Skip to main content
NCBI home page
SAGE - PMC COVID-19 Collection logoLink to SAGE - PMC COVID-19 Collection
. 2022 Jun 2:0192513X221105242. doi: 10.1177/0192513X221105242

Relationship Status and Well-Being in the Context of the COVID-19 Pandemic

Christin L Carotta 1,✉, Erin S Lavender-Stott 1, Aileen S Garcia 1, Hung-Ling (Stella) Liu 2
PMCID: PMC9163655

Abstract

The purpose of this study was to examine well-being, loneliness, and hope among single and partnered adults in the context of the COVID-19 pandemic. A total of 560 adults in the U.S. (50.2% female, 48.9% male, 28.7% single, 71.3% partnered) completed an online survey regarding their experiences amid the global health crisis. Results indicated that single and partnered individuals reported similar experiences of loneliness, hope, and well-being. Furthermore, hope served as a significant positive predictor of psychological well-being for both single and partnered individuals. Single and partnered individuals also engaged in a similar number of social interactions during the pandemic. The nature of these interactions (i.e., in-person vs. digital), however, uniquely predicted well-being across relationship status. Among single individuals, connecting with others in person significantly predicted well-being, whereas digital connections did not. The inverse was found for partnered individuals, where digital connections predicted well-being, but in-person interactions did not.

Keywords: COVID-19, well-being, singlehood, hope, loneliness

Introduction

In January 2020, the World Health Organization (WHO) declared that the outbreak of a new coronavirus, COVID-19, was a Public Health Emergency of International Concern. The WHO stated that there was a high risk of COVID-19 spreading to other countries around the world and, in March 2020, made the assessment that COVID-19 met the characteristics of a pandemic (World Health Organization [WHO], 2022). With more than 77 million COVID-19 cases in the United States (U.S.) and more than 900,000 deaths as of February 2022 (World Health Organization, 2022), the pandemic’s impact on physical health is profound.

In the United States, this unprecedented time is accompanied by an accumulation of pandemic-related stressors including, but not limited to, personal and family health concerns, financial distress, increased parenting and child-care/education demands, and difficulty accessing public health services (American Psychological Association, 2020). From the 2019 Annual Stress in America survey, the average stress level in U.S. adults has increased significantly during the pandemic (American Psychological Association, 2020). Adults also report changes in social interactions, work, caregiving, sleep, mood, concentration, eating habits, physical activity, and personal hygiene (Park, Velez, Kannan, & Chorpita, 2020).

As a result, emerging literature has begun to examine the mental health impact of the COVID-19 world health crisis (Gallagher, Zvolensky, Long, Rogers, & Garey, 2020; Holman, Thompson, Garfin, & Silver, 2020; Pearman, Hughes, Smith, & Neupert, 2020). During the pandemic, adults are reporting elevated rates of depressive symptoms and acute stress (Holman et al., 2020). Furthermore, individuals with personal COVID-19 health experiences (e.g., personally contracted COVID-19 or know someone who has) report greater depression, anxiety, and functional impairment than those without personal COVID-19 health experiences (Gallagher et al., 2020). Demographic analyses also suggest that parents and persons of color are experiencing disproportionate levels of stress, specifically related to health care access and basic family needs (i.e., food and housing) (American Psychological Association, 2020). Although Pearman et al. (2020) found no significant age variation in COVID-19-related stress among adults in the U.S., older adults who reported greater anxiety about contracting the virus experienced greater overall COVID-19 stress in comparison to younger adults. Preexisting health conditions and daily consumption of pandemic media coverage are also associated with acute stress and depressive symptoms (Holman et al., 2020). Thus far, however, there is limited research regarding relationship status and well-being during the COVID-19 pandemic, except from the first month when social isolation guidelines and stay-at-home government orders were first issued in the U.S. (Ray, 2021; Rosenberg, Luetke, Hensel, Kianersi, Fu, & Herbenick, 2021).

The purpose of this study is to examine well-being, loneliness, and hope among single and partnered adults within the context of a global pandemic. In the U.S. and other Western cultures, more people than ever before are single through personal choice, circumstances, postponement of marriage, divorce, and widowhood (Czyzowska, Gurba, Czyzowska, & Kalus, 2020; DePaulo, 2006; Simpson, 2016), as well as living alone, whether single or non-single (Klineberg, 2016). Although more adults are single during adulthood and single for longer periods of their lives, there are still many stereotypes, prejudices, and assumptions about people who are not in a romantic partnership, including that they are lonely, socially isolated, and do not have children or families (Adamczyk, 2016; DePaulo, 2006; Simpson, 2016). However, being single or living alone does not in and of itself mean an absence of social connection (Djundeva, Dykstra, & Fokkema, 2019), being isolated, or feeling lonely (Klineberg, 2016).

