Health Management and Policy Section DOI : 10.7860/JCDR/2019/40306.12932
Year : 2019 | Month : Jun | Volume : 13 | Issue : 06 Page : IC01 - IC05

The Bivariate Correlation of Health Literacy and Cell Phone Addiction amongst Iranian Healthcare Students

Elyas Soltani1, Masoud Rezaei2, Morteza Nasiri3, Salman Barasteh4, Fatemeh Rahmati-Najarkolaei5, Maryam Amidi Mazaheri6

1 Student Research Committee, Department of Critical Care Nursing, Faculty of Nursing and Midwifery, Tehran University of Medical Sciences, Tehran, Iran.
2 Student Research Committee, Department of Nursing, Faculty of Nursing and Midwifery, Iran University of Medical Sciences, Tehran, Iran.
3 Student Research Committee, Department of Operating Room Technology, Faculty of Nursing and Midwifery, Shiraz University of Medical Sciences, Shiraz, Iran.
4 Student Research Committee, Faculty of Nursing, Baqiyatallah University of Medical Sciences, Tehran, Iran.
5 Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
6 PhD Scholar, Department of Health, Faculty of Health, Isfahan University of Medical Sciences, Isfahan, Iran.


NAME, ADDRESS, E-MAIL ID OF THE CORRESPONDING AUTHOR: Dr. Fatemeh Rahmati-Najarkolaei, Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
E-mail: fatemeh_rahmati@bmsu.ac.ir
Abstract

Introduction

Health Literacy (HL) is negatively associated with substance addiction. However, no study has examined the bivariate correlation of HL with cell phone addiction.

Aim

To investigate the correlation between HL and cell phone addiction amongst Iranian healthcare students.

Materials and Methods

This descriptive study was carried out on 287 male students (nursing, health, medicine and dentistry) in two medical universities in the northern and central part of Tehran, Iran, during February to May 2016. Data were collected via the Persian version of Mobile Phone Addiction Scale (PMPAS) and the Test Of Functional Health Literacy in Adults (TOFHLA).

Results

The total score of TOFHLA showed a significant and positive correlation with the total score of PMPAS in nursing students (r=0.063, p=0.040), whereas this relationship was negatively significant for non-nursing students (r=-0.219, p=0.023). The total score of TOFHLA significantly and positively correlated with the psychological improvement subscale of PMPAS in total and also nursing students. The same correlation was found between the total score of TOFHLA and self-control inability subscale in total (r=0.142, p=0.016), and also non-nursing students (r=0.286, p=0.003). However, a significant and negative correlation was observed between the total score of TOFHLA and anxiety and sense of loss subscale in total (r=-0.137, p=0.020) as well as non-nursing students (r=-0.260, p=0.007).

Conclusion

HL is significantly correlated with cell phone addiction in some dimensions. Based on findings, it is recommended that authorities should pay attention to HL and cell phone addiction, especially among nursing students.

Introduction

Healthcare professionals from different fields are responsible to increase society health information through information and decision making process [1]. In this domain, HL has attracted much interest in recent decades and is believed to be a powerful element for promoting health-behaviours and information, by determining health inequalities, both in industrial and developing countries [2,3]. HL is considered as a person’s ability to acquire, describe, understand, appraise, and use basic information of health and medical services, which is appropriate for decision making and judgment regarding healthcare, disease prevention, and health promotion in everyday life [4,5]. In Iran, as a developing country, HL has attracted much attention and investigations have revealed insufficient HL in a large percentage of Iranian healthcare students [6-9]. In a cross-sectional study, the students had average HL about the management and recycling of solid waste [8]. In another study, students had low HL about depression in some domains [9].

Despite the importance of HL, few studies were conducted on the link between HL and addiction amongst healthcare students. In this regards, findings revealed that there is an inverse association between HL and substance addiction (i.e., alcohol, smoking, and narcotic drugs) [10-12]. However, there is a lack of knowledge about the relation between HL and behavioural addictions in this population.

