Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-23T05:27:32.094Z Has data issue: false hasContentIssue false

Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress

Published online by Cambridge University Press:  16 August 2023

Fong-Ching Chang*
Affiliation:
Department of Health Promotion and Health Education, National Taiwan Normal University, Taipei, Taiwan
Chingching Chang
Affiliation:
Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan
Chen-Chao Tao
Affiliation:
Department of Communication and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
*
Corresponding author: Fong-Ching Chang; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

COVID-19 has led to an increase in mental health problems for adolescents. In this study, we examined the factors related to the eHealth literacy of adolescents and how that impacted their pursuit of health information and mental health information online during the COVID-19 pandemic. We analyzed data from the 2020 Taiwan Communication Survey, which involved a total of 1,250 national representative adolescents who completed an online questionnaire. The results showed that two-thirds of adolescents reported searching for health information online, and about half of them reported searching for mental health information online during the COVID-19 pandemic. Multivariate analysis results indicated that adolescents who spent more time learning online, had higher levels of bonding social capital and self-determination, and had higher levels of parental active internet mediation were more likely to have higher levels of eHealth literacy. In addition, multivariate analysis results showed that adolescents who had higher levels of eHealth literacy and had higher depression and anxiety were more likely to seek health information and mental health information online. In conclusion, the levels of eHealth literacy and psychological distress of adolescents played a crucial role in their pursuit of health information and mental health information online during the COVID-19 pandemic.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Impact statement

Adolescents are showing an increase in vulnerability to mental health illness, and studies have documented an increase in psychological distress among adolescents during the COVID-19 pandemic. Adolescents spent more time online, and their pursuit of mental health information online has facilitated their autonomy to control their help-seeking journey and allow them to connect with others with more privacy and less stigma. The abundance of misinformation online, however, particularly during the COVID-19 outbreak, has enhanced the need for eHealth literacy in seeking health information online, appraising health information, making healthy decisions and implementing protective behaviors. This study examined the role of factors such as self-determination, eHealth literacy and psychological distress in determining adolescents’ pursuit of health / mental health information online during the COVID-19 pandemic.

Introduction

Adolescents are showing an increase in vulnerability to mental health illness (Gunnell et al., Reference Gunnell, Kidger and Elvidge2018), and studies have documented an increase in psychological distress among adolescents during the COVID-19 pandemic (Nearchou et al., Reference Nearchou, Flinn, Niland, Subramaniam and Hennessy2020). School closures, social distancing measures and isolation had negatively impacted the mental health of children and adolescents during the COVID-19 pandemic (Meherali et al., Reference Meherali, Punjani, Louie-Poon, Abdul Rahim, Das, Salam and Lassi2021). Adolescents tend to be reluctant to seek mental health services in person, but may seek mental health information online due to less stigma and more privacy (Pretorius et al., Reference Pretorius, Chambers and Coyle2019). Studies have shown that the recent pursuit of mental health information online has been high among adolescents (Park and Kwon, Reference Park and Kwon2018; Rideout et al., Reference Rideout and Fox2018), and that individuals with psychological distress and mental health problems were more likely to pursue health information online (Gallagher and Doherty, Reference Gallagher and Doherty2009; Rowlands et al., Reference Rowlands, Loxton, Dobson and Mishra2015; Pretorius et al., Reference Pretorius, Chambers and Coyle2019). A review study found that for young people with a preference for self-reliance, the pursuit of mental health information online is either therapeutic or acts as a gateway to further help (Pretorius et al., Reference Pretorius, Chambers and Coyle2019).

Children and adolescents spend more time online than adults, which is a global phenomenon. The 2020 EU Kids Online survey showed that in many countries the time that children report spending online almost doubled compared with the 2010 findings (Smahel et al., Reference Smahel, Machackova, Mascheroni, Dedkova, Staksrud, Ólafsson, Livingstone and Hasebrink2020). In particular, during the COVID-19 pandemic adolescents spent more time than ever on the internet, which they used for socializing, entertainment and learning (Ofcom, 2020). The internet is the main source of information for adolescents, while a review study found that the primary purpose for adolescents’ health-related use of the internet is the pursuit of health information (Park and Kwon, Reference Park and Kwon2018). Studies showed that about half of adolescents have reported using the internet to search for health information (Jiménez-Pernett et al., Reference Jiménez-Pernett, de Labry-Lima, Bermúdez-Tamayo, García-Gutiérrez and del Carmen Salcedo-Sánchez2010; Gazibara et al., Reference Gazibara, Cakic, Cakic, Grgurevic and Pekmezovic2020), but many of those adolescents also reported a lack of search skills to find reliable web pages and had difficulties in filtering overabundant content and determining the quality of information (Esmaeilzadeh et al., Reference Esmaeilzadeh, Ashrafi-Rizi, Shahrzadi and Mostafavi2018; Patterson et al., Reference Patterson, Hilton, Flowers and McDaid2019).

The COVID-19 pandemic has provoked a greater number of healthcare organizations to provide eHealth resources and to stress the importance of individual eHealth literacy for the use of eHealth services. The abundance of misinformation online, particularly during the COVID-19 outbreak, has enhanced the role of eHealth literacy in appraising online information, making health decisions and implementing protective behaviors (Brørs et al., Reference Brørs, Norman and Norekvål2020). eHealth literacy refers to an individual’s ability to seek out, understand, appraise and apply electronic health information to solve health problems (Norman and Skinner, Reference Norman and Skinner2006). A study has shown that individuals with higher eHealth literacy were more likely to search for COVID-19 information online and adopt preventive behaviors (Guo et al., Reference Guo, Zhao, Guo, Wu, Weng, Wong, Lam and Wang2021). Prior studies also found a positive association between higher levels of eHealth literacy and the pursuit of health information online (Gazibara et al., Reference Gazibara, Cakic, Cakic, Grgurevic and Pekmezovic2020), healthy lifestyle behaviors in adolescents (Gürkan and Ayar, Reference Gürkan and Ayar2020; Eyimaya et al., Reference Eyimaya, Özdemir, Tezel and Apay2021) and positive mental health effects (Chen et al., Reference Chen, Zheng, Liang, Xie and Gu2020). Most studies assessed eHealth literacy using self-reporting of perceived skills, while few studies have measured performance-based eHealth literacy through the testing of actual performance to determine eHealth literacy levels, such as the completion of computerized simulation tasks. Prior studies showed that perceived and performed eHealth literacy were either moderately (Neter and Brainin, Reference Neter and Brainin2017) or weakly correlated (van der Vaart et al., Reference van der Vaart, van Deursen, Drossaert, Taal, van Dijk and van de Laar2011). Some studies have shown a large discrepancy between perceived and performance-based eHealth literacy, which has highlighted the levels of poor critical self-awareness among adolescents (Maitz et al., Reference Maitz, Maitz, Sendlhofer, Wolfsberger, Mautner, Kamolz and Gasteiger-Klicpera2020; McKinnon et al., Reference McKinnon, Caldwell and Scott2020.