Loneliness, Social Distancing, and Computer-Based Technology

Although overlapping features exist between loneliness and social isolation, they are separate constructs (Smith & Victor, 2019). Loneliness involves feelings of isolation, disconnection, and not belonging, especially when there is a discrepancy between one’s desired and actual relationships (Hawkley et al., 2008; Hughes, Waite, Hawkley, & Cacioppo, 2004). Social isolation, on the other hand, is conceptualized as how integrated one is and the degree to which one has meaningful communications within their community, family, and friends (Smith & Victor, 2019). Loneliness is often related to high levels of stress and mental health concerns, including depressive symptoms, anxiety, and suicidal thoughts (Hawkley et al., 2008; Richardson et al., 2017; Stickley & Koyanagi, 2016; Wang, Mann, Lloyd-Evans, Ma, & Johnson, 2018).

Within the context of the COVID-19 pandemic, social distancing and quarantining can have public health benefits by slowing the transmission of infectious diseases, but they may also contribute to loneliness and mental health concerns by inhibiting access to social support (Fumagalli, Dolmatzian, & Shrum, 2021; Rosenberg et al., 2021). Individuals in quarantine can experience several negative emotions, including fear for their health or the health of others, frustration, anger, boredom, and a sense of isolation (Brooks et al., 2020). Previous studies have found that this period of separation and restriction can contribute to adverse mental health outcomes, including symptoms of anxiety, acute stress disorder, post-traumatic stress, and depression (for a review, see Brooks et al., 2020). Among adults in the U.S., Luchetti et al. (2020) also found that individuals who were living alone or who had chronic conditions reported greater loneliness at the start of the pandemic.

One unique avenue for combating loneliness and connecting with others during the COVID-19 pandemic is through the use of computer-based technology (Fumagalli et al., 2021; Nowland, Necka, & Cacioppo, 2018). As computer-based technology, such as the Internet, has become more prominent in our lives, research has begun to examine the impact of digital versus in-person connections on well-being, including mental health and loneliness, with contradictory findings (Nowland et al., 2018). Often, previous studies have treated all Internet and technology use as the same, whether it is active use (e.g., video chats [Skype, Zoom, Facetime], synchronous text messaging, and phone calls) or passive use (e.g., social media, asynchronous message posting, and online gaming; Liu, Baumeister, Yang, & Hu, 2019). Recent research among adolescents and adults has found high use of passive and/or asynchronous technology, such as social media or e-mail, combined with low in-person social interactions is related to higher levels of loneliness (Liu et al., 2019; Twenge, Spitzberg, & Campbell, 2019). However, when technology is used to enhance existing relationships, especially active digital technologies, it is a useful tool for reducing loneliness (Nowland et al., 2018), including during the COVID-19 pandemic, as it allows for continued quality engagement with people outside of one’s own home (Fumagalli et al., 2021; Nguyen et al., 2021).

Social Support, Hope, and Well-Being

Social support is one of the most consistent indicators of resilience after a disaster (Bonanno et al., 2008; Rodriguez-Llanes et al., 2013). Social support and personal connections with others can help protect individuals against adversity and intense social change (Lee & Goldstein, 2016). For example, among college students in China, COVID-19 stress was a risk factor for acute stress disorder symptoms (Ye et al., 2020). This relationship, however, was mediated by social support, adaptive coping strategies, and resilience. Social connections can support well-being by providing companionship, social engagement in shared activities, and a sense of community or belonging (Djundeva et al., 2019).

Hope can also play an important role in resiliency, well-being, and buffering against adversity, such as a global pandemic (Chang, Yu, & Hirsch, 2013; Gallagher & Lopez, 2009; Mathew, Dunning, Coats, & Whelan, 2014). Hope is a positive motivational state “based on a reciprocally derived sense of successful (a) agency (goal-directed determination) and (b) pathways (planning to meet goals)” (Snyder et al., 1991, p. 571). Pathway thinking refers to a person’s perception that they are capable of formulating pathways for achieving their goals, and agency thinking is an individual’s perceived ability to utilize identified pathways until goal obtainment is achieved (Snyder et al., 1991). During times of stress and adversity, hope supports positive outcomes for both physical and mental health (for a review, see Alarcon, Bowling, & Khazon, 2013; Gallagher & Lopez, 2009) and is inversely correlated with depression (Chang et al., 2013; Mathew et al., 2014).

Relationship Status and Well-Being

With regard to single and partnered individuals, marriage and committed romantic relationships are a structural form of social support (Shapiro & Keyes, 2008)—relationships supported by laws and society. Existing research has highlighted several benefits of having a satisfying marriage, including greater financial stability, a more satisfying sex life, less engagement in unhealthy behaviors (e.g., drug or alcohol abuse), and fewer depressive symptoms, compared with those who are unmarried (Carr & Springer, 2010; Waite & Gallagher, 2001). However, the quality of a relationship is an important factor, as it contributes to psychological well-being beyond marital status. Satisfying romantic relationships can provide a sense of belonging, purpose, and social support, which can buffer against stress and adversity (Dehle, Larsen, & Landers, 2001; Waite & Gallagher, 2001). Being in an unsatisfying or conflict-ridden marriage, however, is associated with greater mental health concerns when compared to those who are not married (Williams, 2003).

