The Path from Personality to Anxiety and Depression Is Mediated by Cognition in Multiple Sclerosis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Measures
2.3. Design and Procedure
2.4. Statistical Analysis
3. Results
Multiple Regression and Mediation
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Alfredsson, L.; Olsson, T. Lifestyle and Environmental Factors in Multiple Sclerosis. Cold Spring Harb. Perspect. Med. 2019, 9, a028944. [Google Scholar] [CrossRef] [PubMed]
- Maier, S.; Bajkó, Z.; Roșescu, R.; Bărcuțean, L.; Sărmășan, E.; Voidăzan, S.; Bălașa, R. Sociodemographic and Clinical Determinants of Fatigue in Multiple Sclerosis. Life 2023, 13, 2132. [Google Scholar] [CrossRef]
- Walton, C.; King, R.; Rechtman, L.; Kaye, W.; Leray, E.; Marrie, R.A.; Robertson, N.; La Rocca, N.; Uitdehaag, B.; van der Mei, I.; et al. Rising prevalence of multiple sclerosis worldwide: Insights from the Atlas of MS, third edition. Mult. Scler. 2020, 14, 1816–1821. [Google Scholar] [CrossRef] [PubMed]
- European MS Platform. 2020 MS Barometer. Brussels: EMSP. Available online: https://www.emsp.org/wp-content/uploads/2021/03/MS-Barometer2020-Final-Full-Report-Web.pdf (accessed on 3 May 2024).
- Lublin, F.D.; Reingold, S.C.; Cohen, J.A.; Cutter, G.R.; Sørensen, P.S.; Thompson, A.J.; Wolinsky, J.S.; Balcer, L.J.; Banwell, B.; Barkhof, F.; et al. Defining the clinical course of multiple sclerosis: The 2013 revisions. Neurology 2014, 83, 278–286. [Google Scholar] [CrossRef] [PubMed]
- Freeman, L.; Longbrake, E.E.; Coyle, P.K.; Hendin, B.; Vollmer, T. High-Efficacy Therapies for Treatment-Naïve Individuals with Relapsing-Remitting Multiple Sclerosis. CNS Drugs 2022, 36, 1285–1299. [Google Scholar] [CrossRef] [PubMed]
- Winkelmann, A.; Loebermann, M.; Reisinger, E.C.; Hartung, H.P.; Zettl, U.K. Disease-modifying therapies and infectious risks in multiple sclerosis. Nat. Rev. Neurol. 2016, 12, 217–233. [Google Scholar] [CrossRef]
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-5™, 5th ed.; American Psychiatric Publishing: Washington, DC, USA, 2013. [Google Scholar] [CrossRef]
- Widiger, T.A.; McCabe, G.A. The Alternative Model of Personality Disorders (AMPD) from the Perspective of the Five-Factor Model. Psychopathology 2020, 53, 149–156. [Google Scholar] [CrossRef]
- Barlow, D.H.; Ellard, K.K.; Sauer-Zavala, S.; Bullis, J.R.; Carl, J.R. The Origins of Neuroticism. Perspect. Psychol. Sci. 2014, 9, 481–496. [Google Scholar] [CrossRef]
- Tyrer, P. Personality dysfunction is the cause of recurrent non-cognitive mental disorder: A testable hypothesis. Pers. Ment. Health 2015, 9, 1–7. [Google Scholar] [CrossRef]
- Gore, W.L.; Widiger, T.A. The DSM-5 dimensional trait model and five-factor models of general personality. J. Abnorm. Psychol. 2013, 122, 816–821. [Google Scholar] [CrossRef]
- Dixon-Gordon, K.L.; Conkey, L.C.; Whalen, D.J. Recent advances in understanding physical health problems in personality disorders. Curr. Opin. Psychol. 2018, 21, 1–5. [Google Scholar] [CrossRef] [PubMed]
- Stathopoulou, A.; Christopoulos, P.; Soubasi, E.; Gourzis, P. Personality characteristics and disorders in multiple sclerosis patients: Assessment and treatment. Int. Rev. Psychiatry 2010, 22, 43–54. [Google Scholar] [CrossRef] [PubMed]
- Maggio, M.G.; Cuzzola, M.F.; Latella, D.; Impellizzeri, F.; Todaro, A.; Rao, G.; Manuli, A.; Calabrò, R.S. How personality traits affect functional outcomes in patients with multiple sclerosis: A scoping review on a poorly understood topic. Mult. Scler. Relat. Dis. 2020, 46, 102560. [Google Scholar] [CrossRef]
- Altaweel, N.; Upthegrove, R.; Surtees, A.; Durdurak, B.; Marwaha, S. Personality traits as risk factors for relapse or recurrence in major depression: A systematic review. Front. Psychiatry 2023, 14, 1176355. [Google Scholar] [CrossRef] [PubMed]
- Latas, M.; Milovanovic, S. Personality disorders and anxiety disorders: What is the relationship? Curr. Opin. Psychiatry 2014, 27, 57–61. [Google Scholar] [CrossRef] [PubMed]
- Patten, S.B.; Marrie, R.A.; Carta, M.G. Depression in multiple sclerosis. Int. Rev. Psychiatry 2017, 29, 463–472. [Google Scholar] [CrossRef] [PubMed]
