The Journal of School Nursing
2022, Vol. 38(4) 387–396© The Author(s) 2020Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/1059840520963647journals.sagepub.com/home/jsn
Glasses wearing at school remains low even when glasses are provided. This study investigated whether a classroom intervention to promote glasses wearing was associated with increased glasses wearing and improved classroom behavior. A pretest, posttest design was implemented with 44 students in Grades 1–4 at an urban public elementary school. Over 5 weeks, teachers encouraged eyeglass wearing through a classroom tracker, verbal reminders, and incentives. Glasses wearing and student behavior were monitored using the Direct Behavior Rating Scale of academic engagement and behavior for 13 weeks, including 4 weeks before and after the intervention. Glasses wearing increased from 56% to 73% (95% confidence interval [CI] = [0.08, 0.26]) in the first 2 weeks of the intervention, but not after a spring recess. The intervention was associated with significantly improved academic engagement (4.31%, 95% CI [2.17, 6.45]), respect (3.55%, 95% CI [1.77, 5.34]), and disruption (–4.28%, 95% CI [–6.51, –2.06]) compared to baseline. Higher academic engagement and disruption persisted 4 weeks after the intervention ended. A classroom-based glasses tracking and incentive system is associated with improved eyeglass wearing and classroom behavior among elementary students. A longer term randomized trial is needed to confirm these promising results.
Keywords
school-based clinics, coordinated school health program, elementary, program development/evaluation, health and wellness, evidence-based practice, school nurse
An estimated 20%–25% of school-aged children in the United States have a diagnosed vision difficulty (Ethan et al., 2010; Ferebee, 2004; Zaba, 2011), and vision problems disproportionately affect the learning of children from poor urban areas (Basch, 2011). Data from the Centers for Disease Control and Prevention (CDC) and others demonstrate that children living below the poverty level are nearly twice as likely to experience vision difficulties as their wealthier counterparts (CDC, 2005; Gould & Gould, 2003).
Vision screening in schools offers an opportunity to effectively capture students requiring vision correction (Peterseim & Arnold, 2015), and significant efforts to improve connection with follow-up care are ongoing. A recent systematic review by Evans et al. (2018) found that programs that pair vision screening with the provision of free glasses have more success in ensuring students receive and wear the glasses they need in comparison to programs that only provide prescriptions. However, these efforts are most useful if students continue to wear their glasses as recommended. Several studies have demonstrated that glasses-wearing compliance among students remains low even after receiving free pairs of glasses (Congdon et al., 2008; Gogate et al., 2013; Keay et al., 2010; Messer et al., 2012; Narayanan et al., 2017; Preslan & Novak, 1996) with adherence ranging from 13.4% (Castanon Holguin et al., 2006) to 56% (von-Bischhoffshausen et al., 2014) 1 or more years after glasses provision.
Documented barriers to glasses wearing include negative societal perceptions, limited parental involvement, dislike of glasses, or simply forgetting to wear them (Kodjebacheva et al., 2014, 2015; von-Bischhoffshausen et al., 2014). In one study of Native American students who received two free pairs of glasses, loss and breakage were major contributors to lack of compliance 1 year later (Messer et al., 2012).
Focus groups with parents, teachers, nurses, and adolescents have identified potential solutions to these barriers within a school setting. These include teacher involvement in encouraging glasses use, providing vision education for parents and children, conducting school-wide campaigns to promote glasses wearing, and creating reminders and incentives to wear glasses at school (Kodjebacheva et al., 2014, 2015; von-Bischhoffshausen et al., 2014).
While results from a recent systematic review suggest that health education interventions alone might not improve glasses wearing in children (Evans et al., 2018), there is some evidence that classroom-based approaches can incentivize glasses wearing and improve adherence among students. One study of New York City public school students demonstrated that obtaining glasses for children and implementing a classroom-based intervention increased glasses wearing from 19% to 47% (Ethan et al., 2010). Other studies among young students in Massachusetts and California paired glasses distribution with health education and a classroom-based tracker also finding a positive impact on glasses-wearing adherence (Johnson et al., 2016; Kodjebacheva et al., 2014).
