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. 2026 Jan 9;5(3):100477. doi: 10.1016/j.focus.2026.100477

Vision Impairment and Falls Among Older Mexican Americans Over 16 Years Follow-Up

Mandi L Sonnenfeld 1,2,⁎, Monique R Pappadis 3, Timothy A Reistetter 4, Mukaila A Raji 5, Soham Al Snih 3,5,6
PMCID: PMC13094491  PMID: 42016724

Highlights

  • •

    Near vision impairment predicted high risk of falls over 16 years of follow-up.

  • •

    Distant vision impairment alone did not increase fall risk.

  • •

    Limited access to vision screening access may heighten fall risk in older Mexicans.

  • •

    Ensuring equitable eye care access is essential for effective fall prevention strategies.

Keywords: Vision impairment, falls, older Mexican Americans, longitudinal

Abstract

Introduction

Research examining the relationship between vision impairment and falls is limited among older Mexican Americans. The purpose of this study was to determine the relationship between vision impairment and new-onset falls among Mexican American older adults without a history of falls at baseline over 16 years of follow-up.

Methods

The authors studied 851 participants aged ≥72 years from the Hispanic Established Populations for the Epidemiologic Study of the Elderly (2000/2001–2016). Fall status was categorized as having no falls and having 1 or more falls. Self-reported vision impairment was defined as difficulty in recognizing a friend at arm’s length’s away, across the room, or across the street. Covariates included sociodemographics, BMI, Mini Mental State Examination, depressive symptoms, smoking status, and hearing impairment. Generalized estimating equation models were used to examine the relationship between near vision impairment, distant vision impairment, and vision impairment (near or distant) and falls.

Results

Percentage of falls ranged 4.17% to 35.63% over time. Greater odds of falls (OR=1.45, 95% CI=1.00, 2.10) were found for participants with near or distant vision impairment and near vision impairment (OR=2.08, 95% CI=1.22, 3.55) over time, controlling for all covariates. However, no significant association was found between distant vision impairment and incident falls over time (OR=1.30, 95% CI=0.89, 1.92), controlling for all covariates.

Conclusions

Participants with vision impairment had greater odds of falls over time. Near vision impairment was the primary vision impairment category driving this relationship, suggesting timely near vision impairment screening among older Mexican Americans as an important step in preventing falls.

INTRODUCTION

The WHO defines a fall as “an event which results in a person coming to rest inadvertently on the ground or floor or other lower level.”1 Falls are a significant public health problem, the second leading cause of unintentional injury deaths worldwide, and the leading cause of unintentional injury deaths in the U.S.1,2 Adults aged ≥65 years are at high risk of experiencing a fall; however, falls are not an inevitable part of aging and are preventable.3 Intrinsic factors associated with falls include older age, history of falls, fear of falling, muscle weakness in the legs, poor gait and balance, slower reflexes, postural hypotension, depression, cognitive impairment, chronic conditions (including arthritis, cancer, stroke, incontinence, diabetes, and Parkinson’s), use of psychoactive medications, and vision deficits related to the environment.4, 5, 6, 7, 8 Data from the Centers for Disease Control and Prevention indicate that the unintentional fall death rate in 2007 was approximately 47.0 deaths per 100,000 population, rising steadily to approximately 61.6 deaths per 100,000 in 2016.9 The fatal fall rate has been reported to be higher among men than among women and higher among White adults than among other racial/ethnic groups.9,10

Approximately 2 billion persons worldwide and 4 million persons in the U.S. report having a vision impairment (VI).11,12 This number is projected to double to 8 million by 2050.12 Furthermore, the largest segment of Americans with low vision over the next 20 years will be Hispanic men (mostly Mexican Americans), according to the American Academy of Ophthalmology.13 Using the 2010 U.S Census Population data set, the National Eye Institute and Prevent Blindness America found that the prevalence of low vision varied by age (1.54% in those aged 40–64 years vs 24.54% in those aged ≥65 years), sex (63% for females vs 37% for males), and race and ethnicity (2.20% for non-Hispanic Whites, 1.70% for Hispanics, 1.20% for non-Hispanic blacks, and 1.50% for other races).14

Previous longitudinal studies indicated that VI was associated with falls. For example, participants in the Australian Blue Mountains Eye Study with incident bilateral VI were 1.45 times more likely to report ≥2 falls in 5 years.15 In the Singapore Epidemiology of Eye Diseases study, participants with bilateral VI had 1.79 greater odds of any incidence of falls over a 6-year follow-up than those with normal vision in both eyes.16

There is a scarcity of research examining the long-term relationship between VI and new-onset falls in older Mexican Americans, a population with a high prevalence of the diseases that lead to VI.17 The purpose of this study was to determine the relationship between VI and falls among Mexican American older adults without history of falls at baseline over 16 years of follow-up. It is hypothesized that individuals with VI will have an increased odds of falls over time.