During the COVID-19 pandemic, parents and adolescents were living with increased stress (Cluver et al., Reference Cluver, Lachman, Sherr, Wessels, Krug, Rakotomalala, Blight, Hillis, Bachman, Green, Butchart, Tomlinson, Ward, Doubt and McDonald2020). Parents have reported increases in the difficulties associated with controlling their children’s screen time and increased levels of concern related to the online risks to children (Ofcom, 2021). When adolescents spend more time using the internet, online risks and psychological distress increase (Deslandes and Coutinho, Reference Deslandes and Coutinho2020; Guessoum et al., Reference Guessoum, Lachal, Radjack, Carretier, Minassian, Benoit and Moro2020). Parents play a crucial role in the use of the internet by their children. A review study found that the parent–child relationship, parental mediation practices and parents’ own use of media influences children’s media use, attitudes and effects (Coyne et al., Reference Coyne, Radesky, Collier, Gentile, Linder, Nathanson, Nathanson, Rasmussen, Reich and Rogers2017). A study found that parental eHealth literacy, active parental internet mediation and adolescent internet health information literacy all were related to the pursuit of health information online by adolescents (Chang et al., Reference Chang, Chiu, Chen, Miao, Lee, Chiang and Pan2015).

Self-determination theory emphasizes that the satisfaction of basic psychological needs including competence, autonomy and relatedness were associated with development, health-behavior change and better mental health (Deci and Ryan, Reference Deci and Ryan2000). A prior study associated a higher level of self-determination with seeking online health information (Lee and Lin, Reference Lee and Lin2016). Despite studies that have examined the relationships between eHealth literacy and the pursuit of health information online and related factors, most research has focused on adults. By comparison, only a scant amount of research has explored adolescent pursuit of health information online and examined the influence of self-determination, eHealth literacy, psychological distress and parental mediation. For the present study, we analyzed data from the 2020 Taiwan Communication Survey conducted during the COVID-19 pandemic. Our aims included (1) an assessment of adolescents’ pursuit of health information and health topics online during the COVID-19 pandemic; (2) an examination of the relationships between internet use, self-determination and parental internet mediation with adolescents’ eHeatlh literacy; and (3) a further examination into how self-determination, eHealth literacy, psychological distress and parental internet mediation are associated with adolescents’ pursuit of health information online (i.e., the pursuit of health/ mental health information online and the number of health topics searched online).

Methods

Participants

This study analyzed data from the 2020 Taiwan Communication Survey (second phase, fourth wave) (Chang, Reference Chang2022). The cluster sampling method was used, while the six socioeconomic strata from Taiwan townships (Hou et al., Reference Hou, Tu, Liao, Hung and Chang2008) were adopted as a sampling scheme to draw the sample schools. A total of 19 elementary schools, 20 middle schools and 23 high schools were randomly selected from the strata and invited to join the survey. The classes were randomly selected from the sample schools. Teachers gave students consent forms to take home to parents requesting consent for their children to participate in the survey. Students were assured that their information would be protected and anonymous. This study analyzed 1,250 national representative adolescents from 43 middle schools (n = 582) and high schools (n = 668). Adolescents completed an online self-administered questionnaire between November 2020 and January 2021, during the COVID-19 pandemic. Approval was obtained from the Institutional Review Board at Academia Sinica, Taiwan.

A self-administered questionnaire was developed based on previous studies (Norman and Skinner, Reference Norman and Skinner2006; Williams, Reference Williams2006; Löwe et al., Reference Löwe, Wahl, Rose, Spitzer, Glaesmer, Wingenfeld, Schneider and Brähler2010; Nishimura and Suzuki, Reference Nishimura and Suzuki2016; Rideout et al., Reference Rideout and Fox2018). A group of experts was invited to assess the content validity of the questionnaire. In addition, a pilot survey was conducted at one middle school and two high schools in order to assess the appropriateness of the survey questions and to evaluate the reliability of the data that the questionnaire would yield.

Pursuit of health information online

Questions concerning the pursuit of health information online were adapted from a study found in the literature (Rideout et al., Reference Rideout and Fox2018). Participants were asked, “Have you used the internet to search the following health topics?” If participants answered that they did not use the internet to search for any health topics, then they were categorized as not seeking health information online. If participants answered that they use the internet to search for health topics (i.e., exercise, physical fitness, nutrition, sexual health, stress management, depression, anxiety, mental health and others), then they were categorized as having sought health information online. In addition, if participants answered that they used the internet to search for any mental health topics (i.e., sexual health, stress management, depression, anxiety and mental health), then they were categorized as having sought mental health information online.

Internet use time

Internet use time was measured using six items. Participants were asked how much time (amount of hours and minutes) they spend on computers, tablets and/or smartphones for learning and recreation, respectively. Sample questions follow: “How long do you surf the internet using a computer (excluding the usage of smartphones and tablets; only including your internet-surfing screen time) for learning and working purposes every day?”; “Excluding your learning and working time online, how long do you surf the internet using a computer for entertainment and leisure purposes every day on average?” The sum of internet use time on a computer, a tablet, or a smartphone for learning and working purposes was considered internet learning time. On the other hand, the sum of time using the internet on a computer, a tablet, or a smartphone for entertainment and leisure purposes was considered internet entertainment and leisure time.

eHealth literacy

eHealth Literacy (5 items) was measured by adapting a previously developed eHealth literacy scale (Norman and Skinner, Reference Norman and Skinner2006) to measure participants’ perceived skills at finding, evaluating and applying electronic health information to health problems. Participants were asked about their opinions and experiences using the internet for health information. Sample statements follow: “I know how to find helpful health resources on the internet”; “I know how to use the internet to answer my health questions”; “I know how to use the health information I find on the internet to help me”; “I can tell high-quality from low-quality health resources on the internet”; “I feel confident in using information from the internet to make health decisions.” The response options were graded on a 5-point Likert-type scale that ranged from strongly disagree (scoring 1) to strongly agree (scoring 5), with higher scores indicating a higher level of eHealth literacy. The Cronbach’s alpha of eHealth literacy was 0.87.

