Exploring comorbidity between anxiety and depression among migrant Filipino domestic workers: A network approach.BACKGROUND
 Depression and anxiety are comorbid.  From the network model perspective, comorbidity is due to direct interactions between depression and anxiety symptoms.  These interacting symptoms are called bridge symptoms, suppression of which is expected to halt other symptoms.  This study investigates the network structure of depression, anxiety, and bridge symptoms in a sample of migrant domestic workers, who are among the most vulnerable and marginalized groups of workers.


 Data were collected from 1375 Filipino domestic workers in Macao Special Administrative Region, China.  Data from a subsample of 355 consisting of participants who met criteria for depression and anxiety were used in analysis.  R software was used to estimate the network.


 RESULTS
 The eight strongest edges were between items from the same disorder.  Six were between depression symptoms, like "concentration difficulties" and "psychomotor agitation/retardation," and "psychomotor agitation/retardation" and "thoughts of death."  Two were between anxiety symptoms, including "worry too much" and "trouble relaxing."  For centrality indices, "fatigue" had highest strength and closeness, and "restlessness" had highest betweenness.  Results revealed three bridge symptoms: "fatigue," "depressed mood," and "anhedonia."


 The results may not generalize to the entire Filipino population.  Further, while the centrality index of strength had adequate stability, it was not highly stable.


 The current study highlighted critical transdiagnostic bridge symptoms as specific candidates for intervention.  "Psychomotor agitation/retardation" was identified as key priority due to its association with suicidal ideation.  Systemic multilevel interventions at the person-level (e.g., cognitive therapy and behavioral activation), and at the structural and policy-level to alleviate psychosocial stressors, could be applied to address disorder comorbidity in this population.
R
R software was used to estimate the network.



R software