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Saber S, Mardani-Hamooleh M, Seyedfatemi N, Kianian T, Bahrami R. Concept Analysis of Relapse in Chronic Mental Disorders Using Rodgers’ Evolutionary Approach. IJN 2025; 38 (S1 )
URL: http://ijn.iums.ac.ir/article-1-3883-en.html
Concept Analysis of Relapse in Chronic Mental Disorders Using Rodgers’ Evolutionary Approach
Saman Saber1 , Marjan Mardani-Hamooleh2 , Naima Seyedfatemi3 , Toktam Kianian4 , Raheleh Bahrami5
1- Department of Psychiatric Nursing, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
2- Department of Psychiatric Nursing, Nursing and Midwifery Care Research Center, Health Management Research Institute, School of Nursing and Midwifery, Iran University of Medical Sciences, Tehran, Iran. , mardanihamoole.m@iums.ac.ir
3- Department of Psychiatric Nursing, Nursing and Midwifery Care Research Center, School of Nursing and Midwifery, Iran University of Medical Sciences, Tehran, Iran.
4- Department of Public Health Nursing, Nursing and Midwifery Care Research Center, School of Nursing and Midwifery, Iran University of Medical Sciences, Tehran, Iran.
5- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, United States.
Keywords: Mental disorders, Concept analysis, Relapse
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Introduction
Chronic mental disorders are one of the causes of disabilities in the world that affect all aspects of a person’s life. The most common chronic mental disorders include major depressive disorder, schizophrenia, and bipolar disorder. These disorders are associated with frequent relapses. Despite the importance of the concept of relapse in chronic mental disorders, the existing knowledge in this field has not been well explained, and a comprehensive definition has not been provided for it. Considering that a single definition of the concept of relapse in chronic mental disorders is not available, and the application of this concept in the current situation is ambiguous and unclear, we decided to analyze this concept.  In all scientific disciplines, scientists need concepts for the systematic study and analysis of facts and specific phenomena in their respective fields, and hence to define them. Discussing concepts helps reach consensus and reduces the risk of using them without thinking. In addition to helping to classify phenomena, concept analysis leads to a common interpretation of phenomena, prevents personal perceptions and conflicts, clarifies many hidden issues, and finally strengthens disciplines. 
Since human reality and its related phenomena are constantly changing, elements are interdependent and can only be interpreted in a set of contextual factors, which is consistent with Rodgers’ evolutionary approach. This is one of the basic approaches in concept analysis, emphasizing the desired concepts and their role in expanding and developing knowledge. In this approach, the dynamic nature of concepts is taken into consideration. Rodgers’ approach differs from traditional approaches to concept analysis, which assume that concepts are analyzed separately from their social context or their dependence on other concepts, because in this approach, concepts do not have a fixed nature but a dynamic one. In fact, in this approach, it is believed that every concept always has a dynamic and evolving nature and always needs clarification. The goal of this approach is not to search for absolute truth, but to treat truth as relative and dependent on time and context. According to Rodgers’ approach, every concept is always accompanied by changes over time. The evolutionary approach generally follows an inductive method and always provides a basis and background for future investigation and research.
In this study, we aimed to clarify the concept of relapse in chronic mental disorders, and determine its attributes, antecedents, and consequences, and assess its changes over time using Rodgers’ evolutionary approach.
Materials & Methods
In this study, Rodgers’ evolutionary approach was used. For this purpose, reliable national and international databases were searched for related articles published in Persian or English from 2014 to 2024. In the initial search, 1025 studies were found. After screening titles and removing duplicates, 456 articles remained. After screening abstracts, 205 articles were selected. After screening the full texts, 28 studies were finally selected for analysis.
Results
The attributes of the relapse concept were identified in two areas of initial and specific symptoms. The onset of symptoms of relapse can be acute or gradual; there may be mild precursor symptoms months before the definitive diagnosis of relapse, or the symptoms of the disease may show themselves acutely, severely, and suddenly. The antecedents were identified in two areas, of facilitators and barriers. Being prone to relapse, family-related factors, social stigma, disease-related factors, disease management inefficiency, care system failure, and perceived stress were identified as relapse facilitators, while efficient family and social support were identified as two relapse barriers. The consequences of relapse in chronic mental disorders were also classified into two groups: Disease burden on the patient and disease burden on the family. The disease burden on the patient included the visible and tangible costs for the clients that result from the recurrence of mental disorder and are felt in a wide range of physical and psycho-social dimensions. On the other hand, the disease burden on the families of a patient with relapse included the direct and indirect costs of medical and care services (education, regular visits to medical centers, transportation, and daily needs).
