Abstract
-
Purpose
This study explored the threat and efficacy factors influencing children’s eye health behaviors using an Extended Parallel Process Model for parents of preschool children.
-
Methods
Data were collected from October 30 to November 6, 2023, using a web-based survey. In total, 166 parents of preschool children participated in this cross-sectional study. Data were analyzed using Pearson’s correlation coefficients and multiple regression analyses. Parents’ eye health knowledge, eye health threat factors (perceived severity and susceptibility), and eye health efficacy factors (self-efficacy and response efficacy) related to preschoolers were measured. Eye health behavior was assessed by observing the children’s behavior over the past week.
-
Results
The eye health behaviors of preschool children were positively correlated with their parents’ eye health knowledge (r=.21, p=.006), perceived severity (r=.22, p=.004), response efficacy (r=.36, p<.001), and self-efficacy (r=.64, p<.001). Children’s eye health behavior showed a negative correlation with perceived susceptibility (r=-.27, p<.001). As seen on multiple regression analysis, the factor influencing children’s eye health behavior was self-efficacy (β=.57, p<.001), and the model’s explanatory power was approximately 43% (F=24.09, p<.001).
-
Conclusion
To promote eye health behavior in preschool children, it is necessary to strengthen the self-efficacy of parents. The results of this study can be used to develop eye health programs for preschool children and their parents.
-
Key words: Eye; Health behavior; Preschool child; Self-efficacy
INTRODUCTION
There are approximately 19 million children with vision impairment worldwide, eye health problems in children are an important issue, as they can cause numerous problems in adulthood [
1]. In South Korea, 645,488 children aged 0–9 years were diagnosed with refractive and accommodative disorders in 2021, making them the second most prevalent group after children aged 10–19 years [
2], and the prevalence increased as they entered school (4.8% compared to 2019) [
3]. This suggests that if eye health interventions are not actively implemented during the preschool years, more serious eye problems may arise as children reach school age. Since the COVID-19 (coronavirus disease 2019) pandemic, preschool children have been spending more time indoors, which has increased their screen time: TV, computers, and smartphones [
4]. Time spent using electronic devices, viewing posture, viewing distance from screens, unbalanced diets, and time spent outdoors are factors that affect the eye health of preschool children [
5].
The preschool years are a critical period for vision development [
6] and an opportune time to form eye health habits that can have lifelong implications [
7]. Children’s vision reaches adult levels around the age of 5 to 6 years [
8], if normal vision development does not occur till then, it can cause more serious problems later in childhood, resulting in irreversible vision loss [
9]. Poor vision in the preschool years can lead to poor concentration and learning difficulties, which can significantly impact growth and development in subsequent years [
6].
Because of preschoolers’ language and cognitive development, they understand simple concepts and have a partial understanding of cause and effect, which allows them to avoid behaviors labeled dangerous. Therefore, as long as parents warn their children about behaviors that threaten eye health and encourage them to engage in eye health-promoting behaviors, they can lead to positive changes in preschoolers’ eye health behaviors. Since parents significantly influence children [
10] and smartphone and electronic device use primarily occurs at home, it can be said that parents have a significant impact on children’s eye health behaviors.
Parents’ knowledge and perception of eye health are important factors influencing children’s eye health behaviors [
11]. When parents have misinformation about children’s eye health, children’s eye health problems can be overlooked [
12]. In addition, parents’ perceptions of threat factors, such as prolonged media viewing and risk perception of eye problem symptoms, affect children’s screen time and eye care behaviors [
13]. One factor that directly influences children’s health behaviors is parental self-efficacy. Self-efficacy is an individual's belief in their ability to successfully accomplish a task in a particular situation [
14]. Previous studies have shown that higher levels of self-efficacy in parents are associated with healthier behaviors in their children [
15].