These classroom-based interventions have often been studied in the setting of a multicomponent school vision program that includes vision screening, free provision of eyeglasses, and in some cases vision education. We sought to examine the role of a classroom reminder and tracker system in glasses wearing and classroom behavior in a population of students who received their glasses from a variety of sources, including in- and out-of-school providers. To our knowledge, no other study has examined the association of a classroom-based intervention with glasses-wearing compliance in a varied participant population such as this. Multicomponent school vision programs offer the opportunity to link glasses provision with vision education and classroom-based interventions, supporting students’ glasses-wearing habits soon after they receive them. These students may also experience a cohort effect, with one or several other classmates also receiving glasses at the same time. In contrast, students who source their glasses externally may do so at different times throughout the year. A classroom-based intervention may be supporting these students many months after they receive their glasses, potentially making it more difficult to build beneficial glasses-wearing habits.
Other studies have investigated the link between vision correction and academic performance (Ethan & Basch, 2008; Glewwe et al., 2018; Krumholtz, 2000; Ma et al., 2014; Mathers et al., 2010), demonstrating improvement on achievement test scores and other measures of educational attainment with vision correction. Furthermore, parents, teachers, and students have observed that vision correction may also improve student behavior through improved focus and a willingness to practice academic skills (Dudovitz et al., 2016). However, there has been limited research quantifying an association between vision correction and classroom behavior outcomes. While one study among Florida elementary school students found no correlation between vision screening efforts and disciplinary incidents (Glewwe et al., 2018), our study set out to measure the impact of a classroom-based vision intervention on more subtle measures of student behavior including academic engagement, respect, and disruption.
A classroom-based intervention to directly support glasses-wearing recommendations presents an opportunity to both improve adherence and evaluate the impact on educational outcomes such as classroom behavior. This study set out to evaluate such an intervention. We hypothesized that following the intervention, eyeglass wearing, academic engagement, and respect would increase, while classroom disruption would decrease compared to preimple-mentation measurements. We also explored variation in intervention effectiveness by baseline eyeglass-wearing adherence, students’ perceptions of their need for glasses, and levels of parent reminders to wear glasses. We hypothesized that students with low adherence at baseline would improve more than their peers in response to the intervention, as would those who did not, at baseline, feel that wearing glasses improved their vision, and those who reported no parental reminders to wear their glasses.
The protocol for this pretest, posttest evaluation was approved by the institutional review boards (IRBs) of the Johns Hopkins University School of Medicine and the participating school district’s IRB.
Data were collected from a large urban public charter school during the 2017–2018 school year. The school serves elementary (Grades K–4) and middle (Grades 5–8) school students in the same building. Over 99% of students are African American, more than 80% qualify for free- or reduced-price meals. A school health program provides school nursing care and comprehensive preventive care and chronic disease management through a school-based health center (SBHC). The program also provides a range of vision care services including vision screening, onsite optometry visits, and eyeglass prescription management.
A needs assessment conducted in the 2014–2015 school year cited vision problems and glasses wearing as major areas of unmet need at the school. During the 2015–2016 school year, SBHC staff conducted vision screening for Grades 3, 5, and 6. Screening components include visual examination, pupillary light response and accommodation, red reflex, extraocular movements, cover–uncover test, color vision, stereopsis, and visual acuity (Snellen chart) 46% of students failed the screening and required further evaluation (Rales Center data, unpublished). Through a partnership with a community-based vision provider, the SBHC provided optometric evaluation for students who failed vision screening and desired in-school optometry visits. Specific content of the optometric exam was determined by the treating optometrist and dilated exams were performed when appropriate. Those who needed glasses were provided with two pairs free of charge, through a combination of insurance benefits and grant funding. However, reports from school staff and observations from school nurses indicated that some students were not regularly wearing their glasses.
Participants were recruited from known glasses-wearing students in Grades 1–4. To be eligible, students needed to have at least one functional pair of glasses at the start of the study. They were not required to have received their glasses through the school vision program in order to participate. Existing school health records were used to generate a list of potentially eligible third- and fourth-grade students. Once a teacher agreed to participate in the intervention, a letter was sent to potentially eligible students in their classroom inviting the student to participate and providing contact information for study staff. Study staff spoke with interested families by phone to describe study procedures and to schedule an in-person meeting. In-person meetings between families and study staff took place in a private area of the school health center and written informed consent procedures were completed at this time.