Parental internet mediation

Parental internet mediation (six items) was measured by adapting scales from prior studies (Nathanson, Reference Nathanson1999; Valkenburg et al., Reference Valkenburg, Krcmar, Peeters and Marseille1999). Parental internet mediation included parental restrictive internet mediation (three items) and parental active internet mediation (three items). Participants were asked about their experience regarding their parents’ internet mediation. Parental restrictive internet mediation statements follow: “My parents don’t allow me to visit certain websites”; “My parents set rules regarding when I can use the internet and when I cannot”; “My parents set a limit on how long I use the internet.” Active parental internet mediation statements follow: “My parents encourage me to use the internet”; “My parents discuss internet use experiences with me”; “My parents discuss online stories and events with me.” The response options included never (scoring 1), seldom (scoring 2), sometimes (scoring 3), often (scoring 4), with higher scores indicating a higher level of parental restrictive/active mediation. The Cronbach’s alpha scores for parental restrictive internet mediation and for active parental internet mediation were 0.76 and 0.68, respectively.

Bonding social capital

Bonding social capital (one item) was measured by adapting an approach from a social capital study (Williams, Reference Williams2006) to measure participants’ perceived emotional support and access to resources from strong-tie networks. Participants were asked to complete the following statement: “There are several people I trust to help solve my problems.” The response options were graded on a 5-point Likert-type scale that ranged from strongly disagree (scoring 1) to strongly agree (scoring 5), with higher scores indicating a higher level of bonding social capital.

Self-determination

Self-determination (three items) was measured by factors that included competence, autonomy and relatedness, and was adapted from a study found in the literature (Nishimura and Suzuki, Reference Nishimura and Suzuki2016). Participants were asked their opinions and experiences regarding the following statements: “I feel confident that I can do things well”; “I feel I have been doing what really interests me”; “I feel close and connected with other people who are important to me (e.g. family, friends).” The response options were graded on a 5-point Likert-type scale that ranged from strongly disagree (scoring 1) to strongly agree (scoring 5), with higher scores indicating higher levels of self-determination (competence, autonomy and relatedness).

Depression and anxiety

Depression and anxiety (four items) were measured using a scale developed in a previous study (Löwe et al., Reference Löwe, Wahl, Rose, Spitzer, Glaesmer, Wingenfeld, Schneider and Brähler2010). Participants were asked “Over the last week, how often have you been bothered by the following problems? (1) Little interest or pleasure in doing things; (2) Feeling down, depressed or hopeless; (3) Feeling nervous, anxious or on edge; (4) Not being able to stop or control worrying.” The response options ranged from 0 (scoring 0) to 7 days (scoring 7), with higher scores indicating a higher level of depression and anxiety. The Cronbach’s alpha of depression and anxiety was 0.90.

Physical and emotional exhaustion

To gauge physical and emotional exhaustion, two items were adopted from the Copenhagen Burnout Inventory (Kristensen et al., Reference Kristensen, Borritz, Villadsen and Christensen2005). The questions were “How often are you physically exhausted?” and “How often are you emotionally exhausted (such as feeling helpless or frustrated)?” The response options included never (scoring 1), seldom (scoring 2), sometimes (scoring 3) and often (scoring 4), with higher scores indicating a higher level of physical and emotional exhaustion.

Characteristics of the adolescents

The characteristics of the adolescents who participated in this study included gender (male or female), age, school type (middle school or high school) and academic performance (very good, good, average, poor, very poor).

Statistical analysis

SAS was used to perform the statistical analysis. A series of t-tests were conducted to compare adolescents’ eHealth literacy, internet use time and related factors by gender and by school type. Chi-square tests were conducted to compare adolescents’ pursuit of health information and mental health online. In addition, multiple regression was conducted to examine the factors related to adolescents’ eHealth literacy and the number of health topics searched online. Multiple logistic regression was conducted to examine factors related to adolescents’ pursuit of health information online and the factors associated with the pursuit of mental health information online. A 95% confidence interval (95% C.I.) and p value was presented. The outcome variable was the pursuit of health information online including the pursuit of health information online, pursuit of mental health information online and number of health topics searched online. The independent variables included internet use time, eHealth literacy, parental internet mediation, bonding social capital, self-determination, depression and anxiety, physical and emotional exhaustion. The covariate variables were adolescents’ characteristics including gender, age and academic performance.

Results

Internet use by adolescents

Of the 1,250 participant students, 655 were boys (52.4%) and 595 were girls (47.6%). The age range of participant students was 12–18 years, while the mean age of middle school students and high school students was 12.9 years, and 16.1 years, respectively. Overall, adolescents spent 29.8 h per week using the internet for recreation and 12.5 h per week using the internet for learning. In addition, adolescents mainly accessed the internet via smartphones (22.2 h/week for recreation and 8.3 h/week for learning). By gender, boys spent more time using computers to go online than girls. By school type, high school students spent more time using computers and smartphones to go online than middle school students (Table 1).

Table 1. Adolescent’s internet use, eHealth literacy and health status

Note: Boy n = 655 girl n = 595, middle school n = 582 high school n = 668.

eHealth literacy of adolescents and related factors

The eHealth literacy of the adolescent participants was above average (Mean = 3.69) (Table 1). The participants had higher scores for the searching of health information than for appraising and applying the health information they found. By gender, boys had slightly higher levels of eHealth literacy (Mean = 3.73) than girls (Mean = 3.64) (Table 1).

Multiple regression results indicated that adolescents who were boys, who spent more time using the internet for learning, who had higher levels of bonding social capital, who higher self-determination (competence, relatedness), and who had higher levels of active parental internet mediation were more likely to have higher levels of eHealth literacy (Table 3).

Pursuit of health information online by adolescents and related factors

The rates of adolescents’ pursuit of health information online are listed in Table 2. Overall, 75.6% of adolescents searched health information online, while 47.7% of adolescents searched mental health information online during the COVID-19 pandemic. The percentage of girls who searched mental health topics online (50.8%) was higher than that for boys (44.9%). The percentage of high school students who searched health topics online (79.5%) was higher than that for middle school students (71.5%). Similarly, the percentage of high school students who searched mental health topics online (60.1%) was higher than that for middle school students (33.5%) (Table 2).

Table 2. Adolescents’ pursuit of health information online and health topics searched

Note: Boy n = 655 girl n = 595, middle school n = 582 high school n = 668.

Table 3. Factors related to adolescents’ eHealth literacy

Note: (1) N = 1,236. (2) Multiple regression was conducted.

Table 4. Factors related to adolescent pursuit of health information online

Note: (1) N = 1,236. (2) Multiple logistic regression was conducted. (3) Pursuit of health information online: yes n = 931 no n = 305, pursuit of mental health information online: yes n = 596 no n = 640.

Table 5. Factors related to the number of health topics searched online

Note: (1) N = 1,236. (2) Multiple regression was conducted.

Multiple logistic regression results showed that adolescents who were boys, who had higher levels of eHealth literacy, who had higher levels of depression and anxiety, or who had higher levels of parental active internet mediation were more likely to seek health information online. In addition, adolescents who were high school students, who had higher levels of eHealth literacy, who had higher levels of depression and anxiety, and who had higher levels of emotional exhaustion were more likely to seek mental health information online (Table 4).

