cused on the reading performance of those with AMD using four different font styles. Research Reports Reading performance was best with the Cou­ rier font, while the Arial font produced the Age-Related Macular poorest performance. In contrast, a systematic Degeneration and Reading review of 18 studies found no conclusive ev­ Performance: Does Font Style idence to support a relationship between print Make a Difference? legibility and serif choice for reading with Christina Hedlich, Elizabeth Barstow, low vision (Russell-Minda et al., 2007). The and Laura K. Vogtle studies included in that review focused on the The National Eye Institute (2015) reports different typeface characteristics, which lim­ that by the year 2050, the number of individ­ ited the investigators’ ability to provide de­ uals with age-related macular degeneration finitive recommendations. (AMD) will rise from 2.07 million to 5.44 Advocacy groups such as the American million. AMD causes central vision loss, Foundation for the Blind (n.d.), the Canadian which can affect independence in activities National Institute for the Blind (n.d.), and the such as medication management, meal prep­ Council of Citizens with Low Vision Interna­ aration, and personal finances (Smallfield, tional (n.d.) that publish guidelines of text Clem & Myers, 2013). Most of these activi­ composition for readers with vision loss rec­ ties require reading, making an inability to ommend the use of mono-spaced, san-serif read a concern for those with AMD (Hassell, font styles. These guidelines are not evidence Lamoureaux, & Keeffe, 2006). based but represent the preferences of readers Font size and style of text may improve with low vision (Tarita-Nistor et al., 2013). reading performance for individuals with low The aim of this mixed-methods study was vision. Most recommendations addressing to determine the preferred font style of indi­ font styles are not evidence based. One font viduals with AMD, and whether a sans-serif, characteristic with conflicting outcomes is the proportionally-spaced font (Arial) or a serif, use of serifs, decorative extensions placed on mono-spaced font (Courier New) improved ends of characters. Many persons with low reading performance for individuals with vision report reading serif fonts as easiest, a AMD. Reading performance was defined as text style frequently used in reading materials reading acuity, critical print size, and maxi­ (Strizver, 2015). A sans-serif font is void of mum reading speed. any serifs and is commonly used in charts and captions (Strizver, 2015). METHODS Studies have investigated attributes of fonts A mixed-methods design was used in which for typical vision readers and low vision read­ the researchers collect and analyze qualitative ers, but few have focused on individuals with and quantitative data in a single study AMD. Mansfield, Legge, and Bane (1996) (Driscoll, Appiah-Yeboah, Salib, & Rupert, compared font styles on reading performance 2007). The advantage of this design was the in those with and without low vision. Results ability to compare and contrast data types to indicated that participants with central visual better understand font preferences for those field loss were more sensitive to differences with AMD. This study was approved by the in font style, and the Courier font produced University of Alabama at Birmingham insti­ the fastest reading speed. Tarita-Nistor, Lam, tutional review board, and written consent Brent, Steinbach, and Gonza´lez (2013) fo­ was provided by each participant. 398 Journal of Visual Impairment & Blindness, July-August 2018 ©2018 AFB, All Rights Reserved Participants Table 1 Characteristics of the participants. We recruited participants using a convenience sample from an outpatient low vision clinic Morgan and support group. Inclusion criteria were: Age Gender Visual acuity (grade) Contrast visual acuity between 20/30 and 20/400, con­ 74 M 20/50 13.8 10% trast sensitivity of at least 10%, intact cogni­ 82 F 20/60 16.5 5% tion, and AMD. Conditions other than cata­ 82 F 20/100 7.6 5% ract or cataract removal were excluded; 88 F 20/125 15.2 10% participants had to be 55 years of age or older, 91 M 20/200 5.1 10% 86 F 20/125 7.5 10% able to speak English, and had to demonstrate 76 M 20/200 13.9 5% at least a third-grade literacy level. 