METHODS

Study Sample

Data are from the Hispanic Established Populations for the Epidemiologic Study of the Elderly (H-EPESE). The H-EPESE survey has collected data longitudinally from Mexican Americans aged ≥65 years residing in the states of Arizona, California, Colorado, New Mexico, and Texas. At baseline (1993/1994), 3,050 participants were interviewed, and follow-ups were conducted every 2 or 3 years. This study used data obtained from Wave 4 (2000/2001, referred to as baseline in the remaining parts of this paper) to Wave 9 (2016). Data from Wave 4 were used because this wave was the first to include self-reported VI and falls. The H-EPESE data sets are available at the National Archive of Computerized Data on Aging.18

Of the 1,597 participants aged ≥72 years interviewed at baseline, the authors excluded 368 who reported falls and 378 because of missing information on VI, falls, and covariates, leaving a final sample size of 851 (Appendix Figure 1, available online). Excluded participants were more likely to be older; to be unmarried; to have financial strain; to be interviewed in English; to report comorbidities (heart attack, hip fracture, and stroke); to have high depressive symptoms, hearing impairment, VI, and falls; and to have lower scores on the Mini Mental State Examination (MMSE) than those included. At the end of follow-up (2016), 168 participants were reinterviewed in person, 62 were lost to follow-up or refused to be reinterviewed, and 621 were confirmed dead through the National Death Index and report from relatives. At the time of each interview, each participant provided oral informed consent, and the study protocol was approved by the University of Texas Medical Branch’s IRB (IRB Number 16-004).

Measures

Distant VI (DVI), the independent variable, was assessed with the following question: When wearing your glasses/contacts can you see well enough to recognize a friend across the street or across the room? Near VI (NVI) was assessed with the following question: When wearing your glasses/contacts, can you see well enough to recognize a friend who is at arm’s length away? If near and/or distant vision difficulty was indicated, the participant was classified as having VI. The VI assessment questions are similar to those in the Behavioral Risk Factor Surveillance System data set.19, 20, 21

Falls, the dependent variable, were assessed at each interview with the following question: During the past 12 months, how many times did you fall and land on the floor or ground? Fall status was categorized as having no falls versus having 1 or more falls.

Covariates included age, sex (female versus male), marital status (married versus not married), years of education, nativity status (U.S. born versus foreign born), language of interview (English versus Spanish), social isolation (lives with family versus alone), and current smoking status (yes versus no). Financial strain was assessed by self-report of difficulty in paying monthly bills (yes versus no). BMI was calculated as measured weight in kilograms divided by measured height in meters squared. Medical conditions included self-reported hypertension, arthritis, cancer, diabetes, heart attack, hip fracture, and stroke. Hearing impairment was assessed through self-report of difficulty in hearing (yes versus no). High depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (≥16), and cognitive function was assessed with the MMSE.22,23

Statistical Analysis

t-test and chi-square tests were used to compare the baseline characteristics of the sample by falls. The authors used generalized estimating equation (GEE) models to estimate the ORs and 95% CI of falls as a function of VI among participants without a history of falls at baseline (n=851). The models used logit link binomial distribution and the autoregressive covariance structure to account for repeated measures of participants. Quasi-likelihood information criterion estimation values were used to choose the covariance matrix for GEE. All included variables were treated as time varying (potential to change from interview to interview) except for sex, education, and nativity. Participants were classified at each time point on the basis of VI. For example, a participant who reported no VI at baseline but reported VI at the next follow-up would be reclassified into the responding VI category. Using the GEE model, the authors minimized selection bias from missing data using all available information from follow-up interviews, regardless of variations in follow-up duration. This procedure estimates the working correlation structure using all nonmissing data pairs on the basis of repeated measures of the same participants over time. This approach excludes only the specific missing observations, instead of removing entire cases, thus preserving as much longitudinal data as possible.24 Participants who died, refused to participate, or were lost to follow up were included in the analyses until their last interview date over the 16-year follow up. All analyses were performed using SAS, Version 9.0 (SAS Institute, Inc., Cary, NC).