Conclusion
Relapse in chronic mental disorders is a multifactorial phenomenon that can start with initial symptoms and gradually show specific symptoms. This theoretical definition provides the basis for studies in the field of relapse in chronic mental disorders so that researchers can obtain a practical definition of the concept according to the existing conditions. It can be applied in the educational, clinical and management fields. Several factors can facilitate or prevent the relapse of these disorders. It can put a heavy burden on the patients and their families, but can be reduced by relying on the family’s efficiency and improving social support. 

Ethical Considerations
Compliance with ethical guidelines
This study was approved by the Ethics Committee of Iran University of Medical Sciences (Code: IR.IUMS.REC.1402.396).
Funding
This article is part of a research project, funded by the Nursing and Midwifery Care Research Center of Iran University of Medical Sciences.
Authors' contributions
The authors contributed equally to the preparation of this article.
Conflict of interest
The authors declared no conflict of interest.
Acknowledgments
The authors would like to thank the Nursing and Midwifery Care Research Center of Iran University of Medical Sciences for the financial support.

References
  1. Moureau L, Verhofstadt M, Liégeois A. Mapping the ethical aspects in end-of-life care for persons with a severe and persistent mental illness: A scoping review of the literature. Front Psychiatry. 2023; 14:1094038. [DOI:10.3389/fpsyt.2023.1094038] [PMID]
  2. Saber S, Mardani-Hamooleh M, Seyedfatemi N, Hamidi H. Nurses’ perception regarding barriers of palliative care provision for people with severe mental illness: A qualitative study. Prog Palliat Care. 2022; 30(5):288-94. [DOI:10.1080/09699260.2022.2053394]
  3. den Boer K, de Veer AJE, Schoonmade LJ, Verhaegh KJ, van Meijel B, Francke AL. A systematic review of palliative care tools and interventions for people with severe mental illness. BMC Psychiatry. 2019; 19(1):106. [DOI:10.1186/s12888-019-2078-7] [PMID]
  4. Mötteli S, Schori D, Schmidt H, Seifritz E, Jäger M. Utilization and Effectiveness of Home Treatment for People With Acute Severe Mental Illness: A Propensity-Score Matching Analysis of 19 Months of Observation. Front Psychiatry. 2018; 9:495. [DOI:10.3389/fpsyt.2018.00495] [PMID]
  5. Ayano G, Duko B. Relapse and hospitalization in patients with schizophrenia and bipolar disorder at the St Amanuel Mental Specialized Hospital, Addis Ababa, Ethiopia: A comparative quantitative cross-sectional study. Neuropsychiatr Dis Treat. 2017; 13:1527-31. [DOI:10.2147/NDT.S139075] [PMID]
  6. Kennard BD, Mayes TL, Chahal Z, Nakonezny PA, Moorehead A, Emslie GJ. Predictors and moderators of relapse in children and adolescents with major depressive disorder. J Clin Psychiatry. 2018; 79(2):15m10330. [DOI:10.4088/JCP.15m10330] [PMID]
  7. Sullivan S, Northstone K, Gadd C, Walker J, Margelyte R, Richards A, et al. Models to predict relapse in psychosis: A systematic review. Plos One. 2017; 12(9):e0183998. [DOI:10.1371/journal.pone.0183998] [PMID]
  8. Moges S, Belete T, Mekonen T, Menberu M. Lifetime relapse and its associated factors among people with schizophrenia spectrum disorders who are on follow up at Comprehensive Specialized Hospitals in Amhara region, Ethiopia: A cross-sectional study. Int J Ment Health Syst. 2021; 15(1):42. [DOI:10.1186/s13033-021-00464-0] [PMID]
  9. Belete H, Ali T, Legas G. Relapse and clinical characteristics of patients with bipolar disorders in Central Ethiopia: A cross-sectional study. Psychiatry J. 2020; 2020:8986014.  [DOI:10.1155/2020/8986014] [PMID]
  10. Leach MJ, Jones M, Bressington D, Nolan F, Jones A, Muyambi K, et al. The association between mental health nursing and hospital admissions for people with serious mental illness: A protocol for a systematic review. Syst Rev. 2018; 7(1):2. [DOI:10.1186/s13643-017-0658-5] [PMID]
