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ORIGINAL RESEARCH

The Impact of Smartphone Addiction on Chinese University Students’ Physical Activity: Exploring the Role of Motivation and Self-Efficacy

ORCID Icon, &
Pages 2273-2290 | Received 28 May 2022, Accepted 12 Aug 2022, Published online: 23 Aug 2022

References

  • Statista. Number of smartphone users in China from 2015 to 2019 with a forecast until 2025 (in millions). Available from: https://www.statista.com/statistics/467160/forecast-of-smartphone-users-in-china/#statisticContainer. Accessed August 18, 2022.
  • Head M, Ziolkowski N. Understanding student attitudes of mobile phone features: rethinking adoption through conjoint, cluster and SEM analyses. Comput Hum Behav. 2012;28(6):2331–2339. doi:10.1016/j.chb.2012.07.003
  • Naz A, Khan W, Daraz U, Hussain M. The malevolence of technology: an investigation into the various socioeconomic impacts of excessive cell phone use among university students: a case study of University of Malakand, KPK Pakistan. Int J Acad Res Bus Soc Sci. 2011;1(3):321–336. doi:10.6007/ijarbss.v1i3.42
  • Thomée S, Härenstam A, Hagberg M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults-a prospective cohort study. BMC Public Health. 2011;11(1):1–11. doi:10.1186/1471-2458-11-66
  • Panova T, Carbonell X. Is smartphone addiction really an addiction? J Behav Addict. 2018;7(2):252–259. doi:10.1556/2006.7.2018.49
  • Lin YH, Chiang CL, Lin PH, et al. Proposed diagnostic criteria for smartphone addiction. PLoS One. 2016;11(11):e0163010. doi:10.1371/journal.pone.0163010
  • Hanphitakphong P, Keeratisiroj O, Thawinchai N. Smartphone addiction and its association with upper body musculoskeletal symptoms among university students classified by age and gender. J Phys Ther Sci. 2021;33(5):394–400. doi:10.1589/jpts.33.394
  • Shah PP, Sheth MS. Correlation of smartphone use addiction with text neck syndrome and SMS thumb in physiotherapy students. Int J Commun Med Public Health. 2018;5(6):2512. doi:10.18203/2394-6040.ijcmph201
  • Chen IH, Pakpour AH, Leung H, et al. Comparing generalized and specific problematic smartphone/internet use: longitudinal relationships between smartphone application-based addiction and social media addiction and psychological distress. J Behav Addict. 2020;9(2):410–419. doi:10.1556/2006.2020.00023
  • Elhai JD, Tiamiyu M, Weeks J. Depression and social anxiety in relation to problematic smartphone use: the prominent role of rumination. Internet Res. 2018;28(2):315–332. doi:10.1108/IntR-01-2017-0019
  • You JC, Xiang MQ, Tan XM, Xu SY. Relationship between mobile phone addiction and depression in college students: the role of modification effect of the behavior of using mobile phones after lights out at night. China J Health Psychol. 2021;29(5):734–739. doi:10.13342/j.cnki.cjhp.2021.05.020
  • Kim IK, Park SW, Choi HM. The relationship among smartphone addiction, communication ability, loneliness and interpersonal relationship for university students. J Korea Academia Industr Cooperation Soc. 2017;18(1):637–648. doi:10.5762/kais.2017.18.1.637
  • Choi H-S, Lee H-K, Ha J-C. The influence of smartphone addiction on mental health, campus life and personal relations-Focusing on K university students. J Korean Data Inform Sci Soc. 2012;23(5):1005–1015. doi:10.7465/jkdi.2012.23.5.1005
  • Li L. Impulsivity, other related factors and therapy of smartphone addiction in college students. Doctoral dissertation. Jilin University; 2016.
  • Ithnain N, Ghazali SE, Jaafar N. Relationship between smartphone addiction with anxiety and depression among undergraduate students in Malaysia. Int J Health Sci Res. 2018;8(1):163–171.
