Back to Journals » Risk Management and Healthcare Policy » Volume 17

The Moderating Effect of Self-Efficacy on Pregnancy Stress and Smartphone Addiction of Pregnant Women in Late Pregnancy: A Longitudinal Study

Authors Ma D, Li B, Liu X, Sun Y, Sun J

Received 19 October 2023

Accepted for publication 27 December 2023

Published 5 January 2024 Volume 2024:17 Pages 41—48

DOI https://doi.org/10.2147/RMHP.S445581

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Jongwha Chang



Di Ma, Bingfen Li, Xiaoyan Liu, Ying Sun, Jingli Sun

Department of Gynaecology and Obstetrics, General Hospital of the Northern Theater Command, Shenyang, People’s Republic of China

Correspondence: Jingli Sun, Department of Gynaecology and Obstetrics, General Hospital of the Northern Theater Command, Shenyang, People’s Republic of China, Email [email protected]

Purpose: We aimed to understand the current situation of smartphone addiction in pregnant women, and explored the moderating effect of self-efficacy between pregnancy stress and smartphone addiction.
Patients and Methods: This study adopted a longitudinal design to collect pregnant women from the obstetrics and gynecology department of a tertiary hospital in Shenyang in 2020 from early pregnancy (T1) to their late pregnancy (T2). A total of 342 questionnaires were collected, including the Smartphone Addiction Scale-Short Version (SAS-SV), the Pregnancy Pressure Scale (PPS), and the Chinese version of the General Self-Efficacy Scale (GSES). Multiple hierarchical regression and simple slope test were used to test the moderating effect of self-efficacy.
Results: Smartphone addiction in T2 (44.74) was more sever than in T1 (33.11). The interaction item of T1 pregnancy stress and T2 self-efficacy was positively correlated with smartphone addiction (β=0.205, P< 0.01) and explained an additional 3.2% variance (ΔR2=0.032, P< 0.01). The influence of pregnancy stress on smartphone addiction was gradually decreased in the low, mean, and high groups of self-efficacy.
Conclusion: Smartphone addiction in late pregnancy was more severe than that in early pregnancy, possibly due to increased pregnancy stress. The self-efficacy of pregnant women could reduce the impact of pregnancy stress on smartphone addiction. Medical staff can alleviate the bad behavior by improving their self-efficacy.

Keywords: late pregnancy, pregnancy stress, smartphone addiction, self-efficacy, moderating effect

Introduction

In recent years, with the popularity of smartphones, the focus of researchers has gradually shifted to the study of smartphone addiction behavior which is a common phenomenon in the social environment.1,2 Smartphone addiction refers to the negative impact on individuals or society caused by long-term excessive use of smartphones, such as impulsive use of phones, ignoring the surrounding environment, or affecting interpersonal communication.3 The unique accessibility and convenience of smartphones, as well as the ease and usefulness of application push messages, make addiction more likely to occur and affect more people.4 Previous studies have shown that women were more prone to smartphone addiction than men, so the mobile phone addiction behavior of pregnant women cannot be ignored.5 Firstly, pregnant women rely on smartphones to obtain parenting information. Secondly, changes in the emotions and personal experiences of pregnant women, as well as their ability to cope with persistent emotional distress, greatly enhance addiction and develop sustained coping strategies, namely, escaping reality through smartphones.6 Smartphone addiction can lead to various psychological problems and affect an individual’s physical health.7,8 In addition, the high comorbidity of smartphone addiction and psychiatric disorders can also affect major social functions and daily life.9 For pregnant women, smartphone addiction not only leads to the aforementioned hazards, but is also highly likely to lead to adverse pregnancy outcomes.10

Pregnancy stress referred to the psychological threat caused by various stress events during pregnancy, mainly manifested as concerns about the health of mother and baby, difficulty adapting to multiple roles (mother, wife, patient, etc.), and family economic burden.11 A study on pregnant women in northwest China showed that Among 750 respondents, 709 (94.53%) had mild or above pregnancy stress.12 The ACE (Anonymity, Convenience, and Escape) theoretical model proposed by Young13 illustrated that the network had the characteristic of avoidance, and individuals used the network to escape the pressure generated in life. The cognitive-behavioral model of PIU (pathological internet use) proposed by Davis14 believed that the occurrence of internet addiction behavior was closely related to negative psychological factors. Therefore, people with higher levels of stress were more inclined to use their phones as a way to alleviate negative emotions, thus forming addiction behavior.15,16