Existing studies on children’s eye health have mainly focused on parents’ knowledge and perceptions regarding eye screening examinations or relevance to screen time exposure [
16]. However, these studies often lack an integrated analysis that incorporates child behavior change and psychological factors such as self-efficacy and threat perception. The Extended Parallel Process Model (EPPM) by Witte [
17] offers a comprehensive framework that accounts for both cognitive and psychological factors influencing health-related behaviors. This model predicts individual attitudes or behavioral responses to health messages based on two key components: perceived threat and efficacy [
18]. Although EPPM was initially applied to feared disease prevention efforts, such as acquired immunodeficiency syndrome [
19], its use has recently expanded to health promotion contexts, such as encouraging dental visits [
20] and breast cancer prevention [
21]. For instance, Askelson et al. [
20] applied the EPPM to identify factors for parents’ decisions to seek preventive dental care for their children, concluding that the model is well-suited to understanding parental motivations in early childhood health decisions. Given its broad applicability, the EPPM provides a valuable theoretical framework for examining how parents influence eye health behaviors in preschool children. Moreover, it enables the exploration of how perceived threat and efficacy among parents shape actions related to their children’s eye health.
Witte and Allen [
19] found that behavioral change occurs when individuals respond to fear messages with a high perceived threat and high efficacy of recommended behavior. Applying the EPPM to this study, when parents have high threat perception and high efficacy in response to messages about their children’s eye health, they recognize the threat and engage in active threat-control behaviors. However, if they have a low threat perception or low efficacy, they may not acknowledge the threat and take no action, or they may feel fearful but ignore their health concerns. This study was conducted to examine parents’ perceived threat and efficacy levels regarding their children’s eye health and to explore how these factors influence children’s eye health behaviors (
Figure 1).
This study is the second step of the “Study on the development and effectiveness of eye health promotion programs for preschool children,” and the questionnaire was constructed based on the primary research, which is a literature review and focus group interview study [
22]. The EPPM by Witte [
17] was used as the theoretical framework to examine the effects of parents’ perceived threats and efficacy on children’s eye health behaviors. The results will be used as a basis for developing a parental education intervention to promote eye health behaviors in preschool children.
This study was conducted among parents of preschool children to identify factors influencing eye health behaviors. The objectives of this study were: (1) To compare differences in eye health behaviors of preschool children according to parents’ and children’s general characteristics; (2) To identify the relationships among parents’ eye health knowledge, perceived threats, perceived efficacy, and preschool children’s eye health behaviors; and (3) To identify the effects of parents’ eye health knowledge, perceived threat, and perceived efficacy on preschool children’s eye health behaviors.
METHODS
Ethical statements: This study was approved by the Institutional Review Board (IRB) of a Woosong university (IRB No., 1041549-231010-SB-176). Informed consent was obtained from all participants.
1. Study Design
This descriptive survey study aimed to identify factors influencing preschool children’s eye health behaviors. This study followed the guidelines outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [
23].
The theoretical framework of this study is the EPPM of Witte [
17], which is measured by including variables related to preschool children’s eye health.
According to this model, an individual exposed to messages first evaluates the seriousness of the threat. If the individual perceives the threat as significant, they are more likely to seek or process additional information about it. This threat recognition can lead to fear, which then prompts the individual to evaluate their own efficacy in responding to the threat [
17]. Based on this efficacy assessment, if the individual recognizes that they possess sufficient efficacy to avoid threats, they engage in the threat control process. Finally, they accept the message and change their behavior [
17].
EPPM incorporates both cognitive and emotional factors, such as fear, and recognizes that information provision may be part of the message component [
24]. Therefore, in this study, eye health knowledge was measured as a message component to determine whether parents were aware of the symptoms and management of children’s eye health. Perceived threat comprises perceived severity and susceptibility. Perceived severity is an individual’s perception of the extent of harm when the negative consequences of a threat occur, and perceived susceptibility is the perception of the likelihood of encountering issues [
17]. In this study, the perceived severity measured how seriously parents were aware of children’s eye health hazards. Perceived susceptibility was measured how sensitive parents are to the occurrence of eye health problems in their children. Perceived efficacy comprises self-efficacy and response efficacy. Self-efficacy refers to individual’s belief in their capability to engage in behaviors to prevent threats, whereas response efficacy refers to individual’s perception of the usefulness of behaviors [
17]. In this study, the self-efficacy was measured by the parents’ belief that they could discipline children to engage in eye health behavior. Response efficacy was measured by parents’ belief that disciplining children to engage in eye health behavior is beneficial to eye health. Behavioral changes measured changes in children’s eye health behaviors (
Figure 1).