RESULTS

Descriptive baseline (2000/2001) characteristics of the sample by falls are presented in Table 1. The overall sample had a mean age of 78.67 (SD=4.96) years, 60.21% were female, 50.21% were married, and the mean years of education was 4.97±3.89. Thirty percent reported 1 or more falls during the past 12 months. Participants with ≥1 falls were significantly more likely to be older (79.14 [SD=5.34] vs 78.46 [SD=4.77] years); to be female (68.48% vs 56.64%); to be unmarried (56.52% vs 46.89%); to be living alone versus with family (79.57% vs 24.56%) and to report comorbid conditions such as hypertension (54.62% vs 47.83%), arthritis (62.50% vs 50.53%), cancer (7.07% vs 4.35%), diabetes (36.14% vs 28.79%), hip fracture (1.56% vs 1.29%), or stroke (4.89% vs 2.35%) than those with no falls. Participants with ≥1 falls were significantly more likely to report lower MMSE scores (21.88 [SD=5.50] vs 22.79 [SD=5.13]), high depressive symptoms (15.22% vs 8.23%), DVI (19.57% vs 9.87%), and VI (near or distant) (20.92% vs 10.22%) than those with no falls.

Table 1.

Baseline Descriptive Characteristics of the Overall Sample and by Falls (Near or Distant) Among Older Mexican Americans (N=1,219)

Characteristic Total
N (%)		 Falls ≥1
n (%)		 No falls
n (%)		 p-value
Total 1,219 (100) 368 (30.19) 851 (69.81)
Age, mean±SD 78.67± 4.96 79.14±5.34 78.46±4.77 0.0364
Sex (female) 734 (60.21) 252 (68.48) 482 (56.64) 0.0001
Married 612 (50.21) 160 (43.48) 452 (53.11) 0.0020
Education (years), mean±SD 4.97 ± 3.89 4.81 ± 3.78 5.03 ± 3.93 0.3612
Financial strain 719 (58.98) 230 (62.50) 489 (57.46) 0.1006
Nativity (U.S. born) 701 (57.51) 209 (56.79) 492 (57.81) 0.7406
Spanish interview 1,055 (86.55) 314 (85.33) 741 (87.07) 0.4116
Lives with family 891 (73.09) 249 (20.43) 642 (75.44) 0.0049
Hypertension 608 (49.88) 201 (54.62) 407 (47.83) 0.0294
Arthritis 660 (54.14) 230 (62.50) 430 (50.53) 0.0001
Cancer 63 (5.17) 26 (7.07) 37 (4.35) 0.0491
Diabetes 378 (31.01) 133 (36.14) 245 (28.79) 0.0108
Heart attack 52 (4.27) 16 (4.35) 36 (4.23) 0.9257
Hip fracture 30 (2.46) 19 (1.56) 11 (1.29) <0.0001
Stroke 38 (3.12) 18 (4.89) 20 (2.35) 0.0191
BMI (kg/m2), mean±SD 28.02±5.42 28.22±5.59 28.93±5.35 0.4008
BMI categories 0.6955
 Underweight 25 (2.05) 8 (2.17) 17 (2.00)
 Normal 344 (28.22) 102 (27.72) 242 (28.44)
 Overweight 455 (37.33) 129 (35.05) 326 (37.31)
 Obese Category 1 273 (22.40) 87 (23.64) 186 (21.86)
 Obese Category 2 122 (10.01) 42 (11.41) 80 (9.40)
MMSE (total), mean±SD 22.51±5.26 21.88±5.50 22.79±5.13 0.0054
Depressive symptoms (CES-D ≥16) 126 (10.34) 56 (15.22) 70 (8.23) 0.0002
Current smoking 95 (7.79) 31 (8.42) 64 (7.52) 0.5891
Hearing impairment 253 (20.75) 66 (17.93) 187 (21.97) 0.1104
Near VI 39 (3.20) 17 (4.62) 22 (2.59) 0.0639
Distant VI 156 (12.80) 72 (19.57) 84 (9.87) <0.0001
VI (near or distant) 164 (13.45) 77 (20.92) 87 (10.22) <0.0001
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Note: Data set for falls outcome starts from Wave 4.

CES-D, Center for Epidemiologic Studies Depression Scale; MMSE, Mini Mental State Examination; VI, vision impairment.