The perception of stressors factors depended on the personal capacity to elaborate. In the presence of stressors, individuals might or might not have obvious stress symptoms.17 Self efficacy was an individual’s subjective judgment and level of confidence in whether they could successfully complete a certain behavioral goal or activity task when facing a specific situation.18 Many studies have shown that individuals with high self-efficacy can better control internet addiction.19,20 When faced with the same source of stress, individuals with high self-efficacy adopted different corresponding strategies, which in turn affected healthy behavior.21,22 Studies on college students have shown that self-efficacy played a positive role in the relationship between physical activity and internet addiction.23 However, there was no research to confirm that self-efficacy can moderate the impact of pregnancy stress on smartphone addiction.

Transition refers to the transition from one life stage or state to another, during which individuals may face changes in their physical health, role relationships, expectations, and abilities, making them vulnerable to the impact of risk.24 The pregnancy in this study belongs to a transitional developmental transition period, which might have an impact on the health and behavior of pregnant women. The self-efficacy theory emphasizes the exploration of internal psychological processes and the regulatory role of self factors on behavior, which can help pregnant women better adapt to their own changes.25 Based on the above theory, this article proposed the following hypothesis: self-efficacy can moderate the relationship between pregnancy stress and smartphone addiction.

Materials and Methods

Study Design and Sample

This study adopted a longitudinal design to collect pregnant women in early pregnancy (T1) who underwent examinations in the obstetrics and gynecology department of a tertiary hospital in Shenyang in 2020, and conducted follow-up surveys in their late pregnancy (T2). All pregnant women signed a written informed consent form. According to Kendall’s26 sample size standard, the sample size was 10–20 times the number of variables. This study contained 17 variables, and considering a 20% dropout rate, the sample size was 306–408. Finally, a total of 400 Chinese questionnaires were sent out in this survey, 26 invalid questionnaires (incomplete content and a large number of duplicates) were eliminated in T1 stage, and 374 valid questionnaires remained. During T2 stage, 374 respondents were followed up, and a total of 356 completed the follow-up (18 were lost). After removing 14 invalid questionnaires, 342 (85.5%) valid questionnaires were finally recovered. Inclusion criteria: gestational age before 14 weeks (T1); no complications or endocrine system diseases; no mental illness.

Measurements

Demographic Variables

A self-filled questionnaire was used, which included age, occupation (business/ service industry, civil servants/public institutions, unemployed, and others), personal monthly income (RMB) (<2000 yuan, 2001–4000 yuan,>4001yuan), whether the husband smoked, daily exercise time (<2h, 2–4h, 4–8h), daily exposure to noise (no,<15min, 15min −1h,>1h).

Measurement of Smartphone Addiction

The Smartphone Addiction Scale-Short Version (SAS-SV) was used.27 The scale included 10 items and used a 1–6 level scoring system from “strongly disagree” to “strongly agree”. Add the scores of all items to get the total score. The total score range was 10–60, and high scores represented a high level of smartphone addiction. Cronbach’s alpha coefficient was 0.89 in this study.

Measurement of Pregnancy Stress

The Pregnancy Pressure Scale (PPS)was used.28 The scale included 30 items and used a 1–4 level scoring system from “not at all” to “always”. Add the scores of all items to get the total score. The total score range was 30–120, and high scores represented a high level of pregnancy stress. Cronbach’s alpha coefficient was 0.91 in this study.

Measurement of General Self-Efficacy

The Chinese version of the General Self-Efficacy Scale (GSES) was used.29 The scale included 10 items and used a 1–4 level scoring system from “completely incorrect” to “completely correct.” Add the scores of all items to get the total score. The total score range was 10–40, and high scores represented a high level of self-efficacy. Cronbach’s alpha coefficient was 0.94 in this study.

Statistic Analysis

This study was analyzed by IBM SPSS 26.0 software. Descriptive statistics, t-tests, and analysis of variance were used for one-way analysis. Partial correlations analysis was used to describe the correlation between variables. The multiple stratified regression analysis was uses to preliminary test the moderating effect of self-efficacy on the impact of pregnancy stress on smartphone addiction. If the standardized regression coefficient of the interaction term was meaningful, it could indicate the existence of a moderating effect, and centralized variables before regression analysis.30 The simple slope test was used to visualize the moderating effect of self-efficacy. Using a two tailed test, the significance level was set to α= 0.05.