The participants in this study were parents raising children aged 3 to 6 years who were able to read and write Korean and are agreed to participate in an online survey. The study was conducted as a web survey using an online questionnaire. The number of participants was calculated using G*power ver. 3.1.9.2 (Heinrich-Heine-Universität Düsseldorf) with a significance level of α=.05, medium effect size of .15, and power (1–β)=.80, based on prior studies that used regression analysis [
25], resulting in a number of 146 participants. Considering a dropout rate of 10%, 163 parents were recruited as study participants.
The measurement tools were selected in consultation with a professor of pediatric nursing and reviewed by a PhD (Doctor of Philosophy) in child nursing to ensure the appropriateness of their wording and content. Moreover, the original English instruments were translated into Korean by the author and another researcher. To ensure semantic equivalence, the Korean versions were back-translated by international nursing students fluent in both English and Korean.
1) Eye health knowledge
Eye health knowledge was measured using a tool developed by Shin and Oh [
26] for eye health in elementary school students and modified to be relevant to preschool children. A sample question is as follows: “What kind of glasses do you wear when your eyes are nearsighted?” Each correct response scored 1 point, whereas an incorrect response scored 0 points. The tool comprises 10 items on eye structure and abnormalities, six items on vision development and care, and nine items on vision protection and eye infection prevention, totaling 25 items. A higher score indicates a greater level of knowledge. The Cronbach’s α was 0.77 in the study by Shin and Oh [
26], and it was 0.63 in this study.
2) Perceived threat
(1) Perceived severity
Perceived severity was measured by modifying three items concerning perceived severity using the Eye Health Beliefs tool by Liu et al. [
27]. Perceived severity measured the extent to which respondents agreed with statements such as “I think it is a serious problem for children to develop myopia early due to the frequent use of electronic devices (smartphones, TV tablets, and other electronic devices).” Each item is scored on a 5-point scale ranging from strongly disagree to strongly agree, with higher scores indicating greater perceived severity. The Cronbach’s α was 0.86 in the study by Liu et al. [
27] and 0.90 in this study.
(2) Perceived susceptibility
Perceived susceptibility was measured by modifying the ‘eye health problem’ tool by Shin and Oh [
26]. It consists of 12 items, including options such as “My child is irritable because of eye discomfort.” Each item was scored on a scale from 1 (strongly disagree) to 4 (agree), with higher scores indicating more frequent recognition of eye abnormality symptoms by the child. Cronbach’s α was 0.87 in the study by Shin and Oh [
26] and 0.92 in this study.
3) Perceived efficacy
(1) Self-efficacy
Self-efficacy was measured by modifying the Eye Health Self-Efficacy tool by Liu et al. [
27]. The tool comprises 11 items, including “I can ensure that my child maintains an appropriate distance when using electronic devices. A five-point scale ranging from strongly disagree (1) to strongly agree (5) was used for each statement. Higher scores indicated higher self-efficacy in eye health behaviors. The Cronbach’s α was 0.83 in the study by Liu et al. [
27] and 0.87 in this study.
(2) Response efficacy
The perceived benefit item was modified from the Eye Health Beliefs tool by Liu et al. [
27]. It consists of six items, such as, “I believe that limiting my child’s use of electronic devices to 1 hour or less per day will help my child’s vision management.” This was measured according to the degree of agreement with each item on a scale of 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating higher response efficacy. The Cronbach’s α was 0.86 in the study by Liu et al. [
27] and 0.83 in this study.
