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Gender difference in the associations between health literacy and problematic mobile phone use in Chinese middle school students
BMC Public Health volume 23, Article number: 142 (2023)
Problematic mobile phone use (PMPU) is becoming increasingly popular and has serious harmful effects on physical and mental health among adolescents. Inadequate health literacy (HL) is related to some risky behaviors and mental health problems in adolescents. Nevertheless, few studies have explored the relationship between HL and PMPU and the gender difference in the relationship among Chinese adolescents. The aim of this study was to examine the associations between HL and PMPU and explore gender difference in the associations.
A total of 22,628 junior and senior high school students (10,990 males and 11,638 females) in 6 regions of China participated in this study. HL and PMPU were measured by self-report validated questionnaires. Chi-square tests and logistic regression analysis were conducted in the study.
Logistic regression analysis showed that students with inadequate HL are likely to have PMPU (OR = 2.013, 95% CI: 1.840–2.202), and different degrees of association can be seen in six dimensions. Besides, in both males and females, students with inadequate HL had a higher risk of PMPU (OR male = 1.607, 95% CI: 1.428–1.807; OR female = 2.602, 95% CI: 2.261–2.994). Regarding the gender difference, the results showed that males had more PMPU than females, and the difference was more significant for students with adequate HL than those with inadequate HL (OR inadequate = 1.085, 95% CI: 1.016–1.159; OR adequate = 1.770, 95% CI: 1.490–2.101). Similarly, there were associations in the six dimensions.
HL decreases PMPU, and males have a higher risk of PMPU than females. These findings suggest a reasonable strategy to reduce PMPU by improving the HL level of adolescents.
In recent years, the usage of mobile phones has increased dramatically. A report from the WHO estimated approximately 6.9 billion mobile phone users worldwide in 2014 . In developed countries such as the United States, approximately 64% of the population used smartphones in 2017 . In addition, smartphone usage in developing countries, such as India, is also expected to reach 36.0% by 2018, and approximately 50.6% of Turkish teenagers are problem phone users [3, 4]. Meanwhile, the China Youth Internet Behavior Survey Report of 2015 indicated that the number of Chinese youth internet users reached 287 million, accounting for 85.3% of the total Chinese youth population, which is much higher than the overall national internet users in 2015 (50.3%) . Obviously, mobile phone use is very widespread among teenagers around the world.
Mobile phones not only bring us convenience but also harm our health. Studies have revealed that excessive use of mobile phones can trigger various physical disorders, such as blurred vision, local pain and obesity [6, 7]. Moreover, the use of smartphones may cause some addictive behaviors and further induce mental health problems, including phone addiction, sleep disorders, anxiety and depression [8,9,10]. Problematic mobile phone use (PMPU) refers to “Failure to regulate personal cell phone use that may have a negative impact on daily life” . Because of the high sensitivity of adolescents to PMPU, concerns have been raised about the possible influences on health of mobile phone use, particularly on children and adolescents . It is thus important to develop strategies to countervail PMPU in adolescents. Some strategies have been used in many families for example limiting the use of cellphone by specific software or implementation plan, which are proven effective. Besides, it has been reported that exercise intervention, improvement of self-control, or psychological treatment that are strongly associated with better health literacy (HL), are effective to improve PMPU . It is thus reasonable to reduce PMPU by improving HL.
HL is defined as how well a person can obtain and understand health information and services, and use them to make good health decisions . Additionally, Nutbeam proposed that HL is a more advanced cognitive and literacy skill that can be used to actively participate in everyday activities and apply new information to changing circumstances . More notably, the theoretical framework of adolescence HL suggests that HL can have different degrees of influence on a variety of health behaviors . Many studies have examined and demonstrated the negative association between HL and health-risk behaviors, such as smoking, alcohol use, self-harm, screen time, and suicidal behaviors [15,16,17], which strongly supports the important role of HL in adolescent health promotion .
Adolescence is an important period in everyone’s life, and improving health status during this period is thus of vital importance and can greatly affect people’s lifelong health . However, adolescents often lack correct health awareness and health management ability, so they frequently fail to make correct health choices, which will lead to a series of health risk behaviors, such as sexual risk behavior, and internet addiction [20, 21]. Regarding internet addiction, some literatures have pointed to that there is a difference in mobile phone use between males and females, and male have a greater possibility of having PMPU and internet addiction [22, 23]. However, controversy exists in this issue, and some other studies have shown that females are more addicted to phones than males [13, 24]. It can be seen that the gender difference in mobile phone use is an issue worthy of discussion.