  • Aljomaa SS, Qudah MFA, Albursan IS, Bakhiet SF, Abduljabbar AS. Smartphone addiction among university students in the light of some variables. Comput Hum Behav. 2016;61:155–164. doi:10.1016/j.chb.2016.03.041
  • Davey S, Davey A. Assessment of smartphone addiction in Indian adolescents: a mixed method study by systematic-review and meta-analysis approach. Int J Prev Med. 2014;5(12):1500–1511.
  • Kautiainen S, Koivusilta L, Lintonen T, Virtanen SM, Rimpelä A. Use of information and communication technology and prevalence of overweight and obesity among adolescents. Int J Obes. 2005;29(8):925–933. doi:10.1038/sj.ijo.0802994
  • Barkley JE, Lepp A. Mobile phone use among college students is a sedentary leisure behavior which may interfere with exercise. Comput Hum Behav. 2016;56:29–33. doi:10.1016/j.chb.2015.11.001
  • Fennell C, Barkley JE, Lepp A. The relationship between cell phone use, physical activity, and sedentary behavior in adults aged 18–80. Comput Hum Behav. 2019;90:53–59. doi:10.1016/j.chb.2018.08.044
  • Lepp A, Barkley JE, Karpinski AC. The relationship between cell phone use and academic performance in a sample of US college students. SAGE Open. 2015;5(1):1–9. doi:10.1177/2158244015573169
  • Xiang MQ, Lin L, Wang ZR, Li J, Xu ZB, Hu M. Sedentary behavior and problematic smartphone use in Chinese adolescents: the moderating role of self-control. Front Psychol. 2020;10:3032. doi:10.3389/fpsyg.2019.03032
  • World Health Organization. Global Recommendations on Physical Activity for Health. Geneva, Switzerland: World Health Organization; 2010.
  • Ye M, Zhai XY, Gu Q, Huang T, Fan X. Associations between physical activity, screen time and anxiety, sleep quality among Chinese college students. Chinese J Sch Health. 2019;40(10):1509–1513. doi:10.16835/j.cnki.1000-9817.2019.10.020
  • Sharan D, Mohandoss M, Ranganathan R, Jose J. Musculoskeletal disorders of the upper extremities due to extensive usage of hand held devices. Ann Occup Environ Med. 2014;26(1):1–4. doi:10.1186/s40557-014-0022-3
  • Berolo S, Wells RP, Amick BC. Musculoskeletal symptoms among mobile hand-held device users and their relationship to device use: a preliminary study in a Canadian university population. Appl Ergon. 2011;42(2):371–378. doi:10.1016/j.apergo.2010.08.010
  • Subramani Parasuraman ATS, Yee SWK, Chuon BLC, Ren LY, Ren L. Smartphone usage and increased risk of mobile phone addiction: a concurrent study. Int J Pharm Investig. 2017;7(3):125–131. doi:10.4103/jphi.JPHI_56_17
  • Jung SI, Lee NK, Kang KW, Kim K, Do YL. The effect of smartphone usage time on posture and respiratory function. J Phys Ther Sci. 2016;28(1):186–189. doi:10.1589/jpts.28.186
  • Palfrey J, Gasser U. Born Digital: Understanding the First Generation of Digital Natives. Basic Books; 2011.
  • Hutchins MD. Relationships among self-efficacy, self-motivation, and other factors affecting physical activity: Health implications for health education. Doctoral dissertation. Southern Illinois University Carbondale; 2008. Available from: https://www.proquest.com/openview/34b02fe5025617580a0a65731aa2c57f/1?pq-origsite=gscholar&cbl=18750. Accessed August 18, 2022.
  • McAuley E, Blissmer B. Self-efficacy determinants and consequences of physical activity. Exerc Sport Sci Rev. 2000;28(2):85–88.
