Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Activity Inventory Goals as a Low Vision Clinical Intake Questionnaire
Author Affiliations & Notes
  • Phillippa Dorling
    New England College of Optometry, Boston, Massachusetts, United States
  • Heather Donovan
    New England College of Optometry, Boston, Massachusetts, United States
  • Bianca Guzman
    New England College of Optometry, Boston, Massachusetts, United States
  • Sonaina Merchant
    New England College of Optometry, Boston, Massachusetts, United States
  • Chris Bradley
    New England College of Optometry, Boston, Massachusetts, United States
  • Nicole Ross
    New England College of Optometry, Boston, Massachusetts, United States
  • Micaela R Gobeille
    New England College of Optometry, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Phillippa Dorling None; Heather Donovan None; Bianca Guzman None; Sonaina Merchant None; Chris Bradley Radius XR, Code C (Consultant/Contractor); Nicole Ross None; Micaela Gobeille None
  • Footnotes
    Support  NECO Topcon Early Investigator Award
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 6181. doi:
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      Phillippa Dorling, Heather Donovan, Bianca Guzman, Sonaina Merchant, Chris Bradley, Nicole Ross, Micaela R Gobeille; Activity Inventory Goals as a Low Vision Clinical Intake Questionnaire. Invest. Ophthalmol. Vis. Sci. 2024;65(7):6181.

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

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Abstract

Purpose : Clinical history taking is an unstandardized process that directs the course of care provided during a low vision exam. A standardized intake questionnaire could reduce bias and create equipoise in history taking. Here, Activity Inventory items described as goals (AI-g) were administered to low vision patients ahead of their exam to assess the use of AI-g as a low vision intake questionnaire.

Methods : New and existing patients scheduled for a low vision exam at a NECO affiliated clinic were enrolled (N = 64), completing AI-g by phone an average 11 days prior to their exam. Goals rated as not important or not difficult were excluded.
Goals addressed during low vision exam represent a patient’s highest priority goals identified by discussion between patient and provider. These goals were extracted from medical records. Clinical and AI-g goals were divided into 8 functional categories: reading, driving, social interactions, hobbies, technology, activities of daily living (ADL), and mobility. The percentage of patients identifying a goal in each category in both the AI-g and clinical goals was compared. Discrepancies between goals identified clinically and with AI-g were explored.

Results : Patients had a mean age of 61 years (SD=19), with a mean better eye visual acuity of 0.60 logMAR (SD=0.44). Diagnoses included: macular degeneration (N=13), glaucoma (N=12) and retinitis pigmentosa (N=9).
AI-g identified an average of 19 goals (SD=11) per patient. Across patients, goals were most often identified in categories of: hobbies (97%), social interactions (94%), technology (81%) and ADLs (77%). AI-g less often identified goals in mobility (55%) and driving (45%).
An average of 5 clinical goals (SD=2) were identified per patient. Across patients, clinical goals were most often identified in categories of reading (66%), technology (31%), mobility (27%), and driving (22%). Clinical goals were less often identified in hobbies (9%), ADLs (5%), and social interactions (2%).
Goals not represented in AI-g that were identified as clinical goals included: glare control (31%), support in obtaining resources (11%), contrast enhancement (3%), and emotional adjustment to vision loss (2%).

Conclusions : While AI-g identified more goals per patient than clinical goals overall and across all categories, it lacked items to identify some categories of clinical goals. This study highlights limitations of AI-g for use as a clinical intake questionnaire.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

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