Table 2 presents the GEE models for falls as a function of NVI (Model 1), DVI (Model 2), and VI (Model 3) over time. Participants with NVI had greater odds of falls (OR=2.08, 95% CI=1.22, 3.55) over time than those without NVI, after controlling for all covariates. Participants with VI (near or distant) had greater odds of falls (OR=1.45, 95% CI=1.00, 2.10) over time than those without VI (near or distant), after controlling for all covariates. No significant association was found between DVI and falls after controlling for all covariates (OR=1.30, 95% CI=0.89, 1.92). Time (years), diabetes, heart attack, stroke, and high depressive symptoms were also factors associated with falls. The authors stratified the analysis by age categories (<80 years, ≥80 years). The authors found that those aged <80 years had greater odds of falls (OR=3.92, 95% CI=1.74, 8.80) over time, after controlling for all covariates. The association between VI and falls was statistically nonsignificant among those aged ≥80 years (OR=1.10, 95% CI=0.74, 1.63) over time, after controlling for all covariates.

Table 2.

Generalized Estimating Equation Models for Falls as a Function of Vision Impairment Over 16 Years of Follow-Up Among Older Mexican Americans With No Falls Reported at Baseline (n=851)

Model 1 Model 2 Model 3
Predictor variables OR (95% CI) OR (95% CI) OR (95% CI)
Time 1.21 (1.16, 1.25) 1.21 (1.16, 1.25) 1.21 (1.16, 1.25)
Near VI 2.08 (1.22, 3.55) — —
Distant VI — 1.30 (0.89, 1.92) —
VI (near or distant) — — 1.45 (1.00, 2.10)
Age 1.00 (0.97, 1.04) 1.00 (0.97, 1.04) 1.00 (0.97, 1.04)
Sex (female) 1.19 (0.89, 1.60) 1.18 (0.88, 1.59) 1.18 (0.88, 1.58)
Married 0.88 (0.63, 1.22) 0.88 (0.64, 1.23) 0.88 (0.63, 1.22)
Education (years) 1.02 (0.98, 1.06) 1.02 (0.98, 1.06) 1.02 (0.98, 1.06)
Financial strain 1.15 (0.90, 1.47) 1.14 (0.89, 1.46) 1.14 (0.89, 1.46)
Nativity (foreign born) 1.03 (0.78, 1.35) 1.04 (0.79, 1.37) 1.04 (0.79, 1.37)
Spanish interview 0.83 (0.56, 1.21) 0.84 (0.57, 1.23) 0.83 (0.57, 1.22)
Lives with family 0.85 (0.60, 1.20) 0.84 (0.60, 1.19) 0.85 (0.60, 1.19)
Current smoking 0.65 (0.35, 1.20) 0.67 (0.37, 1.24) 0.67 (0.36, 1.23)
BMI Categories
 Underweight 1.21 (0.49, 2.97) 1.13 (0.45, 2.84) 1.13 (0.60, 1.07)
 Normal ref ref ref
 Overweight 0.80 (0.60, 1.07) 0.79 (0.59, 1.06) 0.80 (0.60, 1.06)
 Obese Category 1 0.71 (0.48, 1.04) 0.71 (0.48, 1.04) 0.71 (0.48, 1.04)
 Obese Category 2 0.77 (0.47, 1.26) 0.74 (0.46, 1.22) 0.75 (0.46, 1.22)
Hypertension 1.16 (0.87, 1.54) 1.19 (0.89, 1.58) 1.19 (0.90, 1.58)
Arthritis 1.29 (0.99, 1.68) 1.27 (0.98, 1.66) 1.27 (0.97, 1.66)
Cancer 1.17 (0.74, 1.88) 1.19 (0.75, 1.89) 1.18 (0.75, 1.88)
Diabetes 1.50 (1.15, 1.97) 1.50 (1.15, 1.97) 1.51 (1.15, 1.97)
Heart attack 1.61 (1.02, 2.55) 1.60 (1.01, 2.53) 1.60 (1.01, 2.53)
Hip fracture 1.31 (0.56, 3.09) 1.30 (0.54, 3.15) 1.30 (0.54, 3.13)
Stroke 2.08 (1.24, 3.48) 2.11 (1.25, 3.55) 2.10 (1.25, 3.51)
Cognitive impairment (MMSE <21) 0.95 (0.71, 1.27) 0.95 (0.71, 1.27) 0.93 (0.69, 1.25)
Depressive symptoms (CES-D ≥16) 1.53 (1.09, 2.15) 1.50 (1.07, 2.10) 1.49 (1.07, 2.09)
Hearing impairment 0.97 (0.69, 1.36) 0.99 (0.70, 1.39) 0.97 (0.69, 1.36)
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CES-D, Center for Epidemiologic Studies Depression Scale; MMSE, Mini Mental State Examination; VI, vision impairment.