  • Standage M, Sebire SJ, Loney T. Does exercise motivation predict engagement in objectively assessed bouts of moderate-intensity exercise?: A self-determination theory perspective. J Sport Exerc Psychol. 2008;30(4):337–352. doi:10.1123/jsep.30.4.337
  • Sullum J, Clark MM, King TK. Predictors of exercise relapse in a college population. J Am Coll Health. 2000;48(4):175–180. doi:10.1080/07448480009595693
  • 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(12):e83558. doi:10.1371/journal.pone.0083558
  • Griffiths MD. Does Internet and computer “addiction” exist? Some case study evidence. Cyberpsychol Behav. 2000;3(2):211–218. doi:10.1089/109493100316067
  • Armstrong L, Phillips JG, Saling LL. Potential determinants of heavier Internet usage. Int J Hum Comput Stud. 2000;53(4):537–550. doi:10.1006/ijhc.2000.0400
  • Davis RA. A cognitive-behavioral model of pathological Internet use. Comput Hum Behav. 2001;17(2):187–195. doi:10.1016/S0747-5632(00)00041-8
  • Randjelovic P, Stojiljkovic N, Radulovic N, Stojanovic N, Ilic I. Problematic smartphone use, screen time and chronotype correlations in university students. Eur Addict Res. 2021;27(1):67–74. doi:10.1159/000506738
  • Carbonell X, Chamarro A, Griffiths M, Oberst U, Cladellas R, Talarn A. Problematic Internet and cell phone use in Spanish teenagers and young students. Anales de psicología. 2012;28(3):789–796. doi:10.6018/analesps.28.3.156061
  • Cocoradă E, Maican CI, Cazan AM, Maican MA. Assessing the smartphone addiction risk and its associations with personality traits among adolescents. Child Youth Serv Rev. 2018;93:345–354. doi:10.1016/j.childyouth.2018.08.006
  • Gökçearslan Ş, Mumcu FK, Haşlaman T, Çevik YD. Modelling smartphone addiction: the role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students. Comput Hum Behav. 2016;63:639–649. doi:10.1016/j.chb.2016.05.091
  • Nayak JK. Relationship among smartphone usage, addiction, academic performance and the moderating role of gender: a study of higher education students in India. Comput Educ. 2018;123:164–173. doi:10.1016/j.compedu.2018.05.007
  • Venkatesh E, Al Jemal MY, Al Samani AS. Smart phone usage and addiction among dental students in Saudi Arabia: a cross sectional study. Int J Adolesc Med Health. 2017;31(1):20160133. doi:10.1515/ijamh-2016-0133
  • Bandura A. Social Foundations of Thought and Action. Vol. 1986. Englewood Cliffs, NJ: Prentice-Hall; 1986.
  • Bandura A. Self-Efficacy: The Exercise of Control. W.H. Freeman and Company; 1997.
  • Bandura A. Guide for constructing self-efficacy scales. In: Pajares F, Urdan T, editors. Self-Efficacy Beliefs of Adolescents. Greenwich, CT: Information Age; 2006:307–337.
  • Taylor SE. Health Psychology. New York: McGraw-Hill Education; 2015.
  • Bandura A. Social cognitive theory: an agentic perspective. Annu Rev Psychol. 2001;52(1):1–26. doi:10.1111/1467-839x.00024
  • Oyibo K, Adaji I, Vassileva J. Social cognitive determinants of exercise behavior in the context of behavior modeling: a mixed method approach. Digit Health. 2018;4:1–19. doi:10.1177/2055207618811555
  • Lee HS. Convergent study of the effect of university students’ addiction to smartphones on self-esteem and self-efficacy: stress level and mental health as mediating factors. J Korean Converg Soc. 2017;8(1):139–148. doi:10.15207/JKCS.2017.8.1.139
  • Li L, Gao HY, Xu YH. The mediating and buffering effect of academic self-efficacy on the relationship between smartphone addiction and academic procrastination. Comput Educ. 2020;159:104001. doi:10.1016/j.compedu.2020.104001
  • Gür F, Gür GC, Ayan V. The effect of the ERVE smartphone app on physical activity, quality of life, self-efficacy, and exercise motivation for inactive people: a randomized controlled trial. Eur J Integr Med. 2020;39:101198. doi:10.1016/j.eujim.2020.101198
  • Hamid SFA, Ismail NN, Razak FAA, Shahudin NN. Motivation in Physical Activity: Smartphone Sport Tracker Applications. Springer; 2019:463–470.
