Do initial mental health, somatic, and social problems predict postdisaster lack of social support in the medium term? A latent profile analysis.

2021 ◽  
Author(s):  
Pien van de Ven ◽  
Rolf J. Kleber ◽  
Peter G. van der Velden
Keyword(s):  
Mental Health ◽  
Social Support ◽  
Latent Profile Analysis ◽  
Social Problems ◽  
Profile Analysis ◽  
Medium Term ◽  
Latent Profile

scholarly journals Classification of Mental Health among Korean Vietnam War Veterans: A Latent Profile Analysis

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 637-637
Author(s):  
Hyunyup Lee ◽  
Carolyn Aldwin ◽  
Sungrok Kang ◽  
Xyle Ku
Keyword(s):  
Mental Health ◽  
Vietnam War ◽  
Military Service ◽  
Latent Profile Analysis ◽  
Service Providers ◽  
Profile Analysis ◽  
Well Being ◽  
War Veterans ◽  
Vietnam War Veterans ◽  
Latent Profile

Abstract We investigated the dimensional structure of mental health among aging Korean Veterans using latent profile analysis (LPA) on posttraumatic stress disorder symptoms (PTSD), late onset stress symptomology (LOSS), and psychosocial well-being (PWB). The Korean Vietnam War Veterans Study consists of 367 men (Mage=72, SD=2.66). LPA identified five classes of mental health as best fitting the data. Most men were in the normal (38%) and moderate distress (31%) groups, while smaller proportions were in the low affect (13%) and severe distress (7%) groups. The resilient group (12%) had low PTSD, medium LOSS, and high PWB, and were highest on optimism, positive appraisals of military service, and social support. Negative and positive aspects of mental health outcomes were on separate dimensions rather than on a single bipolar dimension. Service providers should attempt to both reduce Veterans’ negative psychological symptoms and increase psychosocial well-being. Part of a symposium sponsored by the Aging Veterans: Effects of Military Service across the Life Course Interest Group.

scholarly journals Mental Health in Affectionate, Antagonistic, and Ambivalent Relationships During the COVID-19 Pandemic: A Latent Profile Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Jasmina Mehulić ◽  
Željka Kamenov
Keyword(s):  
Mental Health ◽  
Intimate Relationships ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Health Indicators ◽  
Well Being ◽  
Relationship Functioning ◽  
Relationship Type ◽  
Relationship Types ◽  
Latent Profile

The ongoing coronavirus disease-2019 (COVID-19) pandemic presents an acute stressor affecting mental health. In these stressful times, intimate relationships functioning could serve as a protective or a risk factor to the well-being of partners. Adult Croatian citizens engaged in intimate relationships (N = 727) reported their relationship characteristics and assessed symptoms of depression, anxiety, and stress during the state lockdown in May 2020. Three relationship profiles based on variations in key relationship characteristics were identified using latent profile analysis. Profiles represented distinct relationship types described as affectionate, ambivalent, and antagonistic relationships. These relationship types differed in their levels of love and perception of humility, responsiveness, and behavior of the partner. Relationship type was associated with mental health symptoms such as depression, anxiety, and stress during the COVID-19 pandemic and state lockdown. Being in an affectionate relationship was associated with the lowest levels of depression, anxiety, and stress, while in an antagonistic relationship these are in the highest levels. Ambivalent relationships were characterized by moderate levels on all measured mental health indicators with no difference in anxiety compared with affectionate relationships. The results emphasized the link between relationship functioning and successful coping with mental health hazards such as the fear of disease or restrictive measures put in place to contain the COVID-19 pandemic.

Coping profiles and health outcomes among individuals with systemic sclerosis: A latent profile analysis approach

2020 ◽  
Vol 5 (3) ◽  
pp. 231-236
Author(s):  
Shelley E Condon ◽  
Scott C Roesch ◽  
Philip J Clements ◽  
Daniel E Furst ◽  
Michael H Weisman ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Social Support ◽  
Psychological Distress ◽  
Systemic Sclerosis ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Health Related ◽  
And Coping ◽  
Latent Profile

Background: Systemic sclerosis has negative implications for quality of life, and coping is a mechanism by which individuals can adapt more successfully to illness. This study (1) identified coping profiles in patients with systemic sclerosis and (2) examined distress and disability correlates of the profiles. Methods: A sample of 93 patients with confirmed diagnoses of systemic sclerosis received clinical examinations and reported on coping, psychological distress, and health-related disability. Latent profile analysis was used to identify coping-based profile groups. The profile groups were then compared on psychological distress and health-related disability, controlling for disease severity. Results: A two-profile solution was supported: Active Copers emphasized problem-focused, social support, counting blessings, and religious approaches to coping with systemic sclerosis. Passive Copers emphasized blaming self and others, avoidance, and wishful thinking approaches to coping. Active Copers reported significantly less psychological distress than Passive Copers, but no significant differences were found for health-related disability. Discussion: The findings identify multidimensional patterns of coping that are differentially related to psychological distress in systemic sclerosis patients. These findings can inform coping-based interventions for patients with systemic sclerosis.

Latent profile analysis of mental health among Chinese healthcare staff during the COVID-19 pandemic

2021 ◽  
pp. 1-14
Author(s):  
Li Li ◽  
Zhimin Niu ◽  
Hongying Li ◽  
Mark D. Griffiths ◽  
Songli Mei ◽  
...  
Keyword(s):  
Mental Health ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Healthcare Staff ◽  
Latent Profile
Sign in / Sign up

Export Citation Format

Share Document