individuals in their own homes. Then, we compare the DR detection accuracy of smartphone-based portable retinal imaging systems using a deep learning framework.In this section, we first present the details of smartphone-based portable retinal imaging systems available on the market to compare their features and image qualities. Second, we introduce the layout of the adopted deep learning architecture for DR detection.There are four smartphone-based retinal imaging systems available in the market including iExaminer, D-Eye, Peek Retina, and iNview. First, we attach each smartphone-based retinal imaging devices to the smartphone to capture retinal images. Since the retina is located at the back of the eye and light does not reflect back through the retina, it is not possible to take a picture of the retina directly without any external illumination. Therefore, these imaging systems attached to the smartphone needs to illuminate the dark retina by reflecting the smartphone flashlight on the retina or using its own light to brighten the retina. Figure Even in a controlled environment, pupil dilation level of the human subject and the eye gaze between a human subject and the retinal imaging system changes easily. Since the visible portions of the retina will change, the retina images captured from a human subject changes over time for different smartphone-based retinal imaging systems. To fix the visible retina, a synthetic eye model can be used. For our experimental setup, we used the synthetic eye model box provided with Peek Retina smartphone-based retinal imaging system as shown in Fig. In the following subsections, we present the details about the publicly available smartphone-based portable retinal imaging systems and their features. Table One of the early and simple design for smartphone-based retinal imaging is developed using 20D lens at Harvard Medical School and the Massachusetts Eye Hospital . As showIExaminer is the another simple early design for fundus photography method using a smartphone . It is dTo capture retina images, iExaminer provides up to 25-degree field-of-view for dilated eyes and allows adjusting focus ranging from -20 to +20 diopter. It offers several apertures and filter options including small spot, large spot, microspot, slit aperture, red-free filter, cobalt blue filter, half-moon, and fixation aperture. Its optic design generates its own light, converges it to a point at the cornea, and diverges around the retina. This allows easy entry into small pupils and wide area illumination of the fundus. Therefore, it does not require pupil dilation for retinal imaging. The operator can also control the amount of illumination manually. It also has an eyecup at the patient side that helps stabilization for the view and occludes ambient light to prevent the interference from outside light. The smartphone application allows capturing up to five images from a patient. After capturing retina images, the iExaminer system can send them to the doctor via an e-mail without applying any image processing algorithms.To capture images with iExaminer, we attached the phone to the adapter on the PanOptic Ophthalmoscope. Since iExaminer uses its own light, we disabled the flashlight of the phone and set the carousel settings for large light in the ophthalmoscope. Then, we positioned the iExaminer on the synthetic eye model box and touched the eyecup to the box as shown in Fig. D-Eye retinal imaging system  illuminaPeek Retina is another plug-in imaging system  that hasSince Peek Retina system still waiting for approval from the Food and Drug Administration in the US, it can only be used for educational purposes not for medical purposes. However, there is a synthetic eye model box in its package for synthetic data capture. Therefore, we can only collect synthetic data provided in its package with eight different retina images that have different eye disease conditions from the normal eye to proliferative diabetic retinopathy. For data capture with Peek Retina, we positioned the Peek Retina adapter to align with the camera and tighten the knob to hold the device in the correct position as shown in Fig. The Volk iNview  smartphoiNview provides the widest field of view compared to other smartphone-based retinal imaging systems but it is also the biggest and heaviest design  is one of the most popular deep learning frameworks so this work adopts the CNN based AlexNet  using thAlexNet first uses five convolutional layers to extract low-level features. Then, it maps the final features to the set of the pre-determined number of classes using three fully connected layers and a softmax layer. In order to transfer the network knowledge, we use the general purpose features learned previously to retrain the softmax layer on a different dataset with different classes. In each layer, network architecture contains different layers such as convolutions, fully connected, activation functions, dropouts, and max-pooling. More complex features are extracted gradually in each convolution layer using the features from previous layers in the network. To introduce nonlinearity into the network, we use Rectified Linear Units (ReLU) as an activation function after each convolutional layer and fully-connected layer. Max pooling layers are used to keep the number of parameters required to be learned by outputting the maximum value of each square kernel and discarding the rest. This helps to reduce the redundancies among the features learned by the network. Dropout layers are introduced after the last two ReLU activations during training to force the network learning more robust features from training samples and avoid the overfitting problem. Using the output of the last fully connected layer, softmax classify images into different classes based on the highest probability.e−5, and a momentum of 0.9. During the retraining, the network updates the parameters of