Nevertheless, most of the previous studies were based on relatively small populations, and few Chinese studies concerned the relationship between HL and PMPU as well as the gender difference in the relationship. In this study, we investigated the association of HL and PMPU in Chinese adolescents and tackled the gender difference in the association based on a questionnaire survey among junior and senior high school students in six cities of China to provide guidance for reducing PMPU in Chinese adolescents.
Material and methods
From November 2015 to January 2016, convenience sampling was used to select samples from junior and senior high schools in 6 cities in China, including urban and rural areas. The 6 cities are Xinxiang(a city in northern Henan Province), Shenyang (the capital of Liaoning Province), Bengbu(a city in northeastern Anhui Province), Chongqing (one of China’s four direct controlled municipalities), Ulanqab(a city in the central Inner Mongolia Autonomous Region) and Yangjiang(a city in the southwest coast of Guangdong Province). Then, we selected 8 schools from each city, and 4–6 classes were selected for each grade of every school for investigation.
The questionnaires consist of questions on demographic variables (i.e., gender, grade, registered residence, accommodation type, type of school, household structure, parents’ educational level, self-reported family economy and number of friends), the Self-rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU) and the Chinese Adolescent Interactive Health Literacy Questionnaire (CAIHLQ), as described below.
The CAIHLQ was used to assess the HL level. It consists of 31 items grouped into 6 domains, including physical activities (e.g., ‘Following a planned exercise program’), interpersonal relationships (e.g., ‘Taking times with your family or friends’), stress management (e.g., ‘Balance time between study and play’), self-actualization (e.g., ‘Feeling each day is very meaningful’), health awareness (e.g., ‘Constricting sugars and food containing sugar’), and dietary behavior (e.g., ‘Eating 200–400 g of fresh fruit each day’) . Each item is rated on a 5-point Likert scale (never and no desire, never but with desire, occasionally and irregularly, often, and routinely), and the total score ranges from 31 to 155, with higher scores indicating better HL . Participants in this study were categorized as adequate HL groups when their scores were ≥ 120. In this study, the internal consistency test showed that the Cronbach’s α coefficient was 0.910 and 0.662 to 0.847 for the six subscales, and the reliability and validity of the CAIHLQ have been demonstrated in previous studies [15, 26].
The SQAPMPU includes 13 items and 3 domains, including withdrawal symptoms (e.g., ‘If I don’t have a phone, I will feel overwhelmed’); craving (e.g., ‘I always feel that I don’t have enough time to use my phone’), and psychosomatic effects (e.g., ‘Too much mobile phone use leads to insufficient sleep’) . Each item is responded to on a 5-point Likert scale (never, occasionally, sometimes, often, and always). Exploratory factor analysis showed that the cumulative variance contribution rate of the questionnaire was 59.13%, and Cronbach’s α coefficient was 0.87. In this study, the Cronbach’s α coefficient was 0.923. The Cronbach’s α coefficients of the three dimensions are 0.879 (withdrawal symptoms), 0.711(craving), and 0.832(psychosomatic effects). According to previous studies, students in this study were categorized as PMPU when this score was ≥ P75 .
The study was conducted in accordance with the Declaration of Helsinki and obtained approval from the Ethics Committee of Anhui Medical University (March 1, 2014; Approval No. 20140087). Informed consent was obtained from all subjects and their parents. In addition, we trained investigators through lectures, discussions and practice. During the investigation, the investigators explained the purpose of the investigation and the instructions for completing the questionnaire, and then each participant completed a self-report questionnaire within 20 to 30 minutes. The investigators withdrew the questionnaires at the scene. After the investigation, the investigators sorted out and recorded the questionnaires.
Statistical analysis was performed by SPSS ver. 23.0 for Windows (SPSS, Inc., Chicago, IL). Cronbach’s alpha analysis was performed to determine the reliability of the survey. The chi-square test was used to compare the prevalence of PMPU among different demographic variables. Binary logistic regression models were performed to examine the association between the 6 domains of HL and PMPU in all students, males, and females. In addition, subgroup analysis was used to separate gender differences in different groups of HL. Analyses were adjusted based on control for key demographic and socioeconomic variables. Statistical significance was set at P < 0.05.