Results

The Impact of Demographic Characteristics on Smartphone Addiction

The results showed that there was a statistically significant difference in smartphone addiction of pregnant women among different professions and daily exercise hours (P<0.05), as shown in Table 1.

Table 1 Demographic Variables of Participants in Relation to Smartphone Addiction

Psychological Health Status in Early and Late Pregnancy

Compared to early pregnancy, the pregnancy stress and smartphone addiction in late pregnancy were more severe, as shown in Table 2.

Table 2 Psychological Health Status in Early and Late Pregnancy

Correlation Analysis of Pregnancy Stress, Self-Efficacy, and Smartphone Addiction

From Table 3, it could be seen that pregnancy stress was negatively correlated with self-efficacy (P<0.01), and positively correlated with smartphone addiction tendency (P<0.01). There was a negative correlation between self-efficacy and smartphone addiction tendency (P<0.01).

Table 3 Correlation Analysis of Pregnancy Stress, Self-Efficacy, and Smartphone Addiction

The Moderating Effect of Self-Efficacy on Pregnancy Stress and Smartphone Addiction

In the first step, age, occupation, and daily exercise time were added to the regression model as control variables. In the second step, pregnancy stress and self-efficacy were added to the regression model, with regression coefficients of 0.436 and −0.148, respectively, jointly explaining the 24.8% variation in the smartphone addiction of pregnant women. Add the pregnancy stress * self-efficacy after centralized treatment to the regression model in Step 3, and its interaction term (ΔR2=0.032, β=0.205, P<0.01) had a significant impact on smartphone addiction, explaining a 3.2% variation in smartphone addiction. Self-efficacy played a moderating role between pregnancy stress and smartphone addiction, as shown in Table 4.

Table 4 Multiple Regression Analysis of Pregnancy Stress, Self-Efficacy, and Smartphone Addiction

Divide the subjects into high self-efficacy group (Mean±SD), medium self-efficacy group (Mean), and low self-efficacy group (Mean±SD) based on the mean of self-efficacy and its next standard deviation, and draw a moderating effect map. The results in Figure 1 showed that as self-efficacy increased from low to high, the impact of pregnancy stress on smartphone addiction gradually decreased. Self-efficacy played a moderating role in the relationship between pregnancy stress and smartphone addiction.

Figure 1 Simple slope test chart of self-efficacy regulation effect.

Discussion

The smartphone addiction among women in the third trimester of pregnancy in this study was above average. Compared to early pregnant women, late pregnant women have a higher smartphone addiction. Pregnant women showed more concern for fertility as their gestational age increased, and they needed to search online for information related to fertility. At the same time, as the workload decreased, they spent more time on smartphones, increasing the smartphone addiction. Excessive use of smartphone could have adverse effects on the main social functions and daily life of pregnant women.31 In addition, smartphone addiction could lead to physiological problems such as headaches, ear pain, enlarged median nerve, decreased grip and hand function, arm or shoulder soreness, poor immune system, and psychological problems such as irritability, sleep disorders, and depression.5,32 Medical staff should remind pregnant women to control their smartphone addiction, thus avoiding adverse risks during pregnancy.

The overall level of pregnancy stress in this article was higher than similar studies.33 This might be because our research was carried out in 2020, when the whole country was suffering from COVID-19, which had a certain impact on their admission and also increased their psychological burden.34 Our study showed that compared to early pregnant women, late pregnant women had higher pregnancy stress. Pregnant women, as a special group, not only bear the pressure of ordinary people, but also face the pregnancy related pressure brought about by the pregnancy itself, role changes, and changes in surrounding social relationships. As the gestational age continued to increase, the psychological sensitivity and vulnerability of pregnant women also changed, and the pressure of pregnancy also increased.35 Previous study had shown that there was a stronger correlation between psychological stress in pregnant women in the late stages of pregnancy and neurological development in children.36 Therefore, medical staff should pay attention to the stress situation during pregnancy, especially during the late pregnancy period, to avoid adverse pregnancy outcomes. The results also showed a positive correlation between pregnancy stress and smartphone addiction, indicating that the greater pregnancy stress, the more likely pregnant women were to develop smartphone addiction behavior, consistent with previous studies.16 Previous studies showed that individuals could alleviate psychological stress in various ways in situations of psychological conflict or stress, such as excessive consumption, excessive drinking, smoking, or excessive use of certain drugs, which had become a response to stress behavior, thereby achieving the goal of transferring psychological stress or temporarily paralyzing oneself.13 Pregnant women in the later stages of pregnancy, when facing increasing pressure, chose to use smartphones to temporarily escape. This immediate psychological avoidance, combined with the illusory online environment, became the main reinforcement factor for forced online behavior among pregnant women.

