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 * Cited by (38)


THE JOURNAL OF PEDIATRICS

Volume 213, October 2019, Pages 203-210.e1


ORIGINAL ARTICLE
VISUAL ACUITY ASSESSMENT AND VISION SCREENING USING A NOVEL SMARTPHONE
APPLICATION

Author links open overlay panelLloyd Zhao BS 1, Sandra S. Stinnett DrPH 2 3, S.
Grace Prakalapakorn MD, MPH 2 4
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https://doi.org/10.1016/j.jpeds.2019.06.021Get rights and content




OBJECTIVES

To evaluate a smartphone-based application's (Peek Acuity) ability to assess
visual acuity and screen for ocular conditions in children, we compared visual
acuity assessment between Peek Acuity and the pediatric ophthalmology
examination and evaluated Peek Acuity's ability to identify children with
referable ocular conditions.


STUDY DESIGN

We prospectively recruited 111 children age 3-17 years, presenting to a
pediatric ophthalmology clinic, who could follow instructions. Monocular visual
acuity assessments by Peek Acuity and standard clinical methods were performed
in randomized order. We compared visual acuity assessments between methods using
intraclass correlation coefficient (ICC) and evaluated Peek Acuity's ability to
identify children with referable ocular conditions.


RESULTS

ICC comparing visual acuity assessed between methods was 0.88 (95% CI 0.83-0.92)
for first and 0.85 (95% CI 0.78-0.89) for second eyes examined. ICC among 3 to
5-year-olds (preschool-age children) was 0.88 (95% CI 0.77-0.94) for first and
0.45 (95% CI 0.13-0.68) for second eyes examined. Peek Acuity had a sensitivity
of 83%-86% for decreased vision and 69%-83% for referable ocular disease.
Sensitivity was highest among 3 to 5-year-olds with decreased vision, 93%-100%.


CONCLUSIONS

Overall, Peek Acuity visual acuity assessment correlated well with visual acuity
assessed by standard clinical methods, though preschool-age children appeared
more susceptible to examination fatigue. Peek Acuity performed adequately as a
screening tool and had the greatest sensitivity among those with decreased
vision and preschool-age children.


TRIAL REGISTRATION

ClinicalTrials.gov: NCT03212222.



SECTION SNIPPETS


METHODS

This prospective study was approved by the Duke University Health System
Institutional Review Board. The Standards for Reporting Diagnostic Accuracy
Studies reporting guidelines were used for this study.10
Peek Acuity was downloaded from the Google Play Store as a free beta onto a
Samsung Galaxy SIII SGH-1747 (Samsung Electronics, Suwon-si, South Korea)
running Android 4.1.2.


RESULTS

We enrolled 111 children, average age of 7.8 (range: 3-17) years, into the
study. One child was excluded because she left before being seen by the
ophthalmologist. Our study included 1 child with Down syndrome, 1 with an
unspecified developmental delay, 1 with autism, and 5 with attention deficit
hyperactivity disorder; 106 (96%) children completed visual acuity assessments
by both Peek Acuity and standard clinical methods; 91% (32/35) of 3 to
5-year-olds and 99% (74/75) of 6 to 17-year-olds.


DISCUSSION

Overall, our study found good correlation between visual acuity assessed by Peek
Acuity and standard pediatric ophthalmology clinical examination methods and
that Peek Acuity performed best as a screening tool for children with decreased
vision and among preschool age children.
In a prior study, Peek Acuity was compared with clinic-administered Snellen
examination in a rural Kenyan adult population and found to have excellent
correlation, Pearson correlation coefficient = 0.95 (95% CI 0.94-0.96)
Recommended articles



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CITED BY (38)


 * DIGITAL HEALTH INTERVENTIONS TO ENHANCE PREVENTION IN PRIMARY CARE: SCOPING
   REVIEW
   
   2022, JMIR Medical Informatics
   Show abstract
   Disease prevention is a central aspect of primary care practice and is
   comprised of primary (eg, vaccinations), secondary (eg, screenings), tertiary
   (eg, chronic condition monitoring), and quaternary (eg, prevention of
   overmedicalization) levels. Despite rapid digital transformation of primary
   care practices, digital health interventions (DHIs) in preventive care have
   yet to be systematically evaluated.
   This review aimed to identify and describe the scope and use of current DHIs
   for preventive care in primary care settings.
   A scoping review to identify literature published from 2014 to 2020 was
   conducted across multiple databases using keywords and Medical Subject
   Headings terms covering primary care professionals, prevention and care
   management, and digital health. A subgroup analysis identified relevant
   studies conducted in US primary care settings, excluding DHIs that use the
   electronic health record (EHR) as a retrospective data capture tool.
   Technology descriptions, outcomes (eg, health care performance and
   implementation science), and study quality as per Oxford levels of evidence
   were abstracted.
   The search yielded 5274 citations, of which 1060 full-text articles were
   identified. Following a subgroup analysis, 241 articles met the inclusion
   criteria. Studies primarily examined DHIs among health information
   technologies, including EHRs (166/241, 68.9%), clinical decision support
   (88/241, 36.5%), telehealth (88/241, 36.5%), and multiple technologies
   (154/241, 63.9%). DHIs were predominantly used for tertiary prevention
   (131/241, 54.4%). Of the core primary care functions, comprehensiveness was
   addressed most frequently (213/241, 88.4%). DHI users were providers
   (205/241, 85.1%), patients (111/241, 46.1%), or multiple types (89/241,
   36.9%). Reported outcomes were primarily clinical (179/241, 70.1%), and
   statistically significant improvements were common (192/241, 79.7%). Results
   were summarized across the following 5 topics for the most novel/distinct
   DHIs: population-centered, patient-centered, care access expansion,
   panel-centered (dashboarding), and application-driven DHIs. The quality of
   the included studies was moderate to low.
   Preventive DHIs in primary care settings demonstrated meaningful improvements
   in both clinical and nonclinical outcomes, and across user types; however,
   adoption and implementation in the US were limited primarily to EHR
   platforms, and users were mainly clinicians receiving alerts regarding care
   management for their patients. Evaluations of negative results, effects on
   health disparities, and many other gaps remain to be explored.