Previous findings have also been mixed regarding whether single adults are more or less lonely compared to their married counterparts, partly because of different definitions and measurements of loneliness, such as subjective loneliness or romantic loneliness. Hawkley et al. (2008) found that among older adults, positive marital relationships offered the greatest degree of protection against loneliness, compared with those who were widowed, divorced/separated, and never married. Lee and Goldstein (2016), however, further noted that among college students in the U.S., support from both friends and romantic partners is negatively associated with loneliness, even when stress is held constant. The more diverse support an individual has, the less loneliness is reported, regardless of levels of stress (Lee & Goldstein, 2016). Thus, having high-quality romantic and social relationships contribute to intimacy and can help protect against loneliness (Lee & Goldstein 2016; Hawkley et al., 2008).

Snyder (1994) has further suggested that meaningful relationships can help foster hopeful thinking. Hope is positively associated with perceived social support and positive relationships (Sevari, Pilram, & Farzadi, 2020), but negatively associated with loneliness, stress, anxiety, and depressive symptoms (Muyan et al., 2016; Yarcheski, Mahon, & Yarcheski, 2011). Bailey & Snyder (2007) found that married and single individuals reported similar levels of hope, and both were more hopeful in total trait hope, agency, and pathway scores, compared with those who were divorced, widowed, or separated.

When singlehood (or living alone), loneliness, hope, and well-being are examined, however, the context and nuances with which these variables occur are rarely acknowledged (Smith & Victor, 2019). Specifically, the unique challenges or strengths that single adults may experience regarding loneliness and resilience in the face of the COVID-19 pandemic remain unknown. Because there is limited knowledge about how chronic stress and social distancing affect individuals with different relationship statuses during a global pandemic, the aim of this study was two-fold: (1) to explore how well-being, loneliness, and hope differed among single and partnered individuals during the pandemic; (2) to further examine the relationships between hope, loneliness, well-being, and COVID-19 pandemic experiences (e.g., digital vs. in-person social interactions) among single and partnered individuals.

Methods

Procedures and Participants

All study procedures were approved by the university’s Institutional Review Board. Study information was posted on social media (e.g., Facebook, Twitter, etc.) to recruit adults living in the U.S. to participate in an online survey about their experiences and perspectives during the COVID-19 pandemic. Convenience sampling was used to reach adults 18 years or older and a total of 564 participants completed the survey during July 2020. The average time to complete the survey was 16 minutes. Participants who completed the survey received a $10 gift card.

Four individuals who were dating but not cohabiting were excluded from the analysis, as they could be classified as either partnered or single depending on additional contextual information that was not obtained. A total of 560 adults were included in the analysis. Single individuals (n = 161; 28.7%) included those who were never married, widowed, or divorced. Partnered participants (n = 399; 71.3%) included individuals who were in romantic relationships with legal standing or were cohabitating with a committed partner (Morris, Sinclair, & DePaulo, 2007; Slonim, Gur-Yaish, & Katz, 2015). Participants ranged from 20–71 years of age (M = 33.69). Participants described their race or ethnicity as White or Caucasian (44.6%), Hispanic or Latino (22%), American Indian or Alaskan Native (11.8%), Black or African American (9.5%), Asian (7.3%), Native Hawaiian or other Pacific Islander (4.5%), and two individuals preferred not to respond (0.4%). Participants described their gender as female (50.2%), male (48.9%), and gender fluid, a-gender, or gender non-conforming (0.9%). Education levels were diverse, from high school or equivalent (2.9%), some college but no degree (14.1%), trade/vocational/technical degree (15.2%), associate’s degree (19.6%), bachelor’s degree (34.1%), and graduate education of master’s degree, professional degree (i.e., MD, DDS, DVM), or doctorate (i.e., PhD, EdD) (14.1%).

The sample also reported a diverse income range, from $0–24,999 (3.6%), $25,000–49,999 (15.7%), $50,000–$74,999 (32.5%), $75,000–99,999 (20.5%), and more than $100,000 (27.7%). Regarding the COVID-19 pandemic’s influence on their employment, some participants reported no change or an increase in employment (31.7%), whereas the majority reported reduced employment (52.4%) or unemployment (15.9%). At the time of the survey, 24.8% of participants also reported that they or someone they knew had tested positive for the COVID-19 virus.