Cell phone addiction, is a common behavioural addiction resulting from modern technology, is defined as excessive behavior in using technology, such as smart phones, phone applications or online games [13]. Lately, this type of addiction is on the rise amongst healthcare students in developing countries, especially Iran [14-17]. The prevalence of excessive mobile phone usage was reported to be 36.7% among the healthcare students in northeastern Iran, which was higher than other countries [16]. In another study at Isfahan University of Medical Sciences, the prevalence of cell phone addiction was 56.2% and 64.5% for female and male students [17].

Some recent investigations have emphasised on the role of HL in cell phone usage in different population [18-22]. As far as we know, no study has examined the bivariate correlation of HL with cell phone addiction among college students, yet. Giving the importance of cell phone addiction and HL in healthcare students, we decided to investigate the correlation of these two variables in a sample of Iranian healthcare students and also compare this correlation amongst nursing and non-nursing students. We hypothesised that low HL would be associated with higher cell phone addiction compared to those with higher HL.

Materials and Methods

The present cross-sectional, descriptive, correlational study was carried out on male students of nursing, health, medicine, and dentistry in two Iranian universities in the northern and central part of Tehran, Iran, during February to May 2016. The inclusion criteria were as follow: 1) being 18 years or older; 2) having a simple or smart phone; and 3) lack of any confirmed psychological problems. Students who filled out the questionnaires incompletely and those who were unwilling to participate in the study were excluded.

Sampling was done through a cluster random method in a way that students of each educational degree (associate, bachelor, master, and doctor of medicine) were categorised as separate clusters. Clusters were selected randomly and sampling in each cluster was conducted based on the inclusion and exclusion criteria. Based on Cochran formula, a total of 310 students were calculated as sample size, with N (target population number)=1600, p=0.5, q=0.5, d=0.05, and type I error of 5%. To obtain confident results, we considered 350 students. Out of these, 63 students were excluded due to incomplete questionnaires and final analysis was done on 287 students (114 in one university and 173 in another).

The study was approved by the local Ethics Committee of Baqiyatallah University of Medical Sciences, Tehran, Iran (IR.BMSU.REC.1395.42). Prior to enrolment, a written informed consent was taken from all students. Then, data were collected with three questionnaires including basic information, the Persian version of TOFHLA [23], and the PMPAS [24] through self-report method. In the questionnaire of basic information, the students were investigated in terms of age, marital status, economic status, educational degree, major, and type of cell phone.

The Persian version of the TOFHLA questionnaire was used to measure HL. This questionnaire consists of two sections:

Calculation: This section measures the individual’s ability to understand and act based on instructions of healthcare providers or their instructors, which requires calculating capabilities. The section has 10 instructions according to real-life situations which include: a) directions to take medications; b) appointment time to see a doctor; c) calculating financial aid; and d) an example of a clinical test result. The instructions were presented to the students through a series of flash cards and also they were given some relevant questions.

Reading comprehension: This section consists of 50 questions that evaluates the individual’s ability to read and comprehend the three prose passages which include: a) instructions to prepare upper gastrointestinal X-ray imaging; b) patient’s rights and responsibilities; and c) a standard hospital consent forms.

According to the number of correct answers, the scores of both sections ranges from 0-50 and the total score of the sections is from 0-100 (the higher score indicates the higher HL). Students’ HL scores were categorised as insufficient (0-59), border (60-74), and satisfactory (75-100). The validity and reliability of the Persian version of the TOFHLA questionnaire has been evaluated previously, revealing a reliability of 0.79 and 0.88 for calculation and reading comprehension sections [23].

The PMPAS was applied to investigate cell phone addiction. This 15-item scale investigates three subscales of cell phone addiction which include: a) self-control inability (8 items); b) anxiety and sense of loss (5 items); and c) psychological improvement (2 items). Each item has a five-point Likert scale (1=not at all, 2=rarely, 3=occasionally, 4=often, and 5=always). The total score ranges from 15-75, and the higher score indicates the higher addiction to cell phone. In a previous study [24], the Cronbach’s Alpha coefficient for internal correlation of the total, subscales of a, b, and c obtained 0.86, 0.84, 0.81 and 0.77, respectively.