Health topics searched by adolescents and related factors

The health topics that adolescents searched included exercise (53.0%), mental health (31.8%), stress (31.0%), nutrition (28.2%), depression (23.0%), physical fitness (21.8%), anxiety (19.2%), and sexual health (13.0%) (Table 2). The average number of health topics adolescents searched was 2.2. High school students searched more health topics (mean = 2.60) than middle school students (1.76) (Table 1). Multiple regression results showed that adolescents who were high school students, who had higher levels of eHealth literacy, who had higher competence, who had higher levels of depression and anxiety, who had higher levels of physical and emotional exhaustion, and who had higher levels of active parental internet mediation were more likely to search more health topics online (Table 5).

Discussion

This study found that two-thirds of adolescents searched health topics online during the COVID-19 pandemic. Prior studies conducted in the United States (Rideout et al., Reference Rideout and Fox2018), Serbia (Gazibara et al., Reference Gazibara, Cakic, Cakic, Grgurevic and Pekmezovic2020), Saudi Arabia (Neumark et al., Reference Neumark, Lopez-Quintero, Feldman, Hirsch Allen and Shtarkshall2013) and Spain (Jiménez-Pernett et al., Reference Jiménez-Pernett, de Labry-Lima, Bermúdez-Tamayo, García-Gutiérrez and del Carmen Salcedo-Sánchez2010) also found that more than half of adolescents reported seeking health information online. In addition, the results found in this study are consistent with prior studies that found adolescents searched a variety of health topics including exercise, fitness, nutrition, and mental and sexual health, with exercise and fitness being the most common health topics searched (Jiménez-Pernett et al., Reference Jiménez-Pernett, de Labry-Lima, Bermúdez-Tamayo, García-Gutiérrez and del Carmen Salcedo-Sánchez2010; Neumark et al., Reference Neumark, Lopez-Quintero, Feldman, Hirsch Allen and Shtarkshall2013; Park and Kwon, Reference Park and Kwon2018; Rideout et al., Reference Rideout and Fox2018). These results indicated that online information was an important source for adolescents to obtain health information. However, a study reviewed websites and found that very few webpages were written specifically for adolescents and suggested that governments invest in co-designing excellent-quality and more interactive health information online that better targets an adolescent audience (Ruan et al., Reference Ruan, Raeside, Singleton, Redfern and Partridge2021).

In addition, the present study found that half of adolescents searched mental health topics online, and that adolescents who had higher levels of depression and anxiety were more likely to search health information and mental health information online. Prior studies also found that individuals with psychological distress were more likely to engage in seeking help online (Pretorius et al., Reference Pretorius, Chambers and Coyle2019) and in searching for health information (Gallagher and Doherty, Reference Gallagher and Doherty2009; Rowlands et al., Reference Rowlands, Loxton, Dobson and Mishra2015). An Australian study found that young women experiencing “stigmatized” conditions were more likely to search health information online (Rowlands et al., Reference Rowlands, Loxton, Dobson and Mishra2015). A review study indicated that the benefits for young people who use online help-seeking searches of mental health included anonymity, immediacy, ease of access, inclusivity, shared experiences and a sense of control over the help-seeking journey (Pretorius et al., Reference Pretorius, Chambers and Coyle2019). These results were consistent with help-seeking models (Rickwood et al., Reference Rickwood, Deane, Wilson and Ciarrochi2005) that showed that when young people had psychological needs and could easily access online mental health information, they were more willing to seek mental health resources online. Studies have established that young people were open to accessing mental health information online, as well as pursuing mental health support online (Oh et al., Reference Oh, Jorm and Wright2009; Horgan and Sweeney, Reference Horgan and Sweeney2010).

Moreover, the results of this study were consistent with those of prior studies (James and Harville II, Reference James and Harville2016; Wong and Cheung, Reference Wong and Cheung2019; Gazibara et al., Reference Gazibara, Cakic, Cakic, Grgurevic and Pekmezovic2020) that found individuals with better eHealth literacy were more likely to pursue health information online. Another study also found that the internet skill level of adolescents was associated with their pursuit of health information online (Neumark et al., Reference Neumark, Lopez-Quintero, Feldman, Hirsch Allen and Shtarkshall2013). Results of the present study have shown, however, that adolescents were not as adept at appraising and applying health information as they are at searching for it. Other studies also found that adolescents seldom evaluated search results, had difficulty in selecting appropriate search strings and also had difficulty determining the quality of the information they acquired, which suggests an overall lack of appraisal strategies (Walraven et al., Reference Walraven, Brand-Gruwel and Boshuizen2009; Jiménez-Pernett et al., Reference Jiménez-Pernett, de Labry-Lima, Bermúdez-Tamayo, García-Gutiérrez and del Carmen Salcedo-Sánchez2010; Esmaeilzadeh et al., Reference Esmaeilzadeh, Ashrafi-Rizi, Shahrzadi and Mostafavi2018; Freeman et al., Reference Freeman, Caldwell, Bennett and Scott2018). In addition, in previous studies, adolescents judged their own eHealth literacy much higher than its actual value, and those studies suggested implementing education to strengthen adolescents’ eHealth and critical literacy (Maitz et al., Reference Maitz, Maitz, Sendlhofer, Wolfsberger, Mautner, Kamolz and Gasteiger-Klicpera2020; McKinnon et al., Reference McKinnon, Caldwell and Scott2020). At least one study associated exposure to credible sources of health information online with higher eHealth literacy and suggested that credible health information resources online be incorporated into school health education curricula (Ghaddar et al., Reference Ghaddar, Valerio, Garcia and Hansen2012). Schools could implement eHealth literacy combined with critical media literacy programs to strengthen adolescents’ eHealth literacy competence and enhance their pursuit of health information online.

This study positively associated active parental internet mediation and bonding social capita with adolescent eHealth literacy. These results indicated the crucial roles of parents and significant others in supporting and providing resources to help adolescents solve online problems and enhance their eHealth literacy. Prior studies have also related active parental internet mediation to adolescent eHealth literacy (Chang et al., Reference Chang, Chiu, Chen, Miao, Lee, Chiang and Pan2015). In addition, previous studies have positively associated individual social capital with health information self-efficacy, the scope of health information sources and intentions to pursue health information (Kim et al., Reference Kim, Lim and Park2015). Social capital has also been shown to have a positive effect on technological literacy (Yang et al., Reference Yang, Huang, Lai, Yang and Yu2012). These results underscore the importance of strengthening individual social capital to enhance eHealth literacy. Governments could implement parental internet mediation and eHealth literacy training to improve eHealth and the online pursuit of health information, which would decrease the digital divide and health inequality among children and adolescents.

