Social support and quality of life among rural family caregivers of persons with severe mental illness in Sichuan Province, China: mediating roles of care burden and loneliness

2021 ◽  
Author(s):  
Baiyang Zhang ◽  
Kyaien O. Conner ◽  
Hongdao Meng ◽  
Naidan Tu ◽  
Danping Liu ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Social Support ◽  
Mental Illness ◽  
Severe Mental Illness ◽  
Family Caregivers ◽  
Sichuan Province ◽  
Care Burden ◽  
Rural Family

scholarly journals The Influence of Social Support and Care Burden on Depression among Caregivers of Patients with Severe Mental Illness in Rural Areas of Sichuan, China

2019 ◽  
Vol 16 (11) ◽  
pp. 1961 ◽  
Author(s):  
Xiaxia Sun ◽  
Jingjing Ge ◽  
Hongdao Meng ◽  
Zhiguo Chen ◽  
Danping Liu
Keyword(s):  
Social Support ◽  
Mental Illness ◽  
Severe Mental Illness ◽  
Family Caregivers ◽  
Rural Areas ◽  
Structural Equation ◽  
Sichuan Province ◽  
Equation Modeling ◽  
Psychological Consequences ◽  
Care Burden

Depression is one of the most common psychological consequences of caregiving. Caring for patients with severe mental illness (SMI) adds significant challenges to family caregivers’ mental health. The purpose of this study was to describe the prevalence of depression among caregivers of SMI patients in rural areas of Sichuan province of China, to examine the influence of social support and care burden on depression, and to explore the intermediary effect of care burden between social support and depression among caregivers of SMI patients. Data were collected from 256 primary caregivers of SMI patients in rural Sichuan Province in China. We used structural equation modeling (SEM) to test the hypothesized relationship among the variables. We found that a total of 53.5% of caregivers had depression. Both care burden (β = 0.599, 95%CI: 0.392–0.776) and social support (β = −0.307, 95%CI: (−0.494)–(−0.115)) were directly related to depression, while social support had a direct association with care burden (β = −0.506, 95%CI: (−0.672)–(−0.341)). Care burden mediated the relationship between social support and depression. For the socio-demographic variables, gender, education level and per capita annual income of household had significant correlations with depression (p < 0.05). The results strongly demonstrated that social support and care burden were predictors of depression, especially social support. Policymakers should fully recognize the role of primary family caregivers in caring for SMI patients and promote interventions to decrease care burden and reduce caregivers’ depression by improving social support and network. More attention should be given to female caregivers and caregivers with lower education and lower household income levels.

scholarly journals Role of Social Support and Ego Network Characteristics on Quality of Life

2021 ◽  
Vol 20 (3) ◽  
pp. 637-654
Author(s):  
David C. Kondrat ◽  
W. Patrick Sullivan ◽  
Kelli E. Canada ◽  
Jeremiah W. Jaggers
Keyword(s):  
Quality Of Life ◽  
Mental Health ◽  
Social Support ◽  
Social Networks ◽  
Mental Illness ◽  
Severe Mental Illness ◽  
Mental Health Court ◽  
Mental Health Courts ◽  
Network Characteristics

Mental health courts offer alternatives to incarceration for persons with severe mental illness who are involved in the criminal justice system. These courts have the dual function of ensuring treatment for persons involved in the court as well as ensuring the safety of the public. Persons with severe mental illness who are involved in mental health courts rely on others for support, such as family members. Others may buttress the participant from engaging in criminal activities and provide for needs of the participant. The supportiveness as well as the composition of one’s network members may play a role in the success of mental health court participants, such as successfully completing the mental health court program and avoiding incarceration. Little research has explored how social support impacts mental health court participants. We explored how the composition and sense of support of network members were associated with mental health court participants’ quality of life. We regressed quality of life on social support and network characteristics of 80 participants in two mental health courts. Findings suggest that perceived support is positively associated with quality of life, and the proportion of family in one’s network was negatively related to quality of life. Findings suggest that persons involved in mental health courts need supportive others in their social networks in addition to family. More research is needed to explore the reasons having a higher proportion of family members in one’s network is associated with lower quality of life. Practitioners need to pay attention to and leverage mental health court participants’ social networks to help improve their quality of life.