  • Zhang P, Burns RD, Fu Y, Godin S, Li Z, Zhang X. Efficacy of a 4-week smartphone application intervention on college students’ BMI, physical activity, and motivation. Int J Kinesiol High Educ. 2021;1–12. doi:10.1080/24711616.2020.1866467
  • Zhang P, Fu Y, Burns R, Godin S. Effect of efitbuddy on promoting physical activity and motivation in college students. J Hum Sport Exerc. 2018;13(4):799–809. doi:10.14198/jhse.2018.134.08
  • Doree RE. The Relationship between Cell Phone Use and Motivation to Exercise in College Students. Master dissertation. The University of North Dakota; 2019. Available from: https://commons.und.edu/theses/2452.
  • Rogers HE, Morris T. An overview of the development and validation of the Recreational Exercise Motivation Measure (REMM). Conference presentation presented at: XIth European Congress of Sport Psychology Proceedings Book; 2003; Copenhagen, Denmark.
  • Deci EL, Ryan RM. Self-determination theory: when mind mediates behavior. J Mind Behav. 1980;1(1):33–43.
  • Frederick CM, Ryan RM. Differences in motivation for sport and exercise and their relations with participation and mental health. J Sport Behav. 1993;16(3):124–146.
  • Kilpatrick M, Hebert E, Bartholomew J. College students’ motivation for physical activity: differentiating men’s and women’s motives for sport participation and exercise. J Am Coll Health. 2005;54(2):87–94. doi:10.3200/JACH.54.2.87-94
  • Ryan RM, Frederick C, Lepes D, Rubio N, Sheldon K. Intrinsic motivation and exercise adherence. Int J Sport Psychol. 1997;28(4):335–354.
  • Deci EL, Ryan RM. The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychol Inq. 2000;11(4):227–268. doi:10.1207/S15327965PLI1104_01
  • Markland D, Tobin VJ. Need support and behavioural regulations for exercise among exercise referral scheme clients: the mediating role of psychological need satisfaction. Psychol Sport Exerc. 2010;11(2):91–99. doi:10.1016/j.psychsport.2009.07.001
  • McDonough MH, Crocker PR. Testing self-determined motivation as a mediator of the relationship between psychological needs and affective and behavioral outcomes. J Sport Exerc Psychol. 2007;29(5):645–663. doi:10.1123/jsep.29.5.645
  • Thøgersen-Ntoumani C, Ntoumanis N. The role of self-determined motivation in the understanding of exercise-related behaviours, cognitions and physical self-evaluations. J Sports Sci. 2006;24(4):393–404. doi:10.1080/02640410500131670
  • Vallerand RJ, Rousseau F. Intrinsic and extrinsic motivation in sport and exercise: a review using the hierarchical model of intrinsic and extrinsic motivation. In: Singer RN, Hausenblas HA, Janelle CM, editors. Handb Sport Psychol. Wiley; 2001:389–416.
