Development of the University of Houston near work, environment, activity, and refraction (UH NEAR) survey for myopia

Abstract

Clinical Relevance:

There is a need to better elucidate demographic and behavioral factors that are contributing to the rising prevalence of myopia. Doing so will aid in developing evidence-based recommendations for behavioral modifications to prevent onset and slow progression of myopia in children.

Background:

The contributions of environmental and behavioral factors in myopia remain unclear. The goal of this work was to provide a standardised survey to better understand risk factors for myopia.

Methods:

Development of the survey was carried out in 4 phases. In phase 1, three methods (direct, lay terms, and indirect) of parental reporting for the presence of myopia in their child were investigated through a questionnaire (N = 109) to determine sensitivity and specificity. The best method determined from phase 1 was used in phase 2, where questions regarding demographics, ocular history, and visual behavior were compiled and refined. In phase 3, the survey was administered to focus groups of parents (N = 9). In phase 4, a scoring system was developed.

Results:

The highest sensitivity for parental reporting for myopia of their child was the indirect method (0.84), and the lowest sensitivity was the direct method (0.41). The highest specificity was the direct method (0.86), once excluding the “do not know” responses, and the lowest specificity was the indirect method (0.53). The direct method yielded a 53.2% “do not know” response rate, 50.5% for the lay method, and 1.8% for the indirect method. Time to complete the survey was 10:09 ± 2:45 minutes.

Conclusion:

This study provides a comprehensive and up-to-date myopia risk factor survey that can be utilized by researchers and clinicians. Parents found the survey to be easy to understand and relatively quick to answer, and the scoring system allows quantification of behaviors across different categories using provided equations.

Introduction

Myopia occurs when there is a mismatch between the optics of the eye and the axial length, resulting in images coming to focus in front of the retina.¹ Myopia is increasing in prevalence, with an estimated 50% of the global population expected to be myopic by 2050.² Any degree of myopia increases the risk for associated ocular pathologies, such as myopic macular degeneration, choroidal neovascularization, posterior subcapsular and nuclear cataracts, and primary open angle glaucoma.³

Family history and genetics play a significant role in the pathogenesis of myopia. One of the strongest predictors of myopia is number of myopic parents.⁴ However, the prevalence of myopia is increasing faster than genetics alone can account for, implicating a role for environmental and behavioral factors.²

Environmental and behavioral risk factors that have been studied with respect to myopia include time outdoors and light exposure, near work, physical activity, education, urbanization, and electronic device use.^5–8 Accumulating evidences shows that time outdoors is protective against myopia onset,^9,10 with some studies also showing that increased time outdoors is associated with slower myopia progression.^11,12 For children enrolled in the Correction of Myopia Evaluation Trial (COMET), myopia progressed faster during winter months and slower during summer months.¹³ This observation could be due to decreased time spent outdoors during winter months or increased time engaged in near work. Indeed, studies using objective measures of light exposure in children show that time outdoors and overall light exposure during the summer school break is greater than when children are in school sessions.¹⁴

The relationship of near work and myopia is complex; some studies report that an association between more near work and myopia exists,^15,16 while others find the opposite.¹⁷ For example, the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error (CLEERE) study found no no difference in the amount of near work before myopia onset between children who became myopic compared to those that remained emmetropic, therefore concluding that near work does not contribute to myopia onset.¹⁸

On the other hand, recent reviews and meta-analyses have reported statistically significant associations between near work and myopia,^19,20 with some studies showing that specific characteristics of near viewing, such as absolute viewing distance and number of viewing breaks, could be more important than total duration of near work.²¹

Difficulty in defining precise risk factors in myopia likely stems from the subjective and varied methods of data collection across studies. New technology allows for continuous and objective measurement of light exposure and near work through wearable sensors. Several myopia-related studies have utilised the Hobo light sensor²² and wrist worn Actiwatch,²³ which provide measures of ambient illumination, as well as physical activity and sleep for the latter device. The RangeLife²⁴ and Clouclip²⁵ are two examples of spectacle mounted rangefinders that have been utilised to quantify near viewing behaviors. These objective devices have the potential to characterise precise roles of light exposure and near work in myopia.