Statistical Analysis

All statistical analysis was carried out using SPSS software version 18 (SPSS, Inc. Chicago, IL, USA). The p-value <0.05 was considered to be significant. Quantitative variables are shown as mean±SD and qualitative variables are represented as the number of frequency and their percentage. The Kolmogorov-Smirnov test showed the normal distribution of data. Hence, comparison of cell phone addiction between the border and satisfactory status of HL was done using independent sample t-test, considering the fact that none of the students had insufficient HL. To investigate the correlation between HL and cell phone addiction in total, nursing, and non-nursing students, the Pearson’s correlation test was used.

Results

The mean age of the students was 26.2±4.5 years and 71.1% were single. Most students (67.2%) had average monthly income. Regarding educational status, most of them (52.6%) were in bachelor degree program and most (62.4%) were nursing students. In terms of cell phone type, 91.3% used smart cell phones [Table/Fig-1].

General characteristics of the students (n=287).

VariablesNumberPercent
Marital statusSingle20471.1
Married8328.9
Monthly incomeWeak6723.3
Average19367.2
Well279.5
Educational degreeAssociate3110.8
Bachelor15152.6
Master or doctor of medicine10536.6
MajorNursing17962.4
Non-nursingMedicine4013.9
Health258.7
Dentistry4315
Cell phone typeSimple258.7
Smart phone26291.3

Total score of TOFHLA and PMPAS were 86.9±8.3 and 34.6±4.1 [Table/Fig-2]. Pertaining to HL, 22 (7.7%) and 265 (92.3%) of the students had a border and satisfactory status. Only the score of psychological improvement subscale of PMPAS among the students with satisfactory HL was significantly higher than those with border HL (p=0.01) [Table/Fig-3].

Pearson product moment correlation matrix of the Test of Functional Health Literacy in Adults (TOFHLA) with the Persian version of Mobile Phone Addiction Scale (PMPAS).

TOFHLAPMPASReading comprehension sectionCalculation sectionTotal
Mean: 45.3Mean: 41.5Mean: 86.9
SD: 4.7SD: 6.2SD: 8.3
Non-nursing(n=108)MeanSDrp-valuerp-valuerp-value
Self-control inability subscale16.543.17-0.1650.0870.2860.0030.1540.113
Anxiety and sense of loss subscale13.792.52-0.0220.036-0.1440.137-0.2600.007
Psychological improvement subscale3.521.43-0.1140.2410.0740.447-0.0560.565
Total33.874.27-0.2190.0230.0920.346-0.0570.599
Nursing(n=179)TOFHLAPMPASMean: 44.87Mean: 41.45Mean: 86.32
SD: 5.03SD: 6.48SD: 9.24
MeanSDrp-valuerp-valuerp-value
Self-control inability subscale17.443.210.0630.0400.0700.3510.0150.842
Anxiety and sense of loss subscale13.882.38-0.0680.362-0.0680.363-0.0850.257
Psychological improvement subscale3.821.490.2440.0010.1830.0140.271< 0.001
Total35.153.95-0.0240.7550.1080.1510.0630.040
TOFHLAPMPASMean: 46.25Mean: 41.66Mean: 87.91
SD: 4.12SD: 5.84SD: 6.44
MeanSDrp-valuerp-valuerp-value
TotalSelf-control inability subscale17.13.2-0.1130.0560.1420.0160.0420.482
Anxiety and sense of loss subscale13.82.4-0.1150.052-0.0960.105-0.1370.020
Psychological improvement subscale3.71.40.1330.0250.1520.0350.1690.004
Total34.64.1-0.1100.0630.0980.0990.0110.859

Comparison of cell phone addiction in the students with border and satisfactory health literacy (n=287).

Health literacyCell phone addictionBorderSatisfactoryp-value*
Mean±SDMean±SD
Self-control inability subscale17.0±2.617.1±3.20.98
Anxiety and sense of loss subscale14.5±2.313.7±2.40.14
Psychological improvement subscale2.9±1.43.7±1.40.01
Total34.6±4.634.6±4.00.96

*t-test


The correlations between TOFHLA and PMPAS in total, nursing, and non-nursing students are presented in [Table/Fig-2]. The total score of TOFHLA showed a significant and positive correlation with the total score of PMPAS in nursing students (r=0.063, p=0.040), whereas this correlation was negatively significant for non-nursing students (r=-0.219, p=0.023). Also, the total score of TOFHLA significantly and positively correlated with the psychological improvement subscale of PMPAS in total (r=0.169, p=0.004) and also nursing students (r=0.271, p<0.001), whereas, a significant and negative correlation was observed for the anxiety and sense of loss subscale in total (r=-0.137, p=0.020) as well as non-nursing students (r=-0.260, p=0.007).

