Journal of Education and Health Promotion

Design and psychometric properties of willingness to mobile learning scale for medical sciences students: A mixed‑methods study

Document Type : Original Article

Authors

. Nayereh Baghcheghi
. Hamid Reza Koohestani 1
. Mahmood Karimy 2

1 Departments of Medical Education

2 Departments of Public Health, Social Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran

Abstract
BACKGROUND AND AIM: Given the absence of a scale specially designed to measure willingness
to mobile learning (m‑learning) in medical sciences students, the present study was conducted to
design and evaluate the psychometric properties of “willingness to m‑learning” scale for medical
sciences students.
METHODOLOGY: The study was carried out as a mixed‑method study in two phases at Saveh
University of Medical Sciences in 2019. Phase one was a qualitative study to elaborate on the students’
perception of m‑learning. Then, the statements were extracted, and statement pool was completed
through reviewing the text. In the second phase, the psychometric properties including face, content,
and construct validities (using explorative factor analysis), internal consistency (Cronbach’s alpha),
and test–retest reliability (intercluster correlation test) were measured. A total of 482 students who
were selected randomly participated in the second phase. Data analysis was done with MAXQDA
software (VERBI Software 2019, Berlin, Germany) for qualitative data and SPSS 19 software
(SPSS Inc., Chicago, IL, USA) for quantitative data.
RESULTS: Based on qualitative content analysis and literature review, 92 statements were extracted.
After checking face and content validity, 55 statements remained in the study. Construct validity of the
questionnaire based on explorative factor analysis removed 10 more statements and the remaining 45
statements were categorized into nine factors, namely technophilia, perceived attraction, perceived
ease, perceived conflict, self‑management, attitude, behavioral intention to use, educational use,
and efficacy of m‑learning. Reliability of the scale was obtained as 0.95 based on Cronbach’s alpha
and stability was checked using test–retest method (intercluster correlation coefficient; r = 0.92).
CONCLUSION: Willingness to m‑learning scale had an acceptable reliability and validity in medical
sciences students. Therefore, it can be used for medical sciences students for improve learning
and education.

Keywords

Medical sciences students
mobile learning
psychometric properties
scale
validation
willingness
1. Koohestani HR, Baghcheghi N, Karimy M, Hemmat M,
Shamsizadeh M. Lived experiences of nursing students about
ethical concerns regarding mobile learning in educational and
clinical contexts. J Med Ethics Hist Med 2019;12:5.
2. Barzegar R. From electronic learning to mobile learning:
Theoretical principles. MEDIA. 2012;3:35‑41.
3. Dent J, Harden RM. A Practical Guide for Medical Teachers.
Amsterdam (Netherlands): Elsevier Health Sciences; 2013.
4. Gallegos C, Nakashima H. Mobile devices: A distraction, or a
useful tool to engage nursing students? J Nurs Educ 2018;57:170‑3.
5. Mather C, Cummings E, Allen P. Nurses’ use of mobile devices
to access information in health care environments in Australia:
A survey of undergraduate students. JMIR Mhealth Uhealth
2014;2:e56.
6. Iqbal S, Qureshi IA. M‑learning adoption: A perspective from a
developing country. IRRODL 2012;13:147‑64.
7. Koohestani HR, Arabshahi SK, Ahmadi F, Baghcheghi N.
The experiences of healthcare professional students about the
educational impacts of mobile learning. Qual Rep 2019;24:1593‑609.
8. Koohestani HR, Arabshahi SK, Ahmadi F. The paradox
of acceptance and rejection: The perception of healthcare
professional students about mobile learning acceptance in Iran
University of medical sciences. Qual Res Educ 2018;7:144‑69.
9. Graneheim UH, Lundman B. Qualitative content analysis in
nursing research: Concepts, procedures and measures to achieve
trustworthiness. Nurse Educ Today 2004;24:105‑12.
10. Guba EG. Criteria for assessing the trustworthiness of naturalistic
inquiries. ETRD 1981;29:75.
11. Mousazadeh S, Rakhshan M, Mohammadi F. Investigation of
content and face validity and reliability of sociocultural attitude
towards appearance questionnaire‑3 (SATAQ‑3) among female
adolescents. Iran J Psychiatry 2017;12:15‑20.
12. Lawshe CH. A quantitative approach to content validity 1. Pers
Psychol 1975;28:563‑75.
13. Mohammadbeigi A, Mohammadsalehi N, Aligol M. Validity and
reliability of the instruments and types of measurements in health
applied researches. J Rafsanjan Univ Med Sc 2015;13:1153‑70.
14. Ashktorab T, Baghcheghi N, Seyedfatemi N, Baghestani A.
Psychometric parameters of the Persian version of the BriefCOPE
among wives of patients under hemodialysis. Med J Islam Repub
Iran 2017;31:20.
15. Yaghmaei F. Content validity and its estimation. J Med Educ
2003;3:25‑7.
16. Tabachnick BG, Fidell LS, Ullman JB. Using Multivariate Statistics.
Boston, MA: Pearson; 2007.
17. Munro BH. Statistical Methods for Health Care Research.
Philadelphia (United States): Lippincott Williams and Wilkins;
2012.
18. SalareeMM, ZareiyanA, EbadiA. Development and psychometric
properties of the military nurses’ job burnout factors questionnaire.
J Mil Med 2019;20:645‑54.
19. Zarmpou T, Saprikis V, Markos A, Vlachopoulou M. Modeling
users’ acceptance of mobile services. Electron Commer Res
2012;12:225‑48.
20. Chong JL, Chong AY, Ooi KB, Lin B. An empirical analysis of the
adoption of m‑learning in Malaysia. Int J Commun 2011;9:1‑18.
21. Sun Y, Liu L, Peng X, Dong Y, Barnes SJ. Understanding Chinese
users’ continuance intention toward online social networks: An
integrative theoretical model. Electron Mark 2014;24:57‑66.
22. Osiceanu ME. Psychological implications of modern technologies:
“technofobia” versus “technophilia”. Procedia Soc Behav Sci
2015;180:1137‑44.
23. Sohrabi Z, Koohestani HR, Baghcheghi N, Delavari S, Rezaei
Shahsavarloo Z. The effects of group blogging on the attitude
towards virtual education in nursing students. Med J Islam Repub
Iran 2017;31:132.
24. Fishbein M, Ajzen I. Belief, Attitude, Intention, and Behavior:An Introduction to Theory and Research. Reading, MA:
Addison‑Wesley; 1977.
25. Koohestani HR, Soltani Arabshahi SK, Fata L, Ahmadi F. The
educational effects of mobile learning on students of medical
sciences: A systematic review in experimental studies. J Adv Med
Educ Prof 2018;6:58‑69.
Journal of Education and Health Promotion
Volume 10, Issue 6
June 2020
Pages 1-7

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