However, limitations that prevent the widespread use of wearable sensors in myopia research include the high cost of the devices, limited availability, participant compliance, and ease of wear. Additionally, currently available devices are not capable of collecting data for all of the factors of interest, such as electronic device use. Therefore, subjective methods of data collection for environmental and behavioral factors remain relevant and informative, especially for collecting data from large populations as part of epidemiological studies.

Questionnaires are common in myopia research, particularly for investigating the influence of behavioral factors. However, in the case of myopia research, surveys have often been long,⁵ used surrogate measures to quantify near work, such as number of books read or grades in school,²⁶ or have not been validated or widely used.²⁷ There is no single questionnaire that is standard across studies. In order to address some of these limitations, here, a visual activity questionnaire was designed that comprehensively addresses demographic, environmental, and behavioral factors that can widely be used in research and clinical applications to assess risk factors for myopia. This required first validating and testing methods for parents to describe refractive status of their child (i.e. being myopic or not), then creating a battery of questions. To this aim, the University of Houston Near Work, Environment, Activity, and Refractive Error (UH NEAR) Survey, a comprehensive visual activity survey was developed, and scoring guidelines are provided.

Methods

The UH NEAR Survey for children is designed for parents of children ages 5 to 17 years old to answer on behalf of their child. Development of the UH NEAR Survey was carried out in several phases. In phase 1, methods of parental reporting for the presence of myopia for children were investigated.

In phase 2, questions regarding demographic factors and visual behavior were compiled, assessed, and refined by the research team based on a thorough review of the literature. In phase 3, the UH NEAR Survey was administered to focus groups to collect feedback for further refinement. In phase 4, a scoring system was developed.

The study was approved by the institutional review board at the University of Houston and procedures followed the tenets of the Declaration of Helsinki. Informed consent was obtained after explaining the nature of the study to participants.

Phase 1: Validation of parent-reported refractive error status

Parents of children between the ages of 5 and 17 years that presented to the University Eye Institute in Houston, Texas between May 2022 and August 2022 were recruited to answer a survey regarding refractive status of their child immediately prior to their eye exam (N = 109).

After obtaining parental permission and child assent, the survey was administered to the parent. The parent was handed the paper survey on a clipboard. The investigator stepped away, and the survey was returned to the investigator when complete. The survey used three methods of assessing refractive status, as adapted from a similar study carried out in patients ages 14 to 85 years (median age 33 years),²⁸ and included a direct method, lay terms method, and indirect method (Appendix 1). The questions were always presented in the order shown in Appendix 1.

The direct method asked the parent to report refractive status of their child in optometric terminology, with the question, “Is your child myopic?” The lay terms method asked the parent to report refractive status of their child using more common terminology, with the question, “Is your child nearsighted?” The indirect method used a series of three questions, including, “Does your child wear glasses?” and if so, “What age did they receive glasses?” and “What is the purpose for wear (distance, near, or both)?”

For the indirect method, the questions were derived from the Orinda Longitudinal Study of Myopia, which was used to determine whether a person was myopic.²⁹ Respondents who indicated glasses were used for distance viewing or equally used for distance and near viewing were identified as myopic. Additionally, all parents were asked whether their child had astigmatism.

Once completed, the parent returned the survey to study personnel. After the eye exam of the child, study personnel retrieved refractive information, determined at the eye exam, from the electronic medical records system. Myopia was defined as an average spherical equivalent refractive error of the two eyes ≤ −0.50 D. Children were considered emmetropic if the average spherical equivalent refraction was −0.50 D to ≤ +1.50 D, and hyperopic if the average spherical equivalent refraction was > +1.50 D. Astigmatism was defined as ≥ 0.50 D cylinder in any meridian.