scholarly journals The Full Mediating Role of Loneliness on the Relationship Between Social Support and Depression Among Rural Family Caregivers of Persons With Severe Mental Illness

2021 ◽  
Vol 9 ◽  
Author(s):  
Baiyang Zhang ◽  
Xin Lv ◽  
Mutian Qiao ◽  
Danping Liu
Keyword(s):  
Social Support ◽  
Mental Illness ◽  
Severe Mental Illness ◽  
Family Caregivers ◽  
Linear Regression Models ◽  
Mediating Role ◽  
Rural Family ◽  
The Social ◽  
Three Components

Objective: Depression is a common and overwhelming psychiatric disorder among family caregivers of persons with severe mental illness (SMI). The interrelationships among social support, loneliness, and depression, especially among this relatively vulnerable group, are poorly understood. The aim of the present study was to test the hypothesis that the social support contributes to the alleviation of depression, through its effect on reducing loneliness.Methods: A survey of 256 rural family caregivers of persons with SMI was conducted between December 2017 and May 2018 in Chengdu City, Sichuan Province, China. Social support, loneliness and depression were measured. A series of multiple linear regression models and bootstrapping procedure were performed to examine the mediating effects of loneliness on the association between social support as well as its components and depression.Results: The proportion of family caregivers of persons with SMI who reported significant depressive symptoms was 53.5%. Loneliness fully mediated the negative association between social support and depression. As to three components of social support, subjective support and objective support only had indirect associations with depression mediated by loneliness, while support utilization had both direct and indirect relationships with depression.Conclusion: The current study highlighted that social support and its three components may acted as protective factors by decreasing the feelings of loneliness, which created a beneficial effect on depression among family caregivers of persons with SMI.

scholarly journals Factors Influencing the Quality of Life among Family Caregivers of the Elderly with Dementia

2021 ◽  
Vol 28 (4) ◽  
pp. 500-509
Author(s):  
Hwasoon Kim
Keyword(s):  
Quality Of Life ◽  
Social Support ◽  
Family Caregivers ◽  
Pearson Correlation ◽  
Family Relationship ◽  
Subjective Health ◽  
Life Care ◽  
Care Burden ◽  
Problematic Behaviors

Purpose: The purpose of this study was to identify quality of life of family caregivers and to investigate factors positively and negatively affecting family caregivers’ quality of life.Methods: Participants were 153 family caregivers taking care of dementia elderly. Collected data were general characteristics, quality of life, care burden, depression, social support, family relationship, and problematic behaviors. Data were analyzed using descriptive statistics, independent t-tests, Pearson correlation coefficient, and multiple regression.Results: Mean age of participants was 58.70±13.88. The average scores of main variables for family relationship, social support, quality of life, care burden, problematic behaviors and depression were 3.99±1.08, 3.34±0.84, 3.00±0.63, 1.96±0.51, 1.48±1.06, 1.17±0.71 and 1.13±0.61, respectively. In regression analysis, depression (β=-.20), subjective health (β=.26), social support (β=.23), education level (β=-.20), and care burden (β=-.22) accounted for 59.1% of the variance in quality of life.Conclusion: To increase quality of life for family caregivers, interventions should be focused on reducing depression and care burden, enhancing caregiver’s health and social support. especially for family caregivers who received lower education.

scholarly journals Perceived quality of life and associated factors among patients with severe mental illness in Ethiopia: a cross-sectional study

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Seid Shumye ◽  
Tadele Amare ◽  
Habtamu Derajew ◽  
Merdia Endris ◽  
Wondwosen Molla ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Mental Health ◽  
Social Support ◽  
Mental Illness ◽  
Severe Mental Illness ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
The Mean