4) Eye health behavior
Parents assessed eye health behaviors by observing the preschool children’s eye health behaviors during the previous week. The behaviors were measured using the modified Eye Health Behavior tool by Lee et al. [
5]. This tool comprises questions such as “When I look at my smartphone, I look at it from a distance of more than 30 centimeters.” It includes 18 questions on lifestyle activities that support eye health, eye care, eye infections, and trauma prevention. Each question is evaluated on a 4-point Likert-type scale (1=strongly disagree, 2=disagree, 3=agree, and 4=strongly agree). Higher scores indicate better eye health behaviors. The Cronbach’s α was 0.76 in the study by Lee et al. [
5] and 0.80 in this study.
The survey was conducted by a professional research company and conducted using a web-based online survey from October 30th to November 6th in 2023. Participants were recruited through an online announcement distributed to the company’s nationwide panel. Only those who provided consent to participate in the study at the beginning of the online questionnaire were surveyed. The time required to complete the questionnaire was approximately 15 to 20 minutes.
An explanation of the study was provided at the beginning of the online questionnaire given to the participants, including the purpose of the study, confidentiality, autonomy, and the possibility of withdrawal, and how personal information would be managed. Only those who indicated their consent to participate in the study began the survey. The explanation stated that even if the participants consented to participate in the study, they could stop and withdraw at any time they wish.
6. Data Analysis
The collecting data were analyzed using IBM SPSS/WIN ver. 24.0 (IBM Corp.). The general characteristics of the participants were analyzed using real numbers and percentages. Differences in eye health behaviors based on general characteristics were analyzed using an independent t-test with analysis of variance, and post-hoc tests were conducted using the Scheffé test. The eye health knowledge, perceived severity, perceived susceptibility, self-efficacy, response efficacy, and eye health behaviors of preschool children’s parents were analyzed using means and standard deviations. The correlation between each variable was calculated using Pearson’s correlation coefficient. Multiple regression analysis was used to analyze the factors influencing the participants’ eye health behaviors.
RESULTS
1. General Characteristics and Differences in Eye Health Behaviors
The participants in this study were parents with children aged 3–6 years, comprising 89 female (53.6%) and 77 male (46.4%) parents. The mean age of the parents was 39.39±4.63 years, and the majority of parents had a college degree or higher (95.8%). The usage status of eyeglasses was 76 (45.8%) for fathers and 78 (47.0%) for mothers. Among the children, 85 were girls (51.2%) and 81 were boys (48.8%), with 11 children wearing eyeglasses (6.6%). The number of children who had undergone eye examination was 106 (63.9%). Not all the differences in eye health behaviors based on the general characteristics of parents and children were statistically significant (
Table 1).
Children spent the most time on electronics on the weekdays, with 68 children (41.0%) spending 1–2 hours per day, while 61 (36.8%) spent more than 2 hours per day. Three hours or more was the most common, with 64 children (38.6%) during weekends. While viewing their smartphones, 88 children (53.0%) held their device in an upright position on a table, 62 (37.3%) held it in their hands, and 16 (9.6%) viewed it while lying down. When looking at a smartphone, the distance between the eyes and the smartphone was between 15 and 30 centimeters, with 108 participants (65.1%) reporting this distance and 39 (23.5%) reporting more than 30 centimeters (
Table 1).
The mean score of the participants’ eye health knowledge was 16.62±2.67, with 66.48% correct answers. The mean scores for perceived severity were 13.52±1.87, perceived susceptibility was 21.66±7.02, self-efficacy was 40.80±6.74, response efficacy was 26.19±3.32, and eye health behaviors were 54.36±6.38 (
Table 2).
Eye health behaviors were positively correlated with eye health knowledge (r=.21,
p=.006) and perceived severity (r=.22,
p=.004), respectively. Additionally, they were positively correlated with self-efficacy (r=.64,
p<.001) and response efficacy (r=.36,
p<.001), respectively. Eye health behaviors were negatively correlated with perceived susceptibility (r=–.27,
p<.001) (
Table 3).
