Social Science Research/Quality of Life and Mental Health in Disabled People

Social Science Research Quality of Life and Mental Health in Disabled People Social Science Research Rehabilitation of the Homeless The Swiss study https://bmcpsychology.biomedcentral.com/articles/10.1186/s40359-018-0276-6, titled "Productive Activities, Mental Health, and Quality of Life in Disability: Exploring the Role Enhancement and Role Strain Hypotheses," examined how different productive activities (paid work, volunteering, education, and housework) relate to mental health and quality of life in people with physical disabilities, particularly spinal cord injuries. Fekete, C., Siegrist, J., Post, M. W. M., & Brinkhof, M. W. G. (2019). Data from: Productive Activities, Mental Health, and Quality of Life in Disability: Exploring the Role Enhancement and Role Strain Hypotheses [Dataset]. Zenodo. https://doi.org/10.5061/dryad.6265g37 The study dataset is available on Zenodo: https://zenodo.org/records/4969076 and contains the variables sum_well (quality of life) with a score ranging from 0 to 20 and sum_mental (mental health) with a score ranging from 0 to 100. Other useful variables are paid workload ("None", "1-16 hours per week", ">16 hours per week"), volunteer workload ("None", "1-8 hours per week", ">8 hours per week"), education workload ("None", "1-8 hours per week", ">8 hours per week"), and housework load ("None", "1-16 hours per week", ">16 hours per week"). Paid Work As can be seen from the following table calculated in R, as hours of paid work increase, quality of life increases for both women and men with disabilities. However, while men's mental health improves, women's mental health declines, going from no paid work to 1-16 hours. Indeed, competing family and domestic obligations could reduce the positive effect of paid work on women's mental health. For men, exclusion from the labor market due to disability can have more serious consequences on mental health, potentially linked to feelings of lack of social reward, social exclusion, and lack of autonomy. df %>% group_by(gender,paid_workload) %>% summarise(mean_quality_of_life=mean(sum_well), mean_mental_health=mean(sum_mental)) Gender workload_pay…¹ mean_quality_of_life mean_mental_health 1 Women None 12.8 66.1 2 Women 1-16 ore per week 13.7 65.8 3 Women >16 ore per week 14.3 71.3 4 Men None 12.2 67.8 5 Men 1-16 ore per week 13.7 73.3 6 Men >16 ore per week 14.9 76.7 Volunteering As can be seen from the following table, Moderate volunteering (1-8 hours per week) benefits both the quality of life and mental health of men and women with disabilities. Gender Volunteer Work Average Quality of Life Average Mental Health 1 Women None 12.8 65.2 2 Women 1-8 ore per week 14.1 70.3 3 Women >8 ore per week 14.1 69.6 4 Men None 13.2 70.5 5 Men 1-8 ore per week 14.3 76.4 6 Men >8 ore per week 13.9 71.7 Education As can be seen from the following table, the quality of life and mental health of women with disabilities increases with increasing hours of education. For men with disabilities, a moderate education load (1-8 hours per week) is preferable. Gender Average Education Average Quality of Life Average Mental Health 1 Women None 13.2 67.3 2 Women 1-8 ore per week 14.1 67.8 3 Women >8 ore per week 15.5 72 4 Men None 13.6 72.2 5 Men 1-8 ore per week 14.4 76.3 6 Men >8 ore per week 13.9 72.2 Housework Moderate housework (1-16 hours per week) increases quality of life and mental health in both men and women with disabilities. Gender Average household workload Average mental health quality of life 1 Women None 11.7 64 2 Women 1-16 hours per week 13.3 68.7 3 Women >16 hours per week 13.6 66.8 4 Men None 12.4 70.3 5 Men 1-16 hours per week 14.2 74.4 6 Men >16 hours per week13.7 72.3 Gender household workload Average quality of life Average mental health 1 Women None 11.7 64 2 Women 1-16 ore per week 13.3 68.7 3 Women >16 ore per week 13.6 66.8 4 Men None 12.4 70.3 5 Men 1-16 ore per week 14.2 74.4 6 Men >16 ore per week 13.7 72.3 Correlations Calculating the Pearson correlation index between the number of productive activities and quality of life and mental health, we obtain 29.12% and 20.34%, so as productive activities increase, both parameters increase. cor(df$sum_well, df$prod_nr, use = "na.or.complete") cor(df$sum_mental, df$prod_nr, use = "na.or.complete") Productivity Benefits The main benefits identified in the study include: Improved mental health and quality of life: Engagement in productive activities was found to be an important determinant of mental health and quality of life. In general, higher total productivity is associated with better mental health and quality of life, especially in men. Satisfaction of basic human needs: Productive activities provide opportunities to satisfy basic needs such as a sense of belonging and social affiliation, the development and maintenance of skills, and recognition and appreciation from others. Lack of engagement in such activities can lead to social exclusion, lack of autonomy, and a lack of social reward, which negatively impact mental health and quality of life. Providing sources of socioemotional support and rewards: Engagement in diverse activities leads to a wide range of interactions with others, which can offer sources of socioemotional support and various types of rewards, with a positive impact on mental health and quality of life. Support for the role enhancement hypothesis: The simultaneous availability of different roles and role combinations across a variety of commitments improves mental health and quality of life, as they increase with the number of activities performed. Having a partner Using statistical inference, we can state that we are 95% confident that having a partner for a physically disabled person increases the quality of life variable on average, so we reject the null hypothesis H0, given that p_value <0.05: library(statsr) inference(y = sum_well, x = partner, data = df, statistic = "mean", type = "ht", null = 0, alternative = "less", method = "theoretical") Response variable: numerical Explanatory variable: categorical (2 levels) n_No = 376, y_bar_No = 12.7739, s_No = 3.8017 n_Si = 747, y_bar_Si = 14.1272, s_Si = 3.4863 H0: mu_No = mu_Si HA: mu_No < mu_Si t = -5.7856, df = 375 p_value = < 0.0001 The same applies to mental health.