Volume 13, Issue 3 (September 2026)
Health Spiritual Med Ethics 2026, 13(3): 185-194 |
Back to browse issues page
Ethics code: 0
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Kahalian N. Computational Analysis of the Effect of Islamic Spirituality on Heart Rate Response to Stress. Health Spiritual Med Ethics 2026; 13 (3) :185-194
URL: http://jhsme.muq.ac.ir/article-1-652-en.html
URL: http://jhsme.muq.ac.ir/article-1-652-en.html
Department of Electrical, Computer and Medical Engineering, Faculty of Engineering, Shahabdanesh University, Qom, Iran. , kahalian@shdu.ac.ir
Abstract: (973 Views)
Background and Objectives: Stress is a significant contributor to various diseases, necessitating effective management strategies. This study aimed to investigate the potential role of Islamic spirituality, conceptualized as both long-term disposition (“being spiritual”) and short-term practice (“engaging in spiritual acts”), in modulating heart rate (HR) responses to stress.
Methods: In this observational study, 24 female students (mean age = 28 years) were categorized using the Golzari religious belief commitment questionnaire. HR was recorded using a digital pulse oximeter during exposure to five standardized stress scenarios. For the short-term spirituality assessment, the experimental group performed Dhikr during recovery periods. HR signals were processed, and 20 features were extracted using a Daubechies-4 wavelet transform. Analysis of variance (ANOVA) was used for feature selection, and an extreme learning machine (ELM) classifier with a five-neuron hidden layer was employed for classification.
Results: ELM classifier achieved 94.4% accuracy in distinguishing between high and low long-term spirituality groups based on HR responses. For short-term spirituality, it differentiated the Dhikr group from controls with 88.8% accuracy during recovery phases.
Conclusion: Findings indicate that both facets of Islamic spirituality are associated with attenuated HR responses to stress, suggesting their potential role in mitigating physiological stress reactivity.
Methods: In this observational study, 24 female students (mean age = 28 years) were categorized using the Golzari religious belief commitment questionnaire. HR was recorded using a digital pulse oximeter during exposure to five standardized stress scenarios. For the short-term spirituality assessment, the experimental group performed Dhikr during recovery periods. HR signals were processed, and 20 features were extracted using a Daubechies-4 wavelet transform. Analysis of variance (ANOVA) was used for feature selection, and an extreme learning machine (ELM) classifier with a five-neuron hidden layer was employed for classification.
Results: ELM classifier achieved 94.4% accuracy in distinguishing between high and low long-term spirituality groups based on HR responses. For short-term spirituality, it differentiated the Dhikr group from controls with 88.8% accuracy during recovery phases.
Conclusion: Findings indicate that both facets of Islamic spirituality are associated with attenuated HR responses to stress, suggesting their potential role in mitigating physiological stress reactivity.
Keywords: Spirituality, Stress, Heart rate, Extreme learning machine classification, Computational analysis
Type of Study: Original Article |
Subject:
Special
Received: 2025/09/14 | Accepted: 2025/12/29 | Published: 2026/05/31
Received: 2025/09/14 | Accepted: 2025/12/29 | Published: 2026/05/31
References
1. Schramme T. Health as complete well-being: The WHO definition and beyond. Public Health Ethics. 2023; 16(3):210-8. [DOI:10.1093/phe/phad017] [PMID] [PMCID] [DOI:10.1093/phe/phad017]
2. Slimmen S, Timmermans O, Mikolajczak-Degrauwe K, Oenema A. How stress-related factors affect mental wellbeing of university students A cross-sectional study to explore the associations between stressors, perceived stress, and mental wellbeing. PLoS One. 2022; 17(11):e0275925. [DOI:10.1371/journal.pone.0275925] [PMID] [PMCID] [DOI:10.1371/journal.pone.0275925]