A multiple regression analysis was conducted using the variables of parents’ eye health knowledge, perceived severity, perceived susceptibility, response efficacy, and self-efficacy as factors influencing eye health behaviors. As a result of the Shapiro-Wilk test of major variables-eye health knowledge, self-efficacy, and eye health behaviors-showed normality at the significance level of .05. Additionally, Mardia’s test for multivariate normality indicated that the assumption of multivariate normality was satisfied. The tolerance limits ranged from .48 to .93, which is greater than 0.1 when multicollinearity among the independent variables was checked, and the variance inflation factor ranged from 1.07 to 2.10, which is not greater than 10; therefore, no multicollinearity issues were found. The multiple linear regression analysis showed that self-efficacy (β=.57,
p<.001) was the factor that influencing eye health behavior, and the model had an explanatory power of approximately 43% (F=24.09,
p<.001) (
Table 4).
DISCUSSION
The duration and frequency of smartphone and tablet use among children have increased in recent years, leading to several eye health problems. Eye health problems in children are an important health issue because they can negatively affect a child’s growth and development and are preventable. Therefore, this study aimed to examine parents’ knowledge, threats, and perceived efficacy of eye health in relation to preschool children, and determine their impact on preschoolers’ eye health behaviors.
The main results are: the average weekday screen time for children was 1.46 hours per day. The largest group (41%) of children had 1–2 hours of screen time per day. However, 36.8% of the children exceeded 2 hours of screen time daily. Screen time was even higher on weekends than weekdays, with an average of 2.41 hours per day, and 38.6% of children spent over 3 hours a day, which is becoming increasingly concerning. This exceeds the American Academy of Pediatrics’ recommendation of 2 hours of screen time [
28], suggesting that active interventions are needed to reduce screen time among Korean children. Furthermore, 46.9% of Korean children used their smartphones in a posture that is either handheld, head down, or lying down. Poor posture while looking at a smartphone increases the risk of musculoskeletal disorders [
29] and increases the risk of myopia owing to difficulty in maintaining the appropriate distance between the smartphone and the eyes [
30]. Even a distance between the smartphone and eye is recommended at least 30 cm [
31]. However, the majority, 65.1%, view their smartphone at a distance of 15–30 centimeters. Only 23.5% maintained a distance of more than 30 centimeters. Prolonged smartphone viewing at close range can increase eye strain and cause myopia [
30]. This study is significant because it identifies the current eye health behaviors of preschool children in Korea and suggests the need for active interventions to establish good eye health habits from preschool age.
There were no statistically significant differences in eye health behaviors based on the general characteristics of preschoolers. In a study of children aged under 2 years, Goh et al. [
10] found differences in screen viewing based on the child’s age and mother’s education. The higher the child’s age and the lower the mother’s education level, the longer the child’s screen time and the more electronic devices used in the study. In a study of preschool children, Määttä et al. [
32] found that children’s screen time varied based on parents’ education level. The children in this study were 3–6 years old. In contrast, a study by Goh et al. [
10] found that 90% of children aged 18–24 months already spend an average of 1.5 hours per day viewing screens. This study was conducted among children aged 3–6 years, and since children over the age of 3 are already familiar with using smartphones and tablets [
4], it is unlikely that there is a significant difference with increasing age. In addition, because the parents’ education levels were very high, with 95% of parents having at least a college degree in this study, there were no differences based on parents’ education.
Preschool children’s eye health behaviors were positively associated with parents’ eye health knowledge, perceived severity, perceived efficacy, and response efficacy. Parents’ eye health knowledge is a major factor that influences children’s eye health behaviors. Goh et al. [
10] also found that higher parental knowledge of screen-viewing recommendations was associated with shorter screen time and improved eye health behaviors in children. When parents lack knowledge about children's eye health, they may overlook eye health problems or take inappropriate actions [
12]. As preschool years are a critical time for vision development [
6], it is crucial for parents to gain knowledge to ensure their children’s healthy development.