Discussion

To the best of our knowledge, the present study is the first to investigate the correlation between HL and cell phone addiction amongst university students. Based on the literature review, we could not find any similar study in design to compare with our results.

According to the findings, no significant differences were seen between students with satisfactory and border HL in terms of the total score of PMPAS. In a study amongst pregnant and postpartum women, it was revealed that women with limited HL were more likely to use a cell phone than those with satisfactory HL [25]. Conversely, Bailey SC et al., showed that patients with satisfactory HL were more likely to use mobile phone or smart phone compare to those who had insufficient or border HL, which were more susceptible to cell phone addiction [26]. Also, amongst adults with type 2 diabetes, Bergner EM et al., indicated that participants with limited HL were less likely to use cell phones to access the internet compared to participants with satisfactory HL [27]. Similarly, it was stated that diabetic patients with lower HL levels were less engaged in mobile and Web-delivered self-care interventions [28]. A probable assumption for this finding is that people who have higher HL are more interested and motivated in exploration and understanding of healthcare information in their cell phones and its related virtual networks as scientific resources.

The obtained findings showed a direct and significant correlation of total score of TOFHLA with total score of PMPAS in nursing students, whereas this correlation was indirect and significant for non-nursing students. In total, a non-significant and positive correlation was observed between the total score of TOFHLA with the total score of PMPAS. In a qualitative study using thematic content analysis amongst Iranian Military University students, health information was identified as a strategy to reduce the threats of cell phone [29]. Inconsistent with our findings in a study amongst South Korea nursing students, the quantity of reading had a negative and significant correlation with smart phone addiction [30]. Also, in a study by Choi SW et al., among non-healthcare students in South Korea, an inverse significant association reported between scores of Smart phone Addiction Scale and wisdom and knowledge subscale (encompass curiosity and a love of learning) of Character Strengths Test [31]. In Iranian high school students, a negative significant correlation was reported between score of the Newest Vital Sign questionnaire and daily use of cell phone, measured with a researcher-made questionnaire [32]. Similarly, recent investigations indicated a correlation between HL and internet addiction, which positively correlated with cell phone addiction in university students [17,33]. In a study among students of Iran University of Medical Sciences, a significant and inverse relationship was revealed between information literacy and internet addiction [34]. However, in postgraduate students of Isfahan University of Medical Sciences, Soleymani MR et al., reported no significant association between the internet addiction and none of the dimensions of information-seeking behaviour [35]. In the current study, we found non-significant correlation between the total score of TOFHLA with the total score of PMPAS, which seems to be in line with the findings of Soleymani MR et al., [35].

According to the present study findings, the total score and the reading comprehension and the calculation sections of TOFHLA significantly and positively correlated with the psychological improvement subscale of PMPAS in total and also nursing students. In addition, we found a significant inverse correlation between the total score of TOFHLA and anxiety and sense of loss subscale of PMPAS in total and also non-nursing students. Moreover, the score of the psychological improvement subscale of PMPAS among the students with satisfactory HL was significantly higher than those with border HL, whereas for the anxiety and sense of loss subscale the comparison was not statistically significant. In line with our findings, Dodson S et al., showed that higher HL was associated with fewer symptoms of psychological stress in people receiving dialysis [36]. In the inverse relationship between HL and anxiety and sense of loss, it could be said that those who have satisfactory HL, have much more information on hazards of the excessive use of cell phone; thus, avoid cell phone-driven false excitements and anxiety. Also, those with higher HL might be more aware of the aftermaths of using cell phone and avoid using it constantly.