Measures

Loneliness

The Three-Item Loneliness Scale (Hughes et al., 2004) is derived from the Revised UCLA Loneliness Scale (R-UCLA; Russell, Peplau & Cutrona, 1980) and addresses loneliness in terms of perceived relationship quality and feelings of isolation, lack of companionship, or being left out. The measure consists of three self-reported items on a three-point Likert-type scale ranging from 1 (hardly ever) to 3 (often). Higher total scores represent greater loneliness. In the current sample, Cronbach’s alpha was .802.

Hope

The Adult State Hope Scale (ASHS; Snyder et al., 1996) is based on Snyder et al.’s (1991) cognitive conceptualization of hope. The measure assesses goal-directed thoughts at a given moment in time. The measure consists of six self-report items; three questions assess agency (e.g., “Right now, I see myself being pretty successful.”) and three questions assess pathway thinking (e.g., “I can think of many ways to reach my goals.”). Respondents rate each item on an eight-point Likert-type scale ranging from 1 (definitely false) to 8 (definitely true). Responses are summed to obtain pathway and agency sub-scores and the overall state of hope. Higher scores represent greater hope. In the current sample, Cronbach’s alpha was .906.

Psychological Well-Being

Ryff’s Psychological Well-Being Scale (18-items) (PWB-18; Ryff & Keyes, 1995) is a multi-dimensional measure that assesses six dimensions of psychological well-being: self-acceptance, positive relations with others, autonomy, environmental mastery, purpose in life, and personal growth (Ryff, 1989). The short form consists of 18 self-reported items, three questions for each sub-scale. Respondents rate each item on a seven-point Likert-type scale ranging from 1 (completely disagree) to 7 (completely agree). Higher total scores represent greater well-being. Subscale scores are summed for a composite well-being score. In the current sample, Cronbach’s alpha was .713.

COVID-19 Experiences

During the COVID-19 pandemic, individuals had varying experiences with exposure to the virus, with isolation or social distancing, and with financial strain, which may contribute to their overall well-being (Gallagher et al., 2020). To assess differences in COVID-19 experiences, participants were asked about their health, social interactions, and employment during the pandemic.

Health

Participants were asked about their personal experiences with the COVID-19 virus, including whether they had no symptoms, they had tested positive (self positive), someone in their household had tested positive (someone positive), or someone they knew but did not live with had tested positive (other positive).

Social Interactions

In the context of the COVID-19 pandemic, in which people may practice social distancing or limit their in-person interactions with others, participants were asked how many people they had connected with in person over the past week (excluding members of their own household). They were also asked how many people, outside their household, they had connected with digitally in the past week (e.g., via messaging, Zoom, and Facetime).

Employment

To assess the impact of the COVID-19 pandemic on employment, we asked participants how their employment status had changed since March 2020. Participants reported increased employment, reduced employment (e.g., full to part-time, furloughed), unemployment, or no change in employment.

Data Analyses

Data were de-identified and cleaned prior to analysis using SPSS, version 26. To examine the differences between single and partnered individuals, one-way multiple analysis of variance (MANOVA) was conducted on variables of interest, which included loneliness, hope, well-being, in-person and digital connections during COVID-19, COVID-19 health and employment changes, and demographic characteristics (i.e., gender, income, age, and education). Correlations were run to test the relationships between the variables in the overall sample and sub-samples of partnered and single individuals. Multiple regression analyses were performed on the two sub-samples of single and partnered individuals to understand how loneliness, hope, and COVID-19 experiences predict psychological well-being.

Results

Relationship Status Differences in Hope, Loneliness, Well-Being, and COVID-19 Experiences

One-way multiple analysis of variance (MANOVA) was conducted on the variables of interest to examine the differences between single and partnered individuals during the COVID-19 pandemic, F (13, 519) = 2.51, p < .01; Wilk’s Λ = .941, ηp2 = .059. MANOVA results showed significant differences between the two groups in gender composition and income (Table 1). More men were in the partnered group, F (1, 531) = 4.66, p < .05, ηp2 = .009, and income was greater among the partnered participants, compared to single participants, F(1, 531) = 22.28, p < .05, ηp2 = .04. There were no significant differences between single and partnered individuals regarding age, education, employment changes, well-being, hope, loneliness, knowing someone who had tested positive with COVID-19, and in-person or digital connections outside the household during the COVID-19 pandemic.

Table 1.

Means, Standard Deviations, and Multiple Analysis of Variance for Study Variables.