- Zhang, X.; Song, Y.; Wei, Z.; Chen, X.; Zhuang, X.; Yi, L. The prevalence and risk factorsof anxiety in multiple sclerosis: A systematic review and meta-analysis. Front. Neurosci. 2023, 17, 1120541. [Google Scholar] [CrossRef]
- Marx, W.; Penninx, B.W.; Solmi, M.; Furukawa, T.A.; Firth, J.; Carvalho, A.F.; Berk, M. Major depressive disorder. Nat. Rev. Dis. Primers 2023, 9, 44. [Google Scholar] [CrossRef]
- Korostil, M.; Feinstein, A. Anxiety disorders and their clinical correlates in multiple sclerosis patients. Mult. Scler. 2007, 13, 67–72. [Google Scholar] [CrossRef]
- Slee, A.; Nazareth, I.; Freemantle, N.; Horsfall, L. Trends in generalised anxiety disorders and symptoms in primary care: UK population-based cohort study. Br. J. Psychiatry 2021, 218, 158–164. [Google Scholar] [CrossRef]
- Fournier, J.C.; Derubeis, R.J.; Beck, A.T. Dysfunctional cognitions in personality pathology: The structure and validity of the Personality Belief Questionnaire. Psychol. Med. 2014, 42, 795–805. [Google Scholar] [CrossRef]
- Beck, A.T.; Davis, D.D.; Freeman, A. Terapia Cognitiva a Tulburarilor de Personalitate, Ediția a Treia; Editura ASCR: Cluj-Napoca, Romania, 2019; pp. 21–63. [Google Scholar]
- Ellis, A.; Abrams, M.; Abrams, L. Personality Theories: Critical Perspectives; Sage Publications: Thousand Oaks, CA, USA, 2009. [Google Scholar]
- Beck, J.S. Cognitive Behaviour Therapy: Basics and Beyond, 3rd ed.; Guilford Press: New York, NY, USA, 2021. [Google Scholar]
- Kwon, S.-M.; Oei, T.P. Differential causal roles of dysfunctional attitudes and automatic thoughts in depression. Cogn. Ther. Res. 1992, 16, 309–328. [Google Scholar] [CrossRef]
- DiGiuseppe, R.A.; Doyle, K.A.; Dryden, W.; Backx, W. A Practitioner’s Guide to Rational Emotive Behavior Therapy, 3rd ed.; Oxford University Press: New York, NY, USA, 2014. [Google Scholar]
- Sindermann, C.; Saliger, J.; Nielsen, J.; Karbe, H.; Markett, S.; Stavrou, M.; Montag, C. Personality and Primary Emotional Traits: Disentangling Multiple Sclerosis Related Fatigue and Depression. Arch. Clin. Neuropsychol. 2018, 33, 552–561. [Google Scholar] [CrossRef] [PubMed]
- Incerti, C.C.; Argento, O.; Pisani, V.; Mannu, R.; Magistrale, G.; Di Battista, G.; Caltagirone, C.; Nocentini, U. A Preliminary Investigation of Abnormal Personality Traits in MS Using the MCMI-III. Appl. Neuropsychol. Adult 2015, 22, 452–458. [Google Scholar] [CrossRef] [PubMed]
- Kever, A.; Walker, E.L.S.; Riley, C.S.; Heyman, R.A.; Xia, Z.; Leavitt, V.M. Association of personality traits with physical function, cognition, and mood in multiple sclerosis. Mult. Scler. Relat. Disord. 2022, 59, 103648. [Google Scholar] [CrossRef] [PubMed]
- Roy, S.; Drake, A.S.; Eizaguirre, M.B.; Zivadinov, R.; Weinstock-Guttman, B.; Chapman, B.P.; Benedict, R.H. Trait neuroticism, extraversion, and conscientiousness in multiple sclerosis: Link to cognitive impairment? Mult. Scler. 2018, 24, 205–213. [Google Scholar] [CrossRef] [PubMed]
- Freedman, D.E.; Oh, J.; Kiss, A.; Puopolo, J.; Wishart, M.; Meza, C.; Feinstein, A. The influence of depression and anxiety on cognition in people with multiple sclerosis: A cross-sectional analysis. J. Neurol. 2024. [Google Scholar] [CrossRef] [PubMed]
- Ciancio, A.; Moretti, M.C.; Natale, A.; Rodolico, A.; Signorelli, M.S.; Petralia, A.; Altamura, M.; Bellomo, A.; Zanghì, A.; D’Amico, E.; et al. Personality Traits and Fatigue in Multiple Sclerosis: A Narrative Review. J. Clin. Med. 2023, 12, 4518. [Google Scholar] [CrossRef] [PubMed]
- Hanna, M.; Strober, L.B. Anxiety and depression in Multiple Sclerosis (MS): Antecedents, consequences, and differential impact on well-being and quality of life. Mult. Scler. Relat. Disord. 2020, 44, 102261. [Google Scholar] [CrossRef] [PubMed]
- Tauil, C.B.; Grippe, T.C.; Dias, R.M.; Dias-Carneiro, R.P.C.; Carneiro, N.M.; Aguilar, A.C.R.; da Silva, F.M.; Bezerra, F.; de Almeida, L.K.; Massarente, V.L. Suicidal ideation, anxiety, and depression in patients with multiple sclerosis. Arq. Neuropsiquiatr. 2018, 76, 296–301. [Google Scholar] [CrossRef]
- Buja, A.; Graffigna, G.; Mafrici, S.F.; Baldovin, T.; Pinato, C.; Bolzonella, U.; Barello, S.; Tognetto, A.; Damiani, G. Adherence to Therapy, Physical and Mental Quality of Life in Patients with Multiple Sclerosis. J. Pers. Med. 2021, 11, 672. [Google Scholar] [CrossRef] [PubMed]