Specificity and sensitivity were determined using the below formulas (Equations 1 and 2)³⁰ for each of the three methods of assessing refractive status, as well as for astigmatism.

$$\text{Sensitivity}=\text{True}\text{positives}/(\text{true}\text{positives}+\text{false}\text{negatives})$$ Equation 1.

$$\text{Sensitivity}=\text{True}\text{negatives}/(\text{false}\text{positives}+\text{true}\text{negatives})$$ Equation 2.

Phase 2: Developing the Demographic, Ocular, and Visual Activity Questions

Demographic, ocular history, and visual activity questions for the UH NEAR Survey were developed and compiled. Questions were adapted from previously published questionnaires,^28,31,32 including those used in myopia-related research, such as the Sydney Myopia Questionnaire, as well as the Generation M2 study (Kaiser foundation) and other federally-supported studies.³³ The demographic section includes questions about factors that have been shown to be associated with myopia in the literature, including age, sex, race, ethnicity, place of birth, housing, and education (type of school and grades). Questions regarding ocular history include whether the child and biological parents wear correction and for what purpose (near, distance, or both), as well as the age when they first received correction.

Parents are asked to report whether their child has myopia; the wording for this question was based on the results from phase 1 of this study (see above: validation of parent-reported refractive error status). Questions regarding visual activities ask the parent to estimate the time per day their child spend in a range of indoor and outdoor activities, near work, and electronic device use when they are not in school. Additionally, recent studies have suggested working distance^34,35 and continuous near work³⁶ are important factors in myopiagenesis. Therefore, two questions were included regarding visual breaks during near work and estimation of working distance.

Parents are asked to estimate activities of their child during the school year for (1) weekdays and (2) weekends and during the summer for (3) weekdays and (4) weekends. Additionally, parents are asked to estimate sleep duration of their child per night for these time periods. The formatting for how parents indicate hours per day is shown in Figure 1. For each question, the parent marks the hours on a continuous rating scale from 0 to 12 hours, with 15 minute increments indicated on the scale.

Figure 1.

Formatting for indicating how many hours are spent on a given task in the UH NEAR Survey

Phase 3: Focus groups

The UH NEAR Survey was administered to parents of children aged 5–17 years (N = 9) to gain a better understanding of user perceptions of the survey. Participants were recruited from the patient population, faculty, and staff at the University of Houston and represented a wide socioeconomic range. Respondents were timed and asked a series of questions following the completion of the survey (Appendix 2). Questions were intentionally structured to encourage open-ended responses. Feedback from survey-takers was compiled, and the survey was modified accordingly as discussed in the results section.

Phase 4: Survey scoring

A scoresheet was developed to aid researchers and clinicians in calculating relevant metrics. Given that parents estimate time spent in various activities of their child separately for weekdays and for weekend days, the overall time spent in each activity across the entire week is calculated using the weighted equation (1):

$$\text{Mean}\text{daily}\text{behavior}\text{overall}=\left(\left(5*\text{mean}\text{of}\text{weekday}\text{hours}\right)+\left(2*\text{mean}\text{of}\text{weekend}\text{day}\text{hours}\right)\right)/7$$ Equation 3.

Time outdoors represents all of the time during the day that the child is exposed to sunlight, traditionally considered >1000 lux.³³ Therefore, time outdoors is calculated by adding the amount of time the child spends engaged in physical activity outdoors, leisure activity outdoors, and riding in a vehicle (during the daytime). Physical activity encompasses any sports or vigorous activity that the child may engage in, either indoors or outdoors, so is calculated by adding the amount of time the child spends engaged in outdoor and indoor physical activity.

In order to categorise viewing distances for various activities as “near” or “intermediate,” activities that were previously shown (using objective measures) to occur primarily between 10–50 cm were considered “near,” and included reading and writing on printed material and hand-held device use.^24,37 Questions were designed such that the effects of near work could be examined separately from screen time. Additionally, questions were designed to distinguish whether specific types of screen time are viewed at near (hand-held devices), intermediate (computers), or far (television and gaming consoles). With this in mind, various metrics can be calculated related to near work and/or screen time.