Glasses-wearing adherence. Classroom observation of glasses-wearing adherence was recorded as “yes/wearing glasses,” “no/not wearing glasses,” or “no observation.” If a student put their glasses on after the observer began recording, they were classified as not wearing glasses.
Student behavior. Student behavior was assessed using the Direct Behavior Rating (DBR) Scale a brief rating of students’ classroom behavior through direct observation for a specific period of time (Christ et al., 2010). The DBR rates three specific domains of classroom behavior: academic engagement (DBR1), respect (DBR2), and classroom disruption (DBR3). Raters estimate the percentage of time a student displays a particular behavior during the observation period. Each outcome has a 10-level Likert-type scale of 0%–100%, with valid choices specified over 10-unit intervals (e.g., 0, 10, ..., 100). Several researchers have documented the reliability and validity of this tool as a behavioral measure of positive adaptation to academic and behavioral demands in the classroom (Briesch et al., 2010; Chafouleas, Jaffrey, et al., 2013; Christ et al., 2010).
Observation timing. Because student behavior was expected to vary across the school day and week, the time (morning/afternoon) and day of the week were recorded for each observation or rating.
Student-reported attitudes and behaviors. Before the intervention began, participants completed a paper-and-pencil questionnaire about their experiences, habits, and attitudes regarding their vision and glasses. Students responded to questions such as “I see better when I wear my glasses” (yes/no) and “My parents tell me to wear my glasses” (3-point Likert-type scale of Always, Sometimes, and Never).
Student characteristics. Student grade level and sex were recorded at the time of recruitment.
Teacher satisfaction. To evaluate the acceptability of the intervention, teachers completed a brief anonymous satisfaction survey that included items such as “The sticker charts were easy to use,” “My students were motivated by the sticker charts,” and “I would use glasses sticker charts again” using a 5-point Likert-type scale from strongly agree to strongly disagree. Teachers were also able to provide open-ended written comments. Comments and feedback that were shared in informal interactions between study staff and teachers were recorded as field notes for the duration of the study.
In the morning and afternoon of each school day, a teacher or non-instructional observer (NIO, T. Haag) recorded (1) glasses-wearing adherence and (2) DBR data for participating students. Data were collected over 5 school days per week, with the NIO typically observing students 1 day per week and teachers collecting data on the remaining days. Barring school closures and student or teacher absences, up to 10 observations per student were available in a given week. Each classroom observation session lasted 10–15 min. The NIO recorded DBR assessments during class time in the morning and afternoon, while teachers recorded their assessments during class time or retrospectively (during break periods after class or at the end of the school day). Preintervention data collection continued for 4 weeks to establish baseline adherence and behavior ratings.
At the end of the preintervention phase, each classroom teacher was provided with student-friendly trackers, stickers, and a set of small prizes for each of their participating students. Teachers provided regular reminders and actively encouraged students to wear their glasses. Students who wore their glasses as prescribed that day received a sticker on their tracker; students with four or more stickers at the end of the week were allowed to select a small prize. NIO and classroom teacher observations of adherence and DBR scores continued as above during this time. The intervention lasted approximately 5 weeks in total. Notably, after Weeks 1 and 2, students departed for a 1.5-week spring recess. On their return, the intervention resumed for Weeks 3–5.
Following the intervention period, teachers and the NIO continued to record adherence and DBR data as above for a 4-week postintervention phase. At the end of the study period, teachers were provided with an anonymous online survey to rate their experience with the intervention. Teachers were also provided with a US$25 gift card for each month of study participation, up to US$75.
We examined unadjusted means, standard deviation, and counts of study variables overall and during each stage of the intervention: preintervention, intervention, and postintervention and by evaluator (teacher vs. NIO). Exploratory analyses indicated differential intervention effects by the time of intervention, so the intervention was split into two phases: Weeks 1 and 2 (prespring recess) and Weeks 3–5 (postspring recess). We evaluated the interitem correlations and Cronbach’s a reliability for the three DBR measures.
