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ShojaeiBaghini, Mahdie. (1403). Online Health Information Seeking Behavior of Pregnant Women: A social cognitive perspective. سامانه مدیریت نشریات علمی, 11(4), 171-178. doi: 10.30476/jhmi.2025.104568.1247
Mahdie ShojaeiBaghini. "Online Health Information Seeking Behavior of Pregnant Women: A social cognitive perspective". سامانه مدیریت نشریات علمی, 11, 4, 1403, 171-178. doi: 10.30476/jhmi.2025.104568.1247
ShojaeiBaghini, Mahdie. (1403). 'Online Health Information Seeking Behavior of Pregnant Women: A social cognitive perspective', سامانه مدیریت نشریات علمی, 11(4), pp. 171-178. doi: 10.30476/jhmi.2025.104568.1247
ShojaeiBaghini, Mahdie. Online Health Information Seeking Behavior of Pregnant Women: A social cognitive perspective. سامانه مدیریت نشریات علمی, 1403; 11(4): 171-178. doi: 10.30476/jhmi.2025.104568.1247

Online Health Information Seeking Behavior of Pregnant Women: A social cognitive perspective

Health Management & Information Science
دوره 11، شماره 4، دی 2024، صفحه 171-178    اصل مقاله (949.24 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.30476/jhmi.2025.104568.1247
نویسنده
Mahdie ShojaeiBaghini*
Kerman University of Medical Sciences, Medical University Campus, Haft-Bagh Highway, Kerman, Iran
چکیده
Background: The widespread use of smartphones and the Internet has led to increased online health information-seeking, which can improve public health. This behavior is influenced by individual, environmental, and behavioral factors, all considered in social cognitive theory. This study aims to use social cognitive theory to describe how pregnant women seek health information online.
Methods: This cross-sectional survey was conducted in 2023 to gather data from pregnant women referred to gynecologists' offices in Kerman. A questionnaire was used to collect the data, employing scales that had been validated in prior research and were relevant to this study. The questions were rated on a 5-point Likert scale. The data were analyzed using SPSS version 22.0 and SmartPLS3.
Results: Most participants (45.6%) were in the 20–30 age group and had (53.5%) bachelor's degree. Most of them had their first experience of pregnancy (59.9%) and had no history of chronic disease (65.4%). The internal consistency reliability, convergent validity, and model fit were confirmed. IT self-efficacy and IT innovativeness had a significant positive association with perceived benefits. There was a significant positive association between professional support, social support, and health awareness. Health awareness and perceived benefits did not singularly influence health information-seeking behavior.
Conclusion: According to the study, IT innovation, IT self-efficacy, social support, and professional support encourage pregnant women to seek online health information by increasing perceived benefits and health awareness. Health professionals, particularly gynecologists, should guide pregnant women toward trustworthy online resources for health information.
کلیدواژه‌ها
Information Seeking Behavior؛ Pregnancy؛ Social Cognitive Theory
مراجع
Masoudiyekta L, Nosratabadi M, Tayebpour M, Mehranfard S. Relationship between health literacy and pregnancy consequences in women referring to comprehensive health service centers. Journal of Health Literacy. 2022;6(4):69-76.

    • Javanmardi M, Noroozi M, Mostafavi F, Ashrafi-Rizi H. Exploring Women’s Health Information Needs During Pregnancy: A Qualitative Study. J Family Reprod Health. 2020;14(4):252-8. doi: 10.18502/jfrh.v14i4.5209.

    • Sanders RA, Crozier K. How do informal information sources influence women’s decision-making for birth? A meta-synthesis of qualitative studies. BMC Pregnancy Childbirth. 2018;18(1):21. doi: 10.1186/s12884-017-1648-2.

    • Sayakhot P, Carolan-Olah M. Internet use by pregnant women seeking pregnancy-related information: a systematic review. BMC Pregnancy Childbirth. 2016;16:65. doi: 10.1186/s12884-016-0856-5.

    • Hamzehei R, Kazerani M, Shekofteh M, Karami M. Online health information seeking behavior among Iranian pregnant women: A case study. Library philosophy and practice. 2018;1659.

    • Ofori PP. Social Media in Pregnancy Care: Exploring Adoption Factors and Digital Healthcare Information Utilization among Expectant Mothers in Ghana. Ethiop J Health Sci. 2024;34(1):47-56. doi: 10.4314/ejhs.v34i1.6.

    • Lu Y, Zhang Z, Min K, Luo X, He Z. Pregnancy-Related Information Seeking in Online Health Communities: A Qualitative Study. Divers Divergence Dialogue (2021). 2021;12646:18-36. doi: 10.1007/978-3-030-71305-8_2.

    • Jia X, Pang Y, Liu LS. Online Health Information Seeking Behavior: A Systematic Review. Healthcare (Basel). 2021;9(12). doi: 10.3390/healthcare9121740.

    • Demir Y, Dag E, Özpinar S. The relationship of E-health Literacy with Cyberchondria: a cross-sectional study on pregnant women. Journal of Health Literacy. 2024;9(1):89-101.

    • Kaur N, Kaur S. Role of Libraries in Promoting Health Information Literacy in India. Handbook of Research on Knowledge and Organization Systems in Library and Information Science: IGI Global; 2021. p. 366-83.

    • Kalankesh LR, Mohammadian E, Ghalandari M, Delpasand A, Aghayari H. Health information seeking behavior (HISB) among the university students. Frontiers in Health Informatics. 2019;8(1):13.