  • Ingledew DK, Markland D. The role of motives in exercise participation. Psychol Health. 2008;23(7):807–828. doi:10.1080/08870440701405704
  • Blanchard CM, Fortier M, Sweet S, et al. Explaining physical activity levels from a self-efficacy perspective: the physical activity counseling trial. Ann Behav Med. 2007;34(3):323–328. doi:10.1007/bf02874557
  • Dzewaltowski DA, Noble JM, Shaw JM. Physical activity participation: social cognitive theory versus the theories of reasoned action and planned behavior. J Sport Exerc Psychol. 1990;12(4):388–405. doi:10.1123/jsep.12.4.388
  • Marcus BH, Selby VC, Niaura RS, Rossi JS. Self-efficacy and the stages of exercise behavior change. Res Q Exerc Sport. 1992;63(1):60–66. doi:10.1080/02701367.1992.10607557
  • Morris KS, McAuley E, Motl RW. Self-efficacy and environmental correlates of physical activity among older women and women with multiple sclerosis. Health Educ Res. 2008;23(4):744–752. doi:10.1093/her/cym067
  • Prodaniuk TR, Plotnikoff RC, Spence JC, Wilson PM. The influence of self-efficacy and outcome expectations on the relationship between perceived environment and physical activity in the workplace. Int J Behav Nutr Phys Act. 2004;1(1):1–11. doi:10.1186/1479-5868-1-7
  • Schwarzer R, Luszczynska A, Ziegelmann JP, Scholz U, Lippke S. Social-cognitive predictors of physical exercise adherence: three longitudinal studies in rehabilitation. Health Psychol. 2008;27(Suppl):54–63. doi:10.1037/0278-6133.27.1(Suppl.).S54
  • Buckworth J, Lee RE, Regan G, Schneider LK, DiClemente CC. Decomposing intrinsic and extrinsic motivation for exercise: application to stages of motivational readiness. Psychol Sport Exerc. 2007;8(4):441–461. doi:10.1016/j.psychsport.2006.06.007
  • Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191–215. doi:10.1037/0033-295x.84.2.191
  • Klompstra L, Jaarsma T, Strömberg A. Self-efficacy mediates the relationship between motivation and physical activity in patients with heart failure. J Cardiovasc Nurs. 2018;33(3):211. doi:10.1097/JCN.0000000000000456
  • D’Angelo MES, Pelletier LG, Reid RD, Huta V. The roles of self-efficacy and motivation in the prediction of short-and long-term adherence to exercise among patients with coronary heart disease. Health Psychol. 2014;33(11):1344. doi:10.1037/hea0000094
  • Assael H. A demographic and psychographic profile of heavy internet users and users by type of internet usage. J Advert Res. 2005;45(1):93–123. doi:10.1017/s0021849905050014
  • Kim J, Chun BC. Association of Internet addiction with health promotion lifestyle profile and perceived health status in adolescents. J Prev Med Public Health. 2005;38(1):53–60. doi:10.12965/jer.130080
  • Vandelanotte C, Sugiyama T, Gardiner P, Owen N. Associations of leisure-time internet and computer use with overweight and obesity, physical activity and sedentary behaviors: cross-sectional study. J Med Internet Res. 2009;11(3):e28. doi:10.2196/jmir.1084
  • Nielsen. How smartphones are changing consumers’ daily routines around the globe. Available from: http://www.nielsen.com/us/en/insights/news/2014/how-smartphones-are-changing-consumers-daily-routines-around-The-globe.html. Accessed August 18, 2022.