94 F 20/100 7.6 5% Those who had had cataract surgery in one 75 M 20/40 13.9 1.25% or both eyes were not excluded from this 93 F 20/80 10.0 5% study. Fifty percent (eight) of the participants 78 M 20/60 16.5 5% had bilateral cataract removal in their eye 85 F 20/80 11.4 1.25% health history; 18% (three) had documented 74 M 20/200 13.9 5% cataract removal in one eye. Thirty-two per­ 66 M 20/80 16.5 5% 86 F 20/200 15.2 5% cent (five) of the participants had not under­ 81 M 20/200 16.5 1.25% gone cataract removal in either eye and did not have more than a moderate grade of cat­ Note: Visual acuity = visual acuity according to LEA Numbers Chart for Vision Rehabilitation; aract at the time of the study. Morgan = Morgan Reading Comprehension As­ The sample (N = 16) consisted of eight sessment; Contrast = contrast sensitivity accord­ ing to LEA Numbers Low Contrast Test, 10M. men and eight women with a mean age of 81.9 years (SD = 7.8 years). Six participants (38%) had near-normal vision, five (31%) had which measures contrast sensitivity function moderately low vision, and five (31%) had from 1.25% to 25% (Good-Lite Company, severely low vision (see Table 1). Assignment 2018). Cognitive status had to assessed with a to one of these three groups was determined tool that did not require vision to be a pre­ by visual acuity corresponding to the World requisite. The Short Portable Mental Status Health Organization Levels of Visual Impair­ questionnaire (Pfeiffer, 1975), a reliable ment groups (Dandona & Dandona, 2006). and valid measure of cognition in older adults, was used. Reading comprehension Measures was measured using the Morgan Reading The MNREAD Acuity Chart and qualitative Comprehension Test, which was designed interview transcripts were the primary outcome to determine reading comprehension levels measures used. In the following section, screen­ of individuals with AMD (Watson, Wright, & ing and data collection tools are described. Long, 1996). Screening measures. Participants were Data collection measures. The MNREAD screened for the inclusion criteria. The LEA Acuity Chart (Regents of the University Numbers Chart for Vision Rehabilitation, of Minnesota, 1994) was modified with Courier manufactured by Elgin, Illinois–based Good- New (serif) and Arial (sans-serif) fonts to assess Lite, designed to measure visual acuity the dependent variables of reading acuity, crit­ from the normal to profound range, was used ical print size, and maximum reading speed. to screen for visual acuity (Colenbrander, Written permission was obtained from those 2018). Contrast sensitivity was assessed using authors to create and utilize a modified version the LEA Numbers Low-Contrast Test, 10M, of the test for this study. ©2018 AFB, All Rights Reserved Journal of Visual Impairment & Blindness, July-August 2018 399 The quick lowed those outlined in the MNREAD Acuity Arial brown fox ran Chart manual. fast. Data was analyzed using IBM SPSS Ver­ The quick Courier New brown fox sion 23. Means and standard deviations for age ran fast. were calculated across all participants and within low vision group categories. Means and Figure 1. Examples of Arial and Courier standard deviations for data from the MNREAD New fonts used. Acuity Chart (reading acuity, critical print size, and maximum reading speed) were calculated for both fonts tested. The nonparametric Wil­ Modified charts included print size of 0.0 coxon signed-ranks test was used to determine logMAR to 1.3 logMAR printed on 92 if there was a significant difference of font on bright 67-pound paper using a Xerox D95 the dependent variables. LaserJet printer. The print size of each log- Qualitative elements. MAR level sentence was determined by the Interviews immedi­ height of a lower-case letter x (x-height) on ately following MNREAD administration re­ the original MNREAD Acuity Chart to quired participants to reflect upon preferred font equate the two fonts when creating the test­ style and reasons for this preference. Each in­ ing boards without having to alter the fonts. terview was audio recorded and transcribed The sentences used on the testing charts verbatim. Member checking was used to assure were taken from the original chart to ensure interpretation accuracy. length and lexical difficulty similar to the The qualitative data was organized using the­ original test. See Figure 1 for samples of matic analysis. The primary investigator sorted both fonts used. information into themes that describe font choice To learn participant perspectives for font and reason for preference. Qualitative themes preference, semi-structured interview scripts were compared to the quantitative data to provide were developed using open-ended questions additional insight into font style preference. to guide the interview process. The interview RESULTS script utilized input from four low vision ex­ perts, followed by pilot testing on five clients Quantitative data with low vision, and was modified for clarity. Data analysis was completed on combined levels of vision impairment. Based on the Data collection and analysis analysis from the Wilcoxon signed-ranks test, The location of data collection was chosen by no significant differences were observed be­ the participants, and it occurred in a private tween the median scores on reading acuity location at either the participant’s home or a (Z =�.979, p = .328), critical print size low vision center.