Parents’ perceived severity is also a factor associated with their children’s eye health behaviors. The higher the risk perception that parents have about the harmfulness of their child’s eye health risk factors, the more they promote eye health behaviors in children through active interventions. Moreover, perceived efficacy is a key factor that directly influences behavioral change. In a study of fifth-grade children and their parents, Chang et al. [
13] reported that higher parental risk perception and self-efficacy for children’s eye health were associated with less screen time and higher levels of eye care behavior. Parents with high self-efficacy set rules and limits on when and how their children use electronics to guide them to engage in eye health behaviors [
33]. In particular, promoting eye health behaviors in children during the preschool years is necessary for parents to control their children’s inappropriate behaviors and guide them toward desirable behaviors [
34]. Response efficacy is the perception of how eye health behaviors are beneficial in preventing eye health problems and provide motivation to change behavior [
17]. Parents with higher perceived severity and response efficacy are more active in their children’s eye care and report higher rates of eye care visits [
12].
However, children’s eye health behaviors were negatively correlated with their parents’ perceived susceptibility. Parents’ perceived susceptibility is believed to promote parents’ eye health behaviors, such as early detection of eye health abnormalities in children, prompting them to seek eye examinations and treatment [
12]. This study examined children’s eye health behaviors but not parents’ eye health behaviors, and perceived susceptibility was measured based on parents’ perceptions of their children’s eye-related symptoms. Therefore, children with lower eye health behaviors may have higher perceived susceptibility because their parents observed their child’s behavior, such as ‘rubbing eyes often,’ more frequently. In addition, it is possible that children’s eye health conditions make it difficult for them to engage in healthy behaviors such as looking away from electronics.
Future research should replicate this study while including additional variables, such as the presence of eye diseases in children and parental eye health behaviors.
As a result of the regression analysis, that parents’ self-efficacy was identified as the predisposing factor that directly influenced eye health behaviors in preschool children, with a model explanatory power of 43%. Parental self-efficacy is a key factor that influences preschool children and is strongly associated with healthy growth, development, and physical health outcomes [
15]. However, parental knowledge, perceived severity, and response efficacy were not statistically significant antecedents of their children’s eye health behaviors. To elicit positive eye health behaviors in children requires the ability to discipline them to control misbehavior and elicit positive behaviors [
34]. While parents may have knowledge of eye health, perception of threats, and perception that eye health behaviors are useful, this may not result in the desired behavior change in their children.
Askelson at al. [
35] classified parents of preschool children enrolled in Medicaid into four types based on the EPPM, according to whether the threat and efficacy factors were high and low. Among these groups, parents with low threat and high efficacy, high threat and high efficacy were 2.5 times more likely to ensure preventive dental visits compared to those who did not [
35]. They concluded that parental efficacy was the most critical factor influencing the preventive care of children, which aligns with the findings of this study. Other research grounded in the EPPM framework has identified parental’ perceptions of their children’s dental issue severity and their own self-efficacy as key antecedents for deciding to seek preventive dental care [
20]. In the current study, most preschool children were healthy and did not exhibit sufficient eye health concerns to warrant medical visits. As such, parents’ perceived severity, perceived susceptibility, and response efficacy regarding eye health problems were relatively low and likely did not significantly influence their children’s behavioral changes.
Jago et al. [
34] stated that parental control is essential for promoting eye health behaviors in preschool children and that higher parental self-efficacy is associated with improved eye health behaviors in preschool children. Therefore, the development of strategies to increase parents’ self-efficacy would be useful in limiting eye health behaviors, especially screen time, in preschool children. In the future, parent intervention programs that comprehensively address children’s screen time and posture while using electronics, dietary habits, and eye trauma prevention are needed to improve parents’ self-efficacy.