Study data exhibited a nested structure with students (Level 1) nested within teachers (Level 2) or, in the case of NIO observations, students (Level 1) nested within grades (Level 2). We estimated associations between the stages of the study (Time) and each dependent variable (DBR1, DBR2, DBR3, and glasses-wearing adherence) using two-level mixed models. We used mixed logistic regressions to fit adherence and mixed linear models to fit each of the DBR outcomes. Models included time of day (morning or afternoon), day of observation, and student sex as covariates.
In each model, Time was coded as 0 (preintervention), 1 (Weeks 1 and 2 of the intervention), 2 (Weeks 3–5 of the intervention), and 3 (postintervention). Student-level (L1) intercepts and slopes were specified as random effects, while grade level (models estimated using NIO observations) and teacher identifiers (models estimated using teacher observations) were entered as fixed effects. In preliminary analyses, F tests indicated that teacher and NIO ratings were not significantly different. Therefore, in the models presented here, teacher and NIO ratings were pooled and fit using studentlevel random growth models with fixed intercepts for grade level and observer type (e.g., teacher vs. NIO) as fixed effects.
Finally, we explored variability in intervention effectiveness by our hypothesized moderators. We used interaction terms in mixed-effects models to evaluate effect modification by baseline adherence to glasses wearing (high or low based on mean split) as well as two student attitudes reported at baseline (“I see better when I wear my glasses” and “my parents tell me to wear my glasses”). For student questionnaire responses on the 3-point Likert-type scale, we combined always and sometimes variables.
Of 157 students who were recruited, 44 students participated (see Figure 1 for recruitment details). The sample was 64% male, and more than a third were in Grade 4. Approximately one quarter of study participants received their glasses through an independent, external provider, rather than through the school program. Sixty-six percent of students felt that they see better with their glasses, and 41% reported that their parents remind them to wear their glasses (Table 1).
Student adherence to glasses wearing relative to baseline improved significantly during the first 2 weeks of the intervention (Table 2). Across all students in the sample, the probability of wearing glasses compared to baseline rates increased by 17 percentage points (95% CI [0.08, 0.26]), from 56% to 73%. This improvement was observed across raters (teacher and NIO) and after adjusting for sex, grade level, time of day, and day of observation. However, there was no improvement in adherence relative to preimplementation levels beyond the second week of the intervention.
Student measures of academic engagement, respect, and disruption all demonstrated statistically significant improvement during the first 2 weeks of the intervention (pooled rating improvement of 4.31, 3.55, and –4.28 points, respectively). These improvements persisted for up to 4 weeks after the intervention ended for academic engagement (4.18, 95% CI [1.43, 6.94]) and disruption (–4.02, 95% CI [–7.09, –0.94]; Table 3).
Improvement in the probability of glasses wearing over baseline during the first 2 weeks of the intervention was significantly larger for students who did not feel that wearing their glasses improved their vision (0.29, 95% CI [0.13, 0.45]), those who reported no parental reminders to wear glasses (0.24, 95% CI [0.11, 0.37]), and those whose baseline adherence was below the sample mean (0.29, 95% CI [0.16, 0.42]; Table 4).
As summarized in Table 5, academic engagement scores improved and then persisted through the 4-week postintervention period for students who did not feel that wearing their glasses improved their vision at baseline (5.46, 95% CI [0.80, 10.11]) and those whose baseline glasses-wearing adherence was low (4.79, 95% CI [1.02, 8.55]). Similarly, improvement in disruptive behaviors persisted through the postintervention period for students with low baseline glasses wearing (–4.63, 95% CI [–8.84, –0.42]). Ratings of respect improved during the first 2 weeks of the intervention for students whose baseline glasses wearing was low (5.77, 95% CI [3.29, 8.24]).