After excluding 507 invalid questionnaires (missing rate ≥ 5%), a total of 22,628 questionnaires were included in the survey (effective rate was 97.8%); 10,990 were male (48.6%), and 11,638 were female (51.4%). Participants had a mean age of 15.18 years (SD = 1.79), and the overall CAIHLQ mean score for all students was 104.06 ± 18.68. The CAIHLQ scores were normally distributed, and the variability of the data was consistent. Table 1 presents the prevalence of PMPU by frequency characteristics. Male students had a significantly higher prevalence of PMPU than female students [male (26.5%) vs. female (24.4%)]. Likewise, the prevalence of PMPU in senior high school students, only children, key school students, students without friends and students with poor family economic conditions was significantly higher than that in matched groups, e.g., junior high school students, more than one child, nonkey school students and so on (P < 0.05 for each). However, there were no statistically significant differences in registered residence and parents’ educational levels (P > 0.05 for each, Table 1).
Logistic regression analysis
After adjusting for the effect of gender, grade, accommodation type, type of school, household structure, self-reported family economy, and number of friends, inadequate HL was significantly associated with an increased risk of PMPU (OR = 2.013, 95% CI: 1.840–2.202). Meanwhile, inadequate HL in six domains was significantly positively correlated with PMPU (Table 2).
Gender difference in the association between HL and PMPU
As shown in Fig. 1, students with inadequate HL had a high risk of PMPU in both males (OR male=1.607, 95% CI: 1.428–1.807) and females (OR female=2.602, 95% CI: 2.262–2.994). This relationship was also seen in the six dimensions of HL with PMPU (Fig. 1A, B, Table A1). Besides, regarding gender, the results showed that males had a higher risk of PMPU than females in all the students, regardless of adequate or inadequate HL (OR inadequate=1.085, 95% CI: 1.016–1.159; OR adequate=1.770, 95% CI: 1.490–2.101). This association could also be seen in six dimensions in students with adequate interpersonal relationship HL (Fig. 1C, Table A1).
In this study, we examined the association between PMPU and HL in junior and senior high school students in China. As hypothesized, students with inadequate HL had more PMPU than those with adequate HL. In addition, males had a higher risk of PMPU than females among students with both inadequate and adequate HL.
The results revealed that males, senior high school students, boarding students, key school students, students with lower family income and no friends had a higher prevalence of PMPU than the matched groups, which is consistent with previous studies [29,30,31,32]. According to previous studies, friendships play an important role in problematic behaviors among adolescents . When adolescents lack the companionship of friends, they relieve loneliness by keeping in touch with their peers through online dating, thus leading to PMPU, which is consistent with our study that the students with fewer friends have more PMPU [33, 34]. Additionally, the prevalence of PMPU in commuting students was lower, which may be related to the stricter supervision of parents when students are at home and parents could accompany them and give them support more . However, our results indicated that parents’ educational levels have no significant effects on PMPU among adolescents, whereas a previous study reported the opposite results . The different results may be related to the choice of the population and the inconsistency of the measurement tools, which warrants further investigation in the future.
Our findings suggested that adolescents with inadequate HL (both HL and six domains) are more likely to have PMPU. This may be because adolescents with inadequate HL cannot read, understand, and obtain information sufficiently, resulting in the inability to fully benefit from media interventions, events or educational projects . As known, health awareness is a vital indicator of a person’s awareness of health problems, and individuals unaware of their health problems may be more prone to aggravated health risk behaviors, such as PMPU . Studies have shown that the problems of internet addiction arose among adolescents due to the lack of health awareness and emotional management ability [39, 40]. As the Billieus PMPU access model demonstrates, emotional management and interpersonal relationship are important ways to lead to PMPU. Others studies have also pointed out that good interpersonal relationships can indirectly reduce adolescents’ PMPU by alleviating loneliness and motivation because loneliness can lead to excessive and compulsive use of mobile phones to relieve symptoms and deal with bad emotions, leading to a vicious cycle and thus increasing the risk of PMPU . These findings are in accordance with our study, which suggested that high emotional pressure can lead to problematic mobile use . Besides, stress and stress management are negative predictors of mobile phone addiction [40, 43]. Moreover, a study on adolescents showed that dietary behavior was linked with stress , and stress may affect PMPU in an indirect way through unhealthy dietary behavior. In addition, the relation between physical activity and PMPU can be explained by the use of time, because more physical activity will naturally reduce the time spent on mobile phones. Taken together, it is reasonable to utilize HL and the multiple dimensions of HL for the prediction of adolescents’ PMPU.