Time spent engaged in all near work is calculated by adding the amount of time the child spends reading and writing printed material as well as using hand-held devices. Time spent using all screens is calculated by adding the amount of time the child spends using hand-held devices, computers, and gaming consoles and watching television. A question regarding the amount of time children spent in fine arts (i.e. theater, orchestra, etc.) was removed since it did not factor into any of the scoring system categories.

An additional calculation provided on the score sheet is dioptre hours. Diopter hours is a weighted variable that takes into account the accommodative demand of each activity. Here, activities performed at certain distances were grouped together and multiplied them by the dioptric demand. Specifically, dioptre hours is calculated by adding the number of hours spent using hand-held devices and reading and writing printed material and multiplying by a factor of 3, plus the number of hours spent using a computer and playing cards and board games by a factor of 1.5. Multiplication factors were calculated by taking the inverse of the typical working distance (in meters) of the intended activity(ies), based on objective data.²⁴

Results

Validation of parent-reported refractive error status

Parents of children ages 11.6 ± 3.5 years participated (N = 109). As determined from the eye exams and electronic records, 51 children were myopic (average spherical equivalent refraction ≤0.50D), 45 were emmetropic (> − 0.50 D to ≤ +1.50 D), and 13 were hyperopic (> +1.50 D). Astigmatism (cylinder ≥ 0.50 D) was present in 79 children.

Parent responses (N = 109) are summarised in Tables 1 and 2 for the various methods of assessing whether a child has myopia or astigmatism. The method which procured the most amount of “do not know” responses for determining the presence of myopia was the direct method, followed by the lay terms method, and lastly by the indirect method. “Do not know” responses were not considered in the sensitivity and specificity analysis.

Table 1.

Parent responses (N = 109) to the refractive error survey. Presence of myopia was assessed by three different questionnaire methods, direct, lay terms, and indirect, and compared to eye exam outcomes

		Refractive Information from Eye Exam
		Myopic		Not myopic
Direct method	Yes	12		3
	No	17		19
	Do not know		58
Lay terms method	Yes	19		9
	No	7		19
	Do not know		55
Indirect method	Yes	41		27
	No	8		31
	Do not know		2

Table 2.

Parent responses (N = 109) to the astigmatism survey. Parents were asked if their child has astigmatism and answers were compared to eye exam outcomes

		Refractive Information from Eye Exam
		Astigmatism		No astigmatism
Parent Response	Yes	31		4
	No	17		13
	Do not know		44

For the direct method, 51 parents (46.8%) answered the question, “yes” or “no,” while 58 parents (53.2%) answered, “do not know.” For the lay terms method, 54 parents (49.5%) answered the question, “yes” or “no,” while 55 parents (50.5%) answered, “do not know.”

For the indirect method, 107 parents (98.2%) answered “yes” or “no” to whether their child wore glasses, while 2 parents (1.8%) answered “do not know.” Regarding the presence of astigmatism, 65 parents (59.6%) answered the question, “yes” or “no,” while 44 parents (40.4%) answered, “do not know.” For all questions, a “do not know” response could mean that the parent does not know either the meaning of the term or if their child has that condition.

Table 3 summarises sensitivity and specificity for each method. The highest sensitivity was obtained from the indirect method (0.84), and the lowest sensitivity was from the direct method (0.41). The highest specificity was obtained from the direct method (0.86), and the lowest specificity was from the indirect method (0.53). For the indirect method, twenty-seven parents (25%) answered as if their child was myopic when the child was not myopic (false positive), and 10 parents (9%) answered as if their child was non-myopic when the child was myopic (false negative).

Table 3.

Specificity and sensitivity for each method to determine the presence of myopia and astigmatism. Sensitivity and specificity were calculated only once the “do not know” responses were excluded.