    • Javanmardi M, Noroozi M, Mostafavi F, Ashrafi-Rizi H. Challenges to access health information during pregnancy in Iran: a qualitative study from the perspective of pregnant women, midwives and obstetricians. Reprod Health. 2019;16(1):128. doi: 10.1186/s12978-019-0789-3.

    • Bansal G, Gefen D. The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision support systems. 2010;49(2):138-50.

    • Myrick JG. The role of emotions and social cognitive variables in online health information seeking processes and effects. Computers in Human Behavior. 2017;68:422-33.

    • Zhang X, Chen B, Li G, Dong Y. Exploring the health information seeking behavior of social media users under the background of COVID-19 pandemic: An empirical study based on social cognitive theory. Front Psychol. 2022;13:1045914. doi: 10.3389/fpsyg.2022.1045914.

    • Bandura A. Health promotion from the perspective of social cognitive theory. Understanding and changing health behaviour: Psychology Press; 2013. p. 299-339.

    • Chang C-C, Huang M-H. Antecedents predicting health information seeking: a systematic review and meta-analysis. International Journal of Information Management. 2020;54:102115.

    • Javanmardi M, Noroozi M, Mostafavi F, Ashrafi-Rizi H. Exploring the Motivations of Pregnant Women to Seek Health Information: A Qualitative Study. Iran J Nurs Midwifery Res. 2022;27(5):446-51. doi: 10.4103/ijnmr.ijnmr_327_21.

    • Shao Z, Wang T, Feng Y. Impact of organizational culture and computer self-efficacy on knowledge sharing. Industrial Management & Data Systems. 2015;115(4):590-611. doi: 10.1108/IMDS-12-2014-0377.

    • Lee S. An integrated adoption model for e-books in a mobile environment: Evidence from South Korea. Telematics and Informatics. 2013;30(2):165-76.

    • Ma X, Liu Y, Zhang P, Qi R, Meng F. Understanding online health information seeking behavior of older adults: A social cognitive perspective. Front Public Health. 2023;11:1147789. doi: 10.3389/fpubh.2023.1147789.

    • Al-Debei MM, Akroush MN, Ashouri MI. Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality. Internet Research. 2015;25(5):707-33.

    • Mai Y, Eisenberg A. Self-assembly of block copolymers. Chem Soc Rev. 2012;41(18):5969-85. doi: 10.1039/c2cs35115c.

    • Cao W, Zhang X, Xu K, Wang Y. Modeling Online Health Information-Seeking Behavior in China: The Roles of Source Characteristics, Reward Assessment, and Internet Self-Efficacy. Health Commun. 2016;31(9):1105-14. doi: 10.1080/10410236.2015.1045236.

    • Kang H. Sample size determination and power analysis using the G*Power software. J Educ Eval Health Prof. 2021;18:17. doi: 10.3352/jeehp.2021.18.17.

    • Henseler J, Hubona G, Ray PA. Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems. 2016;116(1):2-20. doi: 10.1108/IMDS-09-2015-0382.

    • Sarstedt M, Ringle CM, Hair JF. Partial least squares structural equation modeling. Handbook of market research. Cham: Springer International Publishing; 2021. p. 587-632. doi: 10.1007/978-3-319-05542-8_15-1.

    • Moradi M, Miralmasi A. Pragmatism Research Method. 1st ed. Tehran: Analysis Academy; 2020. [Persian].

    • Hair Jr JF, Hult GTM, Ringle CM, Sarstedt M, Danks NP, Ray S, et al. An introduction to structural equation modeling. Partial least squares structural equation modeling (PLS-SEM) using R: a workbook. 2021:1-29. doi: 10.1007/978-3-030-80519-7_1.

    • Tenenhaus M, Vinzi VE, Chatelin Y-M, Lauro C. PLS path modeling. Computational statistics & data analysis. 2005;48(1):159-205.

    • Shieh C, Broome ME, Stump TE. Factors associated with health information-seeking in low-income pregnant women. Women Health. 2010;50(5):426-42. doi: 10.1080/03630242.2010.506152.

    • Wang Y, Wang S, Wang J, Wei J, Wang C. An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model. Transportation. 2020;47:397-415.

    • Yang Y, Krupsky K, Keim S, McAdams R, Roberts K, McKenzie L. Online health information seeking behaviors and infant feeding practices: A Social Cognitive Theory perspective. Health Behavior Research. 2021;4(2):10.

    • Sabella SA, Suchan CS. The Contribution of Social Support, Professional Support, and Financial Hardship to Family Caregiver Life Satisfaction After Traumatic Brain Injury. J Head Trauma Rehabil. 2019;34(4):233-40. doi: 10.1097/HTR.0000000000000471.

    • Zhu Y, Song Y, Wang Y, Ji H, Wang D, Cai S, et al. Relationships among patient activation, social support and online health information seeking of community-dwelling older adults living with coronary heart disease. J Adv Nurs. 2023;79(1):161-9. doi: 10.1111/jan.15428.

    • Mwangakala HA. Accessibility of maternal health information and its influence on maternal health preferences in rural Tanzania: A case study of Chamwino District. South African Journal of Information Management. 2021;23(1):1-9.

    • Abadzadeh AS, Sharif SP. Online health information seeking among Malaysian women: Technology acceptance model perspective. Search. 2017;9(1):47-70.

    • Uddin J. Factors Influencing Birth Decision Among Bangladeshi Women: Applying the Health Belief Model and Theory of Planned Behavior. Washington: Howard University; 2023.

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