Figure 1 presents the percentage of falls by VI (near or distant). Over time, the percentage of falls ranged from 15.0% to 35.6% for VI (near or distant), 13.75% to 35.63% for DVI, and 4.17% to 10.14% for NVI.

Figure 1.

Figure 1 dummy alt text

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Percentage of vision impairment and falls over time (sample at Wave 4, n=1,219).

DISCUSSION

In this study, the authors examined the longitudinal relationship (16-year follow-up) between VI and falls among older Mexican Americans reporting no falls at baseline. The authors found that NVI and VI (defined as near or distant) were associated with a greater likelihood of falls over time, after controlling for covariates; however, DVI was not independently associated with falls.

Potential mechanisms that explain why NVI was more likely to be associated with falls than DVI may be the immediate influence of NVI on activities such as reading, recognizing obstacles up close, and safely navigating the home with potential hazards in the walkway path such as throw rugs, cords, and wires.25, 26, 27 Several other mechanisms might elucidate the relationship between VI and falls. The relationship between VI and falls is influenced by multiple interacting mechanisms. For example, eye diseases such as cataracts, glaucoma, and retinal degeneration worsen visual function by causing deficits in peripheral and central vision, reduced visual acuity, poor contrast sensitivity, and impaired depth perception.25,28, 29, 30, 31, 32, 33, 34, 35, 36 These impairments undermine spatial judgment and hazard detection within the home and community. Concurrently, physical factors such as decreased balance, gait dysfunction, and activity limitations increase vulnerability.28,35,37, 38, 39, 40 Personal factors, including frequent nighttime waking and fear of falling, further elevate fall risk.35,41 Environmental challenges combined with visual–spatial misjudgments exacerbate the chance of falls. Together, these personal, physical, visual, and environmental aspects interact to substantially increase fall risk among older adults with VI.

Decreased access to vision screening may be another key mechanism related specifically to older adults and the Mexican Americans population.42, 43, 44 For example, older Mexican Americans may not be getting dilated eye examinations and the treatments needed to address VI. In addition, this population may have limited access to eye care services owing to insurance or language barriers. Poor self-management of chronic conditions, such as diabetes and high blood pressure, might exacerbate symptoms of eye-related conditions. Early vision screening and chronic disease self-management education among older Mexican Americans older adults are important steps in preventing falls.

The findings on VI and falls over time are similar to those published by Olsson Möller et al.45 using the Swedish National Study on Aging and Care, where the authors found that those with VI have greater odds of falls over 3 and 6 years of follow-up, and by Klein and colleagues46 using the Beaver Dam Eye Study, where the authors found that those with VI have greater odds of falls over 5 years of follow-up. Participants with NVI had greater odds of falls but not those with DVI, a result similar to previous findings by Thomas et al.47 using the U.S. National Health and Aging Trends Study over 12 months of follow-up. Similarly, White and colleagues48 found high rates of falls for individuals with VI over 12 months of follow-up among community-dwelling Australian participants aged ≥60 years. Whereas this survey collected data only on Mexican Americans, the findings of this study cannot be compared with those of other racial and/or ethnicity groups. However, results are similar to those published using the University of Michigan’s Health and Retirement Study when analyzing different racial and ethnicity groups.25

Limitations

Limitations exist for this research study. First, VI was assessed by self-report, which is subject to recall bias that may underreport or overreport VI or falls. Objective measures were not collected in the survey. However, Zimdars et al.49 demonstrated no significant difference between self-reported VI measures and objective VI measures. Second, attrition from loss to follow-up or death occurred owing to the 16 years of longitudinal follow-up. However, GEE modeling uses all available information in the analysis from follow-up interviews, independent of follow-up durations among participants. Third, the use of the MMSE as a covariate for cognitive impairment underestimates mild cognitive impairment, which may have underestimated the confounding effects of cognitive impairment in the relationship between falls and VI.23 Fourth, the results of this study are generalizable only to Mexican Americans living in the geographic region of the Southwestern U.S. (Texas, New Mexico, Colorado, Arizona, and California). Finally, the survey did not collect data on prescription glasses or eye disease treatment (medical or surgical).