  11. Brilowski GA, Wendler MC. An evolutionary concept analysis of caring. J Adv Nurs. 2005; 50(6):641-50. [DOI:10.1111/j.1365-2648.2005.03449.x] [PMID]
  12. Rodgers BL, Knafl KA. Concept development in nursing: Foundation, techniques and application. 2nded. Philadelphia. W.B. Saunders; 2000. [Link]
  13. Maramis MM, Sofyan Almahdy M, Atika A, Bagus Jaya Lesmana C, Gerick Pantouw J. The biopsychosocial-spiritual factors influencing relapse of patients with schizophrenia. Int J Soc Psychiatry. 2022; 68(8):1824-33.  [DOI:10.1177/00207640211065678] [PMID]
  14. Gumley A, Bradstreet S, Ainsworth J, Allan S, Alvarez-Jimenez M, Beattie L, et al. Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-Being, Engagement, and Recovery: Protocol for a Feasibility Cluster Randomized Controlled Trial Harnessing Mobile Phone Technology Blended With Peer Support. JMIR Res Protoc. 2020; 9(1):e15058.  [DOI:10.2196/15058] [PMID]
  15. Etain B, Bellivier F, Olié E, Aouizerate B, Aubin V, Belzeaux R, et al. Clinical predictors of recurrences in bipolar disorders type 1 and 2: A FACE-BD longitudinal study. J Psychiatr Res. 2021; 134:129-37. [DOI:10.1016/j.jpsychires.2020.12.041] [PMID]
  16. Barnett I, Torous J, Staples P, Sandoval L, Keshavan M, Onnela JP. Relapse prediction in schizophrenia through digital phenotyping: A pilot study. Neuropsychopharmacology. 2018; 43(8):1660-16. [DOI:10.1038/s41386-018-0030-z] [PMID]
  17. Eisner E, Drake R, Lobban F, Bucci S, Emsley R, Barrowclough C. Comparing early signs and basic symptoms as methods for predicting psychotic relapse in clinical practice. Schizophr Res. 2018; 192:124-30. [DOI:10.1016/j.schres.2017.04.050] [PMID]
  18. Noroozi M, Alibeigi N, Armoon B, Rezaei O, Sayadnasiri M, Nejati S, et al. Patterns of relapse risks and related factors among patients with schizophrenia in razi hospital, iran: A latent class analysis. Pol Psychol Bull. 2018; 49(3):355-9.  [DOI:10.24425/119502]
  19. Gaebel W, Riesbeck M. Are there clinically useful predictors and early warning signs for pending relapse? Schizophr Res. 2014; 152(2-3):469-77. [DOI:10.1016/j.schres.2013.08.003] [PMID]
  20. Salvat-Pujol N, Labad J, Urretavizcaya M, de Arriba-Arnau A, Segalàs C, Real E, et al. Hypothalamic-pituitary-adrenal axis activity and cognition in major depression: The role of remission status. Psychoneuroendocrinology. 2017; 76:38-48.   [DOI:10.1016/j.psyneuen.2016.11.007] [PMID]
  21. Saito Y, Sakurai H, Kane JM, Schooler NR, Suzuki T, Mimura M, et al. Predicting relapse with residual symptoms in schizophrenia: A secondary analysis of the PROACTIVE trial. Schizophr Res. 2020; 215:173-80. [DOI:10.1016/j.schres.2019.10.037] [PMID]
  22. Rotenberg LS, Borges-Júnior RG, Lafer B, Salvini R, Dias RDS. Exploring machine learning to predict depressive relapses of bipolar disorder patients. J Affect Disord. 2021; 295:681-7. [DOI:10.1016/j.jad.2021.08.127] [PMID]
  23. Moriarty AS, Castleton J, Gilbody S, McMillan D, Ali S, Riley RD, et al. Predicting and preventing relapse of depression in primary care. Br J Gen Pract. 2020; 70(691):54-5.   [DOI:10.3399/bjgp20X707753] [PMID]
  24. Spaniel F, Bakstein E, Anyz J, Hlinka J, Sieger T, Hrdlicka J, et al. Relapse in schizophrenia: Definitively not a bolt from the blue. Neurosci Lett. 2018; 669:68-74.  [DOI:10.1016/j.neulet.2016.04.044] [PMID]
  25. Vivalya BMN, Vagheni MM, Piripiri AL, Masuka RK, Omba AN, Mankubu AN, et al. Prevalence and factors associated with relapse and long hospital stay among adult psychiatric patients with a history of childhood trauma. Psychiatry Res. 2022; 316:114745. [DOI:10.1016/j.psychres.2022.114745] [PMID]
  26. Alphs L, Nasrallah HA, Bossie CA, Fu DJ, Gopal S, Hough D, et al. Factors associated with relapse in schizophrenia despite adherence to long-acting injectable antipsychotic therapy. Int Clin Psychopharmacol. 2016; 31(4):202-9.  [DOI:10.1097/YIC.0000000000000125] [PMID]