The results of this study positively associated internet learning time and self-determination factors such as competence and relatedness with higher levels of eHealth literacy among adolescents. Prior studies also positively related self-efficacy to eHealth literacy (Holch and Marwood, Reference Holch and Marwood2020; Maitz et al., Reference Maitz, Maitz, Sendlhofer, Wolfsberger, Mautner, Kamolz and Gasteiger-Klicpera2020). These results were consistent with self-determination theory (Deci and Ryan, Reference Deci and Ryan2000), which addresses adolescent competence, autonomy and relatedness, and shows these factors to be crucial for developing eHealth literacy and enhancing the pursuit of health information online. Our results showed that boys reported higher levels of eHealth literacy than girls; however, this difference could have been related to their self-determinism, such as when boys perceived higher levels of competence in appraising the information on the internet. In addition, at least one study has applied self-determination theory and found that the pursuit of health information online offers individuals greater autonomy, competence and relatedness compared with face-to-face office visits with a physician (Lee and Lin, Reference Lee and Lin2016). Similarly, another study found that individual competence increases with the use of technology, and learning with peers was more engaging when using digital tools to pursue health information to meet health needs (Scott Duncan et al., Reference Scott Duncan, Riggare, Koch, Sharp and Hägglund2019). These results suggest that eHealth services design could incorporate a self-determination perspective to promote adolescent eHealth use.

Limitations

This study had some limitations. First, this was a cross-sectional study, which limits the information that can be used to infer causality. Second, this study analyzed the dataset from the 2020 Taiwan Communication Survey, and some variables such as the psychological distress scale had a limited number of items, which could reduce the reliability. Third, eHealth literacy was measured based on the adolescents’ perceptions, and gaps could exist between perceived eHealth literacy and actual capabilities of searching and evaluating health information. Future studies could assess adolescents in an experimental setting to test their capabilities in searching and appraising health information combined with self-report eHealth literacy. Finally, parental internet mediation was measured based on adolescents’ reporting, and future studies could conduct a parent–child dyad study to examine parental influences on adolescents’ eHealth literacy, the pursuit of health information online, and physical and mental health outcomes. Despite these limitations, the present study adds to the limited amount of literature that addresses adolescents’ pursuit of health information online and the roles of self-determination, eHealth literacy, psychological distress and parental internet mediation.

Conclusions

During the COVID-19 pandemic, adolescents were vulnerable to problems with mental health. The rates of adolescent pursuit of health information / mental health information and health-related topics online during the COVID-19 pandemic were unknown, as were the associations of self-determination, eHealth literacy, psychological distress and parental internet mediation with adolescents’ online health and mental health information seeking. Our results showed that two-thirds of adolescents reported searching for health information online, and about half of adolescents searched mental health information online during the COVID-19 pandemic. The results of this study revealed the significance of the roles of bonding social capital, self-determination and parental active internet mediation in enhancing adolescents’ eHealth literacy. Adolescents’ levels of competence, eHealth literacy, psychological distress and active parental internet mediation played crucial roles in increasing their pursuit of health and mental health information online. These results implied the need to implement eHealth literacy combined with critical media literacy programs to strengthen adolescents’ eHealth literacy competence. Future research could promote a self-determination perspective to develop eHealth literacy intervention, promote the seeking of online health information and underscore the value of appraisal to adolescents.

Open peer review

To view the open peer review materials for this article, please visit http://doi.org/10.1017/gmh.2023.44.

Data availability statement

The data that support the findings of this study are openly available in the 2020 Taiwan Communication Survey (Phase Two, Year Four): New Communication Technologies & Life Boundary Expansion (D00216) (Data file). Further information is available from the Survey Research Data Archive, Academia Sinica. https://doi.org/10.6141/TW-SRDA-D00216-2 (Chang, Reference Chang2022).

Acknowledgements

Many thanks go to the participant schools and students.

Author contribution

Professor Fong-Ching Chang was responsible for the conception and analysis of the study and for the writing of the manuscript. Professor Chingching Chang was the chair to design the Taiwan Communication Survey and the conception of this work. Professor Chen-Chao Tao was the co-chair to conduct the Taiwan Communication Survey and the conception of this work. All authors contributed to manuscript preparation and approved the final manuscript.

Financial support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Competing interest

The authors declare no conflicts of interest.

Ethics statement

Approval of this research was obtained from the Institutional Review Board at Academia Sinica, Taiwan.