Furthermore, we found that PMPU was more likely to occur in males, which was inconsistent with a study in Saudi Arabia , and it may result from males usually showing extroverted personality, which makes them more active in trying new technologies, such as the desire to possess the mobile phone model, to play games or assess the internet, while females use mobile phones mostly for social contact, and fulfilling their need for closeness, communication and emotional expressions . Moreover, males’ impulsive personality may make them more likely to engage in risky health behaviors even with adequate health awareness . Interestingly, the present study revealed that among students with adequate HL, the gender difference in PMPU was slightly greater than that among students with inadequate HL. Based on these results, we considered that inadequate HL can weaken the differences between males and females in PMPU. Nevertheless, the mechanisms by which HL affects this difference remain to be further studied.
This study was an epidemiologic study with large samples, and we selected participants from both rural and urban regions, considering the difference in the different socioeconomic conditions. In addition, the SQAPMPU and CAIHLQ were developed on based the characteristics of Chinese teenagers and have excellent reliability, constructive validity and pertinence. However, some limitations should also be noted. First, only six cities were included, and the validity of this study for students in other regions is not fully clear and needs further investigation. The second issue is the reliance on the self-report nature of the data, in which recall and reporting biases could not be avoided. Finally, the cross-sectional design cannot fully reflect the causal relationships. Longitudinal studies are needed in the future to clarify the causal relationships between HL and PMPU.
In summary, our results suggested a negative association between HL and PMPU. Meanwhile, males have a higher risk of PMPU than females, and students with adequate HL have a slightly higher gender difference in PMPU than students with inadequate HL. From a prevention standpoint, in order to reduce the prevalence of PMPU among adolescents, it should be considered to improve adolescents’ HL levels, especially for males, by, for example, carrying out health education classes or lectures regularly in school and by subscribing to health knowledge.
Availability of data and materials
The datasets generated and/or analysed during the current study are not publicly available, but are available from the corresponding author on reasonable request.
World Health Organization. Electromagnetic fields and public health: mobile phones, 2014. https://www.who.int/zh/news-room/fact-sheets/detail/electromagnetic-fields-and-public-health-mobilephones. Accessed 2 May 2022.
Statista Smartphones in the U.S.: Statistics and Facts. https://www.statista.com/topics/2711/us-smartphone-market/. Accessed 2 May 2022.
Statista Share of Mobile Phone Users That Use a Smartphone in India From 2014 to 2019. https://www.statista.com/statistics/257048/smartphone-user-penetration-in-india/. Accessed 2 May 2022.
World Health Organization. Public health implications of excessive use of the internet, computers, smart phones and similar electronic devices: Meeting report, Main Meeting Hall, Foundation for Promotion of Cancer Research, National Cancer Research Centre, Tokyo, Japan, 27–29 August 2014. Geneva, Switzerland: WHO. http://www.who.int/iris/handle/10665/184264#sthash.iy5Vm60q.dpuf. Accessed 2 May 2022.
China Internet Network Information Center. 2015 Research Report of Chinese Youth Online Behavior. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/qsnbg/201608/P020160812393489128332.pdf. Accessed 2 May 2022.
Ng KC, Wu LH, Lam HY, Lam LK, Nip PY, Ng CM, et al. The relationships between mobile phone use and depressive symptoms, bodily pain, and daytime sleepiness in Hong Kong secondary school students. Addict Behav. 2020;101:105975.
Ahammed B, Haque R, Rahman SM, Keramat SA, Mahbub A, Ferdausi F, et al. Frequency of watching television, owning a mobile phone and risk of being overweight/obese among reproductive-aged women in low- and lower-middle-income countries: a pooled analysis from demographic and health survey data. J Biosoc Sci. 2022;16:1–14.
Oviedo-Trespalacios O, Nandavar S, Newton JDA, Demant D, Phillips JG. Problematic use of Mobile phones in Australia … is it getting worse? Front Psychiatry. 2019;10:105.
Tao SM, Wu XY, Zhang YK, Zhang SC, Tong SL, Tao FB. Effects of sleep quality on the association between problematic Mobile phone use and mental health symptoms in Chinese college students. Int J Environ Res Public Health. 2017;14:185.