Our research has shown that self-efficacy moderated the impact of pregnancy stress on smartphone addiction in pregnant women. As self-efficacy increased, the impact of pregnancy stress on smartphone addiction gradually decreased. Pregnant women with a high sense of self-efficacy could effectively manage their negative emotions, divert attention through healthier ways, and reduce the occurrence of bad behavior.37,38 On the contrary, pregnant women with low self-efficacy were more likely to adopt negative coping styles such as withdrawal and avoidance, and may use mobile internet to escape life and work pressure, ultimately forming smartphone addiction. Self-efficacy could predict an individual’s overall confidence in coping with stress and regulate or alter the correlation between stress and behavior.39,40 In summary, if the self-efficacy of women in late pregnancy was high, they would adopt a positive attitude to face pregnancy stress, thereby reducing their tendency to become addicted to smartphones.

This study provided a new perspective for reducing adverse behaviors in pregnant women in clinical practice, that was, nursing staff could develop intervention methods aimed at improving self-efficacy to improve adverse behaviors. It was recommended that nursing staff can use peer education to improve self-efficacy.41 For example, they could invite mothers who have successfully given birth naturally to share their firsthand experiences, act as role models to encourage expectant mothers, enhance their confidence in childbirth, and enhance their self-efficacy. They can use mobile intervention platforms to explain childbirth knowledge to pregnant women, conduct prenatal training, and reduce pregnancy pressure, further enhancing confidence.42 Pregnant women’s family members also need to provide full companionship, encourage, stabilize their emotions, and improve their self-efficacy.

Conclusion

The pregnancy stress and smartphone addiction in late pregnancy were higher than that in early pregnancy. At the same time, pregnancy stress could also exacerbate smartphone addiction behavior, which mighty bring adverse pregnancy outcomes to pregnant women. The self-efficacy of pregnant women could effectively moderate the impact of pregnancy stress on smartphone addiction, that was, pregnant women with higher self-efficacy had less impact on smartphone addiction due to pregnancy stress. Therefore, it was suggested that obstetric medical staff should pay attention to the pregnancy stress and smartphone addiction behavior in the late pregnancy, and took intervention measures to improve the self-efficacy of pregnant women and reduced the occurrence of adverse behavior.

Data Sharing Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Ethical Approval

This study was reviewed and approved by the Ethics Committee of General Hospital of the Northern Theater Command. The study followed the principles of the Declaration of Helsinki. All participants were requested to read and sign the informed consent form before starting this study.

Acknowledgments

This study was grateful to the staff of the hospital who cooperated and the pregnant women who participated in the survey.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This study did not receive any funding.

Disclosure

The authors reported no conflicts of interest in this work.

References

1. Hosen I, Al Mamun F, Sikder MT, et al. Prevalence and Associated Factors of Problematic Smartphone Use During the COVID-19 Pandemic: a Bangladeshi Study. Risk Manag Healthc Policy. 2021;14:3797–3805. doi:10.2147/RMHP.S325126

2. Larsen H, Wiers RW, Su S, et al. Excessive smartphone use and addiction: when harms start outweighing benefits. Addiction. 2023;118(4):586–588. doi:10.1111/add.16060

3. Shin C, Dey AK Automatically detecting problematic use of smartphones. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing; 2013. 335–344.

4. James RJE, Dixon G, Dragomir MG, et al. Understanding the construction of ‘behavior’ in smartphone addiction: a scoping review. Addict Behav. 2023;137:107503. doi:10.1016/j.addbeh.2022.107503

5. Nikolic A, Bukurov B, Kocic I, et al. Smartphone addiction, sleep quality, depression, anxiety, and stress among medical students. Front Public Health. 2023;11:1252371. doi:10.3389/fpubh.2023.1252371

6. De Berardis D, Fornaro M, Orsolini L, et al. Emotional Dysregulation in Adolescents: implications for the Development of Severe Psychiatric Disorders, Substance Abuse, and Suicidal Ideation and Behaviors. Brain Sci. 2020;10(9):591. doi:10.3390/brainsci10090591

7. Noel JK, Sammartino CJ, Johnson M, et al. Smartphone Addiction and Mental Illness In Rhode Island Young Adults. R I Med J. 2023;106(3):35–41.