	Sensitivity	Specificity	Do not know (%)
Direct method	0.41	0.86	53.2
Lay terms method	0.73	0.68	50.5
Indirect method	0.84	0.53	1.8
Astigmatism	0.65	0.76	40.4

Focus groups and finalising the survey

The finalised UH NEAR Survey is provided as Appendix 3, and the scoring template as Appendix 4. The average time for parents to complete the survey was 10:24 ± 2:38 minutes. All parents answered that their experience with the survey was “fine” or “good.” However, they expressed concerns that questions regarding near work and electronic device use were redundant. Parents also reported some difficulty in precisely quantifying their children’s activities, particularly with relation to time outdoors and electronic device use. Four parents noted confusion with questions relating to frequency of visual breaks during near work and absolute working distance during near work, and therefore, these two questions were subsequently removed from the final survey:

1. How often does your child take a visual break when doing long amounts of near work (i.e. looking out the window, etc)?

   1. Your child works < 30 minutes before taking a visual break
   2. Your child works >30 minutes before taking a visual break
2. How far away is your child when doing any form of near work (i.e. reading, using a phone, etc.)?

   1. Your child is usually at arms-length away or farther when doing near work
   2. Your child is usually closer than arms-length away when doing near work

Discussion

There is a need for a contemporary and easy-to-administer, standardized, myopia risk factor survey that can be utilized by both researchers and clinicians. This work describes the development of the University of Houston Near Work, Environment, Activities, and Refraction (UH NEAR) Survey, which was designed for use in determining risk factors for myopia in research and clinical settings.

The goals in developing this survey were to create a tool that can be administered easily to a large population with clear and unambiguous questions and reasonable time for completion. First, the most specific and sensitive questionnaire method for determining if a child is myopic was determined. Then, a battery of demographic and visual activity questions were compiled and refined to include relevant factors, suggested to be associated with myopia from previous literature. Important items to include were for the parent to identify whether their child is myopic, describe demographic factors, and quantify visual activity, including time spent outdoors, engaged in near work, and using electronic devices.³⁸ Lastly, a scoring system was developed so that researchers and clinicians can calculate metrics of interest.

In large epidemiological studies investigating risk factors for myopia, it is often not possible to examine the refractive status for each child. Therefore, it is important to determine the method with the best sensitivity and specificity for parents to answer whether their child is myopic. Three methods of asking parents whether their child is myopic, the direct method, lay terms method, and indirect method, were examined.

The indirect method was the most sensitive, although least specific method. The indirect method simply asks the parent if the child wears glasses, and if so, what age did they first receive them and are they for distance or near. It requires the least amount of knowledge regarding refractive terminology. Terms such as “nearsighted” or “myopia,” are avoided. This may explain the higher sensitivity compared to the direct and lay terms methods. However, the specificity was low with the indirect method. False positives might have occurred with the indirect method because for both hyperopes and high myopes with full-time spectacle wear, parents may not know if the glasses are specifically for distance or near vision. Additionally, some children who did not wear glasses simply had not been diagnosed before their exam as having a refractive error. Therefore, while the indirect method is highly sensitive, there were still a number of misclassifications, and its usefulness for subjects whose children who have never had an eye exam is limited.

The lay terms method had a higher sensitivity and a lower specificity than the direct method. However, it is important to note that approximately 50% of the surveys were not included in this analysis because parents answered “do not know” to the question. The lower sensitivity of the direct method was largely due to the high number of false negatives. Lack of public knowledge regarding the term “myopia” could account for the high amount of false negatives. Comparatively, while the term “nearsightedness” is more widely known by the public, the term is often misunderstood; this explains its higher, albeit still generally low, sensitivity.

A previous study found the direct method to have a higher “do not know” response rate than the lay terms method,²⁸ as the term “nearsightedness” is more familiar to individuals than “myopia.” However, here, findings show that the “do not know” response rates were similar between the two methods, both at approximately 50%. This suggests that parents are not well-informed about the refractive status of their children. Over half of all parents were unsure whether their child was myopic or nearsighted.