 * TELEOPHTHALMOLOGY: EVALUATION OF PHONE-BASED VISUAL ACUITY IN A PEDIATRIC
   POPULATION
   
   2021, American Journal of Ophthalmology
   Citation Excerpt :
   
   Another method of checking vision at home is using a smartphone or computer.
   Some of these programs are based on peer-reviewed studies (Peek Acuity; Peek
   Vision, London, United Kingdom); EyeHandbook (Cloud Nine Development,
   Overland Park, Kansas); and Jaeb Visual Acuity Screener (Jaeb Center for
   Health Research, Tampa, Florida)11,22–27,41; and some are not (Farsight;
   Farsight.care; London, United Kingdom); Eye Chart Pro (Dok LLC; Apple,
   Cupertino, California); Visual Acuity Charts (Fonlo); and Snellen Acuity
   (João Meneses [available as an application]) (Table 3). There are several
   issues with using electronic applications to check visual acuity.
   
   Show abstract
   With the recent rise of teleophthalmology due to coronavirus disease, health
   care needs accurate and reliable methods of checking visual acuity remotely.
   The visual acuity as measured by the GoCheck Kids application was compared
   with that of the Amblyopia Treatment Study (ATS) and the authors' clinic
   protocol.
   This was a prospective, comparison of visual acuity assessment methods.
   Established patients (3-18 years of age) in the practice of a single
   pediatric ophthalmologist were eligible. Visual acuity was measured 1) by
   GoCheck Kids mobile application, by the patient's family member; 2) by
   HOTV-ATS, by study personnel; and 3) by regular clinic protocol, by an
   ophthalmic technician. To assess agreement between measurement of acuity,
   intraclass correlations with 95% confidence intervals (CI) were computed.
   A total of 53 children participated. The mean differences between GoCheck
   Kids and HOTV-ATS acuities (0.094) were significantly different (P < .001).
   The intraclass correlation coefficient (ICC) was 0.55 (95% CI: 0.40-0.68).
   The mean differences between GoCheck Kids and chart acuities (0.010) were not
   significantly different (P = .319; ICC: 0.59; 95% CI: 0.45-0.71). The mean
   differences between HOTV-ATS and chart acuities (0.084) were significantly
   different (P < .001; ICC: 0.66; 95% CI: 0.53-0.76). The percentages of eyes
   with visual acuity measured by GoCheck Kids within 1 line of the HOTV-ATS and
   chart acuity were 65.3% and 86.7%, respectively.
   GoCheck Kids as checked by a family member provided a modest correlation of
   visual acuity compared to the chart screen and a fair correlation of visual
   acuity compared to HOTV-Amblyopia Treatment Study protocol, although most
   were within 1 line.


 * IS YOUR VISION BLURRY? A SYSTEMATIC REVIEW OF HOME-BASED VISUAL ACUITY FOR
   TELEMEDICINE
   
   2023, Journal of Telemedicine and Telecare
   
   


 * DIGITAL TOOLS FOR THE SELF-ASSESSMENT OF VISUAL ACUITY: A SYSTEMATIC REVIEW
   
   2021, Ophthalmology and Therapy
   
   


 * TELE-NEURO-OPHTHALMOLOGY: VISION FOR 20/20 AND BEYOND
   
   2020, Journal of Neuro-Ophthalmology
   
   


 * TELE-NEURO-OPHTHALMOLOGY DURING THE AGE OF COVID-19
   
   2020, Journal of Neuro-Ophthalmology
   
   

View all citing articles on Scopus

The authors declare no conflicts of interest.
Portions of this study were presented at the annual Association for Research in
Vision and Ophthalmology conference, April 29 - May 3, 2018, Honolulu, HI and at
the Alpha Omega Alpha day at Duke University, August 3, 2018, Durham, NC.
View full text
© 2019 Elsevier Inc. All rights reserved.


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