Research Article

The Effect of Depression Among Working and Non-Working Married Women, A Comparative Study

Zeeshan Maqsood¹*, Rahila Akhtar² and Humaira Latif²

¹Department of Statistics, University of Sialkot, Sialkot, Pakistan

²Department of Quantitative Methods, University of Management and Technology, Lahore, Pakistan

Submission: April 01, 2019; Published: April 29, 2019

*Corresponding author: Zeeshan Maqsood, Department of Statistics, University of Sialkot, Sialkot, Pakistan

How to cite this article: Zeeshan Maqsood*, Rahila Akhtar and Humaira Latif. The Effect of Depression Among Working and Non-Working Married Women, A Comparative Study. Psychol Behav Sci Int J. 2019; 11(4): 555816. DOI: 10.19080/PBSIJ.2019.11.555816

Abstract

Depression is a big problem and takes attention of many researchers to find out the conclusion to know the causes of depression. This study was conducted to explore the determinants of depression among working and non-working married women. The factors Sadness, Guilty Feelings, Past Failure, Self-Criticalness, Agitation, Loss of interest, Loss of Energy and Tiredness or Fatigue. Data is collected from Lahore, Pakistan. The logistic regression technique used to test the hypotheses. Results conclude that working women have more depression as compare to non-working women. So, overview highlights that all factors play critical role. This study helps that the non-working married women can perform batter married life and they are free from depression as compared to working married women.

Keywords: Self-Criticalness; Agitation; Fatigue; Tiredness; Loss of Energy

Introduction

Depression isn’t always «one length suits all,» specifically in relation to the genders. No longer best are women greater vulnerable to depression than men, however the reasons of female depression or even the pattern of signs are often one-of-a-kind. Many factors contribute to the precise photo of melancholy in ladies from reproductive hormones to social pressures to the female response to stress. Learning about these elements assists you to limit your chance of melancholy and deal with it extra successfully. Depression is a serious circumstance that could impact each region of your existence. it could have an effect on your social existence, your circle of relatives relationships, your profession, and your experience of motive. And for girls particularly, depression is not unusual. In case you’re feeling unhappy, responsible, worn-out, and just normally “down in the dumps,” you may be affected by major depression. But the appropriate information is that despair is treatable, and the extra you apprehend about depression precise implications for an effect on girls, the extra geared up you’ll be to tackle the situation head on.

Causes of Depression in Women

Women are approximately two times as probable as men to be afflicted by depression. This -to-one distinction persists throughout racial, ethnic, and monetary divides. In truth, this gender distinction in fees of despair is observed in most international locations around the arena. There are some of theories which attempt to provide an explanation for the higher occurrence of despair in girls. Many elements have been implicated, consisting of organic, psychological, and social factors.

Despair in Married Working and Nonworking Women’s

Despair in a spouse is a difficulty that most couples will face at some point in their marriage. Despair is an ordinary and natural response to loss or grief, whether or not a death, separation from a cherished one, job loss, loss of bodily fitness, or relocation. Marital misery and relationship war additionally make contributions to melancholy. Signs and symptoms of despair include feelings of sadness, hopelessness, helplessness, tension, irritability, agitation, fatigue, low strength, and a reduced activity degree are common, and there may be also withdrawal from social contact and loss of hobby in formerly loved activities, along with intercourse. There can be modifications in urge for food, weight or sleep patterns, reminiscence troubles or difficulty concentrating. Frequently there are emotions of vanity lessness or inadequacy and a reduced feel of self-stem. Married ladies have better rates of depression than unmarried girls, but the opposite is authentic for guys. Marriage appears to confer an extra protecting gain on men than on ladies. In studies, accrued statistics on 695 ladies and 530 guys and then re-interviewed them up to. and conclude that working women may be prone to depression because they bear the double burden of housework and a job outside the home.

Significance of the Study

This study will be a significant attempt and beneficial to the women whom do not understand their depression reasons. Many researchers have been taking place in the field of depression since many years. But their findings cannot be generalized for each geographical area because people differ with respect to their way of responding even residing in the same locality. Realizing the fact, we formulated the hypothesis that working women have more depression as compare to nonworking women in Lahore.

Objectives of the Study

To measure the depression among working and nonworking women

To find out if there is any difference in depression among working and nonworking women.

Literature Review

Hine AH, et al. (2006) have been conducted the take a look at on “Marital Adjustment, stress and depression are among working and Non-working Married women” and aimed of this examine become exploring the relationship between marital adjustment, stress and depression. Sample of this study consists one hundred fifty working and non-working married women (working married women = seventy five, non-working married women = seventy five). Their age ranged between 18 to 50 years. Their training turned into as a minimum gradation and above. They belong to middle and high socio-monetary popularity. Urdu Translation of Dyadic Adjustment Scale (2000), Beck despair stock (1996) and stress Scale (1991) were used. Effects indicate highly significant relationship between marital adjustment, depression and stress. The findings of the results also display that working married women should face extra problems in their married lifestyles as compared to non-working married women. The results similarly show that distinctly knowledgeable working and non-working married women can carry out properly in their married lifestyles and they may be unfastened from depression compared to educated working and non-working married women.