This study is significant in that it applied the EPPM as a theoretical framework to improve the eye health behavior of preschool children. Moreover, it demonstrated that parental perception can be categorized into threat and efficacy components. This theory, previously used mainly in the context of adult-centered, fear-inducing diseases, has now proven to be applicable in the field of child health promotion. In addition, while previous studies examined localized eye health behaviors, such as eye examinations or screen time, as dependent variables, this study differs from previous studies in that it measured the eye health behaviors of preschool children, including screen time, posture while using electronic devices, dietary habits, and prevention of eye trauma, as dependent variables. The results of this study can be used as a basis for developing intervention programs for parents to promote eye health behaviors among preschool children.
This study had a few limitations. This study did not measure changes in parental behavior, and the study design made it difficult to identify contextual relationships between the independent variables. In addition, this study has limitations in terms of external validity and representativeness of the sample. Participants were recruited through convenience sampling via an online survey platform, which may not reflect the broader population. It is necessary to elaborate on the study design in the future and examine the contextual relationships between independent variables.
CONCLUSION
This study identified the parental factors that affect eye health behaviors in preschool children based on the EPPM by Witte [
17]. The factor influencing eye health behaviors in preschool children was parental self-efficacy. In the future, in order to promote the eye health behaviors of preschool children, interventions that can enhance parents’ efficacy factors are needed, and EPPM can be used as a theoretical basis for intervention development. Potential approaches include encouraging early screening for children’s eye health, educating parents about risk factors, and national campaigns promoting healthy eye care habits. Also, it is necessary to develop parental intervention programs, including methods to guide children’s practical eye health behavior. This study could be used as basic data for the development of children’s eye health intervention programs.
ARTICLE INFORMATION
Figure 1.
Table 1.General characteristics and differences in eye health behaviors (N=166)
|
Characteristic |
No. (%) |
Eye health behavior |
|
Mean±SD |
t or F (p) |
|
Parent (n=166) |
|
|
|
|
Sex |
|
|
1.58 (.117) |
|
Female |
89 (53.6) |
55.08±6.52 |
|
|
Male |
77 (46.4) |
53.52±6.15 |
|
|
Age (yr) |
|
|
0.63 (.535) |
|
30–39 |
86 (51.8) |
54.78±5.95 |
|
|
40–49 |
75 (45.2) |
53.77±6.87 |
|
|
≥50 |
5 (3.0) |
55.80±6.26 |
|
|
Education level |
|
|
0.95 (.438) |
|
High school |
7 (4.2) |
51.14±5.43 |
|
|
College |
27 (16.3) |
53.41±6.05 |
|
|
University (<3 yr) |
9 (5.4) |
52.89±5.56 |
|
|
University (<4 yr) |
96 (57.8) |
54.72±6.33 |
|
|
Graduate |
27 (16.3) |
55.33±7.29 |
|
|
Wearing glasses |
|
|
|
|
Father |
|
|
0.32 (.752) |
|
Yes |
76 (45.8) |
54.18±6.73 |