Variable Partnered Single MANOVA
M SD M SD F (1, 531) ηp2
Age 33.72 5.26 33.68 6.30 .01 .000
Income 3.89 1.34 3.26 1.49 22.28** .040
Education 5.17 1.48 5.11 1.33 .14 .000
Gender 1.53 .50 1.43 .50 4.66* .009
Employment change .307 .46 .318 .47 .06 .000
Hope 33.17 6.05 32.20 7.65 2.37 .004
Loneliness 5.68 1.34 5.68 1.32 .00 .000
In-person connection 4.51 3.93 4.64 3.57 .12 .000
Digital connection 7.92 8.31 7.91 5.77 .00 .000
Self positive with COVID-19 .05 .23 .06 .24 .08 .000
Someone positive with COVID-19 .07 .26 .09 .28 .48 .001
Other positive with COVID-19 .13 .33 .14 .35 .08 .000
Well-being 4.21 .54 4.21 .60 .00 .000
Open in a new tab

Note. * p < .05. ** p < .01. Someone Positive with COVID-19 is someone within the home; Other Positive is knowing someone outside the household who has tested positive with COVID-19.

Correlations were run to test the relationship between the variables in the whole sample as well as in the sub-samples of partnered and single individuals (Table 2). In the whole sample, hope had a weak but significant correlation with age, income, education, digital connections with others, knowing someone outside the home who had tested positive with COVID-19, and psychological well-being. Among single individuals, income, gender, loneliness, in-person connection, digital connection, and well-being were correlated with hope. More specifically, single males and single individuals who reported higher income were more hopeful than single females or those with less income.

Table 2.

Correlations for Study Variables.

Variable 1 2 3 4 5 6 7 8 9 10 11 12
1. Age —
 a. Partnered
 b. Single
2. Income −.154** —
 a. Partnered −.215**
 b. Single −.092
3. Education −.032 .341** —
 a. Partnered −.009 .378**
 b. Single −.073 .296**
4. Gender −.012 .073 .090* —
 a. Partnered −.076 .071 .103*
 b. Single .118 −.003 .065
5. Employment change .022 .006 .150** −.102* —
 a. Partnered .029 .086 .213** −.094
 b. Single −.001 −.156 -.006 −.125
6. Hope −.092* .322** .290** .080 .011 —
 a. Partnered .030 .198** .227** .208** .073
 b. Single −.288** .485** .431** −.206** −.111
7. Loneliness .038 −.023 -.118** .046 −.196** −.044 —
 a. Partnered .085 −.049 −.089 .176** −.230** .031
 b. Single −.078 .029 −.183* −.300** −.120 −.186*
8. In-person connection −.018 .017 −.057 .069 .170** .055 −.218** —
 a. Partnered −.104* .027 .013 .020 .265** .181** −.222**
 b. Single .166* -.028 −.236** .199* -.086 −.215** −.220**
9. Digital connection .122** -.121** −.019 −.039 .154** −.124** −.118** .389**
 a. Partnered .082 -.150** .005 −.087 .177** −.063 −.126* .373**
 b. Single .246** -.058 −.101 .124 .079 −.301** −.093 .456**
10. Self positive .059 −.049 −.121** .067 −.081 .024 .061 −.019 −.094* —
 a. Partnered .057 −.088 -.135** −.021 −.035 .061 .065 −.023 −.099
 b. Single .040 .021 -.073 .289** −.180* -.025 .009 −.016 −.074
11. Someone positive −.034 .044 −.047 .093* −.148** .056 .033 .045 −.026 −.038 —
 a. Partnered −.042 .054 −.049 −.002 −.116* .089 .103* .036 −.024 −.064
 b. Single .012 .036 −.021 .305** −.220** .004 −.112 .055 −.037 .027
12. Other positive −.065 .003 .210** −.068 .043 .084* .072 −.026 .026 −.073 −.032 —
 a. Partnered −.008 .152** .165** −.039 .023 .132** .081 .021 .027 −.057 −.013
 b. Single −.147 -.234** .302** −.110 .103 .050 .072 −.110 .036 −.102 −.060
13. Well-being −.060 −.007 .314** −.155** .264** .340** −.292** .065 .093* −.050 −.101* .325**
 a. Partnered .097 .071 .303** −.151** .269** .338** −.320** .118* .176** −.041 −.051 .279**
 b. Single −.337** −.144 .335** −.156 .261** .368** −.235** −.045 −.136 −.066 −.196* .410**
Open in a new tab

Note. * p < .05. ** p < .01.

Loneliness was negatively correlated with education (in the whole sample and single sub-sample), gender (in the partnered and single sub-samples), employment changes during COVID-19 (in the whole sample and partnered sub-sample), in-person and digital connection (except for singles with digital connections), and psychological well-being. Of note, being a partnered male was more strongly associated with loneliness than being a single male. Additionally, there was a positive correlation between someone testing positive for COVID-19 and loneliness, indicating that knowing someone who had COVID-19 was associated with greater loneliness (for the whole sample and for the partnered sub-sample). In-person and digital connections were moderately correlated.