Abstract Background Severe mental illness is strongly associated with an impaired quality of life. This intern can affect the treatment adherence and outcomes of the illness. However, there are insufficient studies in the literature pertaining to the quality of life of patients with severe mental illness in Ethiopia. Therefore, assessing the quality of life of patients with severe mental illness and its correlates is a yardstick measure of the effectiveness of the mental health service. Methods An institutional based cross-sectional study was conducted from May 1 to 16, 2019 at Amanuel Mental Specialized Hospital. A systematic random sampling technique was used to get a total number of 387 samples. Data were collected using interview-administered questionnaires; World Health Organization Quality of Life Brief Version, Morisky Medication Adherence Screening Tool, Oslo Social Support Scale, and Jacoby Stigma Scale. Simple and multiple linear regression analysis were used to assess the contributing factors of quality of life in the participants and B coefficient with 95% CI confidence interval was used. The statistical significance was accepted at p value < 0.05. Results The result showed that the Mean quality of life score of patients with severe mental illness for each domain (mean ± SD) was 41.3 ± 7.5, 42.8 ± 8.2, 38.9 ± 8.9, and 41.8 ± 6.5 for physical, psychological, social and environmental, respectively. Multiple regression analysis showed that age of participants was strongly positively correlated with all domains of quality of life. It predicts above 45% of the variability in each domain. Social support is also another strong predictor which was negatively correlated with all domains of quality of life, except physical. Conclusion This study revealed that the mean score quality of life of patients with severe mental illness in each domain was low. This demonstrates a need for improving the quality of life of people with severe mental illness by integration of a positive mental health approach and bio-psychosocial view with biological treatment of severe mental illness. Moreover, in Collaboration with medical professionals, people with severe mental illness should screen and managed for any comorbid medical conditions.

scholarly journals The SOFIA pilot trial: a cluster-randomized trial of coordinated, co-produced care to reduce mortality and improve quality of life in people with severe mental illness in the general practice setting

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
M. P. Rozing ◽  
A. Jønsson ◽  
R. Køster-Rasmussen ◽  
T. D. Due ◽  
J. Brodersen ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Mental Illness ◽  
General Practice ◽  
Severe Mental Illness ◽  
General Practitioners ◽  
Pilot Trial ◽  
Care Program ◽  
Coordinated Care ◽  
Educational Training

Abstract Background People with severe mental illness (SMI) have an increased risk of premature mortality, predominantly due to somatic health conditions. Evidence indicates that primary and tertiary prevention and improved treatment of somatic conditions in patients with SMI could reduce this excess mortality. This paper reports a protocol designed to evaluate the feasibility of a coordinated co-produced care program (SOFIA model, a Danish acronym for Severe Mental Illness and Physical Health in General Practice) in the general practice setting to reduce mortality and improve quality of life in patients with severe mental illness. Methods The SOFIA pilot trial is designed as a cluster randomized controlled trial targeting general practices in two regions in Denmark. We aim to include 12 practices, each of which is instructed to recruit up to 15 community-dwelling patients aged 18 and older with SMI. Practices will be randomized by a computer in a ratio of 2:1 to deliver a coordinated care program or usual care during a 6-month study period. A randomized algorithm is used to perform randomization. The coordinated care program includes educational training of general practitioners and their clinical staff educational training of general practitioners and their clinical staff, which covers clinical and diagnostic management and focus on patient-centered care of this patient group, after which general practitioners will provide a prolonged consultation focusing on individual needs and preferences of the patient with SMI and a follow-up plan if indicated. The outcomes will be parameters of the feasibility of the intervention and trial methods and will be assessed quantitatively and qualitatively. Assessments of the outcome parameters will be administered at baseline, throughout, and at end of the study period. Discussion If necessary the intervention will be revised based on results from this study. If delivery of the intervention, either in its current form or after revision, is considered feasible, a future, definitive trial to determine the effectiveness of the intervention in reducing mortality and improving quality of life in patients with SMI can take place. Successful implementation of the intervention would imply preliminary promise for addressing health inequities in patients with SMI. Trial registration The trial was registered in Clinical Trials as of November 5, 2020, with registration number NCT04618250. Protocol version: January 22, 2021; original version

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