3. Vancheri F, Longo G, Vancheri E, Henein MY. Mental stress and cardiovascular health-part I. J Clin Med. 2022; 11(12):3353. [DOI:10.3390/jcm11123353] [PMID] [PMCID] [DOI:10.3390/jcm11123353]
4. Franklin BA, Rusia A, Haskin-Popp C, Tawney A. Chronic stress, exercise and cardiovascular disease: Placing the benefits and risks of physical activity into perspective. Int J Environ Res Public Health. 2021; 18(18):9922. [DOI:10.3390/ijerph18189922] [PMID] [PMCID] [DOI:10.3390/ijerph18189922]
5. Halbreich U. Stress-related physical and mental disorders: A new paradigm. BJPsych Adv. 2021; 27(3):145-52. [DOI:10.1192/bja.2021.1] [DOI:10.1192/bja.2021.1]
6. Yan J, Chen Y, Luo M, Hu X, Li H, Liu Q, et al. Chronic stress in solid tumor development: from mechanisms to interventions. J Biomed Sci. 2023; 30(1):8. [DOI:10.1186/s12929-023-00903-9] [PMID] [PMCID] [DOI:10.1186/s12929-023-00903-9]
7. Selye H. The general-adaptation-syndrome. Annu Rev Med. 1951; 2:327-42. [DOI:10.1146/annurev.me.02.020151.001551] [PMID] [DOI:10.1146/annurev.me.02.020151.001551]
8. Obbarius N, Fischer F, Liegl G, Obbarius A, Rose M. A modified version of the transactional stress concept according to Lazarus and Folkman was confirmed in a psychosomatic inpatient sample. Front Psychol. 2021; 12:584333. [DOI:10.3389/fpsyg.2021.584333] [PMID] [PMCID] [DOI:10.3389/fpsyg.2021.584333]
9. Gusilatar SJA, Calungsod JL, Garcia A, Santos B, Ruiz WG. The mediating role of dispositional resilience in the relationship between spirituality and life satisfaction of Filipino older adults. Front Psychol. 2025; 16:1570762. [DOI:10.3389/fpsyg.2025.1570762] [PMID] [PMCID] [DOI:10.3389/fpsyg.2025.1570762]
10. Lefevor GT, Etengoff C, Davis EB, Skidmore SJ, Rodriguez EM, McGraw JS, et al. Religion/spirituality, stress, and resilience among sexual and gender minorities: The religious/spiritual stress and resilience model. Perspect Psychol Sci. 2023; 18(6):1537-61. [DOI:10.1177/17456916231179137] [PMID] [DOI:10.1177/17456916231179137]
11. Khosravi M, Nikmanesh Z. Relationship of spiritual intelligence with resilience and perceived stress. Iran J Psychiatry Behav Sci. 2014; 8(4):52-6. [PMCID]
12. Anderson MR, Scalora SC, Crete A, Mistur EJ, Miller L. Physiological recovery from stress is associated with spiritual recovery: Findings from awakened awareness, a college-based spiritual-mind-body intervention. Integr Med Rep. 2023; 2(1):129-37. [doi:10.1089/imr.2023.0026] [DOI:10.1089/imr.2023.0026]
13. Fernández-Pascual MD, Reig-Ferrer A, Santos-Ruiz AM, Martínez-Rodríguez L. Spirituality in managing perceived stress and promoting self-care: A descriptive study on nursing students in Spain. J Relig Health. 2025; 64(2):882-98. [DOI:10.1007/s10943-024-02232-z] [PMID] [PMCID] [DOI:10.1007/s10943-024-02232-z]
14. Park CL, Hale A. Religious/spiritual meaning systems: Multiple pathways to well-being. In: Kim-Prieto C, editor. Religion and spirituality across cultures. 1th ed. Dordrecht: Springer; 2014. [DOI:10.1007/978-94-017-8950-9_10] [DOI:10.1007/978-94-017-8950-9_10]
15. Golzari M. [The revised form of practicing religious beliefs (Persian)]. Paper presented at: Theoretical Foundations and Psychometrics of Religious Scales. 2001. [Link]
16. Sharma LD, Bohat VK, Habib M, Al-Zoubi AM, Faris H, Aljarah I. Evolutionary inspired approach for mental stress detection using EEG signal. Expert Syst Appl. 2022; 197:116634. [DOI:10.1016/j.eswa.2022.116634] [DOI:10.1016/j.eswa.2022.116634]
17. Taskasaplidis G, Fotiadis DA, Bamidis PD. Review of stress detection methods using wearable sensors. IEEE; 2024. [DOI:10.1109/ACCESS.2024.3373010] [DOI:10.1109/ACCESS.2024.3373010]
18. Sahoo RK, Prusty AR, Rout A, Das B, Sethi P. Mental stress detection using GSR sensor data with filtering methods. In: Udgata SK, Sethi S, Gao XZ, editors. Intelligent Systems. Lecture Notes in Networks and Systems. Singapore: Springer; 2022. [DOI:10.1007/978-981-19-0901-6_47] [DOI:10.1007/978-981-19-0901-6_47]
