Cognitive, emotional, and social factors promoting psychosocial adaptation: a study of latent profiles in people living in socially vulnerable contexts

Adverse environments cause well-established detrimental effects on subjects living there. They ultimately increase the likelihood of developing negative cognitive, emotional, and social outcomes. However, these adverse effects are not ubiquitous across all people. While some individuals develop maladaptive behavior and seem unable to cope with these difficulties, others develop strong coping mechanisms to manage the psychosocial effects of an adverse environment. Most research in this field, however, does not include multiple variables or complex models that allow them to control multivariate interactions simultaneously and as such, it is still unclear what interaction of social, emotional, and cognitive traits promote psychosocial adaptation in adverse environments. To address this, we employ an innovative combined methodological approachusing a theoretically driven person-centered approach (Latent Profile Analysis) aided by machine learning classification to model and predict different profiles of psychosocial adaptation within a sample of 254 adults. Our results showed a two-profile solution discriminated in this sample optimally into good and poor configurations for psychosocial adaptations. These results highlight the importance of distinct social, cognitive, and affective resources in developing adequate coping mechanisms in adults living in adverse environments. Importantly, the machine learning procedures allowed us to identify the most important features. High self-esteem and cognitive and behavioral self-regulation, low-stress levels, higher education, and increased social support are crucial factors for differentiating diverse pathways of psychosocial adaptation signaling risk and protective factors with important and straightforward implications for designing psychosocial interventions in these contexts