In addition to the hope and loneliness relationships mentioned above, well-being was correlated with education, gender (except for singles), stable or improved employment, in-person connections (in the partnered sub-sample only), digital connections (in the whole sample and partnered sub-sample), and knowing someone who had tested positive for COVID-19 in the household or outside the household. Demographics were not significantly correlated, or were weakly correlated, with each other, except for education, which was moderately related to income and weakly correlated to gender and employment changes for the whole sample and partnered sub-sample. However, oneself testing positive was negatively correlated with education in the whole and partnered sub-sample, employment change in the single sub-sample, and a positive correlation with gender in the single sub-sample. Having someone in the household who had tested positive for COVID-19 was correlated with gender and employment change. Knowing someone who lived outside the household who had tested positive with COVID-19 was correlated with income (in the partnered and single sub-samples) and education (in the whole sample and both sub-samples).

Predicting Well-Being Through Hope, Loneliness, and COVID-19 Experiences

Multiple regression analyses were conducted separately on the two groups to understand the relationships between hope, loneliness, COVID-19 experiences, and psychological well-being. Table 3 presents the unstandardized and standardized regression coefficients, standard-error estimates, and p values of the estimates in the final model. For the partnered group, the seven main predictors in the model (i.e., hope, loneliness, and five measures of COVID-19 experiences) and the demographic covariates (gender, educational background, employment change, income, and age) accounted for 39.0% of the variance in the dependent variable (R2 = .390, F (12,372) = 19.83, p < .01). The regression model showed that higher levels of hope were related to higher levels of psychological well-being. Knowing someone outside of the household who had tested positive was also related to higher well-being scores. Digital social connections were also significant, with those who connected more reporting greater well-being. Loneliness, however, was related to lower levels of well-being. Socially connecting with others in-person was not significant. Among the demographic control variables, only income was not significantly related to well-being.

Table 3.

Regression Coefficients (Unstandardized and Standardized), Standard Error Estimates, and Probability (P) Values for the Regression Coefficients in the Regression Model.

Predictor B B SE P
Partnered
 (Constant) 3.404 .222 <.001
 Gender −.158 −.147 .046 .001
 Education .068 .189 .017 <.001
 Employment change .140 .121 .052 .007
 Income −.028 −.070 .019 .132
 Age .009 .086 .004 .044
 Hope .027 .302 .004 <.001
 Loneliness −.115 −.289 .017 <.001
 Self positive with COVID-19 .001 .000 .098 .991
 Someone positive with COVID-19 −.016 −.008 .087 .851
 Other positive with COVID-19 .382 .242 .067 <.001
 In-person connection −.010 −.074 .006 .121
 Digital connection .008 .127 .003 .005
Single
 (Constant) 4.306 .429 <.001
 Gender −.042 −.034 .094 .658
 Education .079 .176 .034 .023
 Employment change .258 .200 .085 .003
 Income −.119 −.294 .032 <.001
 Age −.025 −.257 .006 <.001
 Hope .028 .352 .007 <.001
 Loneliness −.067 −.148 .032 .040
 Self positive with COVID-19 .137 .055 .164 .406
 Someone positive with COVID-19 −.303 −.143 .138 .030
 Other positive with COVID-19 .433 .252 .118 <.001
 In-person connection .026 .152 .012 .035
 Digital connection −.004 −.035 .007 .623
Open in a new tab

Note. The following variables were dummy-coded: gender (0 = female; 1 = male); employment change (0 = became unemployed or decreased employment; 1 = no change in employment or increased employment); and testing positive for self, someone in the household, and someone outside of the household (0 = did not test positive; 1 = tested positive).

In the singles group, the predictors and control variables accounted for 51.4% of the variance in psychological well-being (R2= .514, F (12,135) = 11.887, p < .01). Similar to the partnered group, hope was positively related to well-being. Socially connecting to others in person was significant, with those who connected more reporting higher levels of well-being. Having someone in the household, as well as knowing someone else (outside the household), who had tested positive of the virus was also significant. In addition, loneliness was significantly and negatively related to well-being; thus, the lonelier someone was, the lower their well-being. Connecting with others digitally was not significantly related to well-being. Regarding the demographic control variables, only gender was not significantly related to well-being.

Discussion

In the context of the COVID-19 pandemic, the study aimed to examine well-being, loneliness, and hope among single and partnered adults in the U.S. The results indicated that single and partnered individuals in the U.S. had similar experiences with loneliness, hope, and well-being during the global pandemic. In the face of physical isolation from others, employment restrictions, and other stressors related to the public health crisis, the current findings showed no significant differences in the mental health of single and partnered individuals. The findings also indicated that hope was an important variable in predicting positive psychological well-being for both single and partnered individuals; for instance, those with higher levels of hope had greater psychological well-being. This finding is consistent with previous studies, which have found that hope promotes positive outcomes in the face of adversity (Alarcon et al., 2013; Gallagher & Lopez, 2009; Muyan et al., 2016; Yarcheski et al., 2011).

