Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
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ARVO Annual Meeting Abstract  |   June 2020
Use of Telepresence Robots in Glaucoma Patient Education
Author Affiliations & Notes
  • Ashley Ooms
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Ibraheem S Shaikh
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Nishant Patel
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Thomas Kardashian-Sieger
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Nivetha Srinivasan
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Benjamin Zhou
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Logan Wilson
    Northwestern University, Chicago, Illinois, United States
  • Ben Szirth
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Albert S Khouri
    Rutgers New Jersey Medical School, Somerset, New Jersey, United States
  • Footnotes
    Commercial Relationships   Ashley Ooms, None; Ibraheem Shaikh, None; Nishant Patel, None; Thomas Kardashian-Sieger, None; Nivetha Srinivasan, None; Benjamin Zhou, None; Logan Wilson, None; Ben Szirth, None; Albert Khouri, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 3091. doi:
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      Ashley Ooms, Ibraheem S Shaikh, Nishant Patel, Thomas Kardashian-Sieger, Nivetha Srinivasan, Benjamin Zhou, Logan Wilson, Ben Szirth, Albert S Khouri; Use of Telepresence Robots in Glaucoma Patient Education. Invest. Ophthalmol. Vis. Sci. 2020;61(7):3091.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Patients’ understanding of how glaucoma can affect them can play an important role in lifelong adherence to treatment protocols and disease management. In communities lacking patient education resources, telepresence robots (TR) can provide direct, real-time contact with remote educators. We compared the effect of an interactive education session given by either an in-person lecturer or a TR on glaucoma knowledge and identified factors that may impact patient education.

Methods : 85 glaucoma patients and glaucoma suspects (age 58.3 +/- 2.8 years, 51% male) were invited to participate after a follow-up clinic visit. Patients were split into three groups. Two groups had a scripted education session with either a human or a TR (DoubleRobotics, Burlingame, CA) followed by a questionnaire. The control group was administered the questionnaire before the education session. We used the National Eye Institute’s Eye-Q Test to measure glaucoma knowledge scores (KS), with a maximum score of 10. We also assessed treatment regimen recall (RR) as correctly describing medications, dosage, and eye laterality, with greater than 90% recall considered a success. Linear regression was used to determine variables that affect KS and binary logistic regression was used for RR.

Results : The mean KS were 5.8 +/- .7 in the control group (n=31), 7.9 +/- .5 in the TR group (n=26), and 8.4 +/- .5 in the human group (n=28). Welch’s t-test did not suggest KS or RR differed after a human or TR education session (p=.13, p=.94). ANOVA followed by the Bonferroni correction suggested the control group had a lower mean KS than the human or TR groups (p=3.6 x 10-8; p=5.5 x 10-6). Having the education session (2.5, p < .0001), education greater than high school (.8, p=.016), and diabetes (-.7, p=.037) were significant variables affecting KS (Fig 1). Having diabetes (OR=.14, p=.014) negatively affected RR. Having the education session may affect RR (OR=5.47, p=.07), warranting further studies (Fig 2).

Conclusions : Interactive education sessions with a human and TR improved patients’ glaucoma KS and RR. Thus, TRs may serve as an alternative to in-person education sessions. We identified characteristics that may be associated with a lower KS and RR, indicating these patients may require further educational interventions.

This is a 2020 ARVO Annual Meeting abstract.

 

Figure 1: Significant predictors of KS (p<.05) marked with asterisks.

Figure 1: Significant predictors of KS (p<.05) marked with asterisks.

 

Figure 2: Significant predictors of RR (p<.05) marked with asterisks.

Figure 2: Significant predictors of RR (p<.05) marked with asterisks.

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