Usha RR, et al. [1] have been conducted the take a look at on “working and non-working mothers: a comparative study” which has validated that employment has positive or neutral results on women’s health. This pilot looks at examines whether these effective results could also be determined in hired mothers via comparing working mothers with non-working mothers on measures of mental health, self-stem, and mothers position satisfaction. Also, this look at assesses the pressure experienced mothers and examines the coping techniques utilized by them. Of the 2 hundred questionnaires disbursed, 101have been back giving a 50.5 per cent go back charge of which 78 per cent have been working mothers and 22 percent non-working mothers. The working mothers had better mental fitness and pronounced much less depression than the non-working mothers. The most often pronounced supply of stress for working mothers was not having sufficient time to do the entirety, while for non-working mothers lack of social life become a chief stressor. The findings of this observe support the enlargement hypothesis, which emphasizes the blessings in place of the costs of a couple of function involvement [2].

Khanna S (1992) performed the have a look at on “Life Stress among Working and Nonworking Women in Relation to Anxiety and Depression” and determined existence pressure among working and nonworking women with regards to anxiety and depression. Right here 406 women had been defined in phrases of work status, 220 of them working and 186 non-working were selected from the city localities of Jalandhar (Punjab) and Shimla (Himachal Pradesh) in India. These women were investigated via 3 exams, specifically, Life Experience Survey, State-Trait Anxiety Inventory and Beck’s Depression Inventory. Co-relational analysis reveals that:

a. anxiety was significantly and negatively related to positive life exchange in nonworking women

b. depression was significantly and positively related to life exchange in working women, and negative life exchange in nonworking women.

Those outcomes advised that during India, amongst working high-quality positive existence modifications were related to depression, whereas amongst nonworking women positive life modifications have been associated with anxiety, and negative lifestyles changes to depression.

Shazia H & Seema M (2001) were carried out the examiner on “Effects of Employment on mothers and Their Children after Disruption of the Family” which aimed to evaluate the results of employment repute of mothers on them and their children after the disruption in their own family. Challenge and approach: After literature review it changed into hypothesized that 1) Divorced working moms will score low on the Variables of depression. anxiety and schizophrenic wondering as compared to divorced non-working mothers, 2)kids of divorced working mother can have: a)highly stem and high need for fulfillment compared to kids of divorced non-working mothers b) Low rankings at the variable on aggression and depressed temper as compared to youngsters of divorced non-working mothers [3].

First sample of divorced moms consisted of 30 mothers ( 15 working and 15 non-working ) who have acquired divorce best 12 months back and have been dwelling with their parental own family. Their age ranged from 18 to 35 years. Bothe the groups had been matched at the to be had of age, education, socioeconomic class and variety of children. Second sample consisted of kids of divorced mothers (15 children of working mothers and 15 youngsters of non-working mothers) and age variety of the children became among 6 years as much as 12 years. IMPAT-tension scale, IPAT-depression scale and Whitaker index of schizophrenic thinking had been administered on mothers and children Apperception test (CAT) changed into additionally administered individually on children apperception take a look at (CAT) was additionally administered personally on children. T-test turned into applied to calculate the mean difference on exclusive variables among above mentioned groups of children and women [4].

Research Methodology

The population in this survey was the married women of Lahore. Data collected from 100 women in which 50 were working and 50 were non-working. Beck despair inventory (BDI) used to measure the depression. It is miles global used for psychological despair studies. Logistic regression was used to check the depression among working and nonworking women. All data analysis was done on the R 3.2.2.

Results and Discussion

Table 1 showed that the total sample was of 100 married women in which 50 were working and 50 were nonworking. Table 2 showed that this is the last model of AIC which we selected, because its AIC value is less in all of the others. In all models this model is good fit because it’s AIC =103.34 value is smaller than the others. Table 3 shows the deviance residuals, which are a measure of model fit. The output shows the distribution of the deviance residuals for individual cases as (min=-2.2705, 1Q=-0.6839, median=0.0072, 3Q=0.5677, max=2.3949) used in the model. which summaries the deviance statistics to assess the models fitness. Table 4 shows the output of coefficients, their standard errors, the z-statistic (sometimes called a Wald z-statistic), and the associated p-values. The lowest suggesting a strong association of the age of the women with the probability of having depression. The negative coefficient for this predictor suggests that all other variables being equal, the women are less effect to have depression. P-value of these Seven variables( education), (agitation),( age: loss of interest),( education: loss of interest),( past failure: selfcriticalness), (self-criticalness: loss of interest),( age: past failure) are significantly effect on the dependent variable which is status of women [5]. The logistic regression coefficients give the change in the long odds of the outcome for a one unit increase in the predictor variable. In all models this model is good fit because it’s AIC =103.34 value is smaller than the others. For everyone unit change in age , the log odds of admission (versus non-admission) increases by 0.108. For a one unit increase in education, the log odds of being admitted to graduate school increases by 0.878. The indicator variables for duration have a slightly different interpretation. having status depend with duration changes the log odds of depression by -0.270. the table of coefficient are fit indices, including the null and deviance and the AIC [6].