References

Brørs, G, Norman, CD and Norekvål, TM (2020) Accelerated importance of eHealth literacy in the COVID-19 outbreak and beyond. European Journal of Cardiovascular Nursing 19(6), 458461. https://doi.org/10.1177/1474515120941307CrossRefGoogle ScholarPubMed
Chang, C (2022) The 2020 Taiwan Communication Survey (Phase Two, Year Four): New Communication Technologies & Life Boundary Expansion (D00216) (Data file). Survey Research Data Archive, Academia Sinica. https://doi.org/10.6141/TW-SRDA-D00216-2CrossRefGoogle Scholar
Chang, FC, Chiu, CH, Chen, PH, Miao, NF, Lee, CM, Chiang, JT and Pan, YC (2015) Relationship between parental and adolescent eHealth literacy and online health information seeking in Taiwan. Cyberpsychology, Behavior and Social Networking 18(10), 618624. https://doi.org/10.1089/cyber.2015.0110CrossRefGoogle ScholarPubMed
Chen, W, Zheng, Q, Liang, C, Xie, Y and Gu, D (2020) Factors influencing college students’ mental health promotion: The mediating effect of online mental health information seeking. International Journal of Environmental Research and Public Health 17(13), 4783. https://doi.org/10.3390/ijerph17134783CrossRefGoogle ScholarPubMed
Cluver, L, Lachman, JM, Sherr, L, Wessels, I, Krug, E, Rakotomalala, S, Blight, S, Hillis, S, Bachman, G, Green, O, Butchart, A, Tomlinson, M, Ward, CL, Doubt, J and McDonald, K (2020) Parenting in a time of COVID-19. Lancet 395(10231), e64. https://doi.org/10.1016/s0140-6736(20)30736-4CrossRefGoogle Scholar
Coyne, SM, Radesky, J, Collier, KM, Gentile, DA, Linder, JR, Nathanson, AI, Nathanson, AI, Rasmussen, EE, Reich, SM and Rogers, J (2017) Parenting and digital media. Pediatrics 140(Suppl 2), S112s116. https://doi.org/10.1542/peds.2016-1758NCrossRefGoogle ScholarPubMed
Deci, EL and Ryan, RM (2000) The ‘what’ and ‘why’ of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry 11(4), 227. https://doi.org/10.1207/S15327965PLI1104_01CrossRefGoogle Scholar
Deslandes, SF and Coutinho, T (2020). The intensive use of the internet by children and adolescents in the context of COVID-19 and the risks for self-inflicted violence. Ciência & Saúde Coletiva 25(suppl 1), 24792486. https://doi.org/10.1590/1413-81232020256.1.11472020CrossRefGoogle ScholarPubMed
Esmaeilzadeh, S, Ashrafi-Rizi, H, Shahrzadi, L and Mostafavi, F (2018) A survey on adolescent health information seeking behavior related to high-risk behaviors in a selected educational district in Isfahan. PLoS One 13(11), e0206647. https://doi.org/10.1371/journal.pone.0206647CrossRefGoogle Scholar
Eyimaya, A, Özdemir, F, Tezel, A and Apay, SE (2021) Determining the healthy lifestyle behaviors and e-health literacy levels in adolescents. Revista da Escola de Enfermagem da U.S.P. 55, e03742. https://doi.org/10.1590/s1980-220x2020021603742CrossRefGoogle ScholarPubMed
Freeman, JL, Caldwell, PHY, Bennett, PA and Scott, KM (2018). How adolescents search for and appraise online health information: A systematic review. Journal of Pediatrics 195, 244255.e241. https://doi.org/10.1016/j.jpeds.2017.11.031CrossRefGoogle ScholarPubMed
Gallagher, S and Doherty, DT (2009) Searching for health information online: Characteristics of online health seekers. Journal of Evidence-Based Medicine 2(2), 99106. https://doi.org/10.1111/j.1756-5391.2009.01021.xCrossRefGoogle ScholarPubMed
Gazibara, T, Cakic, J, Cakic, M, Grgurevic, A and Pekmezovic, T (2020) Searching for online health information instead of seeing a physician: A cross-sectional study among high school students in Belgrade, Serbia. International Journal of Public Health 65(8), 12691278. https://doi.org/10.1007/s00038-020-01471-7CrossRefGoogle ScholarPubMed
Ghaddar, SF, Valerio, MA, Garcia, CM and Hansen, L (2012) Adolescent health literacy: The importance of credible sources for online health information. Journal of School Health 82(1), 2836. https://doi.org/10.1111/j.1746-1561.2011.00664.xCrossRefGoogle ScholarPubMed
Guessoum, SB, Lachal, J, Radjack, R, Carretier, E, Minassian, S, Benoit, L and Moro, MR (2020) Adolescent psychiatric disorders during the COVID-19 pandemic and lockdown. Psychiatry Research 291, 113264. https://doi.org/10.1016/j.psychres.2020.113264CrossRefGoogle ScholarPubMed
Gunnell, D, Kidger, J and Elvidge, H (2018) Adolescent mental health in crisis. BMJ 361, k2608. https://doi.org/10.1136/bmj.k2608CrossRefGoogle ScholarPubMed
Guo, Z, Zhao, SZ, Guo, N, Wu, Y, Weng, X, Wong, JY, Lam, TH and Wang, MP (2021) Socioeconomic disparities in eHealth literacy and preventive behaviors during the COVID-19 pandemic in Hong Kong: Cross-sectional study. Journal of Medical Internet Research 23(4), e24577. https://doi.org/10.2196/24577CrossRefGoogle Scholar
Gürkan, KP and Ayar, D (2020) The impact of e-health literacy on health promotion behaviors of high school students. Journal of Pediatric Research 7(4), 286292. https://doi.org/10.4274/jpr.galenos.2019.81488CrossRefGoogle Scholar
Holch, P and Marwood, JR (2020) EHealth literacy in UK teenagers and young adults: Exploration of predictors and factor structure of the eHealth literacy scale (eHEALS). JMIR Formative Research 4(9), e14450. https://doi.org/10.2196/14450CrossRefGoogle Scholar
Horgan, A and Sweeney, J (2010) Young students’ use of the internet for mental health information and support. Journal of Psychiatric and Mental Health Nursing 17(2), 117123. https://doi.org/10.1111/j.1365-2850.2009.01497.xCrossRefGoogle ScholarPubMed
Hou, PC, Tu, SH, Liao, PS, Hung, YT and Chang, YH (2008) The typology of townships in Taiwan: The analysis of sampling stratification of the 2005–2006 “Taiwan Social Change Survey”. Survey Research Method and Application 23, 732. https://doi.org/10.7014/tcycffyyy.200804.0007Google Scholar
James, DC and Harville, C II (2016) eHealth literacy, online help-seeking behavior, and willingness to participate in mHealth chronic disease research among African Americans, Florida, 2014–2015. Preventing Chronic Disease 13, E156. https://doi.org/10.5888/pcd13.160210CrossRefGoogle ScholarPubMed
Jiménez-Pernett, J, de Labry-Lima, AO, Bermúdez-Tamayo, C, García-Gutiérrez, JF and del Carmen Salcedo-Sánchez, M (2010) Use of the internet as a source of health information by Spanish adolescents. BMC Medical Informatics and Decision Making 10, 6. https://doi.org/10.1186/1472-6947-10-6CrossRefGoogle ScholarPubMed
Kim, YC, Lim, JY and Park, K (2015) Effects of health literacy and social capital on health information behavior. Journal of Health Communication 20(9), 10841094. https://doi.org/10.1080/10810730.2015.1018636CrossRefGoogle ScholarPubMed
Kristensen, T, Borritz, M, Villadsen, E and Christensen, K (2005) The Copenhagen burnout inventory: A new tool for the assessment of burnout. Work & Stress 19(3), 192207. https://doi.org/10.1080/02678370500297720CrossRefGoogle Scholar
Lee, ST and Lin, J (2016) A self-determination perspective on online health information seeking: The internet vs. face-to-face office visits with physicians. Journal of Health Communication 21(6), 714722. https://doi.org/10.1080/10810730.2016.1157651CrossRefGoogle ScholarPubMed