  27. Brouwer ME, Williams AD, Forand NR, DeRubeis RJ, Bockting CLH. Dysfunctional attitudes or extreme response style as predictors of depressive relapse and recurrence after mobile cognitive therapy for recurrent depression. J Affect Disord. 2019; 243:48-54. [DOI:10.1016/j.jad.2018.09.002] [PMID]
  28. Lee SU, Soh M, Ryu V, Kim CE, Park S, Roh S, et al. Analysis of the Health Insurance Review and Assessment Service data from 2011 to 2015. Int J Ment Health Syst. 2018 ; 12:9.  [PMID]   
  29. Sun Y, Tong J, Feng Y, Fang H, Jiang T, Zhao L, et al. Attitude and influencing factors of patients with schizophrenia toward long-acting injections: A community-based cross-sectional investigation in China. Front Public Health. 2022; 10:951544. [DOI:10.3389/fpubh.2022.951544] [PMID]
  30. Sureshkumar K, Kailash S, Dalal PK, Reddy MM, Sinha PK. Psychosocial Factors Associated with Relapse in Patients with Alcohol Dependence. Indian J Psychol Med. 2017; 39(3):312-5.  [DOI:10.4103/0253-7176.207337] [PMID]
  31. Parami S, Tapak L, Poorolajal J, Moghimbeigi A, Ghaleiha A. Identifying factors associated with the hospital readmission rate among patients with major depressive disorder. BMC Psychiatry. 2021; 21(1):542. [DOI:10.1186/s12888-021-03559-7] [PMID]
  32. Mumbere Vagheni M, Mutume Nzanzu Vivalya B, Kasereka Muyisa L, Kasereka Masuka R, Manzekele Bin Kitoko G. Prevalence and predictors of relapse among adolescent patients with mental illness in Butembo city (Eastern Part of the Democratic Republic of Congo). Psychiatry Res. 2022; 308:114342. [DOI:10.1016/j.psychres.2021.114342] [PMID]
  33. Ali S, Rhodes L, Moreea O, McMillan D, Gilbody S, Leach C, et al. How durable is the effect of low intensity CBT for depression and anxiety? Remission and relapse in a longitudinal cohort study. Behav Res Ther. 2017; 94:1-8. [DOI:10.1016/j.brat.2017.04.006] [PMID]
  34. Vigod SN, Kurdyak PA, Seitz D, Herrmann N, Fung K, Lin E, et al. READMIT: A clinical risk index to predict 30-day readmission after discharge from acute psychiatric units. J Psychiatr Res. 2015; 61:205-13. [DOI:10.1016/j.jpsychires.2014.12.003] [PMID]
  35. Taylor CL, Broadbent M, Khondoker M, Stewart RJ, Howard LM. Predictors of severe relapse in pregnant women with psychotic or bipolar disorders. J Psychiatr Res. 2018; 104:100-7.   [DOI:10.1016/j.jpsychires.2018.06.019] [PMID]
  36. Berwian IM, Wenzel JG, Kuehn L, Schnuerer I, Kasper L, Veer IM, et al. The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse. Sci Rep. 2020; 10(1):22346. [DOI:10.1038/s41598-020-79170-9] [PMID]
  37. Lye MS, Tey YY, Tor YS, Shahabudin AF, Ibrahim N, Ling KH, et al. Predictors of recurrence of major depressive disorder. Plos One. 2020; 15(3):e0230363. [DOI:10.1371/journal.pone.0230363] [PMID]
  38. Sud D, Bradley E, Tritter J, Maidment I. The impact of providing care for physical health in severe mental illness on informal carers: A qualitative study. BMC Psychiatry. 2024; 24(1):426.   [DOI:10.1186/s12888-024-05864-3] [PMID]
  39. Lal S, Malla A, Marandola G, Thériault J, Tibbo P, Manchanda R, et al. “Worried about relapse”: Family members’ experiences and perspectives of relapse in first-episode psychosis. Early Interv Psychiatry. 2019; 13(1):24-9. [DOI:10.1111/eip.12440] [PMID]
  40. Denissoff A, Taipale H, Tiihonen J, Di Forti M, Mittendorfer-Rutz E, Tanskanen A, et al. Antipsychotic Use and Psychiatric Hospitalization in First-Episode Non-affective Psychosis and Cannabis Use Disorder: A Swedish Nationwide Cohort Study. Schizophr Bull. 2024; 50(6):1287-94.  [DOI:10.1093/schbul/sbae034] [PMID]
Type of Study: Research | Subject: nursing
Received: 2025/02/19 | Accepted: 2025/12/22 | Published: 2025/03/21
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