Findings also showed a significant and positive correlation between the reading comprehension section of TOFHLA and the self-control inability subscale of PMPAS in total and also non-nursing students. However, there was no significant difference in the score of self-control inability subscale among the students with satisfactory and border HL. Indeed, our findings indicated that the higher the reading comprehension, the lower self-control or higher self-control inability. Inconsistent with this finding, it was revealed that lower HL was significantly associated with less self-control of glucose level in adults with diabetes [37]. It seems that students with higher reading comprehension ability are more interested in using cell phone to communicate with others via social media and connect to the internet through cell phone to search for scientific resources [31]. Also, it was indicated that smart phone use motivations were correlated positively with addiction, and addiction correlated negatively with self-control [38]. Hence, students with higher reading comprehension might have higher dependency to their cell phones and lose their self-control by using the cell phone continuously.

Limitation

Although in this research all aspects of cell phone addiction and HL and its sections were studied, there are some points that should be considered when interpreting the findings. First, the study had a considerable dropout rate, which might have affected the results. Second, we enrolled only male students and could not compare male and female about HL and cell phone addiction and also the correlations of these two variables. Third, the study was conducted amongst healthcare students and the results might not be generalizable and applicable to other population. Forth, the study was a cross-sectional; hence, no cause-effect relationship was established between HL and cell phone addiction. Future longitudinal and interventional studies are recommended with focus on the long-term effects of HL on cell phone addiction of both male and female students, considering a much larger sample size.

Conclusion

There was a significant correlation between HL and cell phone addiction in some dimensions. Also, the students with satisfactory HL had significantly higher score in psychological improvement subscale of cell phone addiction. In nursing students, total score of TOFHLA significantly and positively correlated with total score of PMPAS. Based on our findings and due to high prevalence of cell phone addiction amongst students, university authorities should promote quality and quantity of the education related to HL in universities, especially nursing students, to prevent or reduce cell phone addiction.

*t-test

References

[1]Ratzan S, Apfel F, NCD health literacy--what can hospitals do? World Hosp Health Serv 2011 47(2):8-12.PMID: 22073875  [Google Scholar]  [PubMed]

[2]Sykes S, Wills J, Rowlands G, Popple K, Understanding critical health literacy: a concept analysis BMC Public Health 2013 13:15010.1186/1471-2458-13-1502341901  [Google Scholar]  [CrossRef]  [PubMed]

[3]Bragard I, Coucke PA, Pétré B, Etienne AM, Guillaume M, Health literacy, a way to reduce social health inequalities Rev Med Liege 2017 72:32-36.PMID: 28387075  [Google Scholar]  [PubMed]

[4]Bonaccorsi G, Lorini C, Baldasseroni A, Porchia BR, Capecchi L, Health services and health literacy: from the rationale to the many facets of a fundamental concept. A literature review Ann Ist Super Sanita 2016 52:114-18.doi: 10.4415/ANN_16_01_18PMID: 27033626  [Google Scholar]  [CrossRef]  [PubMed]

[5]McNeil A, Arena R, The evolution of health literacy and communication: introducing health harmonics Prog Cardiovasc Dis 2017 59:463-70.10.1016/j.pcad.2017.02.00328216109  [Google Scholar]  [CrossRef]  [PubMed]

[6]Dashti S, Peyman N, Tajfard M, Esmaeeli H, E-Health literacy of medical and health sciences university students in Mashhad, Iran in 2016: A pilot study Electron Physician 2017 9:3966-73.10.19082/396628461871  [Google Scholar]  [CrossRef]  [PubMed]

[7]Bazrafkan L, Hayat AA, Abbasi K, Bazrafkan A, Rohalamini A, Fardid M, Evaluation of information literacy status among medical students at Shiraz University of Medical Sciences J Adv Med Educ Prof 2017 5:42-48.PMID: 28124020  [Google Scholar]  [PubMed]

[8]Hashemi M, Khanjani N, Saber M, Fard NK, Evaluating health literacy of Kerman Medical University, School of Public Health students about recycling solid waste J Educ Health Promot 2012 1:2310.4103/2277-9531.9995523555126  [Google Scholar]  [CrossRef]  [PubMed]

[9]Sayarifard A, Ghadirian L, Mohit A, Eftekhar M, Badpa M, Rajabi F, Assessing mental health literacy: What medical sciences students’ know about depression Med J Islam Repub Iran 2015 29:161PMID: 26000256  [Google Scholar]  [PubMed]