Ten teachers (71.4%) provided feedback through the anonymous end-of-study survey. Teachers reported generally positive attitudes toward incorporating the intervention into their classroom, with 100% of survey respondents agreeing with the statements “The sticker charts were easy to use,” “The sticker charts took up a minimal part of our day,” and “I would use glasses sticker charts again.” Seventy percent of respondents agreed that their students were motivated by the sticker charts. Several teachers remarked on positive interactions with their students: “Making my student responsible made it a lot easier for me, I told her that it was her responsibility to collect her sticker ...and she absolutely loved reminding me each and every day!” One teacher commented on the development of student accountability and ownership over glasses wearing in the classroom: “Whenever I reminded a student to put on their glasses, they were excited to do so because of the chart. In the past, they would give me a hard time about getting their glasses and putting it on.” Another teacher noted a classroom-wide shift: “It developed a culture in my classroom w[h]ere even friends without glasses would politely remind a student if they took the glasses off for recess and needed to put them back on.”
Several teachers shared a preference for starting the intervention earlier in the year, with others stating that they would like to see more students involved and expressing a hope for strengthening the process for replacing students’ broken glasses. Furthermore, the intervention seems to be limited to teacher–student interactions: The majority of respondents (60%) did not feel that the sticker charts created an avenue for collaboration with their students’ families.
Many children receive some form of vision care in schools, ranging from school-wide vision screening to free glasses programs, but it is clear that some students continue to struggle with adherence after they have received glasses. In our setting, students who began the study period with glasses were only wearing them 56% of the time, consistent with other published observations of adherence (Castanon Holguin et al., 2006; von-Bischhoffshuasen et al., 2014). This intervention was associated with improvement in glasses wearing among elementary-age students, raising adherence by 17 percentage points, from 56% to 73%, but only in the first 2 weeks of the intervention. Notably, the intervention period included 1.5 weeks of spring recess, interrupting the continuity of intervention delivery after the first 2 weeks and potentially undercapturing long-term persistence of intervention effects. This drop-off may be the result of students losing or breaking their glasses during the spring recess or getting out of the habit of wearing them.
In addition to improving adherence, the intervention was associated with improvements in classroom behavior as measured by academic engagement, respect, and disruption, consistent with previously documented observations by parents, teachers, and students (Dudovitz et al., 2016). These findings suggest that this intervention successfully decreased the number of days where students experienced impaired vision and supported participants in engaging with their classroom environment. These improvements in behavior may be a result of students being able to better access visual content and engage in the classroom environment, which in turn may lead to better academic engagement. Furthermore, academically engaged students may be less likely to experience boredom and frustration and therefore be less likely to demonstrate disruptive behaviors.
Unlike adherence to glasses wearing, improvement in academic engagement and disruption persisted for all participating students into and through the 4-week postintervention period. This suggests that in addition to supporting students’ visual health, schools may experience sustained positive effects by engaging in programs that encourage glasses-wearing adherence. It is possible that students who felt newly engaged in their classroom environment enjoyed positive feedback at their improved behavior and continued to attempt to engage in those behaviors even if they were not wearing their glasses. It is important to note, however, that the magnitude of the effect was a modest 5–10 points on a 100-point scale. Nonetheless, given the short duration and relatively low intensity of the intervention, these improvements are likely meaningful for student learning.
In contrast to measures of academic engagement and disruption, improvement in ratings of respect was significant only for the first half of the intervention. Chafouleas, Kilgus, et al. (2013) found the DBR to be an effective and consistent behavior screener, and the rating instructions included examples of specific student actions for each of the behavior domains (i.e., “academic engagement” is indicated by writing, raising hands, answering a question, etc.). While academic engagement and disruption might be perceived as snapshots of student behavior at a particular time, respectfulness may be understood by raters as a more immutable quality inherent to a student’s personality. Consequently, ratings of respect might be slower to demonstrate sustained change.
In addition, this study highlights the characteristics of students who might be most likely to benefit from a glasses-wearing intervention. Students whose glasses-wearing adherence was low at baseline showed improvements in glasses-wearing adherence during the first 2 weeks of the intervention. They also demonstrated an improvement across all DBR subtypes during this time; this effect persisted through the postintervention period for academic engagement and disruption. In addition, students who did not feel that wearing glasses helped their vision had a significant improvement in adherence during the first 2 weeks of the intervention. These students also experienced an improvement in academic engagement even after the intervention ended. It is possible that students with this mindset have not internalized the connection between glasses wearing, improved vision, and ability to engage in the academic environment. These students in particular may benefit from external motivation and intervention until they can make this connection on their own.