|
|
No |
90 (54.2) |
54.50±6.10 |
|
|
Mother |
|
|
0.32 (.747) |
|
Yes |
78 (47.0) |
54.53±6.88 |
|
|
No |
88 (53.0) |
54.20±5.93 |
|
|
Child (n=166) |
|
|
|
|
Sex |
|
|
0.66 (.509) |
|
Female |
85 (51.2) |
54.04±6.43 |
|
|
Male |
81 (48.8) |
54.69±6.35 |
|
|
Age (yr) |
|
|
1.15 (.332) |
|
3 |
44 (26.5) |
54.39(6.00) |
|
|
4 |
42 (25.3) |
53.43(5.58) |
|
|
5 |
42 (25.3) |
55.81(7.58) |
|
|
6 |
38 (22.9) |
53.74(6.13) |
|
|
Wearing glasses |
|
|
1.52 (.131) |
|
Yes |
11 (6.6) |
51.55±7.47 |
|
|
No |
155 (93.4) |
54.55±6.27 |
|
|
Experience of eye exam |
|
|
1.20 (.20) |
|
Yes |
106 (63.9) |
54.80±6.89 |
|
|
No |
60 (36.1) |
53.57±5.32 |
|
|
Hours watching electro device (hr) |
|
|
|
|
Week days |
|
1.46±0.92 |
1.58 (.196) |
|
<1 |
37 (22.3) |
56.08±6.17 |
|
|
1–<2 |
68 (41.0) |
54.43±6.13 |
|
|
2–<3 |
37 (22.3) |
53.05±6.28 |
|
|
≥3 |
24 (14.5) |
53.50±7.27 |
|
|
Weekend |
|
2.41±1.39 |
3.69 (.013)* |
|
<1a
|
17 (10.2) |
57.00±5.98 |
a,b,c>d |
|
1–<2b
|
35 (21.1) |
55.89±5.50 |
|
|
2–<3c
|
50 (30.1) |
54.76±6.45 |
|
|
≥3d
|
64 (38.6) |
52.50±6.48 |
|
|
Posture when looking smartphone |
|
|
16.97 (<.001)** |
|
Sitting with it on the tablea
|
88 (53.0) |
56.75±6.01 |
a>b,c |
|
Sitting with it in one’s handb
|
62 (37.3) |
52.18±5.77 |
|
|
Lying positionc
|
16 (9.6) |
49.63±5.06 |
|
|
Distance between eye & smartphone (cm) |
|
|
6.56 (.002)** |
|
<15a
|
19 (11.4) |
51.68±6.68 |
a,b>c |
|
15–<30b
|
108 (65.1) |
53.78±5.97 |
|
|
≥30c
|
39 (23.5) |
57.26±6.48 |
|
Table 2.Descriptive statistic for eye health knowledge, perceived threat & efficacy, and eye health behavior (N=166)
|
Variable |
Mean±SD (correct answer rate %) |
Min–max |
Possible range |
|
Eye health knowledge |
16.62±2.67 (66.48) |
9–23 |
0–25 |
|
Perceived threat |
|
|
|
|
Perceived severity |
13.52±1.87 |
7–15 |
3–15 |
|
Perceived susceptibility |
21.66±7.02 |
12–40 |
12–60 |
|
Perceived efficacy |
|
|
|
|
Self-efficacy |
40.80±6.74 |
23–55 |
11–55 |
|
Response efficacy |
26.19±3.32 |
17–30 |
6–30 |
|
Eye health behavior |
54.36±6.38 |
40–71 |
18–72 |
Table 3.Correlations between eye health knowledge, perceived threat & efficacy, and eye health behavior (N=166)
|
Variable |
Eye health knowledge |
Perceived severity |
Perceived susceptibility |
Self-efficacy |
Response efficacy |
Eye health behavior |
|
Eye health knowledge |
1 |
|
|
|
|
|
|
Perceived severity |
0.17 (.026) |
1 |
|
|
|
|
|
Perceived susceptibility |
–0.13 (.108) |
–0.18 (.017) |
1 |
|
|
|
|
Self-efficacy |
0.16 (.042) |
0.30 (<.001) |
–0.32 (<.001) |
1 |
|
|
|
Response efficacy |
0.24 (.002) |
0.68 (<.001) |
–0.18 (.019) |
0.43 (<.001) |
1 |
|
|
Eye health behavior |
0.21 (.006) |
0.22 (.004) |
–0.27 (<.001) |
0.64 (<.001) |
0.36 (<.001) |
1 |
Table 4.Multiple regression on eye health behavior (N=166)
|
Variable |
B |
SE |
β |
t |
p
|
VIF |
|
Eye health knowledge |
0.23 |
0.15 |
0.10 |
1.54 |
.125 |
1.070 |
|
Perceived severity |
–0.17 |
0.28 |
–0.05 |
–0.61 |
.543 |
1.852 |
|
Perceived susceptibility |
–0.06 |
0.06 |
–0.07 |
–1.03 |
.306 |
1.130 |
|
Self-efficacy |
0.54 |
0.07 |
0.57 |
8.27 |
<.001 |
1.328 |
|
Response efficacy |
0.21 |
0.17 |
0.11 |
1.28 |
.204 |
2.101 |
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