Our findings further contribute to existing literature by noting that both single and partnered individuals had a similar number of social interactions during the COVID-19 pandemic. The nature of these interactions (i.e., in-person vs. digital), however, uniquely predicted well-being across relationship status. More specifically, among single individuals, connecting with others in person significantly predicted well-being, while digital connections did not. The inverse was found in partnered individuals, where digital connections predicted well-being during the COVID-19 pandemic, while in-person interactions did not.

These findings are consistent with previous studies that have found that social support and well-being are positively associated (Bonanno et al., 2008; Lee & Goldstein, 2016; Rodriguez-Llanes et al., 2013). However, our findings highlight the need for additional research to examine variations in social support that are uniquely garnered from in-person and digital interactions by single and partnered individuals and across diverse household compositions (Rosenberg et al., 2021). For example, in-person interactions may have been particularly beneficial for single individuals who were living alone during the COVID-19 pandemic, compared with individuals who were able to connect face-to-face daily with others in their own household. Conversely, digital connections may have allowed for a unique outlet or more diverse social support resources for partnered individuals who were living together and/or individuals who had children at home.

Lastly, we found that knowing someone who had tested positive for COVID-19, outside of one’s own household, significantly predicted well-being for both single and partnered individuals. For single individuals, someone testing positive within the household, but not themselves, also significantly predicted well-being. Our findings differ from emerging literature that has found individuals with personal COVID-19 experiences (e.g., personally contracted COVID or knew someone who had) report higher levels of depression, anxiety, and functional impairment than those without personal COVID-19 health experiences (Gallagher et al., 2020). Our findings suggest that additional research is needed to examine the relationship between personal COVID-19 health experiences and well-being, with particular attention to how the proximity of COVID-19 health experiences (e.g., knowing someone who has tested positive and the closeness of this relationship), the severity/longevity of illness, long-term health outcomes, and perceived antibody immunity can influence well-being at various time points during the global pandemic.

Although our findings are supported by existing research and offer unique contributions, some limitations should be acknowledged. First, our findings provide a snapshot of well-being among adults in the U.S. approximately 5 months after a global pandemic was declared. The COVID-19 world health crisis has now persisted for more than a year. Given the cross-sectional nature of the data, we are not able to conclude the direction of effects between the variables and psychological well-being. Our findings do not reflect mental health changes that may have taken place over the duration of the pandemic. However, some longitudinal research during the pandemic has found stable levels of mental health and well-being, particularly regarding loneliness (Ray, 2021). Secondly, due to the size of the single and partnered sub-samples, our analysis of single and partnered individuals focused on broad relationship statuses (e.g., never-married, divorced, widowed, or non-cohabiting partners) and household structures (e.g., inclusion of children, roommates, or multi-generational households). Further examining relationship status subtypes may provide more nuanced insight into the experiences of loneliness, hope, and well-being during the COVID-19 pandemic. Lastly, data on relationship satisfaction, length of relationship, or time since previous relationship were not collected. These variables may also contribute to variations in well-being across relationship status.

In summary, our finding that single and partnered individuals had similar experiences of well-being, loneliness, and hope during the COVID-19 pandemic helps further challenge stereotypes and misconceptions that individuals who are not in romantic relationships generally experience greater loneliness or mental health issues. Our findings also add to existing literature by denoting no significant differences in the degree to which single and partnered individuals engaged in in-person or digital connections with others during the COVID-19 pandemic. These findings reiterate that being single or living alone does not, in and of itself, mean lacking social connection (Djundeva et al., 2019), being isolated, or feeling lonely (Klineberg, 2016). However, our findings suggest that single and partnered individuals may benefit differently from efforts to increase social support either through digital connections or face-to-face interactions.

Footnotes

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported, in part, by the College of Education and Human Sciences at South Dakota State University (SDSU) and USDA National Institute of Food and Agriculture (NIFA), Multi-state (#1016891) and Hatch (#1016822) project.