  • Lepp A, Barkley JE, Sanders GJ, Rebold M, Gates P. The relationship between cell phone use, physical and sedentary activity, and cardiorespiratory fitness in a sample of US college students. Int J Behav Nutr Phys Act. 2013;10(1):1–9. doi:10.1186/1479-5868-10-79
  • Kim SE, Kim JW, Jee YS. Relationship between smartphone addiction and physical activity in Chinese international students in Korea. J Behav Addict. 2015;4(3):200–205. doi:10.1556/2006.4.2015.028
  • Gumusgul O. Investigation of smartphone addiction effect on recreational and physical activity and educational success. World J Educ. 2018;8(4):11–17. doi:10.5430/wje.v8n4p11
  • Buctot DB, Kim N, Kim SH. The role of nomophobia and smartphone addiction in the lifestyle profiles of junior and senior high school students in the Philippines. Soc Sci Humanit Open. 2020;2(1):100035. doi:10.1016/j.ssaho.2020.100035
  • Demirbilek M, Minaz M. The relationship between physical activity and smart phone use in university students. J Educ Sci Environ Health. 2020;6(4):282–296. doi:10.21891/jeseh.795980
  • Haripriya S, Samuel SE, Megha M. Correlation between smartphone addiction, sleep quality and physical activity among young adults. J Clin Diagn. 2019;13(10). doi:10.7860/JCDR/2019/42168.13212
  • Zhai XY, Ye M, Wang C, et al. Associations among physical activity and smartphone use with perceived stress and sleep quality of Chinese college students. Ment Health Phys Act. 2020;18:100323. doi:10.1016/j.mhpa.2020.100323
  • Zhitomirsky-Geffet M, Blau M. Cross-generational analysis of predictive factors of addictive behavior in smartphone usage. Comput Hum Behav. 2016;64:682–693. doi:10.1016/j.chb.2016.07.061
  • Oulasvirta A, Rattenbury T, Ma L, Raita E. Habits make smartphone use more pervasive. Pers Ubiquitous Comput. 2012;16(1):105–114. doi:10.1007/s00779-011-0412-2
  • Kwon M, Lee JY, Won WY, et al. Development and validation of a smartphone addiction scale (SAS). PLoS One. 2013;8(2):e56936. doi:10.1371/journal.pone.0056936
  • Luk TT, Wang MP, Shen C, et al. Short version of the Smartphone Addiction Scale in Chinese adults: psychometric properties, sociodemographic, and health behavioral correlates. J Behav Addict. 2018;7(4):1157–1165. doi:10.1556/2006.7.2018.105
  • Lin B, Teo EW, Yan T. Development and validation of Chinese university students’ physical activity motivation scale under the constraint of physical education policies. Front Psychol. 2022;13:722635. doi:10.3389/fpsyg.2022.722635
  • Shin YH, Jang HJ, Pender NJ. Psychometric evaluation of the exercise self‐efficacy scale among Korean adults with chronic diseases. Res Nurs Health. 2001;24(1):68–76. doi:10.1002/1098-240X
  • Sabo A, Kueh YC, Kuan G. Psychometric properties of the Malay version of the self-efficacy for exercise scale. PLoS One. 2019;14(5):e0215698. doi:10.1371/journal.pone.0215698
  • Noroozi A, Ghofranipour F, Heydarnia AR, Nabipour I, Tahmasebi R, Tavafian SS. The Iranian version of the exercise self-efficacy scale (ESES) Factor structure, internal consistency and construct validity. Health Educ J. 2011;70(1):21–31. doi:10.22122/arya.v15i3.1839
  • Brislin RW. Back-translation for cross-cultural research. J Cross Cult Psychol. 1970;1(3):185–216. doi:10.1177/135910457000100301
  • Qu NN, Li KJ. Study on the reliability and validity of international physical activity questionnaire (Chinese Vision, IPAQ). Chin J Epidemiol. 2004;25(3):265–268. doi:10.1016/j.csr.2003.12.006
  • Macfarlane DJ, Lee CC, Ho EY, Chan K, Chan DT. Reliability and validity of the Chinese version of IPAQ (short, last 7 days). J Sci Med Sport. 2007;10(1):45–51. doi:10.1016/j.jsams.2006.05.003
  • IPAQ. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ)-short and long forms. Available from: http://www.ipaq.ki.se/scoring.pdf. Accessed August 18, 2022.
  • Kline RB. Principles and Practice of Structural Equation Modeling. 3rd ed. New York: The Guilford Press; 2015.
  • Byrne BM. Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming (Multivariate Applications Series). New York: Taylor & Francis Group; 2010.
  • Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. 7st ed. Pearson Prentice Hall; 2010.