[10]Yang SC, Luo YF, Chiang CH, The associations among individual factors, e-health literacy, and health-promoting lifestyles among college students J Med Internet Res 2017 19:e1510.2196/jmir.596428073739  [Google Scholar]  [CrossRef]  [PubMed]

[11]Panahi R, Ramezankhani A, Tavousi M, Osmani F, Niknami S, Which health literacy skills are associated with smoking? Zahedan J Res Med Sci 2017 19(3):e949310.5812/zjrms.9493  [Google Scholar]  [CrossRef]

[12]Kolnik TS, Hozjan D, Babnik K, Health literacy and health related lifestyle among nursing students Pielegniarstwo XXI wieku 2017 16(2):42-46.10.1515/pielxxiw-2017-0017  [Google Scholar]  [CrossRef]

[13]De-Sola Gutiérrez J, Rodríguez de Fonseca F, Rubio G, Cell-phone addiction: A review Front Psychiatry 2016 7:175doi: 10.3389/fpsyt.2016.0017527822187  [Google Scholar]  [CrossRef]  [PubMed]

[14]Mohammadbeigi A, Absari R, Valizadeh F, Saadati M, Sharifimoghadam S, Ahmadi A, Mokhtari M, Sleep quality in medical students; the impact of over-use of mobile cell-phone and social networks J Res Health Sci 2016 16:46-50.PMID: 27061997  [Google Scholar]  [PubMed]

[15]Babadi-Akashe Z, Zamani BE, Abedini Y, Akbari H, Hedayati N, The relationship between mental health and addiction to mobile phones among university students of Shahrekord, Iran Addict Health 2014 6:93-99.PMID: 25984275  [Google Scholar]  [PubMed]

[16]Tavakolizadeh J, Atarodi A, Ahmadpour S, Pourgheisar A, The prevalence of excessive mobile phone use and its relation with mental health status and demographic factors among the students of Gonabad University of Medical Sciences in 2011-2012 Razavi Int J Med 2014 2(1):e1552710.5812/rijm.15527  [Google Scholar]  [CrossRef]

[17]Mazaheri MA, Rahmati-Najarkolaei F, Cell phone and Internet addiction among Students in Isfahan University of Medical Sciences (Iran) J Health Policy Sustain Health 2014 1(3):101-05.  [Google Scholar]

[18]Zhang SC, Yang R, Li DL, Wang J, Wan YH, Xu SJ, Interactive effects between health literacy and mobile phone dependence as well as its relation with unintentional injuries in middle school students Zhonghua Liu Xing Bing Xue Za Zhi 2018 39(12):1549-54.doi: 10.3760/cma.j.issn.0254-6450.2018.12.003PMID: 30572376  [Google Scholar]  [CrossRef]  [PubMed]

[19]Nurjanah N, Soenaryati S, Rachmani E, Media use behavior and health literacy on high school students in Semarang Advanced Science Letters 2017 23(4):3493-96.10.1166/asl.2017.9145  [Google Scholar]  [CrossRef]

[20]Terras MM, Ramsay J, Family digital literacy practices and children’s mobile phone use Front Psychol 2016 7:195710.3389/fpsyg.2016.0195728066284  [Google Scholar]  [CrossRef]  [PubMed]

[21]Sumani MD, Twine BH, Busingye JD, Mobile phone use and family literacy practices: Perspectives from Uganda Educ Res J 2017 7(4):85-93.  [Google Scholar]

[22]Chen Q, Carbone ET, Functionality, implementation, impact, and the role of health literacy in mobile phone apps for gestational diabetes: scoping review JMIR Diabetes 2017 2(2):e25 10.2196/diabetes.804530291088  [Google Scholar]  [CrossRef]  [PubMed]

[23]Reisi M, Javadzade SH, Heydarabadi AB, Mostafavi F, Tavassoli E, Sharifirad G, The relationship between functional health literacy and health promoting behaviors among older adults J Educ Health Promot 2014 3:11910.4103/2277-9531.14592525540792  [Google Scholar]  [CrossRef]  [PubMed]