each layer for every iteration with each training sample.Since AlexNet contains nearly 60 million parameters in its architecture, training it from scratch requires a very large amount of input images and computational power. When we do not have millions of labeled image, the best approach is to use transfer learning. In this paper, we removed the last three layers of the AlexNet . Then, we replaced them with new two-class fully connected layer, softmax, and classification layers for transfer learning. Finally, we retrained the new network with the retina images from EyePACS dataset using Stochastic gradient descent (SGD) algorithm with a minibatch size of 2 examples, the learning rate of 1For all our experiments, we developed our programs and CNN frameworks using the MatConvNet and image processing toolboxes in MATLAB 2018. The experiments are performed on a DELL Alienware Aurora R8 workstation with 8 core Intel Core i7 9700K processor at 4.6GHz, NVIDIA GeForce RTX 2080 with 8GB GPU, and 32GB memory. Training time for transfer learning is around 117 sec for 686 images.To compare the smartphone-based retinal imaging systems, we set up two sets of experiments using synthetic retina images and real fundus images. We first collected retina images and videos using iExaminer, D-Eye, Peek Retina, and iNview. To make the fair comparison between different retinal imaging systems, we captured retinal images with iPhone 6 using their compatible adapters and bumpers. In order to capture an image of the dark retina, we first needed to use a light source for illumination. For this purpose, we reflected the smartphone flashlight to the retina for D-Eye and iNview or use its own light source on iExaminer and Peek Retina. The smartphone’s camera was used to capture retina images and images were saved to smartphone’s memory.In our first set of experiments, we captured images from the printed retina in the retina box using different smartphone-based retinal imaging systems. We placed the printed real retina images at the bottom of the Peek Retina synthetic eye model box as shown in Fig. Figure To compare the field of view of the retinal imaging systems, Fig. In our second set of experiments, we design several experiments for each smartphone-based retinal imaging device to analyze the DR detection performance of the deep learning framework for smartphone-based systems and compare them with the accuracy of original retina images. The original retina images in the dataset are originally color images and their resolution vary since they captured by different fundus cameras. However, AlexNet Deep Learning framework requires the inputs to have 227x227x3 pixels as color images. Therefore, we first cropped pixels from right and left sides of each original image to make it square shape. Then, we down-sampled the cropped square images into 227x227x3 as shown in Fig. In order to train and test the deep learning network, we need to feed the CNN frameworks with retina images captured by different smartphone-based devices. However, there is no available real data captured by the smartphone-based retinal imaging device in the literature. Therefore, we generate retina images by simulating the field of view for each device using the retina images from EyePACS dataset as illustrated in Fig. In the original image dataset, we have 13624 retina images from five different gradings  where their distributions are 9898, 920, 2108, 424, and 262, respectively. In order to simplify the problem, we dropped the grade 1 and 2 and merged grade 3 and 4. Since no DR images are more than other labels in the dataset, we randomly selected 686 no DR images and removed the rest from the dataset in order to remove the data bias. As a result, we had 686 no DR and 686 DR images remaining in each subset as shown in Fig. Table Figure A specific threshold value in ROC generates an equal error value for false positive and false negative rate that is also known as equal error rate (EER). For lower EER, the overall accuracy is higher. For original, iExaminer, D-Eye, Peek Retina, and iNview datasets respectively, EERs are calculated as 16.92%, 35.09%, 39.52%, 31.37%, and 23.44% for the following threshold values, 0.6283, 0.3915, 0.3007, 0.2625, and 0.7029. The area under the curve (AUC) values for the ROC curves are 0.8835, 0.6536, 0.6826, 0.7318, and 0.8649 for original, iExaminer, D-Eye, Peek Retina, and iNview datasets, respectively as shown in Table This paper first investigated the smartphone-based portable retinal imaging systems, namely iExaminer, D-Eye, Peek Retina, and iNview to compare their image quality. Then, we adapted a deep learning framework using transfer learning. Using smartphones is an emerging research area in designing small-sized, low-power, and affordable retinal imaging systems to perform DR screening and automated DR detection due to the size, weight, and price of fundus cameras. Smartphone-based portable retinal imaging systems available on the market are capable of capturing and saving retina images without analyzing them using any image processing techniques to detect diabetic retinopathy development. Based on the results, iNview retinal imaging system has the largest field of view and better image quality compared with iExaminer, D-Eye, and Peek Retina systems. The overall classification accuracies of smartphone-based systems are sorted as 61%, 62%, 69%, and 75% for iExaminer, D-Eye, Peek Retina, and iNview images, respectively. We observed that the network DR detection performance decreases as the field of view of the smartphone-based retinal systems get smaller, where iNview is the largest and iExaminer is the smallest. The smartphone-based retina imaging systems can be used as an alternative to the direct ophthalmoscope. However, the field of view of the smartphone-based retina imaging systems plays an important role in determining the automatic DR detection accuracy.