DigiVis: Self-testing Vision App for Telephone Consultations

NCT ID: NCT04482387

Last Updated: 2024-08-05

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 120 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2020-07-24
• Study Completion Date: 2021-08-01

Brief Summary

This trial aims to assess the accuracy and test-retest variability of a new digital app which enables community visual acuity testing without requirement of an trained examiner.

Detailed Description

Eye problems like macular degeneration and amblyopia (lazy eye) require regular monitoring to prevent permanent visual impairment. Over 2000 patients a month are seen in Cambridge University Hospitals National Health Service Trust (CUH) eye clinics; concern about Covid-19 infection has led to over 80% of consultations being conducted by telephone with few clinical clues to inform decision making. Patients will face long delays even when routine clinics restart: there is no doubt that some will suffer preventable visual loss.

DigiVis is a web-based vision testing app enabling self-testing of vision at home. Early testing and patient feedback is positive: 80% of children prefer DigiVis to regular testing. The investigators wish to test how accurately the app works for home use, by asking older children and adults to self-test their vision prior to their planned face to face clinic appointment. Once tested, DigiVis will be available free of charge to patients, not only during the Covid-19 crisis, but also to support telephonic consultations in the future.

Visual acuity (VA) is a fundamental measure of vision required for all ophthalmic assessments. It is measured by health professionals using vision charts. DigiVis is a new app which enables self-testing of VA using two wirelessly connected digital devices. By matching letters on a handheld device to those displayed on the second device a distance away, threshold VA can be measured using a staircase algorithm. The distance and scaling of the test is vital to its accuracy and a concept (patent filed by Cambridge Enterprise) in DigiVis enables this without the need for manual distance measurement or an observer.

Early validation using two tablet computers in 150 clinic patients has given positive results, both in testing accuracy and patient feedback. With the current Covid-19 crisis limiting face to face appointments, there is an urgent need for accurate home VA assessment. The DigiVis app has been re-coded for free website delivery for this purpose.

The investigators wish to formally validate DigiVis home testing following Conformitè Europëenne (CE class I) marking so that it can be recommended for clinical use. 250 patients will be invited to self-test their VA twice using DigiVis prior to a planned face to face clinic appointment. The test-retest variability and comparison of DigiVis VA to chart based assessment will be compared.

Conditions

Visual Impairment; Amblyopia Suspect

Study Design

• Allocation Method: NA
• Intervention Model: SEQUENTIAL
• Primary Study Purpose: SCREENING
• Blinding Strategy: NONE

Study Groups

Subjects recruited to visual acuity testing

All recruited subjects will have the intervention (Digivis visual acuity self-testing) and the standard clinical visual acuity assessment in clinic.

Group Type: OTHER

DigiVis visual acuity app

Intervention Type: DEVICE

Self-testing of visual acuity app on two occasions

Interventions

DigiVis visual acuity app

Self-testing of visual acuity app on two occasions

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Age between 5 and 85 years
• Previous recorded visual acuity of at least +0.8 logMAR in or both eyes

Exclusion Criteria

• Individuals with poor conversant English
• Individuals with cognitive impairment
• Subjects unable to access the internet on two digital devices

• Minimum Eligible Age: 5 Years
• Maximum Eligible Age: 85 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Cambridge University Hospitals NHS Foundation Trust

OTHER

Sponsor Role: lead

Responsible Party

Louise Allen

Principal investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Stephen E Kelleher

Role: STUDY_DIRECTOR

Cambridge University Hospitals NHS Foundation Trust

Locations

Cambridge University Hospitals NHS Trust

Cambridge, Cambs, United Kingdom

Countries

United Kingdom

References

Rono HK, Bastawrous A, Macleod D, Wanjala E, Di Tanna GL, Weiss HA, Burton MJ. Smartphone-based screening for visual impairment in Kenyan school children: a cluster randomised controlled trial. Lancet Glob Health. 2018 Aug;6(8):e924-e932. doi: 10.1016/S2214-109X(18)30244-4.

Reference Type: BACKGROUND

PMID: 30012273 (View on PubMed)

Bastawrous A, Rono HK, Livingstone IA, Weiss HA, Jordan S, Kuper H, Burton MJ. Development and Validation of a Smartphone-Based Visual Acuity Test (Peek Acuity) for Clinical Practice and Community-Based Fieldwork. JAMA Ophthalmol. 2015 Aug;133(8):930-7. doi: 10.1001/jamaophthalmol.2015.1468.

Reference Type: BACKGROUND

PMID: 26022921 (View on PubMed)

Thirunavukarasu AJ, Mullinger D, Rufus-Toye RM, Farrell S, Allen LE. Clinical validation of a novel web-application for remote assessment of distance visual acuity. Eye (Lond). 2022 Oct;36(10):2057-2061. doi: 10.1038/s41433-021-01760-2. Epub 2021 Aug 30.

Reference Type: BACKGROUND

PMID: 34462579 (View on PubMed)

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

IRAS196573

Identifier Type: -

Identifier Source: org_study_id