19. Bobade P, Vani M. Stress detection with machine learning and deep learning using multimodal physiological data. Paper presented: Second International Conference on Inventive Research in Computing Applications (ICIRCA). 15-17 July 2020; Coimbatore, India. [DOI:10.1109/ICIRCA48905.2020.9183244] [DOI:10.1109/ICIRCA48905.2020.9183244]
20. Siam AI, Gamel SA, Talaat FM. Automatic stress detection in car drivers based on non-invasive physiological signals using machine learning techniques. Neural Comput Appl. 2023; 35:12891-904. [DOI:10.1007/s00521-023-08428-w] [DOI:10.1007/s00521-023-08428-w]
21. Chen J, Abbod M, Shieh JS. Pain and stress detection using wearable sensors and devices-a review. Sensors (Basel). 2021; 21(4):1030. [DOI:10.3390/s21041030] [PMID] [PMCID] [DOI:10.3390/s21041030]
22. Birjandtalab J, Cogan D, Pouyan MB, Nourani M. (2016). A non-EEG biosignals dataset for assessment and visualization of neurological status. Paper presented: International Workshop on Signal Processing Systems (SiPS). 26-28, October 2016; Dallas, TX, USA. [Link] [DOI:10.1109/SiPS.2016.27]
23. Ziaratnia S, Sripian P, Laohakangvalvit T, Sugaya M. Comparison of physiological responses to stroop word color test and IAPS stimulation. In: Duffy VG, editor. Digital human modeling and applications in health, safety, ergonomics and risk management. Cham: Springer; 2023. [DOI:10.1007/978-3-031-35748-0_15] [DOI:10.1007/978-3-031-35748-0_15]
24. Almazrouei MA, Morgan RM, Dror IE. A method to induce stress in human subjects in online research environments. Behav Res Methods. 2023; 55(5):2575-82. [DOI:10.3758/s13428-022-01915-3] [PMID] [PMCID] [DOI:10.3758/s13428-022-01915-3]
25. Rüttgens T, Suchan B, Wolf OT, Merz CJ. Acute stress does not modulate selective attention in a composite letter task. Stress. 2024; 27(1):2330704. [DOI:10.1080/10253890.2024.2330704] [PMID] [DOI:10.1080/10253890.2024.2330704]
26. Zimmer P, Buttlar B, Halbeisen G, Walther E, Domes G. Virtually stressed? A refined virtual reality adaptation of the Trier Social Stress Test (TSST) induces robust endocrine responses. Psychoneuroendocrinology. 2019; 101:186-92.[DOI:10.1016/j.psyneuen.2018.11.010] [PMID] [DOI:10.1016/j.psyneuen.2018.11.010]
27. Gerritsen C, De Man J, Van Der Meij J. (2013). Physiological and subjective response to injustice: The effects of unjust evaluations on physiological responses and subjective experiences. paper presented: International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). 17-20 November 2013 [DOI:10.1109/WI-IAT.2013.178]
28. Gerritsen C, De Man J, Van Der Meij J. (2013). Physiological and subjective response to injustice: The effects of unjust evaluations on physiological responses and subjective experiences. paper presented: International Joint Conferences on Web Intelligence [DOI:10.1109/WI-IAT.2013.178]
29. (WI) and Intelligent Agent Technologies (IAT). 17-20 November 2013; Atlanta, GA, USA. [DOI:10.1109/WI-IAT.2013.178] [DOI:10.1109/WI-IAT.2013.178]
30. Al-Hurr al-'Amili AS. Manshurat Dhawi l-Qurba. In: Wasa'il al-Shi'a. Qom: Manshurat Dhawi l-Qurba; 2008. [Link]
31. Al-Majlisi, M. B. Bihār al-Anwār al-Jāmi΄ah li-Durar Akhbār al-A΄immah al-Athār. Beirut: Mu΄assasat al-Wafā; 1984. [Link]
32. Razak NNA, Sidek KA, Alaa KYD, Nasir NFM. The response of EEG signal on brain relaxation meditation using different type of Zikr. J Phys Conf Ser. 2021; 2071:012050. [DOI:10.1088/1742-6596/2071/1/012050] [DOI:10.1088/1742-6596/2071/1/012050]
33. Suseno B. Muslim Prayer (Salah), and its restorative effect: Psychophysiological explanation. Asian J Islam Psychol. 2023; 1(1):1-7. [DOI:10.23917/ajip.v1i1.3702] [DOI:10.23917/ajip.v1i1.3702]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
Owned by Qom University of Medical Sciences
Published by Qom University of Medical Sciences Press
eISSN: 2383-3610
pISSN: 2322-4304
Email: j.hsme[at]muq.ac.ir
spirituality14[at]gmail.com