Second, findings suggest that confusion exists regarding the concept of nearsightedness. A modification which may improve sensitivity and specificity for the lay method is to simply include a short description of what nearsightedness means - “without glasses, your child sees blurry far away, such as when looking at the board at school or watching television, but clearly at near.”

Overall, data suggest that parent report of classifying refractive error is generally flawed. These findings bring into question the validity of previous studies which have relied solely on parent responses to categorise refractive error status. Of importance to note, if the UH NEAR Survey is utilised in conjunction with an eye exam, the concern of correctly classifying children by refractive error status is eliminated.

The value of the UH NEAR Survey will certainly increase if used along with a comprehensive eye exam including objective measures of cycloplegic refraction. When cycloplegic refraction is not possible, at least observing the spectacles of the child will improve the accuracy. However, if the only option is parent report, data suggest the indirect method to be superior. A modified version of the lay method, one which includes the description of nearsightedness, may be a reasonable alternative.

In choosing the specific demographic, ocular history, and visual activity questions to include in this survey, the body of literature was carefully examined to identify factors that have been shown to be associated with myopia, particularly considering the ubiquity of various types of electronic device use by children. Demographic factors included in the survey are age, sex, race, ethnicity, geographic location, type of community, type of housing, type of educational system, and grades.

As presented here, the demographic questions regarding school and grades largely apply to the education system in the United States. These questions should be tailored for the specific education system in the country in which the survey is being used. For ocular history, questions ask about parental myopia and the refractive status of the child. Parents are asked about myopia using the indirect method presented here. This survey may be used in research and clinical settings where the refractive status of the participant can be entered by the examiner, thus, eliminating classification errors.

Visual activity questions include estimations of time spent outdoors, engaged in physical activity, performing near work, and using electronic devices. Additionally, an estimation of sleep is included, as accumulating research indicates that sleep and diurnal rhythms are associated with eye growth and refraction.³⁹ Based on previous studies using subjective and objective measures to examine activity across the year, it is known that activities of children vary by day of the week and by time of year.¹⁴ Therefore, it was important to include these variables in the survey by asking parents to estimate activities on both weekdays and weekends, and for school sessions versus summer break. Care was taken to clearly separate outdoor time, i.e. exposure to sunlight regardless of the activity from physical activity, which may occur indoors or outdoors.

Additionally, questions and scoring are designed to distinguish between traditional near work on printed material versus near work on electronic devices, and electronic device use is further distinguishable between near (handheld devices),^25,40 intermediate (computers), and far (television). In recent years, there has been increased concern from parents and clinicians that electronic devices may be contributing to increasing myopia onset and progression. A recent systematic review and meta-analysis showed that smart device exposure might be associated with an increased risk of myopia.⁴¹ However, further research is needed to better understand if electronic devices with backlit screens are the contributing factor, or if the use of electronic devices is simply contributing to increased amount of near work. The goal of this work is to provide a tool that will better allow this distinction to be made, while still keeping the survey as concise as possible.

Focus groups were utilised to determine the time for parents to complete the survey and to obtain feedback regarding parent perceptions of the survey. Total time to take the survey was relatively short, taking approximately 10 minutes. Comprehensibility was good, although parent feedback highlighted some concerns, including a sense of redundancy, comprehension of visual breaks and continuous near work (removed from the final questionnaire), and inherent biases.

Visual breaks and continuous near work may be an important factors related to the influence of near work and myopia. However, parents were not able to reliably answer the questions and the results would most likely not be interpretable. These factors would be better assessed with continuously measuring wearable rangefinders once they become more widely available. While no questions are actually redundant, parents may have perceived redundancy because of the number of questions including different types of electronic device use. In order to distinguish whether electronic device use at near (handheld devices), intermediate (computers), and far (television), it was necessary to include separate questions for these devices.

