Understanding Risk Factors of Recurrent Anxiety Symptomatology in an Older Population with Mild to Severe Depressive Symptoms: A Bayesian Approach  
[PERSON]  
1 Department of Electronic and Computer Engineering, University of Limerick, V94 T9 PX Limerick, Ireland; 1  
[PERSON]Health Research Institute, University of Limerick, V94 T9 PX Limerick, Ireland 2  
[PERSON]  
3 Departamento de Psiquiatiria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05402-000, Brazil; [PERSON] (M.M.d.S.M. ); [PERSON]SS] (C.A.N. ); [EMAIL_ADDRESS] (M.S.) 4 Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA 02115, USA 4  
[PERSON]  
3 Departamento de Psiquiatiria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 05402-000, Brazil; [PERSON] (M.M.d.S.M. ); [EMAIL_ADDRESS] (C.A.N. ); [EMAIL_ADDRESS] (M.S.) [PERSON]  
5 Centre for Global Mental Health, King's College London, London WC2R 2 LS, UK; [EMAIL_ADDRESS]  
[PERSON]  
6 Bristol Dental School, University of Bristol, Bristol BS2 0 PT, UK; [EMAIL_ADDRESS]  
[PERSON]  
1 Department of Electronic and Computer Engineering, University of Limerick, V94 T9 PX Limerick, Ireland; 1
Minimising recurrent anxiety is crucial not only for individuals but also for society, as anxiety symptomatology affects well-being, social relationships, and work productivity [4], resulting in economic burden including increased treatment costs [5]. To prevent recurrent anxiety, it is essential to identify those at highest risk and understand the most important predictors. This understanding is crucial so that relapse prevention efforts can be targeted towards those patients most in need [1]. Several studies have examined the relationships between anxiety recurrence and its predictors. For instance, [PERSON] and [PERSON] [6] identified general measures of anxiety, fearfulness, work, and home disability as key predictors of the recurrence of anxiety symptomatology. In this study, logistic regression was employed to analyse a set of seven predictors, generating a combination of nine different models. The model that achieved the best performance highlighted the key predictors associated with recurrent anxiety symptomatology. Another study demonstrated that the discontinuation of antidepressant medication serves as a predictor for anxiety symptomatology recurrence [7]. This approach utilised odds ratios [8] to assess the impact of medication discontinuation on recurrence rates. Further research has reinforced the importance of other predictors. Comorbid generalised anxiety and depression [2], worsening psychosocial impairment [9], and fear of anxiety-related sensations along with neuroticism [10] were all identified as important predictors of anxiety symptomatology recurrence. In each of these instances, proportional hazards regression was applied to evaluate the influence of these predictors [11]. While these methodologies are valuable for identifying predictors of anxiety recurrence, there are some limitations. In logistic regression, multicollinearity between predictors can cause difficulties in estimating the regression parameters accurately [12]. This issue is particularly challenging when analysing mental health disorders, where many predictors may have overlapping symptoms. Additionally, the interpretation of results from proportional hazards regression and odds ratios can be complex, particularly when dealing with multiple covariates and their interdependencies. It is noteworthy that none of these studies have specifically focused on the older population, despite increasing concerns about anxiety symptomatology within this group. Anxiety in older adults is particularly troubling due to its high recurrence rates and its potential impact on the development and prognosis of other age-related health issues, such as disability and depression [13].