[24]Mazaheri MA, Karbasi M, Validity and reliability of the Persian version of mobile phone addiction scale J Res Med Sc 2014 19:139-44.24778668  [Google Scholar]  [PubMed]

[25]Poorman E, Gazmararian J, Elon L, Parker R, Is health literacy related to health behaviors and cell phone usage patterns among the text4baby target population? Arch Public Health 2014 72(1):1310.1186/2049-3258-72-1324872883  [Google Scholar]  [CrossRef]  [PubMed]

[26]Bailey SC, O’Conor R, Bojarski EA, Mullen R, Patzer RE, Vicencio D, Literacy disparities in patient access and health-related use of Internet and mobile technologies Health Expect 2015 18:3079-87. 10.1111/hex.1229425363660  [Google Scholar]  [CrossRef]  [PubMed]

[27]Bergner EM, Nelson LA, Rothman RL, Mayberry L, Text messaging may engage and benefit adults with type 2 diabetes regardless of health literacy status Health Lit Res Pract 2017 1(4):e192-e202. 10.3928/24748307-20170906-0129214241  [Google Scholar]  [CrossRef]  [PubMed]

[28]Nelson LA, Coston TD, Cherrington AL, Osborn CY, Patterns of user engagement with mobile-and web-delivered self-care interventions for adults with T2DM: a review of the literature Curr Diab Rep 2016 16(7):66 10.1007/s11892-016-0755-127255269  [Google Scholar]  [CrossRef]  [PubMed]

[29]Razavizadeh Sh, Parandeh A, Rahmati-Najarkolaei F, Pathology of mobile phone use in military university students from the views of media and communications professionals: a thematic analysis J Mil Med 2018 19(6):595-606.  [Google Scholar]

[30]Jeong HS, Lee YS, Factors influencing smartphone addiction in nursing students: Focused on empathy Adv Sci Technol Lett 2015 88:224-28.doi: 10.14257/astl.2015.88.47  [Google Scholar]  [PubMed]

[31]Choi SW, Kim DJ, Choi JS, Ahn H, Choi EJ, Song WY, Comparison of risk and protective factors associated with smartphone addiction and Internet addiction J Behav Addict 2015 4:308-14.10.1556/2006.4.2015.04326690626  [Google Scholar]  [CrossRef]  [PubMed]

[32]Olyani S, Peyman N, Assessing health literacy and its relationship with using cell phone among adolescents Health Educ Health Promot 2016 4(4):47-58.  [Google Scholar]

[33]Hong FY, Chiu SI, Huang DH, A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students Comput Human Behav 2012 28(6):2152-59.10.1016/j.chb.2012.06.020  [Google Scholar]  [CrossRef]

[34]Langarizadeh M, Naghipour M, Tabatabaei SM, Mirzaei A, Vaghar ME, Prediction of internet addiction based on information literacy among students of Iran University of Medical Sciences Electron Physician 2018 10(2):6333-40.10.19082/633329629056  [Google Scholar]  [CrossRef]  [PubMed]

[35]Soleymani MR, Garivani A, Zare-Farashbandi F, The effect of the internet addiction on the information-seeking behavior of the postgraduate students Mater Sociomed 2016 28(3):191-95.10.5455/msm.2016.28.191-19527482160  [Google Scholar]  [CrossRef]  [PubMed]

[36]Dodson S, Osicka T, Huang L, McMahon LP, Roberts MA, Multifaceted assessment of health literacy in people receiving dialysis: associations with psychological stress and quality of life J Health Commun 2016 21:91-98.10.1080/10810730.2016.117937027683959  [Google Scholar]  [CrossRef]  [PubMed]

[37]Van Der Heide I, Uiters E, Rademakers J, Struijs JN, Schuit AJ, Baan CA, Associations among health literacy, diabetes knowledge, and self-management behaviour in adults with diabetes: results of a Dutch cross-sectional study J Health Commun 2014 19(Suppl 2):115-31.10.1080/10810730.2014.93698925315588  [Google Scholar]  [CrossRef]  [PubMed]

[38]Cho M, The relationships among smart phone use motivations, addiction, and self-control in nursing students J Digit Converg 2014 12(5):311-23.10.14400/JDC.2014.12.5.311  [Google Scholar]  [CrossRef]