Park SY, Yang S, Shin CS, Jang H, Park SY. Long-term symptoms of Mobile phone use on Mobile phone addiction and depression among Korean adolescents. Int J Environ Res Public Health. 2019;16:3584.
Ge RK, Zhong XM, Chen R. Influence of exercise intervention on mobile phone dependence in university students. Modern Prev Med. 2015;21:3919–21 (In Chinese).
U.S. National Library of Medicine. Health Literacy. https://medlineplus.gov/healthliteracy.html. Accessed 2 May 2022.
Nutbeam D. The evolving concept of health literacy. Soc Sci Med. 2008;67:2072–8.
Manganello JA. Health literacy and adolescents: a framework and agenda for future research. Health Educ Res. 2008;23:840–7.
Zhang SC, Tao FB, Wu XY, Tao SM, Fang J. Low health literacy and psychological symptoms potentially increase the risks of non-suicidal self-injury in Chinese middle school students. BMC Psychiatry. 2016;16:327.
Chang FC, Miao NF, Lee CM, Chen PH, Chiu CH, Lee SC. The association of media exposure and media literacy with adolescent alcohol and tobacco use. J Health Psychol. 2016;21:513–25.
Yang R, Li DL, Hu J, Tian R, Wan YH, Tao FB, et al. Association between health literacy and subgroups of health risk behaviors among Chinese adolescents in six cities: a study using regression. Int J Environ Res Public Health. 2019;30:16.
Paakkari LT, Torppa MP, Paakkari OP, Välimaa RS, Ojala KSA, Tynjälä JA. Does health literacy explain the link between structural stratifiers and adolescent health? Eur J Pub Health. 2019;29:919–24.
Cheng HL, Harris SR, Sritharan M, Behan MJ, Medlow SD, Steinbeck KS. The tempo of puberty and its relationship to adolescent health and well-being: a systematic review. Acta Paediatr. 2020;109:900–13.
Zhen R, Liu RD, Hong W, Zhou X. How do interpersonal relationships relieve Adolescents' problematic Mobile phone use? The roles of loneliness and motivation to use Mobile phones. Int J Environ Res Public Health. 2019;16:2286.
Rolová G, Barták M, Rogalewicz V, Gavurová B. Health literacy in people undergoing treatment for alcohol abuse-a pilot study. Kontakt. 2018;20:394–400.
Shimoni L, Dayan M, Cohen K, Weinstein A. The contribution of personality factors and gender to ratings of sex addiction among men and women who use the internet for sex purpose. J Behav Addict. 2018;1(7):1015–21.
Fernández-Villa T, Alguacil Ojeda J, Almaraz Gómez A, Cancela Carral JM, Delgado-Rodríguez M, García-Martín M, et al. Problematic internet use in university students: associated factors and differences of gender. Adicciones. 2015;27:265–75.
Li L, Lok GKI, Mei SL, Cui XL, Li L, Ng CH, et al. The severity of mobile phone addiction and its relationship with quality of life in Chinese university students. PeerJ. 2020;8:e8859.
Zhang SC, Wan YH, Tao SM, Chen J, Tao FB. Reliability and construct validity of the Chinese adolescent interactive health literacy questionnaire. Chin J Sch Health. 2014;35:332–6 (In Chinese).
Zhang SC, Yang R, Li DL, Wan YH, Tao FB, Fang J. Association of health literacy and sleep problems with mental health of Chinese students in combined junior and senior high school. PLoS One. 2019;14:e0217685.
Tao SM, F JL, Wang H, Hao JH, Tao FB. Development of self-rating questionnaire for adolescent problematic mobile phone use and the psychometric evaluation in undergraduates. Chin. J Sch Health. 2013;34:26–9 (In Chinese).
Li DL, Yang R, Wan YH, Tao FB, Fang J, Zhang SC. Interaction of health literacy and problematic Mobile phone use and their impact on non-suicidal self-injury among Chinese adolescents. Int J Environ Res Public Health. 2019;16:2366–78.
Fischer-Grote L, Kothgassner OD, Felnhofer A. Risk factors for problematic smartphone use in children and adolescents: a review of existing literature. Neuropsychiatr. 2019;33:179–90.
Lee C, Lee SJ. Prevalence and predictors of smartphone addiction proneness among Korean adolescents. Child Youth ServRev. 2017;77:10–7.