It may be of benefit to better explain the purpose of the study and various questions to the parent beforehand to alleviate the impression of redundancy and help parents understand how to report the various near work activities of their child. However, it may not always be possible to provide parents with a thorough explanation.

Despite the care taken to develop the UH NEAR Survey, the following limitations should be considered. Questionnaires inherently suffer from recall and parent biases. In order to improve accuracy and reduce parent bias, it is advisable for parents to answer the survey along with input from their children when possible. However, parent-proxy report for children ages 2–16 years has been shown to exceed a minimum internal consistency reliability standard of 0.70 and remains a fundamental method for pediatric health-related research.⁴²

The survey asks parents to estimate activities while their children are outside of school, so activities during school hours are unaccounted for. While it might be assumed that all children have similar amounts of near work and outdoor time during the school day, this is likely not the case. Future studies should aim to characterise activities during the school day, perhaps by employing objective wearable sensors.

Another limitation is that achieving perfect precision or accuracy with a survey is not possible. The most complete method to characterise the near work profile of a child is likely a combination of subjective and objective methods of data collection.

Conclusion

This study aimed to create a visual activity questionnaire that can be widely used in research and clinical applications to assess and quantify risk factors for myopia. The UH NEAR Survey is novel in that the specific questions and the provided scoring system allow researchers and clinicians to easily quantify behaviors across a variety of distinct categories: outdoor time, physical activity, near work, electronic device use, and sleep. Specifically, the nature of the scoring system allows, for example, not just quantification of near work in general, but the distinction between handheld electronic device use and printed near work.

Similarly, physical activity can be quantified based on outdoor versus indoor physical activity. This is achieved with the inclusion of only 11 different questions, which target the most relevant known risk factors for myopia. While the survey could be used as a simple 11-item survey, it is presented here as a 44-item survey, as the literature shows that visual activity of children is significantly different for weekdays and weekend days, and for school sessions and summer break.^13,14 Therefore, parents are asked to answer the same 11 questions for 4 different times of the year.

The UH NEAR Survey is based on the current understanding of myopiagenesis. It is expected that this survey will evolve and improve with input from users and as potential new risk factors that have not yet been identified become relevant. The UH NEAR Survey utilises a proxy design, given young children may not fully grasp the magnitude of their visual behaviors. Asking older children to self-report, though, may improve accuracy and precision of subjective responses.

The greatest strength of the UH NEAR Survey will come from its use in longitudinal studies and pairing it with objective wearable sensors to precisely quantify light exposure, near work, physical activity, and sleep, along with a comprehensive eye exam including cycloplegic refractive measurement. To improve independent validity of the survey, future studies may focus on psychometric analysis and validation of the survey itself, such as Rasch measurement models.

Appendix 1. Children’s Refractive Error Survey

Appendix 2.

Questions asked during the focus groups

1. What was your experience with the survey?

2. Which questions in the survey, if any, did you feel were not needed? Why?

3. Which questions in the survey, if any, did you feel were poorly worded, or hard to understand? What would you change for those questions?

4. Do you feel this survey accurately measured how much near work you do on a regular basis? If not, how can the survey be modified to better measure your day’s near work?

5. Do you feel this survey accurately represented how much time you spend indoors and outdoors? If not, how can the survey be modified to better represent your time indoors or outdoors?

6. What additional questions, comments, or suggestions do you have?

Appendix 3. UH NEAR Survey

UH NEAR Survey for Children

Please estimate and mark the number of hours PER DAY your child spends involved in these various activities DURING THE SCHOOL YEAR, when your child is NOT in school, on a typical school weekday (Monday-Friday) and a typical school weekend day (Saturday-Sunday) For example, if your child spends 3 hours on a weekday and 2.5 hours on a weekend day doing an activity, please mark it like this:

Please estimate and mark the number of hours PER DAY your child spends involved in these various activities DURING THE SUMMER for a typical weekday (Monday-Friday) and a typical weekend day (Saturday-Sunday)

Appendix 4. Scoring system for the UH NEAR Survey to quantify visual activity