This study also has key strengths. First, the study uniquely included a long follow-up over 16 years of analyzing VI and falls among Mexican American older adults. Second, the relationship with falls was analyzed separately for self-reported NVI and DVI in this study, which allowed for comparison of which was more important in falls prevention. Finally, addressing VI among older Mexican Americans is essential because the population of Hispanic men is expected to be the largest population with low vision in the next few decades.

Findings from this study can guide the development of vision screening interventions tailored to the Mexican American population that will decrease falls. Specific strategies for implementing vision screenings among Mexican American older adults include increasing the use of validated screening tools available in both English and Spanish. Also important to improving accessibility is educating healthcare providers to recognize and address potential barriers such as limited English proficiency, transportation challenges, and inadequate health coverage. Recommendations for improving adherence to vision care among Mexican American older adults include respecting Mexican American cultural values. For example, increasing utilization of family and/or caregiver support is highly recommended because their preference may be family support versus formal support of the healthcare professional or healthcare system.50

Additional strategies to reduce VI and falls include incorporating contrast sensitivity and other visual function tests—frequently overlooked in routine eye exams—into vision screenings.36 Tailoring vision evaluations to assess contrast sensitivity, depth perception, and visual field aspects can significantly impact fall prevention among older adults. Moreover, because vision, physical activity, functional ability, and environmental factors interact complexly to influence fall risk, home safety assessments are recommended for older adults with VI, to identify and mitigate hazards within their living spaces and communities.51

Additional research is needed to determine whether patients adhere to recommendations from vision providers, such as using prescribed glasses, medications, or vision therapy, which can help reduce falls related to VI. Further studies should also focus on improving clinical care practices related to VI by identifying evidence-based techniques that effectively address visual deficits caused by common eye diseases. In addition, research is required to explore the limitations in vision health insurance coverage and reimbursement because VI is a significant predictor of adverse health outcomes, including frailty and falls.52 Addressing these gaps could improve both vision care and fall prevention for older adults with VI.

CONCLUSIONS

Ensuring high-quality vision care among older Mexican Americans is necessary, and research should continue to address the needs of this population. Ensuring vision health policy that adequately addresses the needs of older Mexican Americans is also essential. The Mexican American population has high rates of medical comorbidities known to adversely impact vision and suboptimal access to timely ophthalmological services.53,54 Falls are preventable; VI is preventable. Thus, the examination of these 2 risk factors was important to understand the consequences of untreated VI on falls.

Acknowledgments

ACKNOWLEDGMENTS

During the preparation of this work, the authors did not use any artificial intelligence tool in the writing process. MLS, the corresponding author, affirms that everyone who contributed significantly to this work has been listed and that written consent from all contributors who are not authors and are named in the Acknowledgment section has been obtained. The study and all research protocols were approved by the IRB of the University of Texas Medical Branch (IRB Number 16-004). Oral informed consent was obtained from all study participants. The data sets generated during and/or analyzed during this study are available at https://www.icpsr.umich.edu/icpsrweb/NACDA/series/546.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the Health Professions Education Evaluation and Research program or the Department of Veterans Affairs.

Funding: This work was supported in part by the National Institute on Aging (R01 AG10939) and the National Institute on Minority Health and Health Disparities (R01 MD010355). MLS was supported by the Health Professions Education Evaluation and Research fellowship through the VA Office of Academic Affiliations Advanced Fellowships Program (3HPECCD2020) and partially supported by the Center for Innovations in Quality, Effectiveness and Safety (IQuESt) (Grant Number CIN 13-413).

Declaration of interest: None.

CRediT AUTHOR STATEMENT

Mandi L. Sonnenfeld: Conceptualization, Methodology, Software, Writing – original draft, Data curation, Visualization. Monique L. Pappadis: Conceptualization, Writing – reviewing & editing. Timothy A. Reistetter: Conceptualization, Writing – reviewing & editing. Mukaila A. Raji: Conceptualization, Writing – reviewing & editing. Soham Al Snih: Conceptualization, Methodology, Software, Writing – original draft, Supervision, Funding acquisition.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.focus.2026.100477.

Appendix. Supplementary materials

mmc1.jpg (367KB, jpg)

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