Kwak JY, Kim JY, Yoon YW. Effect of parental neglect on smartphone addiction in adolescents in South Korea. Child Abuse Negl. 2018;77:75–84.
Mollborn S, Lawrence E. Family, peer, and school influences on Children's developing health lifestyles. J Health Soc Behav. 2018;59:133–50.
Reiter AMF, Suzuki S, O'Doherty JP, Li SC, Eppinger B. Risk contagion by peers affects learning and decision-making in adolescents. J Exp Psychol Gen. 2019;148:1494–504.
Kuss DJ, Kanjo E, Crook-Rumsey M, Kibowski F, Wang GY, Sumich A. Problematic Mobile phone use and addiction across generations: the roles of psychopathological symptoms and smartphone use. J Technol Behav Sci. 2018;3:141–9.
Ihm J. Social implications of children’s smartphone addiction: the role of support networks and social engagement. J Behav Addict. 2018;7:473–81.
Sánchez-Martínez M, Otero A. Factors associated with cell phone use in adolescents in the community of Madrid (Spain). CyberPsychol Behav. 2009;12:131–7.
Chen MJ, Ni CH, Hu YH, Wang ML, Liu L, Ji XM, et al. Meta-analysis on the effectiveness of team-based learning on medical education in China. BMC Med Educ. 2018;18:77.
Brasil EGM, Silva RMD, Silva MRFD, Rodrigues DP, Queiroz MVO. Adolescent health promotion and the school health program: complexity in the articulation of health and education. Rev Esc Enferm USP. 2017;51:e03276.
Mazhari S. Association between problematic internet use and impulse control disorders among Iranian university students. Cyberpsychol Behav Soc Netw. 2012;15:270–3.
Wang Q, Liu Y, Wang B, An Y, Wang H, Zhang Y, et al. Problematic internet use and subjective sleep quality among college students in China: results from a pilot study. J Am Coll Heal. 2022;70:552–60.
Billieux J, Gay P, Rochat L, Linden MWD. The role of urgency and its underlying psychological mechanisms in problematic behaviours. Behav Res Ther. 2010;48:1085–96.
Jeong SH, Kim H, Yum JY, Hwang Y. What type of content are smartphone users addicted to? SNS vs games Comput Hum Behav. 2006;54:10–7.
Kwon M, Kim DJ, Cho H, Yang S. The smartphone addiction scale: development and validation of a short version for adolescents. PLoS One. 2013;8:e83558.
Hill DC, Moss RH, Sykes-Muskett B, Conner M, O'Connor DB. Stress and eating behaviors in children and adolescents: systematic review and meta-analysis. Appetite. 2018;123:14–22.
Alkhateeb A, Alboali R, Alharbi W, Saleh O. Smartphone addiction and its complications related to health and daily activities among university students in Saudi Arabia: a multicenter study. J Family Med Prim Care. 2020;9:3220–4.
Warzecha K, Pawlak A. Pathological use of mobile phones by secondary school students. Arch Psychiatry Psychother. 2017;1:27–36.
Bem D, Connor C, Palmer C, Channa S, Birchwood M. Frequency and preventative interventions for non-suicidal self-injury and suicidal behaviour in primary school-age children: a scoping review protocol. BMJ Open. 2017;7:e017291.
We gratefully acknowledge all the participants and data acquisition staff for their on-site cooperation during the data acquisition process.
We are grateful for the financial support offered by the Innovation Team Project of Anhui Medical College (WJH2022001t), the National Ministry of Education Humanities and Social Science Research Planning Fund Project (21YJAZH120), the Natural Science Foundation in Higher Education of Anhui (2022AH052320), and the National Natural Science Foundation of China (81573512) for the data collection, in writing and publishing the manuscript.
Ethics approval and consent to participate
The study was conducted in accordance with the Declaration of Helsinki and obtained the approval from the Ethics Committee of Anhui Medical University (March 1, 2014; Approval No. 20140087), informed consent was obtained from all subjects and their parents.
Consent for publication
The authors declare no conflict of interest.
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Additional file 1: Table A1.
Odds ratio (95% CI) associated with HL and PMPU in male and female, and the gender comparison.
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Li, DL., Wang, S., Zhang, D. et al. Gender difference in the associations between health literacy and problematic mobile phone use in Chinese middle school students. BMC Public Health 23, 142 (2023). https://doi.org/10.1186/s12889-023-15049-4
- Health literacy
- Addictive behavior
- Gender difference