ORCID iDs

Christin L. Carotta https://orcid.org/0000-0001-6881-1510

Erin S. Lavender-Stott https://orcid.org/0000-0003-4189-1121

References

  1. Adamczyk K. (2016). An investigation of loneliness and perceived social support among single and partnered young adults. Current Psychology, 35(4), 674–689. 10.1007/s12144-015-9337-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Alarcon G. M., Bowling N. A., Khazon S. (2013). Great expectations: A meta-analytic examination of optimism and hope. Personality and Individual Differences, 54(7), 821–827. 10.1016/j.paid.2012.12.004 [DOI] [Google Scholar]
  3. American Psychological Association (2020). Stress in America 2020: Stress in the time of COVID-19. https://www.apa.org/news/press/releases/stress/2020/report [Google Scholar]
  4. Bailey T. C., Snyder C. R. (2007). Satisfaction with life and hope: A look at age and marital status. The Psychological Record, 57(2), 233-240. 10.1007/bf03395574. [DOI] [Google Scholar]
  5. Bonanno G. A., Ho S. M., Chan J. C., Kwong R. S., Cheung C. K., Wong C. P., Wong V. C. (2008). Psychological resilience and dysfunction among hospitalized survivors of the SARS epidemic in Hong Kong: A latent class approach. Health Psychology, 27(5), 659. 10.1037/0278-6133.27.5.659 [DOI] [PubMed] [Google Scholar]
  6. Brooks S. K., Webster R. K., Smith L. E., Woodland L., Wessely S., Greenberg N., Rubin G. J. (2020). The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. The Lancet, 395(10227), 912–920. 10.1016/s0140-6736(20)30460-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Carr D., Springer K. W. (2010). Advances in families and health research in the 21st century. Journal of Marriage and Family, 72(3), 743–761. 10.1111/j.1741-3737.2010.00728.x [DOI] [Google Scholar]
  8. Chang E. C., Yu E. A., Hirsch J. K. (2013). On the confluence of optimism and hope on depressive symptoms in primary care patients: Does doubling up on bonum futurun proffer any added benefits? The Journal of Positive Psychology, 8(5), 404–411. 10.1080/17439760.2013.818163 [DOI] [Google Scholar]
  9. Czyzowska D., Gurba E., Czyzowska N., Kalus A. M. (2020). Intimate relationship and its significance for eudaimonic well-being in young adults. Health Psychology Report, 8(2), 155–166. 10.5114/hpr.2020.93768 [DOI] [Google Scholar]
  10. Dehle C., Larsen D., Landers J. E. (2001). Social support in marriage. American Journal of Family Therapy, 29(4), 307–324. 10.1080/01926180126500 [DOI] [Google Scholar]
  11. DePaulo B. (2006). Singled out: How singles are stereotyped, stigmatized, and ignored, and still live happily ever after. St. Martin’s Griffin [Google Scholar]
  12. Djundeva M., Dykstra P. A., Fokkema T. (2019). Is living alone “aging alone”? Solitary living, network types, and well-being. Journal of Gerontology B: Psychological Social Science, 74(8), 1406–1415. 10.1093/geronb/gby119 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fumagalli E., Dolmatzian M. B., Shrum L. J. (2021). Centennials, FOMO, and loneliness: An investigation of the impact of social networking and messaging/VoIP apps usage during the initial stage of the coronavirus pandemic. Frontiers in Psychology, 12(620739), 1–14. 10.3389/fpsyg.2021.620739 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gallagher M. W., Lopez S. J. (2009). Positive expectancies and mental health: Identifying the unique contributions of hope and optimism. The Journal of Positive Psychology, 4(6), 548–556. 10.1080/17439760903157166 [DOI] [Google Scholar]
  15. Gallagher M. W., Zvolensky M. J., Long L. J., Rogers A. H., Garey L. (2020). The impact of Covid-19 experiences and associated stress on anxiety, depression, and functional impairment in American adults. Cognitive Therapy and Research, 44(6), 1043–1051. 10.1007/s10608-020-10143-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Hawkley L. C., Hughes M. E., Waite L. J., Masi C. M., Thisted R. A., Cacioppo J. T. (2008). From social structure factors to perceptions of relationship quality and loneliness: The Chicago health, aging, and social relations study. Journal of Gerontology: Social Sciences, 63B(6), S375–S384. 10.1093/geronb/63.6.s375 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Holman E. A., Thompson R. R., Garfin D. R., Silver R. C. (2020). The unfolding COVID-19 pandemic: A probability-based, nationally representative study of mental health in the US. Science Advances, 6(42), eabd5390. 10.1126/sciadv.abd5390 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Hughes M. E., Waite L. J., Hawkley L. C., Cacioppo J. T. (2004). A short scale for measuring loneliness in large surveys: Results from two population-based studies. Research on Aging, 26(6), 655–672. 10.1177/0164027504268574 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Klineberg E. (2016). Social isolation, loneliness, and living alone: Identifying the risks for public health. American Journal of Public Health, 106(5), 786–787. 10.2105/ajph.2016.303166 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Lee C. Y. S., Goldstein S. E. (2016). Loneliness, stress, and social support in young adulthood: Does the source of support matter? Journal of Youth and Adolescence, 45(3), 568–580. 10.1007/s10964-015-0395-9 [DOI] [PubMed] [Google Scholar]
  21. Liu D., Baumeister R. F., Yang C., Hu B. (2019). Digital communication media use and psychological analysis. Journal of Computer-Mediated Communication, 24(5), 259–274. 10.1093/jcmc/zmz013 [DOI] [Google Scholar]
  22. Luchetti M., Lee J. H., Aschwanden D., