When Husbands Stay Home: Does Persistence of Household Gender Inequality Remain? ()
1. Introduction
It is a natural and globally accepted societal norm that men and women live together in heterosexual families, and in this context, gender inequality in households has become a topic of significant discussion. The literature highlights the issues of gender-based disparity, diverse gender-based roles, and the imbalanced decision-making power between men and women in households. Traditionally, women were expected to engage primarily in household and caregiving roles, while men focused on the family’s financial support by working outside the home (McDaniel, 2008). However, over the past few decades, there has been a notable shift in gender roles and dynamics concerning work outside the home. The Industrial Revolution and two World Wars that women to work outside the home, thereby increasing household income profiles, but challenging traditional gender roles (Shah, 2015; Ramarajan, McGinn, & Kolb, 2012) increased absence from home has thus decreased the time they spend doing household chores. The literature that explores this dynamic reveals a mixed set of findings. Some studies suggest that a husband’s constant presence in the home leads to a more equitable division of household labor (Chesley, 2011; Mangino, 2022), while others argue that his constant presence has warped traditional gendered roles, societal expectations, and ingrained behavioral patterns (Collins et al., 2021; Giacomo, 2019). However, it is notable that previous studies in this field have failed to address the impact of the duration of a male spouse’s daily presence in the home on the dynamics of marital relationships. The degree of gender disparity interferes with the need to share activities and chores at home. Current literature does not provide sufficient understanding of the direct correlation between the duration of time men spend at home and gender in-house dynamics. However, scholars generally tend to agree that the male spouse’s constant presence in the home does impact the marital relationship, especially when conflict arises due to the persistent prevalence of gender inequality. For instance, Giacomo (2019) found clear disparities between couples spending extended time together in the home and those who do not. To understand this phenomenon in more depth, Power (2020) conducted a study to examine the impact of family togetherness during the COVID-19 lockdown period on the care burden of women and their response to their spouses’ constant presence in the home. The COVID-19 crisis highlighted gender disparities in caregiving responsibilities and discovered that the extended presence of both spouses in the home exacerbated these disparities and resulted in a significant impact on women’s well-being and economic prospects Power (2020). Conversely, other studies reported the enhancement of gender equality during this period. For example, Ledent & Salembier (2021) studied the potential of co-housing to free up time for various categories of people, including those facing gender inequality in individual households. The latter study was conducted in Brussels, Belgium, and used qualitative observations and interviews. The results suggest that extended daily cohabitation can limit gender inequality if an egalitarian sharing of household chores is promoted.
Researchers agree that the relationship between husbands’ constant presence in the home and gender equality is complex and multifaceted, and they argue that this situation is impacted by broad societal and cultural factors. For instance, Marcén & Morales (2022) argue that the cultural norms that immigrants bring from their countries of origin influence the division of household labor among such groups in the United States, and they suggest that the presence of a husband who adheres to gender-equal norms is associated with a more equitable division of household chores. However, even though husbands’ extended presence in the home and their participation in domestic tasks are important, these factors do not guarantee gender equality (Sun, 2008). Ngan & Chan (2023) and Sun (2008) agree that the persistence of traditional gender norms and the nature of the family structure and dynamics are critical in shaping the division of labor within households, which, by extension, also impact family relationships and individual members’ well-being.
The current study utilized data from the 2015 United Kingdom (UK) time use survey. It employed a quantitative approach by conducting statistical data analyses to identify patterns and expose gender disparities during extended times couples spent together at home. The study found that gender inequality persisted in such instances and that men’s constant presence in the home exacerbated gender disparity perceptions and practices. This research was conducted in Bukavu, city in the South-Kivu province in the eastern part of the Democratic Republic of Congo (DRC). The DRC has a rich cultural heritage and is characterized by diverse social structures. It is populated by people of diverse ethnicities and each group has its own set of traditions and norms. However, the literature on gender dynamics in the DRC reiterates the notion of problematic gender relations (Frerks & Ypeij, 2016) and presents these relations in an evolutive context in three phases: pre-colonial, colonial, and post-colonial. According to Gouzou et al. (2009), there was considerable diversity between male and female participation in decision-making processes during pre-colonial times across all ethnic groups, while Natou (2017) argues that Congolese society in the pre-colonial era was characterized by mutual harmony between man and wife in households. She asserts that it was a mutually acknowledged association that aimed to establish a sedentary society and that enabled each individual to realize their full potential by engaging in activities that were most compatible with their physiological disposition. The latter author compared traditional household relationships and internal and external affairs ministries at the country level. She said there is no conflict between the two ministries, but a cooperative effort towards a common objective. Hence, the relationship between a husband (as compared to the External Affairs Ministry) and a wife (as compared to the Internal Affairs Ministry) is a collaborative effort to ensure the well-being of the household.
However, according to Mechanic (2004), the colonial era destroyed that harmony and enforced, to a large extent, the marginalization of women. This era created three categories of women: (i) those exposed to polygamy where such women were considered the flock and men the shepherds; (ii) the “prostitution” of the white man’s housewife as she was nothing better than a sex slave; and (iii) the liberated Christian woman who was the successful product of Western civilization’s missionary quest (Natou, 2017).
In the post-colonial period, the new political regime in the DRC has perpetuated gender inequality that was created in the colonial area. In that era, women were solely acknowledged for their roles as wives and mothers and they were routinely excluded from decision-making processes at all levels (Mechanic, 2004, Gouzou et al., 2009). For decades, it was believed that women should stay at home and take care of the family while men were deemed the breadwinners who had to find employment away from the home environment. However, due to economic pressure and increasing opportunities for female employment, family roles evolved, leading to the emergence of working mothers and stay-at-home husbands in urban and even rural settings (Frerks & Ypeij, 2016). Today, as in most countries world-wide, it is expected that both male and female DRC citizens contribute to households’ income. Congolese men and women thus engage in a diverse range of formal and informal household tasks, and this has significantly impacted the amount of time they spend and share in the household.
Nonetheless, Bapolisi (2023) argues that gender disparity persists in households in the DRC despite efforts to address the matter. Various studies have highlighted diverse aspects of gender inequality in households, yet they have not directly addressed the variation in the duration of spouses’ daily presence in the home and the impact of this phenomenon on marital relationships and gender in/equality. According to Drobnič & Ruppanner (2015) and Shi et al. (2016), even partners who spend a similar period of time together at home, gender disparities, that are associated with certain demographic factors, persist. These factors include the education levels and ambitions of spouses, the activities they engage in, and the income each gender generates. The research gap in understanding the dynamics within households where the male spouse is constantly at home has thus become a new research field that necessitates a more nuanced examination of the impact of the duration of co-residence on marital relationships and gender inequality. It is acknowledged that various demographic factors may influence this correlation, yet a comprehensive understanding of this interaction and its impact on the family is important because, by examining the factors that perpetuate unequal power relations within Congolese households, it will be both feasible and possible to formulate targeted strategies to empower women and foster a more equitable relationship between spouses that will ultimately benefit all members of households. It was against this backdrop that the current study investigated gender inequality in the DRC, with specific emphasis on the COVID-19 period. Its key aim was to determine to what extent the long-term and constant presence of husbands in households affected gender dynamics between spouses. In essence, the study set out to determine if the abolishment of the traditional notion of the husband as the “absent member” of the household has brought a more balanced perspective to gendered household practices, or not.