Löwe, B, Wahl, I, Rose, M, Spitzer, C, Glaesmer, H, Wingenfeld, K, Schneider, A and Brähler, E (2010) A 4-item measure of depression and anxiety: Validation and standardization of the patient health Questionnaire-4 (PHQ-4) in the general population. Journal of Affective Disorders 122(1–2), 8695. https://doi.org/10.1016/j.jad.2009.06.019CrossRefGoogle ScholarPubMed
Maitz, E, Maitz, K, Sendlhofer, G, Wolfsberger, C, Mautner, S, Kamolz, LP and Gasteiger-Klicpera, B (2020) Internet-based health information-seeking behavior of students aged 12 to 14 years: Mixed methods study. Journal of Medical Internet Research 22(5), e16281. https://doi.org/10.2196/16281CrossRefGoogle ScholarPubMed
McKinnon, KA, Caldwell, PHY and Scott, KM (2020) How adolescent patients search for and appraise online health information: A pilot study. Journal of Paediatrics and Child Health 56(8), 12701276. https://doi.org/10.1111/jpc.14918CrossRefGoogle ScholarPubMed
Meherali, S, Punjani, N, Louie-Poon, S, Abdul Rahim, K, Das, JK, Salam, RA and Lassi, ZS (2021) Mental health of children and adolescents amidst COVID-19 and past pandemics: A rapid systematic review. International Journal of Environmental Research and Public Health 18(7), 3432. https://doi.org/10.3390/ijerph18073432CrossRefGoogle ScholarPubMed
Nathanson, AI (1999) Identifying and explaining the relationship between parental mediation and Children’s aggression. Communication Research 26(2), 124. https://doi.org/10.1177/009365099026002002CrossRefGoogle Scholar
Nearchou, F, Flinn, C, Niland, R, Subramaniam, SS and Hennessy, E (2020) Exploring the impact of COVID-19 on mental health outcomes in children and adolescents: A systematic review. International Journal of Environmental Research and Public Health 17(22), 8479. https://doi.org/10.3390/ijerph17228479CrossRefGoogle ScholarPubMed
Neter, E and Brainin, E (2017) Perceived and performed eHealth literacy: Survey and simulated performance test. JMIR Human Factors 4(1), e2. https://doi.org/10.2196/humanfactors.6523CrossRefGoogle ScholarPubMed
Neumark, Y, Lopez-Quintero, C, Feldman, BS, Hirsch Allen, AJ and Shtarkshall, R (2013) Online health information seeking among Jewish and Arab adolescents in Israel: Results from a national school survey. Journal of Health Communication 18(9), 10971115. https://doi.org/10.1080/10810730.2013.778360CrossRefGoogle ScholarPubMed
Nishimura, T and Suzuki, T (2016) Basic psychological need satisfaction and frustration in Japan: Controlling for the big five personality traits. Japanese Psychological Research 58(4), 320331. https://doi.org/10.1111/jpr.12131CrossRefGoogle Scholar
Norman, CD and Skinner, HA (2006) eHEALS: The eHealth literacy scale. Journal of Medical Internet Research 8(4), e27. https://doi.org/10.2196/jmir.8.4.e27CrossRefGoogle ScholarPubMed
Ofcom (2020) Ofcom Children’s Media Lives. Life in Lockdown.Google Scholar
Ofcom (2021) Children and parents: Media use and attitudes report.Google Scholar
Oh, E, Jorm, AF and Wright, A (2009) Perceived helpfulness of websites for mental health information: A national survey of young Australians. Social Psychiatry and Psychiatric Epidemiology 44(4), 293299. https://doi.org/10.1007/s00127-008-0443-9CrossRefGoogle ScholarPubMed
Park, E and Kwon, M (2018) Health-related internet use by children and adolescents: Systematic review. Journal of Medical Internet Research 20(4), e120. https://doi.org/10.2196/jmir.7731CrossRefGoogle ScholarPubMed
Patterson, SP, Hilton, S, Flowers, P and McDaid, LM (2019) What are the barriers and challenges faced by adolescents when searching for sexual health information on the internet? Implications for policy and practice from a qualitative study. Sexually Transmitted Infections 95(6), 462467. https://doi.org/10.1136/sextrans-2018-053710CrossRefGoogle ScholarPubMed
Pretorius, C, Chambers, D and Coyle, D (2019) Young People’s online help-seeking and mental health difficulties. Systematic narrative review. Journal of Medical Internet Research 21(11), e13873. https://doi.org/10.2196/13873CrossRefGoogle ScholarPubMed
Rickwood, D, Deane, FP, Wilson, CJ and Ciarrochi, J (2005) Young people’s help-seeking for mental health problems. Australian e-Journal for the Advancement of Mental Health 4(3), 218251. https://doi.org/10.5172/jamh.4.3.218CrossRefGoogle Scholar
Rideout, V, Fox, S and Well Being Trust (2018) Digital health practices, social media use, and mental well-being among teens and young adults in the U.S.Google Scholar
Rowlands, IJ, Loxton, D, Dobson, A and Mishra, GD (2015) Seeking health information online: Association with young Australian Women’s physical, mental, and reproductive health. Journal of Medical Internet Research 17(5), e120. https://doi.org/10.2196/jmir.4048CrossRefGoogle ScholarPubMed
Ruan, S, Raeside, R, Singleton, A, Redfern, J and Partridge, SR (2021) Limited engaging and interactive online health information for adolescents: A systematic review of Australian websites. Health Communication 36(6), 764773. https://doi.org/10.1080/10410236.2020.1712522CrossRefGoogle ScholarPubMed
Scott Duncan, T, Riggare, S, Koch, S, Sharp, L and Hägglund, M (2019) From information seekers to innovators: Qualitative analysis describing experiences of the second generation of E-patients. Journal of Medical Internet Research 21(8), e13022. https://doi.org/10.2196/13022CrossRefGoogle ScholarPubMed
Smahel, D, Machackova, H, Mascheroni, G, Dedkova, L, Staksrud, E, Ólafsson, K, Livingstone, S and Hasebrink, U (2020) EU Kids Online 2020: Survey results from 19 countries. https://doi.org/10.21953/lse.47fdeqj01ofo.CrossRefGoogle Scholar
Valkenburg, PM, Krcmar, M, Peeters, AL and Marseille, NM (1999) Developing a scale to assess three styles of television mediation: “instructive mediation. Restrictive Mediation,” and “Social Coviewing”. Journal of Broadcasting & Electronic Media 43(1), 52. https://doi.org/10.1080/08838159909364474CrossRefGoogle Scholar
van der Vaart, R, van Deursen, AJ, Drossaert, CH, Taal, E, van Dijk, JA and van de Laar, MA (2011) Does the eHealth literacy scale (eHEALS) measure what it intends to measure? Validation of a Dutch version of the eHEALS in two adult populations. Journal of Medical Internet Research 13(4), e86. https://doi.org/10.2196/jmir.1840CrossRefGoogle ScholarPubMed
Walraven, A, Brand-Gruwel, S and Boshuizen, HPA (2009) How students evaluate information and sources when searching the world wide web for information. Computers & Education 52(1), 234246. https://doi.org/10.1016/j.compedu.2008.08.003CrossRefGoogle Scholar
Williams, D (2006) On and off the ′net: Scales for social Capital in an Online era. Journal of Computer-Mediated Communication 11(2), 593628. https://doi.org/10.1111/j.1083-6101.2006.00029.x%jCrossRefGoogle Scholar
Wong, DK and Cheung, MK (2019) Online health information seeking and eHealth literacy among patients attending a primary Care Clinic in Hong Kong: A cross-sectional survey. Journal of Medical Internet Research 21(3), e10831. https://doi.org/10.2196/10831CrossRefGoogle Scholar
Yang, HH, Huang, FF, Lai, YH, Yang, HJ and Yu, JC (2012) Social capital and technological literacy in Taiwan. ScientificWorldJournal 2012, 149132. https://doi.org/10.1100/2012/149132CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Adolescent’s internet use, eHealth literacy and health status