  • Diamantopoulos A, Siguaw JA. Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. Br J Manag. 2006;17(4):263–282. doi:10.1111/j.1467-8551.2006.00500.x
  • Marsh HW, Hocevar D. Application of confirmatory factor analysis to the study of self-concept: first-and higher order factor models and their invariance across groups. Psychol Bull. 1985;97(3):562–582. doi:10.1037/0033-2909.97.3.562
  • Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1–55. doi:10.1080/10705519909540118
  • Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39–50. doi:10.2307/3151312
  • Preacher KJ, Hayes AF. SAS procedures for estimating indirect effects in simple mediation models. Behav Res Meth Instrum Comput. 2004;36(4):717–731. doi:10.3758/BF03206553
  • Preacher KJ, Rucker DD, Hayes AF. Addressing moderated mediation hypotheses: theory, methods, and prescriptions. Multivar Behav Res. 2007;42(1):185–227. doi:10.1080/00273170701341316
  • Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Multivar Behav Res. 2008;40(3):879–891. doi:10.3758/BRM.40.3.879
  • Boelen PA, van den Hout MA, van den Bout J. The factor structure of posttraumatic stress disorder symptoms among bereaved individuals: a confirmatory factor analysis study. J Anxiety Disord. 2008;22(8):1377–1383. doi:10.1016/j.janxdis.2008.01.018
  • Nunnally JC. Psychometric Theory. 3rd ed. New York, NY: Mcgraw-Hill; 1994.
  • Huang CC, Wang YM, Wu TW, Wang PA. An empirical analysis of the antecedents and performance consequences of using the moodle platform. Int J Inf Educ Technol. 2013;3(2):217. doi:10.7763/IJIET.2013.V3.267
  • Buctot DB, Kim N, Park KE. Development and evaluation of smartphone detox program for university students. Int J Contents. 2018;14(4):1–9. doi:10.5392/IJoC.2018.14.4.001
  • Griffiths MD. A ‘components’ model of addiction within a biopsychosocial framework. J Subst Use. 2005;10(4):191–197. doi:10.1080/1465989050011435
  • Choi JW, Lee J, Vittinghoff E, Fukuoka Y. mHealth physical activity intervention: a randomized pilot study in physically inactive pregnant women. Matern Child Health J. 2016;20(5):1091–1101. doi:10.1007/s10995-015-1895-7
  • Fanning J, Roberts S, Hillman CH, Mullen SP, Ritterband L, McAuley E. A smartphone “app”-delivered randomized factorial trial targeting physical activity in adults. J Behav Med. 2017;40(5):712–729. doi:10.1007/s10865-017-9838-y
  • Glynn LG, Hayes PS, Casey M, et al. Effectiveness of a smartphone application to promote physical activity in primary care: the SMART MOVE randomised controlled trial. Br J Gen Pract. 2014;64(624):e384–e391. doi:10.3399/bjgp14X680461
  • Paul L, Wyke S, Brewster S, et al. Increasing physical activity in stroke survivors using STARFISH, an interactive mobile phone application: a pilot study. Top Stroke Rehabil. 2016;23(3):170–177. doi:10.1080/10749357.2015.1122266
  • Pliner P, Chaiken S, Flett GL. Gender differences in concern with body weight and physical appearance over the life span. Pers Soc Psychol Bull. 1990;16(2):263–273. doi:10.1177/0146167290162007
  • Boothby J, Tungatt MF, Townsend AR. Ceasing participation in sports activity: reported reasons and their implications. J Leis Res. 1981;13(1):1–14. doi:10.1080/00222216.1981.11969463
  • Wankel LM. The importance of enjoyment to adherence and psychological benefits from physical activity. Int J Sport Psychol. 1993;24(2):151–169.
  • Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55(1):68–78. doi:10.1037/0003-066X.55.1.68
  • Keating XD, Guan J, Piñero JC, Bridges DM. A meta-analysis of college students’ physical activity behaviors. J Am Coll Health. 2005;54(2):116–126. doi:10.3200/JACH.54.2.116-126