2. Methodology
The study was conducted in Bukavu, a city in the eastern DRC. It is plagued by high rates of unemployment and poverty, especially among men. Bukavu, with an estimated population of 1,308,469, is experiencing rapid population growth (World Population Review, 2024). This growth is associated with the rural exodus caused by conflicts linked to sexual violence, the presence of armed groups, better job opportunities, and the urban population’s access to water and electricity (Bisoka, Mudinga, & Herdt, 2021).
The study examined the duration of men’s presence in households and the impact of their constant presence on gender dynamics and inequality. The study recruited 131 married men and 178 married women who responded to survey questions on gender dynamics and gender inequality in their households. The questions mainly focused on themes such as household interactions, psychological stress, marital conflict, and abusive behavior during intense and non-intense shared times when men stayed at home. Some demographic characteristics were also considered in the evaluation of the data, namely age, duration of time staying together in the same house, education levels, family composition, and employment (job) details. The respondents were asked in each instance to compare their experiences/perceptions of the non-intense times with those of intense times when men stayed at home. The investigation focused on the COVID-19 lockdown period as an “intense household shared time” when couples were compelled to spend an extended period of time in their homes.
This was a cross-sectional study that focused on heterosexual couples. The cross-sectional approach was adopted due to its adaptability and promptness in obtaining the necessary information regarding the topic under investigation (Connelly, 2016). The research utilized twelve trained interviewers who were dispatched to three geographic areas in the city to collect data. Data was collected by these field workers using KoBoCollect on their cellular phones, and the raw data was then collected and recorded under the guidance and supervision of the main researcher. The researcher received the submitted information daily on a computer server, which facilitated the data collection process. Lakshminarasimhappa (2022) and Nampa et al. (2020) affirm that KoBoCollect software is a trustworthy mobile data collection technique that can be used to collect both qualitative and quantitative information using devices like mobile phones and tablets, and this data collection method ensured that the data were collected in a short space of time. Adult men and women were randomly selected. The research excluded individuals who were single, widowed, and too young as such respondents would possess insufficient information regarding the subject matter.
Approval for the study protocol, reference number CIRE 008/DPSK/118PP/2022, was granted by the Interdisciplinary Center for Ethic Research (CIRE) at the Université Evangélique en Afrique (UEA). The study obtained the consent of all the respondents after assuring them of the confidential nature of their participation. In addition, the interviewers adhered to all ethical considerations when collecting the data as required by the Council for International Organizations of Medical Sciences (2016). They therefore obtained the consent of each respondent before administering the survey questionnaire. Data collection was conducted in a secure place to ensure the respondents’ confidentiality and to allow them to respond freely. To ensure anonymity, the interviewers devised an acronym followed by a number to identify each respondent.
The survey employed a semi-structured format and consisted of multiple-choice questions and spaces where respondents’ more in-depth oral explanations could be recorded. The respondents were notified in advance that additional details might be required, and these were securely retained for data analysis. The field workers collected data by going from door to door. The decision to administer 328 questionnaires was guided by the need to ensure that a robust sample could adequately represent the diverse households in Bukavu. A sample size of this magnitude allows for a more comprehensive understanding of gender dynamics and inequality within the population, as it provides a sufficient number of responses to analyze different demographic segments. The objective of achieving data saturation, wherein no new information or themes emerge from the data, further supports the chosen sample size, ensuring that the findings are representative of the community’s experiences and perspectives.
Ultimately, following the application of the inclusion criteria, a total of 309 completed questionnaires were deemed suitable for analysis. This number remains substantial enough to yield statistically significant outcomes and insights, while retaining a strong emphasis on high-quality data collection. The initial data analysis step involved the compilation of the survey data using KoBoCollect, and the recorded data were subsequently transferred to Excel for the purpose of cleaning and processing. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) which generated descriptive tables and figures. T-tests and chi-squared tests were used to show the associations between the variables of interest. Phi and Cramer’s V coefficients and exact significance measurements were determined to evaluate the strength and significance of the associations between the variables. Through content analysis, qualitative data were also analyzed to enhance understanding of the quantitative data. Phi and Cramer’s V coefficients are standard effect size measures in chi-square tests. Phi and Cramer’s V coefficients range from 0 (no association) to 1 (perfect association). Cramer’s V is suitable for tables larger than 2 × 2 and Phi is used for 2 × 2 tables. Effect size helps interpret results beyond just statistical significance. To determine if a correlation existed among couples between intra-household gender dynamics during periods of intense household shared time and periods of low household shared time, non-parametric correlation analyses were conducted.
The research used logistic regression to explore the factors leading to gender inequality in the studied region. The model included 22 independent variables, while gender served as the dependent variable (Table 1).
Table 1. Research variables.
Variable |
Modalities |
Gender |
Male and Female |
Age |
From 20 to 30, 31 to 40, 41 to 50 and 51 and plus |
Marital status |
Single, Married, Widowed, Divorced |
Family composition |
0 to 5 persons, 6 to 10 persons, 11 and above |
Professions |
8 hours paid job a day, Trader, personal job, Army, jobless, Teacher, and Church profession. |
Education level |
People with primary school, secondary school, and university qualifications as well those who were
illiterate |
Period living together |
From 20 to 30, 31 to 40, 41 to 50 and 51 and plus |
How would you describe your relationship with your spouse prior to February 2020 |
Poor, Somewhat, Excellent |
In general, how would you describe your relationship with your partner during the COVID-19 period? |
Poor, Somewhat, Excellent |
Before February 2020, did
arguments with your partner evoke feelings of resentment? |
Often, Sometimes, Never |
During COVID-19 era, did
arguments with your partner evoke feelings of resentment? |
Often, Sometimes, Never |
Before February 2020, were there any internal conflicts that needed to be addressed in your house? |
Often, Sometimes, Never |
During COVID-19 era, were there any internal conflicts that needed to be addressed in your house? |
Often, Sometimes, Never |
Before February 2020, was there any conflict that needed your opinion in order to be resolved? |
Often, Sometimes, Never |
During COVID-19, was there any conflict that needed your opinion in order to be
resolved? |
Often, Sometimes, Never |
Before February 2020, have you ever been scared by something your spouse said or did to you? |
Often, Sometimes, Never |
During COVID-19, have you ever been scared by
something your spouse said or did to you? |
Often, Sometimes, Never |
Before February 2020, has your spouse ever physically harmed you? |
Often, Sometimes, Never |
During COVID-19, has your spouse ever physically harmed you? |
Often, Sometimes, Never |
Before February 2020, has your spouse ever hurt you emotionally? |
Often, Sometimes, Never |
During COVID-19 era, has your spouse ever hurt you
emotionally? |
Often, Sometimes, Never |
Have you ever experienced sexual abuse from your spouse prior to February 2020? |
Often, Sometimes, Never |
Have you ever experienced sexual abuse from your spouse during COVID-19 era? |
Often, Sometimes, Never |
A summary was generated from model testing, revealing values of 421.188 for -2log likelihood, 0.107 for Cox and Snell R Square, and 0.144 for Nagelkerke R square. Based on this summary and the Chi-square test by Hosmer and Lemeshow that was estimated at 1.284 with 8 degrees of freedom (df) and a P value of 0.99, the model was considered viable. All these tests were conducted with a significance level of 5%. To mitigate bias, variables with frequency modalities below 10% were consolidated.
3. Results
3.1. Demographic Attributes of the Respondents
Correlation coefficients using Spearman’s rank correlation, or “rho” method, as well as the significance levels were computed using a two-tailed test. Participants’ characteristics based on their gender distinguish the data between the two genders. It also presents the ages of the respondents in categories from the youngest to the oldest. Of a sample of 309 participants, 178 (57.6%) were female and 131 (42.4%) were male. In terms of employment status, of a total of 108 participants who held a paid job of 8 hours a day, 55 (50.9%) were women and 53 (49.1%) were men. Of a total of 120 participants engaged in trade, 72 (60%) were women and 48 (40%) were men. Of the 7 respondents who were self-employed, 2 (28%) were women and 5 (72%) were men. Of the 9 respondents who were employed in the armed forces (the military or police), 3 (33.3%) were women and 66.7% were men. Of the 4 participants working in the education field, 2 (50%) were women and 2 (50%) were men. Of a total of 61 unemployed respondents, 44 (72.1%) were women and 17 (27.9%) were men.
The data reveal a significant correlation between gender and age group (P value 0.985, Phi exact significance 0.519) duration of stay (P value 0.628, Phi exact significance 0.641), and family composition (P value 0.413, Phi exact significance 0.413). Moreover, based on the Phi exact significance, data indicate a strong and statistically significant association between gender and age groups and duration of stay. This indicates that these variables are likely to be different based on the gender of the participant. However, there is no significant association between gender and education level (P value 0.019, Phi exact significance 0.019), job of respondent (P value 0.026, Phi exact significance 0.026), and spouse’s job (P value < 0.001, Phi exact significance < 0.001). Which means that these variables are not likely to differ based on the gender of the participant.
The findings are presented in tables and show relationships between people in various living situations, particularly in periods when the husbands’ presence was not intense and intense (indicated as intense and non-intense). The study explored situations such as how families interacted, how stressed people felt, how stressed they were physically, and how prevalent abuse was within households. The data are presented as counts and percentages and indicate exact significance. The variables are segmented by age group, duration of time spent as a couple, family composition during data collection, education level of the respondents, and the occupations (referred to as jobs) of both the respondents and their spouses.
3.2. Household Relationship Dynamics
3.2.1. Gender Relationships in Households
Interrelations among married couples include the manner of their marital relationship and their communication habits during day-to-day activities within their households, and these dynamics may affect the gendered relationships in the home (Hossain, Haque, & Fatmi, 2023). For this reason, the study explored issues in marital interrelations and communication, and it considered certain variables associated with these interactions, including age, time spent together as a couple, family composition (number of individuals living in-house), and the nature of the employment of the respondents and their spouses.
Analyses of how often the genders interacted in their respective households. For example, as the duration of the marriage of the spouses increased (9.8% after 41 years). The data revealed that 2.2% of the respondents’ spouses were self-employed, while 0.5% worked in education and in the military. It is important to note that there were fewer gender interrelationship issues in illiterate households (2.3%) than in literate households (33.3%). Additional information is presented in Table 2 below.
Table 2. Marital interrelation dynamics.
|
|
|
Marital Interrelations |
|
|
communication and discussion |
|
|
|
No-intense shared time |
|
Intense shared time |
|
No-intense shared time |
|
Intense shared time |
|
|
|
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Age rank |
Count |
33 |
57 |
90 |
38 |
61 |
99 |
64 |
83 |
147 |
60 |
81 |
141 |
|
Percentage |
25.2% |
32.0% |
29.1 |
29% |
34.3% |
32.0% |
48.9% |
46.6% |
47.6 |
45.8% |
45.5% |
45.6% |
|
Exact
Significance (Phi) |
0.280 |
0.409 |
0.181 |
0.004 |
0.272 |
0.024 |
0.001 |
0.309 |
0.093 |
0.012 |
0.807 |
0.218 |
Years
staying
together |
Count |
33 |
53 |
86 |
37 |
58 |
95 |
62 |
77 |
139 |
58 |
75 |
133 |
|
Percentage |
26.6% |
32.5% |
30.0% |
29.8% |
35.6% |
33.1% |
50.0% |
47.2% |
48.4 |
46.8% |
46.0% |
46.3% |
|
Exact
Significance (Phi) |
0.241 |
0.633 |
0.505 |
0.591 |
0.509 |
0.238 |
0.081 |
0.252 |
0.017 |
0.088 |
0.640 |
0.074 |
Education |
Count |
33 |
57 |
90 |
38 |
61 |
99 |
64 |
83 |
147 |
60 |
81 |
141 |
|
Percentage |
25.2% |
32.0% |
29.1 |
29% |
34.3% |
32% |
48.9% |
46.6% |
47.6 |
45.8% |
45.5% |
45.6% |
|
Exact
Significance (Phi) |
1.000 |
0.384 |
0.381 |
1.000 |
0.665 |
0.732 |
0.616 |
0.302 |
0.203 |
0.448 |
0.681 |
0.341 |
Family
composition |
Count |
31 |
56 |
87 |
36 |
60 |
96 |
62 |
81 |
143 |
58 |
79 |
137 |
|
Percentage |
24.2% |
31.8% |
28.6% |
28.1% |
34.1% |
31.6% |
48.4% |
46.0% |
47.0% |
45.3% |
44.9% |
45.1% |
|
Exact
Significance (Phi) |
0.387 |
0.254 |
0.095 |
0.768 |
0.158 |
0.206 |
0.626 |
0.108 |
0.212 |
0.478 |
0.253 |
0.729 |
Job of the respondent |
Count |
33 |
57 |
90 |
38 |
61 |
99 |
64 |
83 |
147 |
60 |
81 |
141 |
|
Percentage |
25.2% |
32% |
29.1 |
29% |
34.3% |
32% |
48.9% |
46.6% |
47.6 |
45.8% |
45.5% |
45.6% |
|
Exact
Significance (Phi) |
0.011 |
0.044 |
<.001 |
0.027 |
0.167 |
0.006 |
0.483 |
0.148 |
0.126 |
0.644 |
0.206 |
0.166 |
Job of the spouse |
Count |
33 |
57 |
90 |
38 |
61 |
99 |
64 |
83 |
147 |
60 |
81 |
141 |
|
Percentage |
25.2% |
32% |
29.1 |
29% |
34.3% |
32% |
48.9% |
46.6% |
47.6 |
45.8% |
45.5% |
45.6% |
|
Exact
Significance (Phi) |
0.442 |
0.130 |
0.096 |
0.122 |
0.552 |
0.166 |
0.244 |
0.432 |
0.055 |
0.195 |
0.811 |
0.231 |
Total (n) |
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
In terms of household shared time status, Table 4 suggests that there were statistically significant interrelations between individuals’ non-intense household shared time and age (P value 0.181), years staying together (co-habitation) (P value 0.505), education (P value 0.381), family composition (P value 0.095), and job of the spouse (P value 0.096). There were also significant interrelations between intense household shared time and years staying together (co-habitation) (P value 0.238), education (P value 0.732), family composition (P value 0.206), and job of the spouse (P value 0.166). It is noteworthy that there were more individual problems during intense household shared time compared to non-intense household shared time.
However, individuals’ interrelations in categories such as job of the respondent in non-intense household shared time (P value inferior to 001), age category in intense household shared time (P value 0.024), and job of the respondent in intense household shared time (P Value 0.006) were not statistically significant. It is important to note that the exact significance levels (based on Phi) varied depending on the age category under analysis.
In terms of marital communication and discussion, Table 2 indicates that there were also statistically significant relations between individuals during intense household shared time and non-intense household shared time and age category (P value 0.093), years staying together during intense household shared time (P value 0.074), education during both non-intense (P value 0.203) and intense household shared time (P value 0.341), family composition during both non-intense (P value 0.212) and intense household shared time (P value 0.729), job of the respondent during both non-intense (P value 0.126) and intense household shared time (P value 0.166), and job of the spouse during both non-intense (P value 0.055) and intense household shared time (P value 0.231). There was a decreased rate of spousal conflict in terms of communication and discussion during intense household shared time.
There was also a statistically significant relation between gender and years staying together and marital communication and discussion during non-intense household shared time (P value 0.017). According to Hossain, Haque and Fatmi (2023), married individuals are characterized by marital interrelations and the way they communicate about daily activities within their households, and this may affect their gender relationship. This notion underscored the issues in marital interrelations and communication that this study examined. The researcher considered certain variables associated with these interactions. These variables included the age of the spouses, the time they had spent together as a couple, family composition or number of persons living in-house, the job of the respondent, and the job of the respondent’s spouse. Certain variables associated with these interactions, namely the age of the spouses, the time they had spent together as a couple, family composition or number of persons living in-house, the job of the respondent. Furthermore, the job of the respondent’s spouse.
3.2.2. Gendered Conflict in Households
Marital conflict occurs when partners become annoyed with one another (Pathan, 2015). Among the indicators of marital conflict, the study considered two major factors, namely household disputes and not considering the partner’s argument in day-to-day communication situations. This exploration of gender conflict in households revealed a few issues across various categories. For example, conflict decreased with partners’ age, more persons in the house and the duration of their marriage (5% and 0% after 41 years of marriage respectively). It is notable that illiterate households (12.7%) experienced fewer gender interrelationship issues compared to literate households. A comprehensive analysis of conflict between spouses revealed additional information.
Table 3. Gendered conflict in households.
|
|
|
Exposure to psychological stress |
|
|
Being hurt emotionally |
|
|
|
No-intense shared time |
|
Intense shared time |
|
No-intense shared time |
|
Intense shared time |
|
|
|
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Age rank |
Count |
67 |
82 |
149 |
67 |
81 |
148 |
51 |
58 |
109 |
46 |
55 |
101 |
|
Percentage |
51.1% |
46.1% |
48.2% |
51.1% |
45.5% |
47.9% |
38.9% |
32.6% |
35.3% |
35.1% |
30.9% |
32.7% |
|
Exact
Significance (Phi) |
0.475 |
0.008 |
0.008 |
0.598 |
0.007 |
0.014 |
0.091 |
0.008 |
0.002 |
0.160 |
0.008 |
0.004 |
Years
staying
together |
Count |
67 |
82 |
149 |
67 |
81 |
148 |
51 |
58 |
109 |
46 |
55 |
101 |
|
Percentage |
51.1% |
46.1% |
48.2% |
51.1% |
45.5% |
47.9% |
38.9% |
32.6% |
35.3% |
35.1% |
30.9% |
32.7% |
|
Exact
Significance (Phi) |
0.001 |
0.792 |
0.030 |
0.031 |
0.890 |
0.182 |
0.796 |
0.280 |
0.432 |
0.930 |
0.153 |
0.412 |
Education |
Count |
67 |
82 |
149 |
67 |
81 |
148 |
51 |
58 |
109 |
46 |
55 |
101 |
|
Percentage |
51.1% |
46.1% |
48.2% |
51.1% |
45.5% |
47.9% |
38.9% |
32.6% |
35.3% |
35.1% |
30.9% |
32.7% |
|
Exact
Significance (Phi) |
0.450 |
0.040 |
0.037 |
0.801 |
0.411 |
0.424 |
0.436 |
0.826 |
0.404 |
0.187 |
1.000. |
0.394 |
Family
composition |
Count |
65 |
81 |
146 |
65 |
80 |
145 |
49 |
57 |
106 |
44 |
54 |
98 |
|
Percentage |
50.0% |
46.0% |
48.0% |
50.0% |
45.5% |
47.7% |
38.3% |
32.4% |
34.9% |
34.4% |
30.7% |
32.2% |
|
Exact
Significance (Phi) |
0.203 |
0.054 |
0.016 |
0.891 |
0.282 |
0.264 |
0.345 |
0.952 |
0.643 |
0.237 |
0.759 |
0.598 |
Job of the
respondent |
Count |
67 |
82 |
149 |
67 |
81 |
148 |
51 |
58 |
109 |
46 |
55 |
101 |
|
Percentage |
51.1% |
46.1% |
48.2% |
51.1% |
45.5% |
47.9% |
38.9% |
32.6% |
35.3% |
35.1% |
30.9% |
32.7% |
|
Exact
Significance (Phi) |
0.475 |
0.008 |
0.008 |
0.598 |
0.007 |
0.014 |
0.091 |
0.008 |
0.002 |
0.160 |
0.008 |
0.004 |
Job of the spouse |
Count |
67 |
82 |
149 |
67 |
81 |
148 |
51 |
58 |
109 |
46 |
55 |
101 |
|
Percentage |
51.1% |
46.1% |
48.2% |
51.1% |
45.5% |
47.9% |
38.9% |
32.6% |
35.3% |
35.1% |
30.9% |
32.7% |
|
Exact
Significance (Phi) |
0.039 |
0.087 |
0.008 |
0.148 |
0.340 |
0.128 |
0.195 |
0.107 |
0.007 |
0.152 |
0.029 |
0.010 |
Total (n) |
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
The findings in Table 3 highlight the statistically significant connections between the presence of marital dispute in households both in non-intense and intense shared times for some categories. These variables were age (P value 0.180 in non-intense and P value 0.182 in intense household shared time), years of staying together (P value 0.169 in non-intense and 0.274 in intense household shared time), education (P value 0.127 in non-intense and 0.453 in intense household shared time), and family composition (P value 0.366 in non-intense and 0.397 in intense household shared time). In contrast, there was no statistical significance in both non-intense and intense Household shared time based on gender between the presence of marital disputes and categories such as job of the respondent (P value 0.001 in non-intense and 0.017 in intense household shared time) and job of the spouse (P value 0.004 in non-intense and 0.011 in intense household shared time).
However, based on gender, during intense household shared time, there was a statistically significant association between not considering the partner’s arguments in times of conflict and categories such as age (P value 0.071 in non-intense shared time), years staying together (P value 0.343 in non-intense and P value 0.421 in intense household shared time), education (P value 0.449 in non-intense and P value 0.432 in intense household shared time), family composition (P value 0.440 in non-intense and P value 0.627 in intense household shared time), job of the respondent (P value 0.157 in intense household shared time), and the job of the spouse (P value 0.204 in non-intense and 0.804 in intense household shared time). There was no statistically significant difference based on gender between not taking a partner’s argument into consideration and some categories such as age (P value 0.013 in intense household shared time) and job of the respondent (P value 0.014 in non-intense shared time). It should be noted that there was a slight variation in the degree of considering a partner’s argument during both intense and non-intense household shared times. This variation depended on the categories being analyzed. Also, a certain variation within categories was noted.
3.2.3. Psychologic Stress
In the absence of consensus on differentiating psychological abuse from other forms of intimate violence, this study explored only two indicators among many that may prompt psychological abuse, namely “exposure” and “emotional stress” (Heise et al., 2019). The findings regarding psychological stress between/within spouses revealed only a few issues in the various categories. For example, an increase in partners’ age and the duration of the marriage were 5% and 0.1% after 41 years respectively.
Table 4. Marital psychological stress in the intense and non-intense presence of the male partner.
|
|
Presence of marital dispute |
Argument was not taken into consideration |
|
|
No-intense shared time |
|
Intense shared time |
|
No-intense shared time |
|
Intense shared time |
|
|
|
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Age rank |
Count |
28 |
43 |
71 |
27 |
46 |
73 |
32 |
40 |
72 |
27 |
38 |
65 |
|
Percentage |
21.4% |
24.2% |
23.0% |
20.6% |
25.8% |
23.6% |
24.4% |
22.5% |
23.3% |
39.5% |
21.3% |
21.0% |
|
Exact
Significance (Phi) |
0.160 |
0.714 |
0.180 |
0.062 |
0.643 |
0.182 |
0.137 |
0.232 |
0.071 |
0.011 |
0467 |
0.013 |
Years
staying
together |
Count |
28 |
43 |
71 |
27 |
46 |
73 |
32 |
40 |
72 |
27 |
38 |
65 |
|
Percentage |
21.4% |
24.2% |
23.0% |
20.6% |
25.8% |
23.6% |
24.4% |
22.5% |
23.3% |
20.6% |
21.3% |
21.0% |
|
Exact
Significance (Phi) |
0.253 |
0.577 |
0.169 |
0.619 |
0.492 |
0.274 |
0.237 |
0.567 |
0.343 |
0.698 |
0.491 |
0.421 |
Education |
Count |
28 |
43 |
71 |
27 |
46 |
73 |
32 |
40 |
72 |
27 |
38 |
65 |
|
Percentage |
21.4% |
24.2% |
23.0% |
20.6% |
25.8% |
23.6% |
24.4% |
22.5% |
23.3% |
20.6% |
21.3% |
21.0% |
|
Exact
Significance (Phi) |
1.000 |
0.054 |
0.127 |
1.000 |
0.481 |
0.453 |
0.770 |
0.460 |
0.449 |
1.000 |
0.320 |
0.432 |
Family
composition |
Count |
26 |
42 |
68 |
25 |
45 |
70 |
30 |
40 |
70 |
25 |
38 |
63 |
|
Percentage |
20.3% |
23.9% |
22.4% |
19.5% |
25.6% |
23.0% |
23.4% |
22.7% |
23.0% |
19.5% |
21.6% |
20.7% |
|
Exact
Significance (Phi) |
0.759 |
0.230 |
0.366 |
0.723 |
0.060 |
0.397 |
0.190 |
0.305 |
0.440 |
0.434 |
0.656 |
0.627 |
Job of the
respondent |
Count |
28 |
43 |
71 |
27 |
46 |
73 |
32 |
40 |
72 |
27 |
38 |
65 |
|
Percentage |
21.4% |
24.2% |
23.0% |
20.6% |
25.8% |
23.6% |
24.4% |
22.5% |
23.3% |
20.6% |
21.3% |
21.0% |
|
Exact
Significance (Phi) |
0.001 |
0.021 |
<0.001 |
0.044 |
0.202 |
0.017 |
0.165 |
0.074 |
0.014 |
0.684 |
0.139 |
0.157 |
Job of the spouse |
Count |
28 |
43 |
71 |
27 |
46 |
73 |
32 |
40 |
72 |
27 |
38 |
65 |
|
Percentage |
21.4% |
24.2% |
23.0% |
20.6% |
25.8% |
23.6% |
24.4% |
22.5% |
23.3% |
20.6% |
21.3% |
21.0% |
|
Exact
Significance (Phi) |
0.060 |
0.078 |
0.004 |
0.249 |
0.034 |
0.011 |
0.338 |
0.682 |
0.204 |
0.714 |
0.931 |
0.804 |
Total (n) |
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
Based on gender, the statistical analyses pertaining to non-intense shared time indicated that exposure to psychological stress was not related to age (P value 0.008), years staying together (P value 0.03), education (P value 0.037), family composition (0.016), job of the respondent (P value 0.008), and job of the spouse (P value 0.008). However, during intense household shared time, exposure to psychological stress was associated with years staying together (P value 0.182), education (0.424), family composition (P value 0.264), and job of the spouse (P value 0.128). Only age (P value 0.014) and job of the respondent (P value 0.014) were not statistically significant to exposure to psychological stress based on gender. It was noted that there was a slight decrease in terms of exposure to psychological stress during intense household shared time compared to non-intense household shared time.
Additionally, there was a statistically significant relation between being hurt emotionally and variables such as years staying together (P value 0.432), education (0.404), and family composition (P value 0.643) in non-intense household shared time. However, there was no statistically significant relationship between being hurt emotionally and age (P value 0.002), job of the respondent (P value 0.002), and job of the spouse (P value 0.007) based on gender. It is also noteworthy that the exact significance levels (based on Phi) varied depending on the categories being analyzed.
The above table also indicates that, based on gender, during intense household shared time there were some statistically significant relations between individuals who had been hurt emotionally and some variables such as years staying together (P value 0.412), education (P value 0.394), and family composition (P value 0.598). However, there were no statistically significant differences between being hurt emotionally and age (P value 0.004), job of the respondent (P value 0.004), and job of the spouse (P value 0.10). It needs to be pointed out that there was a larger decreasing rate in terms of conflict associated with being hurt during intense household shared time than during non-intense household shared time. It was also noted that the exact significance levels (based on Phi) varied depending on the category being analyzed.
3.2.4. Physical Stress and Sexual Satisfaction
Physical violence refers to one or more person’s inflicting harm to the body of another, such as acts of pushing, slapping, biting, kicking, and punching. Sexual abuse, on the other hand, refers to various forms of aggressive and hurtful sexual activity (Haack et al., 2018). This study’s examination of intimate violence revealed a few harmful issues across various variables. For instance, as spouses got older, fewer physically hurtful issues occurred after the age of 41 years (5.2% and 0.1% respectively). Regarding education, there were only a few illiterate people at a rate of 22%. According to the nature of the respondents’ and their spouses’ employment, 2% and 3.1% were teachers and military/law enforcement personnel respectively. The following analyses provide us with further information.
Table 5. Abusive behavior in non-intense and intense shared time.
|
|
Physical abuse |
Sexual abuse |
|
|
No-intense shared time |
|
Intense shared time |
|
No-intense shared time |
|
Intense shared time |
|
|
|
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Male |
Female |
Total |
Age rank |
Count |
30 |
45 |
75 |
28 |
39 |
67 |
19 |
21 |
40 |
17 |
19 |
36 |
|
Percentage |
22.9% |
25.3% |
24.3% |
21.4% |
21.9% |
21.7% |
14.5% |
12.9% |
38.9% |
13.0% |
10.7% |
11.7% |
|
Exact
Significance (Phi) |
0.117 |
0.104 |
0.007 |
0.389 |
0.173 |
0.074 |
0.567 |
0.484 |
0.432 |
0.195 |
0.409 |
0.085 |
Years staying
together |
Count |
30 |
45 |
75 |
28 |
39 |
67 |
19 |
21 |
40 |
17 |
19 |
36 |
|
Percentage |
22.9% |
25.3% |
24.3% |
21.4% |
21.9% |
21.7% |
14.5% |
12.9% |
38.9% |
13.0% |
10.7% |
11.7% |
|
Exact
Significance (Phi) |
0.520 |
0.262 |
0.121 |
0.253 |
0.457 |
0.440 |
0.699 |
0.726 |
0.365 |
0.489 |
0.847 |
0.411 |
Education |
Count |
30 |
45 |
75 |
28 |
39 |
67 |
19 |
21 |
40 |
17 |
19 |
36 |
|
Percentage |
22.9% |
25.3% |
24.3% |
21.4% |
21.9% |
21.7% |
14.5% |
12.9% |
38.9% |
13.0% |
10.7% |
11.7% |
|
Exact
Significance (Phi) |
0.763 |
0.813 |
0.576 |
1.000 |
0.804 |
0.700 |
0.073 |
1.000 |
0.232 |
0.127 |
0.742 |
0.133 |
Family
composition |
Count |
28 |
44 |
72 |
26 |
38 |
64 |
18 |
21 |
39 |
16 |
19 |
35 |
|
Percentage |
21.9% |
25.0% |
23.7% |
20.3% |
21.6% |
21.1% |
14.1% |
11.9% |
12.8% |
12.5% |
10.8% |
11.5% |
|
Exact
Significance (Phi) |
0.110 |
0.659 |
0.548 |
0.327 |
0.665 |
0.826 |
0.621 |
0.313 |
0.209 |
0.915 |
0.545 |
0.545 |
Job of the
respondent |
Count |
30 |
45 |
75 |
28 |
39 |
67 |
19 |
21 |
40 |
17 |
19 |
36 |
|
Percentage |
22.9% |
25.3% |
24.3% |
21.4% |
21.9% |
21.7% |
14.5% |
12.9% |
38.9% |
13.0% |
10.7% |
11.7% |
|
Exact
Significance (Phi) |
0.202 |
0.075 |
0.009 |
0.275 |
0.275 |
0.092 |
0.891 |
0.031 |
0.168 |
0.828 |
0.058 |
0.298 |
Job of the spouse |
Count |
30 |
45 |
75 |
28 |
39 |
67 |
19 |
21 |
40 |
17 |
19 |
36 |
|
Percentage |
22.9% |
25.3% |
24.3% |
21.4% |
21.9% |
21.7% |
14.5% |
12.9% |
38.9% |
13.0% |
10.7% |
11.7% |
|
Exact
Significance (Phi) |
0.209 |
0.421 |
0.055 |
0.388 |
0.716 |
0.440 |
0.891 |
0.768 |
0.939 |
0.807 |
0.719 |
0.949 |
Total (n) |
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
131 |
178 |
|
Table 5 presents data related to intimate partner violence (IPV) and identifies different types of IPV experienced by women. Based on gender, the data highlight the statistically significant connections between physical abuse for some categories namely age (P value 0.07 in intense household shared time), years staying together (P value 0.121 in non-intense and 0.457 in intense household shared time), education (P value 0.576 in non-intense and 0.804 in intense household shared time), family composition (P value 0.548 in non-intense and 0.665 in intense household shared time), job of the respondent (P value 0.275 in intense household shared time), and job of the spouse (P value 0.055 in non-intense and P value 0.716 in intense household shared time). In contrast, there was no statistical significance between non-intense household shared time and physical abuse and categories such as job of the respondent (P value 0.009) and age (P value 0.007).
Additionally, based on gender, there were statistically significant associations between sexual abuse and the following variables: age (P value 0.432 in non-intense and 0.085 in intense household shared time), years staying together (P value 0.365 in non-intense and 0.411 in intense household shared time), education (P value 0.232 in non-intense and 0.133 in intense household shared time), family composition (P value 0.209 in non-intense and 0.545 in intense household shared time), job of the respondent (P value 0.168 in non-intense and 0.298 in intense household shared time), and job of the spouse (P value 0.939 in non-intense and 0.949 in intense household shared time).
To examine potential causal relationship among variables, logistic regression was performed in the study utilizing 21 independent variables. The dependent variable was gender and the results are presented in Table 6 below.
Table 6. Relationships among variables under study.
|
|
|
|
|
|
95% C.I.for EXP(B) |
|
B |
S.E. |
Wald |
df |
Sig. |
Lower |
Upper |
Job of the respondent |
0.250 |
0.107 |
5.454 |
1 |
0.020 |
1.284 |
1.041 |
Spouse’s job |
−0.356 |
0.101 |
12.367 |
1 |
<0.001 |
0.701 |
0.575 |
How would you describe your
relationship with your spouse prior to February 2020? |
1.887 |
1.138 |
2.748 |
1 |
0.097 |
6.597 |
0.709 |
In general, how would you describe your relationship with your partner during the COVID-19 period. |
−0.368 |
0.855 |
0.185 |
1 |
0.667 |
0.692 |
.0130 |
Before February 2020, did
arguments with your partner evoke feelings of resentment? |
0.330 |
0.998 |
0.110 |
1 |
0.741 |
1.391 |
0.197 |
During the COVID period, did
arguments with your partner evoke feelings of resentment? |
−0.081 |
0.966 |
0.007 |
1 |
0.933 |
0.923 |
0.139 |
Before February 2020, were there any internal conflicts that needed to be addressed? |
0.730 |
1.116 |
0.428 |
1 |
0.513 |
2.076 |
0.233 |
During the COVID-19 period, were there any internal conflicts that needed to be addressed? |
−0.596 |
1.059 |
0.317 |
1 |
0.573 |
0.551 |
0.069 |
Before February 2020, was there any conflict that needed your
opinion in order to be resolved? |
−1.073 |
1.711 |
0.393 |
1 |
0.531 |
0.342 |
0.012 |
During the COVID-19 period, was there any conflict that needed your opinion in order to be resolved? |
0.843 |
1.795 |
0.220 |
1 |
0.639 |
2.323 |
0.069 |
Before February 2020, have you ever been scared by something your spouse said or did? |
−0.877 |
1.032 |
0.722 |
1 |
0.395 |
0.416 |
0.055 |
During COVID-19 period, have you ever been scared by something your spouse said or did? |
−0.388 |
1.099 |
0.125 |
1 |
0.724 |
0.678 |
0.079 |
Before February 2020, has your spouse ever physically harmed you? |
−20.112 |
15180.890 |
0.000 |
1 |
0.999 |
0.000 |
0.000 |
During COVID period has your spouse ever physically harmed you? |
18.71 |
15180 |
0.000 |
1 |
0.999 |
134146609 |
0.000 |
Has your spouse ever hurt you emotionally before February 2020? |
−4.575 |
2.145 |
4.550 |
1 |
0.033 |
0.010 |
0.000 |
Has your spouse ever hurt you emotionally During the COVID
period? |
4.324 |
2.227 |
3.769 |
1 |
0.052 |
75.489 |
0.960 |
Have you ever experienced sexual abuse from your spouse prior to February 2020? |
0.456 |
1.872 |
0.059 |
1 |
0.808 |
1.578 |
0.040 |
Have you ever experienced sexual abuse from your spouse during COVID-19 period? |
1.424 |
2.799 |
0.259 |
1 |
0.611 |
4.156 |
0.017 |
Ages groups |
−0.193 |
0.269 |
0.511 |
1 |
0.475 |
0.825 |
0.486 |
Period staying together |
−0.187 |
0.316 |
0.352 |
1 |
0.553 |
0.829 |
0.447 |
Family composition |
0.558 |
0.411 |
1.841 |
1 |
0.175 |
1.746 |
0.780 |
Predicted Response Category |
0.077 |
0.746 |
0.011 |
1 |
0.918 |
1.080 |
0.250 |
The logistic regression model shown in Table 6 explores the factors associated with selected relationship dynamics and experiences, particularly the changes that may have occurred prior to and during the period of expanded presence of the husband. Individual characteristics, such as job status and relationship factors, such as emotional or physical abuse, that assess the likelihood of specific outcomes include job status and relationship factors. According to Table 6, the positive coefficient for the respondent’s job indicates a significant for the respondent’s job. B = 0.250, P = 0.020, with an odds ratio of 1.284. This infers that a respondent’s job slightly raises the odds of the modeled outcome by about 28%. This could mean that there is a correlation between job status and relationship dynamics or stability. In this respect, the spouse’s job has a negative coefficient: −0.356 with a P value of less than 0.001 and an odds ratio of 0.701, showing it is significantly related to lowering the odds of the outcome by roughly 30%. This may imply that the spouse’s job reduces the stress of or in the relationship, possibly due to stability or external support factors.
The relationship experiences, especially about emotional and physical abuses-have shown a mixed effect on the modeled outcome. For instance, the past emotional abuse during the time when the husband was not around (before COVID-19) is linked to a significant decrease in the chances of the result; this could be a protective factor that might have preserved the relationship dynamic in some contexts (B = −4.575, P = 0.033, Exp (B) = 0.010). Furthermore, emotional hurt during expanded presence of the husband (B = 4.324, P = 0.052, Exp (B) = 75.489) strongly showed a borderline significant increase in odds, indicating how period of expanded presence of the husband may have exacerbated stress and conflict. Nonetheless, emotional pain during the husband’s longer presence is highly negative (−5.059, P = 0.048), demonstrated that this is associated with a much lower likelihood of reporting certain relationship stressors, perhaps due to greater support or resilience built during close interaction. In addition, the number of years spent together is slightly negatively associated with the outcome at B = −0.301, P = 0.049, Exp(B) = 0.740. It would thus appear that longer relationships may provide some resilience to relationship stresses; this may be because coping mechanisms are more developed or stability is achieved over time.
The overall significance of the logistic model indicates that Chi-square = 35.004, df = 18, P = 0.009, suggesting that the model is statistically significant. This significance level would suggest that the predictors are relevant and the model has improved in its predictive capacity over an intercept-only model. Therefore, the model fits well and is significant, but the overall relatively low pseudo-R-squared values indicate that while there were meaningful contributions by the predictors included to explain the outcome, there may be additional factors affecting the dynamics of the relationships under study.
4. Discussion
This paper aims to understand the impact of the duration of male spouses’ stay at the same residence as their female partners and the effect this may have on the prevalence of gender inequality. The study assumed that the duration of a male spouse’s presence in the marital home may be long (intense) or brief (non-intense). The study hypothesized that this impact could vary according to some demographic characteristics such as age, time spent together as a couple, education, the job of the respondent, or the job of the spouse. The impact measurement units explored were household interrelationships, marital conflict, psychological stress, and physical and sexual abuse.
The results on household interrelation dynamics were statistically significant (Pearson’s significance) at the 0.01 level (two-tailed). The null hypothesis was rejected, and it was concluded that there was a relation between household interrelations during both non-intense shared time and intense shared time (i.e., staying together) (P < 0.01). With reference to household interrelationships, the study found that communication and decision-making in non-intense and intense household shared times were both positively correlated with marital interrelations in non-intense household shared time (rho = 0.431 and 0.385 respectively). Additionally, there was a significant positive correlation (rho = 0.819, P < 0.01) between communication and decision-making in both non-intense and intense household shared times based on gender. This implies that intense and non-intense household shared times were closely connected and tended to increase or decrease together. It may this be argued that both the prolonged and less intense presence of the man in the household predispose husbands to adopt egalitarian perspectives on their wives’ decision-making and this is in line with previous study (Prakriti, 2012). When the husband is consistently present, household decision-making dynamics are influenced by multiple factors, but effective communication between spouses leads to more equal views on decision-making roles. This underscores the importance of understanding household communication quality and its impact on decision-making dynamics (Prakriti, 2012). This occurs when spouses collaborate to share household duties and simplify gender roles and power structures (Carrero & Torgeir, 2017; Mirza, 2016). The results of the current study suggest that employment in the public sector, such as in the military, law enforcement, education, and as church leaders, may be associated with limited gender inequality in households. Moreover, household gender inequality seems to decrease as the age of both males and females increase. More particularly, a very sensible decrease in gender inequality was noted in the age category 41 years older. Also, household gender inequality seems to decrease as the years a couple spends together in a household increase. Again, it was notable that couples who had been together for longer tended to shed the burden of gender inequality more readily than their younger counterparts. Further research and research-based interventions could encourage married and other co-habiting couples to adopt gender equality practices and attitudes in their households.
The result regarding gender-based conflict in households showed statistical significance (Pearson significance = 0.781) at the 0.01 level (two-tailed). The null hypothesis was rejected, and it was concluded that there was a relation between household conflict during non-intense shared time and during intense shared time (P < 0.01) based on gender. The study considered the dynamics of marital disputes and arguments leading to spousal conflict in both intense and non-intense shared times. The findings revealed that a correlation existed between marital discord during non-intense and intense household shared time; hence, it was concluded that marital discord could be robust (r = 0692) and could contribute to persistent gender inequality. The correlation was also significant for arguments during which the spouse’s view was not considered during both non-intense and intense shared times (r = 0.767). Furthermore, the correlation between marital disputes during non-intense household shared time and arguments not taking into consideration the spouse’s views during non-intense shared time was positive and strong (r = 0.609). Similarly, the correlation between marital disputes during intense shared time and arguments not taking into consideration the spouse’s views during non-intense shared time was positive but slightly weaker (r = 0.504). Moreover, the correlation between marital disputes during non-intense household shared time and arguments not taking into consideration the spouse’s views during intense household shared time was positively weaker (r = 0.549) than the foregoing correlations. The same correlation for marital disputes during intense household shared time and arguments not taking into consideration intense household shared time was positive and slightly stronger (r = 0.535).
The above findings bring a certain nuance to the previous results. Based on their research, Jafr & Faraj (2023) argue that the length of time a man is present in the household could have an impact on the way marital disputes unfold, positing that this can potentially result in heightened arguments and an increased risk of divorce. Conversely, these outcomes could vary depending on the state of the marital relationship during periods of prolonged and non-prolonged cohabitation. In fact, there is a need to consider other household characteristics, such as non-intense shared time in long-distance marriages that can lead to conflict due to factors like stress, lack of communication, and trust issues (Mohd Zulkifli et al., 2022), or the composition of the family, such as the presence of children and a relative in the household, as all these factors potentially impact the dynamic of conflict between spouses Hatch & Bulcroft, 2004).
Current research has indicated that household gender inequality seems to decrease with an increased number of family members in the household. The presence of children, for instance, tends to reinforce traditional gendered patterns, with men sharing less in engaging in domestic chores the longer they are married and women’s labor force participation having little effect on the division of labor in the household, which is a notion that Charles & Höpflinger (1992) support. However, various scholars have argued that there is increasing paternal involvement in childcare and domestic tasks, but they also caution that this shift in men’s roles does not necessarily equate to gender equality within the family (Ngan & Chan, 2023). However, research that was conducted on nuclear versus extended family households has indicated that, in less affluent nuclear families, sharing household chores between spouses has become more common, indicating a potential for more egalitarian household practices (Sun, 2008).
Regarding the issue of psychological stress in households, the study found the results statistically significant (Pearson significance = 0.786) at the 0.01 level (two-tailed). The null hypothesis was rejected and it was concluded that there was a relation between household conflict during non-intense staying together and intense staying together (P < 0.01) based on gender.
The results also revealed a correlation between exposure to psychological stress and intense household shared time (0.786), which indicated significance at the 0.01 level (two-tailed). Similarly, the correlation coefficient between being hurt emotionally and non-intense household shared time was 0.589, which was also significant at the 0.01 level (two-tailed). The significance levels thus suggest that the correlation between these variables was unlikely to have occurred by chance. Regarding the confidence intervals of Spearman’s rho for each pair of variables, the confidence interval for the correlation between exposure to psychological stress during non-intense and intense household shared times were 0.738 and 0.826 at the 95% confidence level, indicating that we can be 95% confident that the true population correlation falls within the confidence interval.
These results shed light on how the length of time a man spends at home can affect levels of psychological stress, with the impact of this phenomenon varying based on the quality of the marriage and the period spent together. A study conducted by Tanaka et al. (2000) examined the impact of extended periods of husbands’ absence on the stress reactions of wives. The findings revealed that women whose husbands were absent for long periods experienced higher levels of stress compared to those whose husbands returned within shorter periods of time. Moreover, it was discovered that extended periods of absence had a greater negative effect compared to short-term absences, especially when older children were involved in the household. These findings emphasize that a man’s presence in or absence from the household greatly affects the mental well-being of spouses. The results thus suggest that intense household shared time likely influences women’s psychological stress or the fact that they are hurt emotionally more strongly than non-intense household shared time.
Concerning physical and sexual abuse, the results revealed a correlation between physical and sexual abuse during intense household shared time and non-intense household shared time. The correlation coefficient between physical abuse and intense household shared time was 0.783, which indicated significance at the 0.01 level (two-tailed), while the correlation coefficient between physical abuse and non-intense household shared time was also significant at the 0.01 level (two-tailed) at a value of 0.783. Moreover, the correlation coefficient between sexual abuse and intense household shared time was 0.822, which indicated significance at the 0.01 level (two-tailed), and the correlation coefficient between sexual abuse and non-intense household shared time was also significant at the 0.01 level (two-tailed) at a value of 0.822.
These findings support previous researchers’ conclusion that there is a link between physical and sexual abuse within households where there is a significant period of shared time. According to Symes et al. (2014), there is a correlation between higher scores of physical abuses and higher scores of sexual abuses, suggesting that these two forms of violence often coexist. The current research found that illiterate respondents reported very few intimate conflicts compared to their more literate counterparts. There is therefore a need for continued research to understand the influence of level of education on abusive behavior in households.
5. Conclusion
This study focused on the impact husbands may have on gender equality in households should they stay at home for a long time, as was the case during the COVID-19 restrictions. The study was conducted in Bukavu, a city in the DRC and involved a sample of 309 male and female respondents. It responded to the question whether husbands, should they spend more time at home, will exacerbate or improve gender disparities in their households. The findings of this study support those of earlier researchers who have argued that male spouses who stay at home will often become involved in the equal sharing of some household tasks, but not all. This suggests that, while the physical presence of a male partner can influence how tasks are shared, changing traditional views on gender roles is also important to ensure gender equality in households. This research was exploratory, and the results may therefore not be generalized to the entire Congolese population.
The results suggest that better marital interrelations in less intense household shared time are associated with better communication and decision-making in both less intense and more intense household shared time scenarios. It is supported by the finding that exposure to psychological stress has a stronger relationship with intense household shared time than with non-intense household shared time. The results further suggest a significant relationship between marital disputes and the consideration (or rejection) of partners’ opinions. Couples who spent more intense household shared time together and who did not consider their spouses’ different views showed a stronger correlation with marital disputes and arguments than those who were considerate of their partners’ opinions. Finally, there was a strong positive correlation between abusive behaviors and intense household shared time situations. Also, both variables showed a similar correlation between abusive behaviors and non-intense household shared time situations.
The findings thus indicate a strong positive relation between non-intense and intense marital shared time when husbands stay at home. The most extreme behaviors and attitudes regarding gender inequality manifest during both non-intense and intense shared time within the household. For instance, a couple might divide household tasks, so each partner spends an equal amount of time on chores and housework, fostering a balanced partnership and promoting gender equality. Conversely, a considerable disparity in household tasks persists in many homes; women often shoulder most childcare and housework, regardless of the husband’s presence. However, it is not clear from these correlations alone what caused these relationships. Further research should be conducted to understand the underlying factors that were the drivers of the correlations that emerged in this study.
In conclusion, it is acknowledged that comparing variables associated with non-intense household shared time and intense household shared time was a limitation in this research. To uncover potential but hitherto hidden nuances, more in-depth analyses of variable relationships and the inclusion of additional variables are required. To achieve positive outcomes during intense household shared time, the study proposes a proactive gender equality approach in non-intense shared time. Encouraging equal gender representation in public jobs has fostered accountability among both men and women, which presupposes that gender equality can be achieved through equal education. However, gender equality and the development of marginalized women are impeded by illiteracy, which keeps people unaware of their fundamental rights and encourages stagnant behaviors that pose a threat to women’s well-being and their recognition as equal members of society.
One drawback of this study is its inability to address the cultural disparities that exist within households in Bukavu, a city marked by significant ethnic and cultural diversity. Because gender roles and attitudes toward inequality differ significantly among ethnic groups (including Bashi, Barega, and others within and outside the city), the findings might have limited generalizability. Each group may have unique customs and beliefs that influence household dynamics and gender equality perceptions, which were not accounted for in this research. Therefore, the study’s conclusions may not fully reflect the complexities of gender inequality across all cultural contexts within Bukavu, and further research is needed to address this limitation.
Acknowledgements
I acknowledge the award received by the Fulbright Scholarship Program in 2023-2024. I also acknowledge my host institution, Bellevue College, and the Congolese Integration Network for agreeing to oversee this research program. I also thank the DRC Ministry of Education (ESU) and ISDR-Kaziba for allowing me to pursue this Fulbright program in the USA. My gratitude extends to the NIHSS-CODESRIA for their ongoing academic support, and to William Lawrence and Judy for their financial assistance.