8. Xu Y, Zeng K, Dong L, et al. Understanding older adults’ smartphone addiction in the digital age: empirical evidence from China. Front Public Health. 2023;11:1136494. doi:10.3389/fpubh.2023.1136494

9. Tahir MJ, Malik NI, Ullah I, et al. Internet addiction and sleep quality among medical students during the COVID-19 pandemic: a multinational cross-sectional survey. PLoS One. 2021;16(11):e0259594. doi:10.1371/journal.pone.0259594

10. Zhihui G, Xuanyi L, Yang C, et al. Analysis of the impact of early pregnancy mental health and behavioral factors on adverse pregnancy outcomes. Chinese Practical Journal of Rural Doctor. 2022;29(10):17–20.

11. Alves AC, Souza RT, Mayrink J, et al. Measuring resilience and stress during pregnancy and its relation to vulnerability and pregnancy outcomes in a nulliparous cohort study. BMC Pregnancy Childbirth. 2023;23(1):396. doi:10.1186/s12884-023-05692-5

12. Tuxunjiang X, Li L, Zhang W, et al. Mediation effect of resilience on pregnancy stress and prenatal depression in pregnant women. Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2023;48(4):557–564. doi:10.11817/j.issn.1672-7347.2023.220338

13. Young KS. Psychology of computer use: XL. Addictive use of the Internet: a case that breaks the stereotype. Psychol Rep. 1996;79(3):899–902. doi:10.2466/pr0.1996.79.3.899

14. Zeng W, Wei H, Liu M. Need for Distinctiveness Leads to Pathological Internet Use? The Perspective of Cognitive Behavioral Model. Int J Environ Res Public Health. 2023;20(2):1609. doi:10.3390/ijerph20021609

15. Shen X, Wang C, Chen C, et al. Stress and Internet Addiction: mediated by Anxiety and Moderated by Self-Control. Psychol Res Behav Manag. 2023;16:1975–1986. doi:10.2147/PRBM.S411412

16. AlSaif HI, Alhozaimi ZA, Alrashed AS, et al. Is There an Association between Increased Stress and Smartphone Addiction? Insights from a Study on Medical Students from Saudi Arabia during the COVID-19 Pandemic. Medicina (Kaunas). 2023;59(8):1501. doi:10.3390/medicina59081501

17. Ślazyk-Sobol M, Dobrowolska M, Zomerfeld J, et al. Stress and self-efficacy as specific predictors of safety at work in the aviation sector. Med Pr. 2021;72(5):479–487. doi:10.13075/mp.5893.01104

18. Salles A. Self-Efficacy as a Measure of Confidence. JAMA Surg. 2017;152(5):506. doi:10.1001/jamasurg.2017.0035

19. Yang SY. Effects of Self-efficacy and Self-control on Internet Addiction in Middle School Students: a Social Cognitive Theory-Driven Focus on the Mediating Influence of Social Support. Child Health Nurs Res. 2020;26(3):357–365. doi:10.4094/chnr.2020.26.3.357

20. Hasan AA, Abu Jaber A. The relationship between Internet addiction, psychological distress, and coping strategies in a sample of Saudi undergraduate students. Perspect Psychiatr Care. 2020;56(3):495–501. doi:10.1111/ppc.12439

21. Gu Z, Li M, Liu L, et al. The moderating effect of self-efficacy between social constraints, social isolation, family environment, and depressive symptoms among breast cancer patients in China: a cross-sectional study. Support Care Cancer. 2023;31(10):594. doi:10.1007/s00520-023-08063-0

22. Hamerman EJ, Aggarwal A, Poupis LM. Generalized self-efficacy and compliance with health behaviours related to COVID-19 in the US. Psychol Health. 2023;38(8):969–986. doi:10.1080/08870446.2021.1994969

23. Du Z, Zhang X. Analysis of the mediating effects of self-efficacy and self-control between physical activity and Internet addiction among Chinese college students. Front Psychol. 2022;13:1002830. doi:10.3389/fpsyg.2022.1002830

24. Røysland IØ. Moving from one state to another among patients experiencing unexplained chest pain during physical activity: a secondary qualitative analysis by Meleis transition theory. Scand J Caring Sci. 2023;37:851–861. doi:10.1111/scs.13153