Figure 1

Table 2. Adolescents’ pursuit of health information online and health topics searched

Figure 2

Table 3. Factors related to adolescents’ eHealth literacy

Figure 3

Table 4. Factors related to adolescent pursuit of health information online

Figure 4

Table 5. Factors related to the number of health topics searched online

Author comment: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R0/PR1

Comments

Dear Editor,

This study is an original research. Each author has contributed significantly to the work. Authors have no conflict of interest regarding the paper. In this study we assessed adolescent pursuit of health information and mental health information online and examined the relationships with eHealth literacy, psychological distress, and parental Internet mediation during the COVID-19 pandemic. We are grateful for your help and kindness.

Best wishes,

Sincerely,

Fong-ching Chang

Professor,

Department of Health Promotion and Health Education

National Taiwan Normal University

Review: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R0/PR2

Conflict of interest statement

Reviewer declares none.

Comments

This is an interesting study about psychological factors associated with online health information seeking among adolescents in Taiwan. Although the study does have merit, it has some drawbacks that need to be addressed to make the paper stronger.

Introduction

"A UK study showed that the time children and adolescents spend online

is increasing" - please specify from what year to what year. Also, provide a reference after this sentence.

Overall, I suggest that the authors omit the location where the studies cited in the Introductions were from, but rather make the first paragraph have more flow to build your rationale for the study. In the present form, the authors keep on citing different studies, but it seems that there is no link between the sentences.

In the second paragraph, I suggest that the authors provide a more detailed rationale on how the COVID-19 pandemic affected people including adolescents' mental health to build your case.

In the present form, the Introduction is too long, and there is no clear outline of the study rationale.

The aim is not clearly written. The authors first mention the outcomes of the study and then they mention potential independent predictors of their outcomes. It would be better to number the aims and then articulate which independent predictors might be associated with the study outcomes.

Methods

Please cite the studies which you used to develop your questionnaire.

The description of the eHEALS reads oddly. The sentences are written under quotation marks, but it is not clear why they stand alone with no link to the latter and former sentences. Please correct. The same applied to the description of other questionnaires.

“A serious of t tests were...” needs to be corrected. What did the authors want to say?

The authors need to describe the rationale for building their regression model and explain the dependent and the independent variables in the manuscript, as there are several of them. The authors need to describe in detail each and every model.

Results

The results are not clear. The authors say in the text that they examined seeking information about mental health online, but in Table 5 they mention the number of topics sought. It is not clear what the outcome is.

Overall, I suggest removing the regression model for e-health literacy as the results do not materially add much to the main aim of this research.

Please add 95CI for each B in the linear regression.

This manuscript needs to be proofread by a native English speaker.

Review: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R0/PR3

Conflict of interest statement

Reviewer declares none.

Comments

Abstract: might profit from some more background (rationale) and details such as exact statistics of amin outcomes. The Impact section does however provide more background and rationale – one part of the Results is a bit hard to process (i.e., ‘had higher levels of active Internet mediation by parents were more likely to have higher levels of eHealth literacy’).

Introduction: authors report relevant background on adolescents’ search for health information world-wide and the difficulties they encounter. The importance of eHealth literacy to arrive at the appropriate eHealth services is also stressed. A definition of Health literacy is provided but maybe the distinction between perceived and performance based eHealth literacy would be helpful for readers as well (as it seems important the way it is phrased here). I wondered at some point what age group is aimed at here; adolescents 10 to 19 but also student findings are presented. Relevance of parental mediation and in terms of lack of evidence on Health literacy in adolescents is clear. Roughly all relevant concepts have been substantiated in the Introduction accept the role of self-determination.

Methods:

What is meant by ‘representative adolescent nationals’: no diversity in terms of ethnicity? Was a range selected in terms of age? How were respondents approached in the schools? More details are needed here – in order to receive more information on sample selection etc.

Regarding instruments used, a self-administered questionnaire was developed based on previous studies. What studies, please refer to the sources (later on this is provided though). Please provide a more information on psychometrics (particularly validity ‘the extent to which an instrument measures what it asserts to measure’) such as for the eHealth literacy questionnaire and Bonding social capital. The psychological distress scale also needs to be better substantiated: 4 items with two on the main depression symptoms and two on anxiety is very limited.

In the statistical analysis plan, please also define predictors and outcomes more clearly. Were the multiple (logistic) regression models corrected for confounders, were covariates age, gender etc. included in the models? No information on confidence intervals nor p-values provided. This part is insufficiently elaborated; also no information on informed consent provided / anonymity etc.

Results:

No age range of participants provided in Table or Text. The difference between boys and girls in eHealth literacy might be related to by their self-determinism (they think they are more competent in appraising the information on the internet). For proper interpretation, please re-phrase sentences like: ‘….that adolescents who were boys, had higher levels of eHealth literacy, had higher levels of depression and anxiety, had higher levels of parental active Internet mediation were more likely to seek health information online’ into ‘adolescents who were boys, who had higher levels of eHealth literacy, who had higher levels of depression and anxiety, or who had higher levels of parental active Internet mediation were more likely to seek health information online.’ The interpretation of the findings is hard to follow otherwise (please also adapt similar phrasings throughout the manuscript). Tables are simple but informative; level of analyses relatively basic. Age would have been valuable to include as a factors as well but middle vs high school may serve as a proxy for age here.

Discussion:

Main findings are presented and reflected on in light of the literature. Important that authors also stress the practical implications such as the need to implement eHealth literacy combined with critical media literacy programs to strengthen adolescents’ eHealth literacy competence since this is actually not measured in this study. Also, the roles of social bonding and parental mediation in eHealth literacy are interesting and of value. Meta-data of adolescents in an experimental setting where they are asked to search for health related information could be combined with self-reports in future research. Self-determination theory is now adequately related to the findings and topic of study (opposed to the lack of it in the Introduction). The Conclusion section seems more a full replication/recap of the results; this could be more balanced. So include a reiteration of the research problem with a summary of only the key findings and a short discussion of the implications of your research also for future research.

Recommendation: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R0/PR4

Comments

No accompanying comment.

Decision: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R0/PR5

Comments

No accompanying comment.

Author comment: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R1/PR6

Comments

Dear Dr. Bass:

We appreciate the reviewers’ helpful comments. We have made changes in response to the comments. We are grateful for your help.

Best wishes,

Sincerely,

Fong-ching Chang

Review: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R1/PR7

Conflict of interest statement

Reviewer declares none.

Comments

The authors have responded to all my concerns.

I have no further comments.

Recommendation: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R1/PR8

Comments

No accompanying comment.

Decision: Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress — R1/PR9

Comments

No accompanying comment.