Table 5 showed that the 2nd column shows the odds ratio of the independent variables. we interpret those odd ratios which are greater than 1 indicated significant effect. the odd ratio of age interprets as 1.114-1=0.114 which indicated that 0.114 times more chance that the age of women has effect on their status. the odd ratio of education interprets as 2.530- 1=1.530 which indicated that 1.530 times more chance that the education of women has effect on their status. the odd ratio of agitation interprets as 1.114-1=0.114 which indicated that 0.114 times more chance that the agitation of women has effect on their status. the odd ratio of loss of interest interpret as 42.848- 1=41.848 which indicated that 41.848 times more chance that the loss of interest of women has effect on their status. the odd ratio of education: loss of interest interprets as 2.866-1=1.866 which indicated that 1.866 times more chance that the education: loss of interest of women has effect on their status. the odd ratio selfcriticalness: loss of interest interprets as 37.975-1=36.975 which indicated that 36.975 times more chance that the self-criticalness: loss of interest of women has effect on their status. the odd ratio of age: past failure interprets as 1.146-1=0.146 which indicated that 0.146 times more chance that the age : past failure of women has effect on their status. The column number 3 and 4 indicated the 95% confidence interval for odd ratios. The C-I for odd ratios of age is 0.988 to 1.28. which indicated that the true population odds ratio of the age is lies between this interval. same as the true population odd ratios checked for other variables [7-9].

In Graph 1, the 1st plot helps to check the curvilinear trends. But by nature, the fit of a logistic regression is curvilinear. If the residuals are normally distributed, then the 2nd plot helps to detect the normality distribution. 3rd plot helps to identify heteroscedasticity. But logistic regression models are pretty much heteroscedastic by nature. And 4th plot helps to identify possible outliers, so all assumptions are fulfill about this data.

Graph 2 shows the probability of the logistic model with respect to its standardized prediction. The Graph shows the S shape which is fit for the data. All AIC model values show in Table 6. So last model is selected because its AIC value is less in all of the others. In first step AIC model value is 120.90 and 2nd 3rd ....11th model values are 115.34,113.42...103.34.model decreased AIC values even we select last model which AIC=103.34 (Graph 3).

Conclusion

In this study we find out the relationship of the working and non-working women with respect to the other independent variables. In this study 50 women are working and 50 were nonworking. The convenience sampling is used for the selection of sample and collection of information. The logistic regression technique used. In the final model the Age, Education, duration, Past failure, Self-criticalness, Agitation, Loss of interest, Age: Loss of interest, Education: Loss of interest, Past failure: Selfcriticalness, Self-criticalness: Loss of interest, Age: Past failure, duration: Self-criticalness are included as the independent variables. and the significant variables are education, agitation, age: loss of interest, education: loss of interest, past failure: selfcriticalness, self-criticalness: loss of interest, age: past failure. And the odd ratios t of age, education, agitation, loss of interest, odd ratio of education: loss of interest, self-criticalness: loss of interest, age: past failure, these independent variables. those odd ratios are greater than 1 and indicated significant effect. And also indicated the 95% confidence interval for odd ratios. which indicated that the true population odds ratio of the age is lies between this interval. The final model is selected on the basis of AIC. Due to significant results we reject our HO and conclude that working women have more depression as compare to nonworking women.

References

1. Rout UR, Cooper CL, Kerslake H (1997) Working and non-working mothers: A comparative study. Women in Management review 12(7): 264-275.
2. Hashmi HA, Khurshid M, Hassan I (2007) Marital adjustment, stress and depression among working and nonworking married women. Internet Journal of Medical Update2(1).
3. Azar IAS, Vasudeva P (2006) Self-efficacy and self-esteem: a comparative study of employed and unemployed married women in Iran. The German Journal of Psychiatry 9(3): 111-117.
4. Adhikari H (2012) Anxiety and Depression: comparative study between working and non-working mothers. Global Journal of Human-Social Science Research12(12-C).
5. Kandel DB, Davies M, Raveis VH (1985) The stressfulness of daily social roles for women: Marital, occupational and household roles. Journal of health and social behavior 64-78.
6. Beatty CA (1996) The stress of managerial and professional women: is the price too high? Journal of Organizational Behavior 17(3): 233-251.
7. Mostow E, Newberry P (1975) Work role and depression in women: A comparison of workers and housewives in treatment. Am J Orthopsychiatry 45(4): 538.
8. Carl DA, Siddique CM (1985) Marital status and psychological well-being: A cross-national comparative analysis. International Journal of Comparative Sociology26: 149.
9. Rosenfield S (1980) Sex differences in depression; do women always have higher rates? Journal of Health and Social Behavior 33-42.