25. Kafaei-Atrian M, Sadat Z, Nasiri S, et al. The Effect of Self-care Education Based on Self-efficacy Theory, Individual Empowerment Model, and Their Integration on Quality of Life among Menopausal Women. Int J Community Based Nurs Midwifery. 2022;10(1):54–63. doi:10.30476/IJCBNM.2021.86814.1370

26. Kendall HB. Rank Correlation Measures. London: Cha-rles Griffin; 1975.

27. Kwon M, Kim D-J, Cho H, et al. The smartphone addiction scale: development and validation of a short version for adolescents. PLoS One. 2013;8(12):567.

28. Chen CH, Chen HM, Huang TH. Stressors associated with pregnancy as perceived by pregnant women during three trimesters. Gaoxiong Yi Xue Ke Xue Za Zhi. 1989;5(9):505–509.

29. Luszczynska A, Scholz U. The general self efficacy scale: multicultural validation studies. J Psychol. 2005;139:439–457. doi:10.3200/JRLP.139.5.439-457

30. Bolin JH. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. J Educ Meas. 2014;51:335–337. doi:10.1111/jedm.12050

31. Alkhateeb A, Alboali R, Alharbi W, et al. 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(7):3220–3224. doi:10.4103/jfmpc.jfmpc_1224_19

32. Foltran-Mescollotto F, Gonçalves ÉB, Castro-Carletti EM, et al. Smartphone addiction and the relationship with head and neck pain and electromiographic activity of masticatory muscles. Work. 2021;68(3):633–640. doi:10.3233/WOR-203398

33. Tu-xunjiang X, Wu-maier U, Wei Z, et al. Mediating effect of social support on the relationship between pregnancy stress and prenatal depression. Chin Prev Med. 2022;23(03):180–184.

34. Chen S, Zhuang J, Chen Q, et al. Pregnant women: psychology, cognitive and behavioral responses, and solutions towards COVID-19. Psychol Health Med. 2023;28(3):621–628. doi:10.1080/13548506.2022.2104881

35. Silveira ML, Pekow PS, Dole N, et al. Correlates of high perceived stress among pregnant Hispanic women in Western Massachusetts. Matern Child Health J. 2013;17(6):1138–1150. doi:10.1007/s10995-012-1106-8

36. Shi Y, Zhang Y, Wei Q, et al. Longitudinal association between maternal psychological stress during pregnancy and infant neurodevelopment: the moderating effects of responsive caregiving. Front Pediatr. 2022;10:1007507. doi:10.3389/fped.2022.1007507

37. Eslami V, Sany SBT, Tehrani H, et al. Examining health literacy and self-efficacy levels and their association with preventive behaviors of urinary tract infection in Iranian pregnant women: across sectional study. BMC Women's Health. 2023;23(1):258. doi:10.1186/s12905-023-02359-3

38. Cabrera-Aguilar E, Zevallos-Francia M, Morales-García M, et al. Resilience and stress as predictors of work engagement: the mediating role of self-efficacy in nurses. Front Psychiatry. 2023;14:1202048. doi:10.3389/fpsyt.2023.1202048

39. Lightsey OR, Smith BN. Resilience, Generalized Self-Efficacy, and Mindfulness as Moderators of the Relationship Between Stress and Well-Being. J Cogn Psychother. 2023;JCP-2022–0004.R1. doi:10.1891/JCP-2022-0004

40. Zhang X, Liu L, Ning J. The Mediating Effect of General Self-Efficacy Between Occupational Stress and Negative Emotion Among Psychiatric Nurses. J Psychosoc Nurs Ment Health Serv. 2023;61(3):33–39. doi:10.3928/02793695-20220809-02

41. Orsal O, Ergun A. The Effect of Peer Education on Decision-Making, Smoking-Promoting Factors, Self-Efficacy, Addiction, and Behavior Change in the Process of Quitting Smoking of Young People. Risk Manag Healthc Policy. 2021;14:925–945. doi:10.2147/RMHP.S280393

42. Lee Y, Choi S, Jung H. Self-Care Mobile Application for South Korean Pregnant Women at Work: development and Usability Study. Risk Manag Healthc Policy. 2022;15:997–1009. doi:10.2147/RMHP.S360407

Creative Commons License © 2024 The Author(s). This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.