- Fiest, K.M.; Walker, J.R.; Bernstein, C.N.; Graff, L.A.; Zarychanski, R.; Abou-Setta, A.M.; Patten, S.B.; Sareen, J.; Bolton, J.M.; Marriott, J.J.; et al. Systematic review and meta-analysis of interventions for depression and anxiety in persons with multiple sclerosis. Mult. Scler. Relat. Disord. 2016, 18, 96–104. [Google Scholar] [CrossRef] [PubMed]
- Kiropoulos, L.; Kilpatrick, T.; Kalincek, T.; Cherulov, L.; McDonald, E.; Wijeratne, T.; Threader, J.; Rozenblat, V.; Simpson-O’Brien, N.; Van Der Walt, A.; et al. Comparison of the effectiveness of a tailored cognitive behavioural therapy with a supportive listening intervention for depression in those newly diagnosed with multiple sclerosis (the ACTION-MS trial): Protocol of an assessor-blinded, active comparator, randomised controlled trial. Trials 2020, 21, 1–10. [Google Scholar]
- Sava, F.A. Formularul Clinic de Personalitate [Personality Clinical Form]; Editura Art Press: Timișoara, Romania, 2020. [Google Scholar]
- Beck, A.T.; Steer, R.A.; Brown, G.K. Beck Depression Inventory, 2nd ed.; Psychological Corporation: San Antonio, TX, USA, 1996. [Google Scholar]
- Beck, A.T.; Steer, R.A.; Brown, G.K.; David, D.; Dobrean, A. BDI-II Inventarul de Depresie Beck: Manual; RTS Publishing: Cluj-Napoca, Romania, 2012. [Google Scholar]
- Hamilton, M. The assessment of anxiety states by rating. Br. J. Med. Psychol. 1959, 32, 50–55. [Google Scholar] [CrossRef] [PubMed]
- Hamilton, M.; Macavei, B. Scala de anxietate Hamilton. In Sistem de Evaluare Clinica [Clinical Evaluation System]; David, D., Ed.; RTS Publishing: Cluj-Napoca, Romania, 2007. [Google Scholar]
- Hollon, S.D.; Kendall, P.C. Cognitive self-statements in depression: Development of an automatic thoughts questionnaire. Cogn. Ther. Res. 1980, 4, 383–395. [Google Scholar] [CrossRef]
- Moldovan, R. Chestionarul gândurilor automate [Automatic thoughts questionnaire]. In Sistem de Evaluare Clinica [Clinical Evaluation System]; David, D., Ed.; RTS Publishing: Cluj-Napoca, Romania, 2007. [Google Scholar]
- Weissman, A.N.; Beck, A.T. Development and validation of the Dysfunctional Attitude Scale: A preliminary investigation. In Proceedings of the Annual Meeting of the American Educational Research Association, Toronto, ON, Canada, 27–31 March 1978. [Google Scholar]
- Macavei, B. Dysfunctional attitude scale, form A; Norms for the Romanian population. J. Cogn. Behav. Psychother. 2006, 6, 157–171. [Google Scholar]
- DiGiuseppe, R.; Leaf, R.; Exner, T.; Robin, M.W. The development of a measure of irrational/rational thinking. In Proceedings of the World Congress of Behavior Therapy, Edinburgh, Scotland, 5–10 September 1988. [Google Scholar]
- DiGiusepe, R.; Leaf, R.; Exner, T.; Robin, M. Scala de atitudini li convingeri 2 (adaptat dupa Macavei, B.). In Sistem de Evaluare Clinica [Clinical Evaluation System]; David, D., Ed.; RTS Publishing: Cluj-Napoca, Romania, 2007. [Google Scholar]
- Chalder, T.; Berelowitz, G.; Pawlikowska, T.; Watts, L.; Wessely, S.; Wright, D.; Wallace, E.P. Development of a fatigue scale. J. Psychosom. Res. 1993, 37, 147–153. [Google Scholar] [CrossRef] [PubMed]
- EuroQol Research Foundation. EQ-5D-3L User Guide. Available online: https://euroqol.org/publications/user-guides (accessed on 3 April 2024).
- Yfantopoulos, J.N.; Chantzaras, A.E. Validation and comparison of the psychometric properties of the EQ-5D-3L and EQ-5D-5L instruments in Greece. Eur. J. Health Econ. 2017, 18, 519–531. [Google Scholar] [CrossRef] [PubMed]
- R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2024; Available online: https://www.R-project.org/ (accessed on 10 May 2024).
- Kassambara, A. Rstatix: Pipe-Friendly Framework for Basic Statistical Tests. R Package Version 0.7.2. 2023. Available online: https://CRAN.R-project.org/package=rstatix (accessed on 10 May 2024).
- Revelle, W. Psych: Procedures for Psychological, Psychometric, and Personality Research. R Package Version 2.3.9; Northwestern University: Evanston, IL, USA, 2023; Available online: https://CRAN.R-project.org/package=psych (accessed on 10 May 2024).
- Rosseel, Y. lavaan: An R Package for Structural Equation Modeling. J. Stat. Softw. 2011, 48, 1–36. [Google Scholar] [CrossRef]
- Boeschoten, R.E.; Braamse, A.M.J.; Beekman, A.T.F.; Cuijpers, P.; van Oppen, P.; Dekker, J.; Uitdehaag, B.M.J. Prevalence of depression and anxiety in Multiple Sclerosis: A systematic review and meta-analysis. J. Neurol. Sci. 2017, 372, 331–341. [Google Scholar] [CrossRef]
- Peres, D.S.; Rodrigues, P.; Viero, F.T.; Frare, J.M.; Kudsi, S.Q.; Meira, G.M.; Trevisan, G. Prevalence of depression and anxiety in the different clinical forms of multiple sclerosis and associations with disability: A systematic review and meta-analysis. Brain Behav. Immun. Health 2022, 24, 100484. [Google Scholar] [CrossRef]
- Ramirez, A.O.; Keenan, A.; Kalau, O.; Worthington, E.; Cohen, L.; Singh, S. Prevalence and burden of multiple sclerosis-related fatigue: A systematic literature review. BMC Neurol. 2021, 21, 468. [Google Scholar] [CrossRef]
- Krokavcova, M.; Van Dijk, J.P.; Nagyova, I.; Rosenberger, J.; Gavelova, M.; Gdovinova, Z.; Groothoff, J.W. Perceived health status as measured by the SF-36 in patients with multiple sclerosis: A review. Scand. J. Caring Sci. 2009, 23, 529–538. [Google Scholar] [CrossRef] [PubMed]
- Gil-González, I.; Martín-Rodríguez, A.; Conrad, R.; Pérez-San-Gregorio, M.Á. Quality of life in adults with multiple sclerosis: A systematic review. BMJ Open 2020, 10, e041249. [Google Scholar] [CrossRef]
- Güner, M.C.; Yazar, M.S.; Meterelliyoz, K.Ş. Cognitive predictors of depression and anxiety in individuals with newly diagnosed multiple sclerosis. Eur. J. Psychiatry 2020, 34, 202–210. [Google Scholar] [CrossRef]
- Buschmann, T.; Horn, R.A.; Blankenship, V.R.; Garcia, Y.E.; Bohan, K.B. The Relationship Between Automatic Thoughts and Irrational Beliefs Predicting Anxiety and Depression. J. Rat-Emo Cogn. Behav. Ther. 2018, 36, 137–162. [Google Scholar] [CrossRef]
- Yesilyaprak, N.; Batmaz, S.; Yildiz, M.; Songur, E.; Akpinar Aslan, E. Automatic thoughts, cognitive distortions, dysfunctional attitudes, core beliefs, and ruminative response styles in unipolar major depressive disorder and bipolar disorder: A comparative study. Psychiatry Clin. Psychopharmacol. 2019, 29, 854–863. [Google Scholar] [CrossRef]
- Vacaraș, V.; Văcăraș, V.; Nistor, C.; Văcăraș, D.; Opre, A.N.; Blaga, P.; Mureșan, D.F. The influence of Depression and Anxiety on Neurological Disability in Mulptiple Sclerosis Patients. Behav. Neurol. 2020, 2020, 6738645. [Google Scholar] [CrossRef]
- Vîslă, A.; Flückiger, C.; Grosse Holtforth, M.; David, D. Irrational Beliefs and Psychological Distress: A Meta-Analysis. Psychother. Psychosom. 2016, 85, 8–15. [Google Scholar] [CrossRef]
- Southard, A.C.; Noser, A.E.; Pollock, N.C.; Mercer, S.H.; Zeigler-Hill, V. The interpersonal nature of dark personality features. J. Soc. Clin. Psychol. 2015, 34, 555–586. [Google Scholar] [CrossRef]
- Vaheb, S.; Mokary, Y.; Panah, M.Y.; Shaygannejad, A.; Afshari-Safavi, A.; Ghasemi, M.; Shaygannejad, V.; Ghaffary, E.M.; Mirmosayyeb, O. Multiple sclerosis and personality traits: Associations with depression and anxiety. Eur. J. Med. Res. 2024, 29, 171. [Google Scholar] [CrossRef] [PubMed]
- Chu, L.; Casserly, C.; Rosehart, H.; Morrow, S.A. Is there a multiple sclerosis personality? Personality characteristics in newly diagnosed multiple sclerosis and association with mood and cognition. J. Neurol. Sci. 2022, 15, 120145. [Google Scholar] [CrossRef] [PubMed]
- Mirzaei, M.; Jaryani, N.; Masafi, S.; AfsarAski, S.; Dolatshahi, B.; Rezaei, O. Identifying the personality patterns in patients with multiple sclerosis (MS). Int. J. Collab. Res. Intern. Med. Public Health 2012, 4, 1901. [Google Scholar]
- Uca, A.U.; Uguz, F.; Kozak, H.H.; Turgut, K.; Tekin, G.; Altas, M.; Akpinar, Z. Personality disorders in pateints with multiple sclerosis: Prevalence and association with depressive and anxiety disorders and clinical features. Neurol. Asia 2016, 21, 55. [Google Scholar]
- Collison, K.L.; Lynam, D.R. Personality disorders as predictors of intimate partner violence: A meta-analysis. Clin. Psychol. Rev. 2021, 88, 102047. [Google Scholar] [CrossRef] [PubMed]
- Cheli, S.; Chiarello, F.; Cavalletti, V. A Psychotherapy Oriented by Compassion and Metacognition for Schizoid Personality Disorder: A Two Cases Series. J. Contemp. Psychother. 2023, 53, 61–70. [Google Scholar] [CrossRef]
- Demirci, S.; Demirci, K.; Demirci, S. The Effect of Type D Personality on Quality of Life in Patients with Multiple Sclerosis. Noro Psikiyatr. Ars. 2017, 54, 272–276. [Google Scholar] [CrossRef]
- Erickson, J.; El-Gabalawy, R.; Palitsky, D.; Patten, S.; Mackenzie, C.S.; Stein, M.B.; Sareen, J. Educational Attainment as a Protective Factor for Psychiatric Disorders: Findings from a Nationally Representative Longitudinal Study. Depress. Anxiety 2016, 33, 1013–1022. [Google Scholar] [CrossRef]
- Dorstyn, D.S.; Roberts, R.M.; Murphy, G.; Haub, R. Employment and multiple sclerosis: A meta-analytic review of psychological correlates. J. Health Psychol. 2019, 24, 38–51. [Google Scholar] [CrossRef]
- Zhao, Y.; Han, L.; Teopiz, K.M.; McIntyre, R.S.; Ma, R.; Cao, B. The psychological factors mediating/moderating the association between childhood adversity and depression: A systematic review. Neurosci. Biobehav. Rev. 2022, 137, 104663. [Google Scholar] [CrossRef]
- Arimitsu, K.; Hofmann, S.G. Cognitions as mediators in the relationship between self-compassion and affect. Pers. Individ. Dif. 2015, 74, 41–48. [Google Scholar] [CrossRef] [PubMed]
- Sease, T.B.; Perkins, D.R.; Sandoz, E.K.; Sudduth, H. Automatic thoughts: Understanding the precursors of self-concealment within the psychological flexibility framework. J. Context Behav. Sci. 2021, 22, 68–73. [Google Scholar] [CrossRef]
- Popa, C.O.; Rus, A.V.; Lee, W.C.; Cojocaru, C.; Schenk, A.; Văcăraș, V.; Olah, P.; Mureșan, S.; Szasz, S.; Bredicean, C. The Relation between Negative Automatic Thoughts and Psychological Inflexibility in Schizophrenia. J. Clin. Med. 2022, 11, 871. [Google Scholar] [CrossRef] [PubMed]
- Loas, G.; Cormier, J.; Perez-Diaz, F. Dependent personality disorder and physical abuse. Psychiatry Res. 2011, 185, 167–170. [Google Scholar] [CrossRef]
- Beck, A.T.; Bredemeier, K. A unified model of depression: Integrating clinical, cognitive, biological, and evolutionary perspectives. Clin. Psychol. Sci. 2016, 4, 596–619. [Google Scholar] [CrossRef]
- Silveira, C.; Guedes, R.; Maia, D.; Curral, R.; Coelho, R. Neuropsychiatric Symptoms of Multiple Sclerosis: State of the Art. Psychiatry Investig. 2019, 16, 877–888. [Google Scholar] [CrossRef] [PubMed]
- Gromisch, E.S.; Neto, L.O.; Turner, A.P. What Biopsychosocial Factors Explain Self-management Behaviors in Multiple Sclerosis? The Role of Demographics, Cognition, Personality, and Psychosocial and Physical Functioning. Arch. Phys. Med. Rehabil. 2021, 102, 1982–1988.e4. [Google Scholar] [CrossRef] [PubMed]
- Estrada-López, M.; Reguera-García, M.M.; Pérez Rivera, F.J.; Molina, A.J. Physical disability and personality traits in multiple sclerosis. Mult. Scler. Relat. Disord. 2020, 37, 101465. [Google Scholar] [CrossRef]
- Feinstein, A.; Magalhaes, S.; Richard, J.F.; Audet, B.; Moore, C. The link between multiple sclerosis and depression. Nat. Rev. Neurol. 2014, 10, 507–517. [Google Scholar] [CrossRef]
- Cojocaru, C.M.; Popa, C.O.; Schenk, A.; Marian, Ș.; Marchean, H.; Suciu, B.A.; Szasz, S.; Popoviciu, H.; Mureșan, S. Personality and Pain Outcomes in Rheumatic Disease: The Mediating Role of Psychological Flexibility. Healthcare 2024, 12, 1087. [Google Scholar] [CrossRef]
- Voigt, I.; Inojosa, H.; Wenk, J.; Akgün, K.; Ziemssen, T. Building a monitoring matrix for the management of multiple sclerosis. Autoimmun. Rev. 2023, 22, 103358. [Google Scholar] [CrossRef] [PubMed]
- Van Wijmeersch, B.; Hartung, H.P.; Vermersch, P.; Pugliatti, M.; Pozzilli, C.; Grigoriadis, N.; Alkhawajah, M.; Airas, L.; Linker, R.; Oreja-Guevara, C. Using personalized prognosis in the treatment of relapsing multiple sclerosis: A practical guide. Front. Immunol. 2022, 13, 991291. [Google Scholar] [CrossRef] [PubMed]
- McCracken, L.M. Personalized pain management: Is it time for process-based therapy for particular people with chronic pain? Eur. J. Pain. 2023, 27, 1044–1055. [Google Scholar] [CrossRef]
- Brauer, L.; Reinecke, M.A. Dependent Personality Disorder. In Cognitive Therapy of Personality Disorders, 3rd ed.; Beck, A.T., Davis, D.D., Freeman, A., Eds.; The Guilford Press: New York, NY, USA, 2015. [Google Scholar]
- Julia, C.R.; Mankiewicz, P.D. Paranoid, Schizotypal, and Schizoid Personality Disorders. In Cognitive Therapy of Personality Disorders, 3rd ed.; Beck, A.T., Davis, D.D., Freeman, A., Eds.; The Guilford Press: New York, NY, USA, 2015. [Google Scholar]
- Haddad, S.; Khalatbari, J.; Bahri, M.Z. The effectiveness of cognitive therapy based on mindfulness on emotion regulation and type D personality type symptoms in cardiac patients with ICD. J. Adolesc. Youth Psychol. Stud. 2023, 4, 16–23. [Google Scholar] [CrossRef]
- Turner, A.P.; Hartoonian, N.; Hughes, A.J.; Arewasikporn, A.; Alschuler, K.N.; Sloan, A.P.; Ehde, D.M.; Haselkorn, J.K. Physical activity and depression in MS: The mediating role of behavioral activation. Disabil. Health J. 2019, 12, 635–640. [Google Scholar] [CrossRef] [PubMed]
- Siengsukon, C.F.; Beck, E.S., Jr.; Drerup, M. Feasibility and Treatment Effect of a Web-Based Cognitive Behavioral Therapy for Insomnia Program in Individuals with Multiple Sclerosis: A Pilot Randomized Controlled Trial. Int. J. MS Care 2021, 23, 107–113. [Google Scholar] [CrossRef]
- Montañés-Masias, B.; Bort-Roig, J.; Pascual, J.C.; Soler, J.; Briones-Buixassa, L. Online psychological interventions to improve symptoms in multiple sclerosis: A systematic review: Online psychological interventions in Multiple Sclerosis. Acta Neurol. Scand. 2022, 146, 448–464. [Google Scholar] [CrossRef]
Clinical Sample (n = 43) | Controls (n = 31) | Overall (n = 74) | ||||
---|---|---|---|---|---|---|
Age (mean|SD) | 41.9 | 11.5 | 39.8 | 10.3 | 41 | 11 |
N | % | N | % | N | % | |
Sex | ||||||
Female | 31 | 72.1 | 25 | 80.6 | 56 | 75.7 |
Male | 12 | 27.9 | 6 | 19.4 | 18 | 24.3 |
Marital status | ||||||
Divorced | 3 | 7 | 2 | 6.5 | 5 | 6.8 |
In a relationship | 0 | 0 | 1 | 3.2 | 1 | 1.4 |
Married | 29 | 67.4 | 19 | 61.3 | 48 | 64.9 |
Single | 11 | 25.6 | 9 | 29 | 20 | 27 |
Education | ||||||
High school | 17 | 39.5 | 3 | 9.7 | 20 | 27 |
Higher education | 20 | 46.5 | 28 | 90.3 | 48 | 64.9 |
Middle school | 2 | 4.7 | 0 | 0 | 2 | 2.7 |
Post-high school studies | 1 | 2.3 | 0 | 0 | 1 | 1.4 |
Professional studies | 3 | 7 | 0 | 0 | 3 | 4.1 |
Occupation | ||||||
Employed | 17 | 39.5 | 26 | 83.9 | 43 | 58.1 |
Retired | 20 | 46.5 | 1 | 3.2 | 21 | 28.4 |
Student | 4 | 9.3 | 4 | 12.9 | 8 | 10.8 |
Housewife | 2 | 4.7 | 0 | 0 | 2 | 2.7 |
Type of MS | ||||||
RRMS | 40 | 93 | ||||
SPMS | 1 | 2.3 | ||||
PPMS | 2 | 4.7 | ||||
Disease duration (mean|SD) | 10.14 | 7.26 | ||||
EDSS (mean|SD) | 3.59 | 1.69 | ||||
≤4.5 | 33 | 76.7 | ||||
≥5 not >7 | 10 | 3.3 |
Clinical Sample (n = 43) | Controls (n = 31) | |||||||
---|---|---|---|---|---|---|---|---|
Variable | M | SD | M | SD | t | df | p | d |
HRAS | 18.30 | 11.49 | 4.13 | 7.72 | −6.34 | 71.71 | 0.00 | 1.45 |
BDI-II | 15.02 | 11.76 | 6.55 | 5.98 | −4.05 | 65.70 | 0.00 | 0.91 |
ABS II | 96.21 | 52.67 | 65.26 | 38.92 | −2.91 | 71.94 | 0.00 | 0.67 |
DAS-A | 120.67 | 44.04 | 103.81 | 30.01 | −1.96 | 71.82 | 0.05 | 0.45 |
ATQ | 33.23 | 14.24 | 25.58 | 10.69 | −2.64 | 71.86 | 0.01 | 0.61 |
CFS | 15.79 | 7.71 | 12.19 | 4.98 | −2.44 | 71.25 | 0.02 | 0.55 |
EQ5D3L | 7.86 | 2.03 | 5.65 | 0.88 | −6.38 | 60.86 | 0.00 | 1.42 |
Clinical Sample (n = 43) | Controls (n = 31) | |||||||
---|---|---|---|---|---|---|---|---|
Variable | M | SD | M | SD | t | df | p | d |
Negative emotionality | 53.72 | 9.40 | 47.90 | 9.97 | −2.54 | 62.43 | 0.01 | 0.60 |
Social and affective detachment | 51.02 | 9.08 | 45.90 | 7.54 | −2.64 | 70.49 | 0.01 | 0.61 |
Antagonism | 45.81 | 8.97 | 44.84 | 10.60 | −0.42 | 57.96 | 0.68 | 0.10 |
Disinhibition | 46.58 | 8.22 | 49.42 | 8.98 | 1.39 | 61.22 | 0.17 | 0.33 |
Psychoticism | 52.19 | 8.39 | 48.77 | 9.59 | −1.59 | 59.36 | 0.12 | 0.38 |
Avoidant PD | 51.00 | 9.08 | 46.94 | 9.52 | −1.85 | 62.94 | 0.07 | 0.44 |
Dependent PD | 53.40 | 9.07 | 48.74 | 9.26 | −2.15 | 63.99 | 0.04 | 0.51 |
Obsessive-compulsive PD | 53.07 | 11.65 | 49.06 | 10.75 | −1.53 | 67.65 | 0.13 | 0.36 |
Paranoid PD | 50.37 | 9.54 | 46.81 | 8.83 | −1.66 | 67.55 | 0.10 | 0.39 |
Schizotypal PD | 51.47 | 9.84 | 47.90 | 9.48 | −1.57 | 66.18 | 0.12 | 0.37 |
Schizoid PD | 52.23 | 9.40 | 46.97 | 7.71 | −2.64 | 70.72 | 0.01 | 0.61 |
Histrionic PD | 47.07 | 6.89 | 48.35 | 9.65 | 0.63 | 51.15 | 0.53 | 0.15 |
Narcissistic PD | 47.77 | 9.15 | 44.65 | 9.20 | −1.44 | 64.58 | 0.15 | 0.34 |
Borderline PD | 51.28 | 8.31 | 47.94 | 7.96 | −1.75 | 66.39 | 0.08 | 0.41 |
Antisocial PD | 46.58 | 9.28 | 46.45 | 10.56 | −0.05 | 59.51 | 0.96 | 0.01 |
Outcome | Intercept | Slope | F(7, 35) | p | radj2 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B | SE | 95% CI | B | SE | 95% CI | β | t | p | ||||||
LL | UL | LL | UL | |||||||||||
Dependent PT score as predictor | ||||||||||||||
HARS | −16.42 | 11.97 | −40.73 | 7.88 | 0.63 | 0.18 | 0.27 | 0.99 | 0.5 | 3.55 | 0.001 | 2.96 | 0.01 | 0.25 |
BDI-II | −15.4 | 13.73 | −43.28 | 12.48 | 0.53 | 0.2 | 0.12 | 0.94 | 0.41 | 2.61 | 0.01 | 1.37 | 0.24 | 0.06 |
CFS | −16.57 * | 7.75 | −32.29 | −0.84 | 0.53 | 0.11 | 0.30 | 0.76 | 0.62 | 4.62 | <0.001 | 3.6 | 0.005 | 0.30 |
EQ5D3L | 0.72 | 1.83 | −2.99 | 4.44 | 0.07 | 0.03 | 0.02 | 0.13 | 0.31 | 2.6 | 0.01 | 5.7 | <0.001 | 0.44 |
Schizoid PT score as predictor | ||||||||||||||
HARS | −12.2 | 11.51 | −35.56 | 11.17 | 0.6 | 0.18 | 0.24 | 0.97 | 0.49 | 3.34 | 0.002 | 2.75 | 0.02 | 0.23 |
BDI-II | −9.71 | 13.28 | −36.67 | 17.26 | 0.47 | 0.21 | 0.04 | 0.89 | 0.37 | 2.24 | 0.03 | 1.1 | 0.38 | 0.02 |
CFS | −8.97 | 8.06 | −25.34 | 7.40 | 0.43 | 0.13 | 0.17 | 0.69 | 0.52 | 3.41 | 0.002 | 2.11 | 0.07 | 0.16 |
EQ5D3L | 3.11 * | 1.86 | −0.67 | 6.89 | 0.03 | 0.03 | −0.03 | 0.09 | 0.14 | 1.06 | 0.30 | 4.25 | 0.002 | 0.35 |
Dependent PT Score | Schizoid PT Score | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Criteria | Predictor | B | SE | z | p | [95% CI] | B | SE | z | p | [95% CI] | ||
LL | UL | LL | UL | ||||||||||
ABS II | PT | 1.04 | 0.80 | 1.30 | 0.20 | −0.53 | 2.60 | 0.52 | 0.82 | 0.64 | 0.52 | −1.07 | 2.12 |
DAS-A | PT | 1.61 | 0.67 | 2.41 | 0.02 | 0.30 | 2.92 | 0.76 | 0.71 | 1.08 | 0.28 | −0.62 | 2.15 |
ATQ | PT | 0.56 | 0.22 | 2.50 | 0.01 | 0.12 | 1.00 | 0.45 | 0.23 | 1.93 | 0.05 | −0.01 | 0.90 |
HRAS anxiety | PT | 0.40 | 0.15 | 2.64 | 0.01 | 0.10 | 0.69 | 0.42 | 0.14 | 3.09 | 0.002 | 0.16 | 0.69 |
ABS II | 0.01 | 0.03 | 0.33 | 0.75 | −0.04 | 0.06 | −0.001 | 0.02 | −0.04 | 0.97 | −0.05 | 0.05 | |
DAS-A | 0.02 | 0.03 | 0.49 | 0.63 | −0.04 | 0.07 | 0.04 | 0.03 | 1.58 | 0.11 | −0.01 | 0.10 | |
ATQ | 0.36 | 0.09 | 3.96 | <0.001 | 0.18 | 0.53 | 0.33 | 0.09 | 3.83 | <0.001 | 0.16 | 0.49 | |
BDI-II depression | PT | 0.22 | 0.14 | 1.55 | 0.12 | −0.06 | 0.51 | 0.24 | 0.13 | 1.83 | 0.07 | −0.02 | 0.50 |
ABS II | 0.06 | 0.02 | 2.59 | 0.01 | 0.02 | 0.11 | 0.06 | 0.02 | 2.44 | 0.02 | 0.01 | 0.10 | |
DAS-A | 0.01 | 0.03 | 0.23 | 0.82 | −0.05 | 0.06 | 0.02 | 0.03 | 0.86 | 0.39 | −0.03 | 0.08 | |
ATQ | 0.41 | 0.09 | 4.80 | <0.001 | 0.24 | 0.58 | 0.40 | 0.08 | 4.77 | <0.001 | 0.23 | 0.56 | |
CFS fatigue | PT | 0.40 | 0.10 | 4.19 | <0.001 | 0.21 | 0.58 | 0.29 | 0.10 | 3.00 | 0.003 | 0.10 | 0.48 |
ABS II | −0.01 | 0.02 | −0.56 | 0.58 | −0.04 | 0.02 | −0.02 | 0.02 | −1.33 | 0.18 | −0.06 | 0.01 | |
DAS-A | −0.03 | 0.02 | −1.70 | 0.09 | −0.07 | 0.01 | −0.001 | 0.022 | −0.04 | 0.97 | −0.04 | 0.04 | |
ATQ | 0.34 | 0.06 | 6.10 | <0.001 | 0.23 | 0.45 | 0.35 | 0.06 | 5.80 | <0.001 | 0.23 | 0.47 | |
EQ-5D-3L health status | PT | 0.05 | 0.02 | 1.97 | 0.05 | 0.00 | 0.09 | −0.00 | 0.02 | −0.02 | 0.99 | −0.04 | 0.04 |
ABS II | 0.001 | 0.004 | 0.13 | 0.89 | −0.01 | 0.01 | −0.002 | 0.004 | −0.56 | 0.58 | −0.01 | 0.01 | |
DAS-A | −0.01 | 0.01 | −2.62 | 0.01 | −0.02 | −0.003 | −0.01 | 0.01 | −1.75 | 0.08 | −0.02 | 0.001 | |
ATQ | 0.08 | 0.01 | 5.74 | <0.001 | 0.05 | 0.11 | 0.09 | 0.01 | 6.20 | <0.001 | 0.06 | 0.11 |
Dependent PT Score | Schizoid PT Score | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
95% CI | 95% CI | |||||||||||
B | SE | z | LL | UL | p | B | SE | z | LL | UL | p | |
HARS Anxiety as outcome | r2 = 0.56 | r2 = 0.56 | ||||||||||
PT ABS II HRAS | 0.01 | 0.03 | 0.32 | −0.04 | 0.06 | 0.75 | −0.00 | 0.01 | −0.04 | −0.03 | 0.02 | 0.97 |
PT DAS-A HRAS | 0.02 | 0.05 | 0.48 | −0.07 | 0.12 | 0.63 | 0.03 | 0.04 | 0.89 | −0.04 | 0.11 | 0.37 |
PT ATQ HRAS | 0.20 | 0.09 | 2.11 | 0.01 | 0.38 | 0.04 | 0.15 | 0.09 | 1.73 | −0.02 | 0.31 | 0.08 |
Direct effect | 0.40 | 0.15 | 2.64 | 0.10 | 0.69 | 0.01 | 0.42 | 0.14 | 3.09 | 0.16 | 0.69 | 0.002 |
Total indirect | 0.23 | 0.11 | 2.11 | 0.02 | 0.44 | 0.04 | 0.18 | 0.09 | 1.92 | 0.00 | 0.36 | 0.06 |
Total effect | 0.63 | 0.15 | 4.08 | 0.33 | 0.93 | <0.001 | 0.60 | 0.15 | 3.94 | 0.30 | 0.90 | <0.001 |
BDI-II Depression as outcome | r2 = 0.56 | r2 = 0.54 | ||||||||||
PT ABS II BDI-II | 0.06 | 0.06 | 1.16 | −0.04 | 0.17 | 0.25 | 0.03 | 0.05 | 0.62 | −0.07 | 0.12 | 0.54 |
PT DAS-A BDI-II | 0.01 | 0.05 | 0.23 | −0.08 | 0.10 | 0.82 | 0.02 | 0.03 | 0.67 | −0.03 | 0.07 | 0.50 |
PT ATQ BDI-II | 0.23 | 0.10 | 2.22 | 0.03 | 0.43 | 0.03 | 0.18 | 0.10 | 1.79 | −0.02 | 0.37 | 0.07 |
Direct effect | 0.22 | 0.14 | 1.55 | −0.06 | 0.51 | 0.12 | 0.24 | 0.13 | 1.83 | −0.02 | 0.50 | 0.07 |
Total indirect | 0.31 | 0.13 | 2.41 | 0.06 | 0.55 | 0.02 | 0.22 | 0.11 | 1.99 | 0.003 | 0.45 | 0.05 |
Total effect | 0.53 | 0.16 | 3.23 | 0.21 | 0.85 | 0.001 | 0.47 | 0.16 | 2.87 | 0.15 | 0.79 | 0.004 |
CFS Fatigue as outcome | r2 = 0.67 | r2 = 0.60 | ||||||||||
PT ABS II CFS | −0.01 | 0.02 | −0.51 | −0.04 | 0.03 | 0.61 | −0.01 | 0.02 | −0.58 | −0.05 | 0.03 | 0.56 |
PT DAS-A CFS | −0.05 | 0.04 | −1.39 | −0.12 | 0.02 | 0.17 | −0.001 | 0.02 | −0.04 | −0.03 | 0.03 | 0.97 |
PT ATQ CFS | 0.19 | 0.08 | 2.31 | 0.03 | 0.36 | 0.02 | 0.16 | 0.08 | 1.84 | −0.01 | 0.32 | 0.07 |
Direct effect | 0.40 | 0.10 | 4.19 | 0.21 | 0.58 | <0.001 | 0.29 | 0.10 | 3.00 | 0.10 | 0.48 | 0.003 |
Total indirect | 0.13 | 0.09 | 1.42 | −0.05 | 0.31 | 0.16 | 0.14 | 0.09 | 1.62 | −0.03 | 0.32 | 0.11 |
Total effect | 0.53 | 0.12 | 4.59 | 0.30 | 0.75 | <0.001 | 0.43 | 0.12 | 3.52 | 0.19 | 0.67 | <0.001 |
EQ-5D-3L health status as outcome | r2 = 0.72 | r2 = 0.70 | ||||||||||
PT ABS II EQ-5D-3L | 0.001 | 0.004 | 0.13 | −0.01 | 0.01 | 0.89 | −0.001 | 0.003 | −0.42 | −0.01 | 0.004 | 0.67 |
PT DAS-A EQ-5D-3L | −0.02 | 0.01 | −1.77 | −0.04 | 0.002 | 0.08 | −0.01 | 0.01 | −0.92 | −0.02 | 0.01 | 0.36 |
PT ATQ EQ-5D-3L | 0.04 | 0.02 | 2.29 | 0.01 | 0.08 | 0.02 | 0.04 | 0.02 | 1.85 | 0.00 | 0.08 | 0.07 |
Direct effect | 0.05 | 0.02 | 1.97 | 0.00 | 0.09 | 0.05 | −0.00 | 0.02 | −0.02 | −0.04 | 0.04 | 0.99 |
Total indirect | 0.03 | 0.02 | 1.12 | −0.02 | 0.07 | 0.26 | 0.03 | 0.02 | 1.42 | −0.01 | 0.08 | 0.16 |
Total effect | 0.07 | 0.03 | 2.53 | 0.02 | 0.13 | 0.01 | 0.03 | 0.03 | 1.05 | −0.03 | 0.09 | 0.30 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Schenk, A.; Popa, C.O.; Cojocaru, C.M.; Marian, Ș.; Maier, S.; Bălașa, R. The Path from Personality to Anxiety and Depression Is Mediated by Cognition in Multiple Sclerosis. J. Pers. Med. 2024, 14, 682. https://doi.org/10.3390/jpm14070682
Schenk A, Popa CO, Cojocaru CM, Marian Ș, Maier S, Bălașa R. The Path from Personality to Anxiety and Depression Is Mediated by Cognition in Multiple Sclerosis. Journal of Personalized Medicine. 2024; 14(7):682. https://doi.org/10.3390/jpm14070682
Chicago/Turabian StyleSchenk, Alina, Cosmin Octavian Popa, Cristiana Manuela Cojocaru, Ștefan Marian, Smaranda Maier, and Rodica Bălașa. 2024. "The Path from Personality to Anxiety and Depression Is Mediated by Cognition in Multiple Sclerosis" Journal of Personalized Medicine 14, no. 7: 682. https://doi.org/10.3390/jpm14070682