The impact of nursing model supported by digital health technology (wearable device-assisted monitoring and online rehabilitation guidance) on the negative emotions, self-efficacy and quality of life of breast cancer patients: A retrospective study
Abstract
Objective: To explore the impact of nursing model supported by Digital health technology (DHT) on the quality of life, negative emotions, and self-efficacy of breast cancer patients, with a view to providing a basis for the scientific management and intervention of breast cancer patients. Methods: This study retrospectively included 138 breast cancer patients who were treated at The Affiliated Huai’an No.1 People’s Hospital of Nanjing Medical University from January 2022 to December 2024. According to their nursing models, patients were divided into intervention group (70 patients received the nursing model supported by DHT) and control group (68 patients received the conventional nursing model). The differences in the scores of the Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Functional Assessment of Cancer Therapy - Breast (FACT-B) scale, and Self-Efficacy Scale for Patients with Breast Cancer (SUPPH) between the two groups were compared before discharge and three months after discharge. Results: The patients intervened by the nursing model based on DHT had lower scores of SAS (t = 3.308, P = 0.001) and SDS (t = 2.482, P = 0.014), while the scores of FACT-B (t = 7.274, P = 0.014) and SUPPH (t = 1.975, P = 0.050) were higher. Conclusion: This study conducted in-hospital and out-of-hospital nursing interventions for breast cancer patients through the nursing model supported by DHT, and explored the impact of the new nursing model on the quality of life, depression level, and self-efficacy of them. The results show that the nursing model based on DHT has a positive impact on the quality of life, negative emotions, and self-efficacy of patients.
Copyright (c) 2026 Tingting Li, Jing Xu, Qing Zhang, Yanyan Shi, Jia Guo, Ying Lu
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
1. Soerjomataram I, Bray F. Planning for tomorrow: global cancer incidence and the role of prevention 2020-2070. Nature Reviews Clinical Oncology. 2021;18(10):663–672. doi:10.1038/s41571-021-00514-z
2. Siegel RL, Miller KD, Fuchs HE, et al. Cancer statistics. CA: A Cancer Journal for Clinicians. 2022; 72(1): 7–33. doi:10.3322/caac.21708
3. Bovbjerg DH, Keefe FJ, Soo MS, et al. Persistent breast pain in post-surgery breast cancer survivors and women with no history of breast surgery or cancer: associations with pain catastrophizing, perceived breast cancer risk, breast cancer worry, and emotional distress. Acta Oncologica. 2019;58(5):763–768. doi:10.1080/0284186x.2019.1574023
4. Durosini I, Triberti S, Savioni L, Sebri V, Pravettoni G. The Role of Emotion-Related Abilities in the Quality of Life of Breast Cancer Survivors: A Systematic Review. International Journal of Environmental Research and Public Health. 2022;19(19):12704. doi:10.3390/ijerph191912704
5. Cho D, Chu Q, Lu Q. Associations among physical symptoms, fear of cancer recurrence, and emotional well-being among Chinese American breast cancer survivors: a path model. Supportive Care in Cancer. 2018;26(6):1755–1761. doi:10.1007/s00520-017-4010-3
6. Gnall KE, Emrich M, Magin ZE, et al. Anxiety and fear of cancer recurrence as predictors of subsequent pain interference in early cancer survivorship: Exploring the moderating roles of cognitive and emotional factors. Journal of Behavioral Medicine. 2024;47(6):980–993. doi:10.1007/s10865-024-00506-1
7. Wang YH, Li JQ, Shi JF, et al. Depression and anxiety in relation to cancer incidence and mortality: a systematic review and meta-analysis of cohort studies. Molecular Psychiatry. 2020;25(7):1487–1499. doi:10.1038/s41380-019-0595-x
8. Bai Y, Zhang J, Sun Y, et al. Latent profile analysis and related factors for fear of cancer recurrence among Chinese breast cancer patients in rehabilitation. European Journal of Oncology Nursing. 2024; 71: 102651. doi:10.1016/j.ejon.2024.102651
9. Bedillion MF, Ansell EB, Thomas GA. Cancer treatment effects on cognition and depression: The moderating role of physical activity. The Breast. 2019;44:73–80. doi:10.1016/j.breast.2019.01.004
10. Puigpinós-Riera R, Graells-Sans A, Serral G, et al. Anxiety and depression in women with breast cancer: Social and clinical determinants and influence of the social network and social support (DAMA cohort). Cancer Epidemiology. 2018;55:123–129. doi:10.1016/j.canep.2018.06.002
11. Cho YU, Lee BG, Kim SH. Coping style at diagnosis and its association with subsequent health-related quality of life in women with breast cancer: A 3-year follow-up study. European Journal of Oncology Nursing. 2020;45:101726. doi:10.1016/j.ejon.2020.101726
12. Tsaras K, Papathanasiou IV, Mitsi D, et al. Assessment of Depression and Anxiety in Breast Cancer Patients: Prevalence and Associated Factors. Asian Pac J Cancer Prev. 2018;19(6):1661–1669. doi:10.22034/apjcp.2018.19.6.1661
13. Zhang J, Zhou Y, Feng Z, et al. Longitudinal Trends in Anxiety, Depression, and Quality of Life During Different Intermittent Periods of Adjuvant Breast Cancer Chemotherapy. Cancer Nursing. 2018;41(1):62–68. doi:10.1097/ncc.0000000000000451
14. World Health Organization. Global strategy on digital health 2020–2025. Available online: https://iris.who.int/handle/10665/344249 (accessed on 20 January 2025).
15. Morton K, Dennison L, May C, et al. Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. Patient Education and Counseling. 2017;100(4):616–635. doi:10.1016/j.pec.2016.10.019
16. Bodenheimer T, Sinsky C. From Triple to Quadruple Aim: Care of the Patient Requires Care of the Provider. The Annals of Family Medicine. 2014;12(6):573–576. doi:10.1370/afm.1713
17. Association AM. AMA digital health care 2022 study findings. Available online: https://www.ama-assn.org/about/research/ama-digital-health-care-2022-study-findings (accessed on 20 January 2025).
18. Contreras Sánchez SE, Doubova SV, Grajales Álvarez R, et al. Design and evaluation of a digital health intervention with proactive follow-up by nurses to improve healthcare and outcomes for patients with breast cancer in Mexico: protocol for a randomised clinical trial. BMJ Open. 2023;13(11):e077322. doi:10.1136/bmjopen-2023-077322
19. Lidington E, McGrath SE, Noble J, et al. Evaluating a digital tool for supporting breast cancer patients: a randomized controlled trial protocol (ADAPT). Trials. 2020;21(1):86. doi:10.1186/s13063-019-3971-6
20. Vrancken Peeters N, Husson O, Kulakowski R, et al. Evaluating a digital tool for supporting people affected by breast cancer: a prospective randomized controlled trial-the ADAPT study. Supportive Care in Cancer. 2024;32(11):740. doi:10.1007/s00520-024-08923-3
21. Piper BF, Dibble SL, Dodd MJ, et al. Piper Fatigue Scale—Revised. PsycTESTS Dataset; 1998. doi: 10.1037/t18854-000
22. Zung WW. A Self-Rating Depression Scale. Archives of General Psychiatry. 1965;12(1):63. doi:10.1001/archpsyc.1965.01720310065008
23. Matthies LM, Taran FA, Keilmann L, et al. An Electronic Patient-Reported Outcome Tool for the FACT-B (Functional Assessment of Cancer Therapy-Breast) Questionnaire for Measuring the Health-Related Quality of Life in Patients With Breast Cancer: Reliability Study. Journal of Medical Internet Research. 2019;21(1):e10004. doi:10.2196/10004
24. Lev EL, Owen SV. A measure of self-care self-efficacy. Res Nurs Health. 1996;19(5):421–429. doi:10.1002/(SICI)1098-240X(199610)19:5<421::AID-NUR6>3.0.CO;2-S
25. Lev EL, Eller LS, Gejerman G, et al. Quality of life of men treated with brachytherapies for prostate cancer. Health and Quality of Life Outcomes. 2004;2(1):28. doi:10.1186/1477-7525-2-28
26. Johnson RH, Anders CK, Litton JK, et al. Breast cancer in adolescents and young adults. Pediatric Blood & Cancer. 2018;65(12). doi:10.1002/pbc.27397
27. Youlden DR, Cramb SM, Yip CH, Baade PD. Incidence and mortality of female breast cancer in the Asia-Pacific region. Cancer Biol Med. 2014;11(2):101–115. doi:10.7497/j.issn.2095-3941.2014.02.005
28. Edib Z, Kumarasamy V, Binti Abdullah N, et al. Most prevalent unmet supportive care needs and quality of life of breast cancer patients in a tertiary hospital in Malaysia. Health and Quality of Life Outcomes. 2016;14(1). doi:10.1186/s12955-016-0428-4
29. Bozo Ö, Akıncı İ, Akyüz C. The Psychometric Properties of Cancer Behavior Inventory as a Predictor of Quality of Life in Turkish Cancer Patients. Current Psychology. 2019;38(1):229–238. doi:10.1007/s12144-017-9609-5
30. Ehlers SL, Davis K, Bluethmann SM, et al. Screening for psychosocial distress among patients with cancer: implications for clinical practice, healthcare policy, and dissemination to enhance cancer survivorship. Translational Behavioral Medicine. 2019;9(2):282–291. doi:10.1093/tbm/iby123
31. Eller LS, Lev EL, Yuan C, Watkins AV. Describing Self-Care Self-Efficacy: Definition, Measurement, Outcomes, and Implications. International Journal of Nursing Knowledge. 2018;29(1):38–48. doi:10.1111/2047-3095.12143
32. Huang Q, Wu F, Zhang W, et al. Risk factors for low self-care self-efficacy in cancer survivors: Application of latent profile analysis. Nursing Open. 2022;9(3):1805–1814. doi:10.1002/nop2.926
33. Phillips SM, Lloyd GR, Awick EA, McAuley E. Relationship between self-reported and objectively measured physical activity and subjective memory impairment in breast cancer survivors: role of self-efficacy, fatigue and distress. Psycho-Oncology. 2017;26(9):1390–1399. doi:10.1002/pon.4156