This study has several limitations. Eligible students were identified based on data from the school health center’s vision services records as well as teacher reports. While every attempt was made to produce a comprehensive list of eligible students, this method may have undercaptured the population of very low-adherence glasses wearers.
Given the nature of intervention, it was not feasible to blind the observers who were assessing glasses wearing and behavior. In addition, throughout the intervention, students had a high rate of glasses loss and/or breakage that interrupted their ability to participate, consistent with documented challenges of other school-based vision programs (Messer et al., 2012). Further research is needed to determine whether the rate of glasses loss and breakage among students in the intervention differs from that of their peers. Finally, this was a pretest–posttest design so causality cannot be inferred. Future randomized controlled trials are needed to confirm these findings.
A classroom-based glasses tracking and incentive system is associated with increased short-term adherence to glasses-wearing recommendations and longer term classroom behavior among elementary students and is well received among teachers who incorporated it into their classroom. Students who struggle to wear their glasses consistently in class, those who are ambivalent about their need for glasses, and those whose parents do not remind them to wear their glasses may benefit disproportionately from such an intervention. The results of this study suggest that a larger randomized trial with longer follow-up is warranted.
The prevalence and impact of vision issues on learning will undoubtedly evolve through large-scale online learning in response to the COVID-19 pandemic. Many states waived vision screening requirements for the 2019–2020 school year due to school closures. However, there are many ways that school nurses can engage with families regarding vision care in the virtual environment. Most of the above suggestions for supporting glasses wearing can be adapted for virtual implementation. Some additional options for supporting vision health in the virtual environment could include:
Tania M. Haag drafted the manuscript. Tania M. Haag, Gabriela Calderon Velazquez, Paul Spin and Katherine A. Connor contributed to acquisition, analysis, or interpretation. Tania M. Haag, Gabriela Calderon Velazquez, Tresa Wiggins, Paul Spin, Sara B. Johnson and Katherine A. Connor contributed to conception or design, critically revised the manuscript, gave final approval, and agreed to be accountable for all aspects of work ensuring integrity and accuracy.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Norman and Ruth Rales Family Foundation and the Johns Hopkins University School of Medicine Office of the Dean.
Gabriela Calderon Velazquez, MSEd https://orcid.org/0000-0001-8651-8254
Supplemental material for this article is available online.
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Tania M. Haag, MD, is a medical student at Johns Hopkins University School of Medicine in Baltimore, MD. Email: taniahaag@gmail.com
Gabriela Calderon Velazquez, MSEd, is a research program coordinator at Rales Health Center, Division of General Pediatrics and Adolescent Medicine, Johns Hopkins University School of Medicine in Baltimore, MD. Email: acalder8@jhu.edu
Tresa Wiggins, MSN, CPNP, is a nurse practitioner at Rales Health Center, Division of General Pediatrics and Adolescent Medicine, Johns Hopkins University School of Medicine in Baltimore, MD. Email: tschuma1@jhu.edu
Paul Spin, PhD, is a senior research data analyst at Rales Center for the Integration of Health and Education, Johns Hopkins University School of Medicine in Baltimore, MD. Email: pauljspin@gmail.com
Sara B. Johnson, PhD, MPH, is an associate professor of pediatrics at Johns Hopkins School of Medicine in Baltimore, MD. Email: sjohnson@jhu.edu
Katherine A. Connor, MD, MSPH, is a medical director and assistant professor at Rales Health Center, Division of General Pediatrics and Adolescent Medicine, Johns Hopkins University School of Medicine in Baltimore, MD. Email: kconno14@jhmi.edu
1 Division of General Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
2 Rales Center for the Integration of Health and Education, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Corresponding Author:
Katherine A. Connor, MD, MSPH, Rales Health Center, Division of General Pediatrics and Adolescent Medicine, Johns Hopkins University School of Medicine, 200 N. Wolfe Street, Room 2074, Baltimore, MD 21287, USA.Email: kconno14@jhmi.edu
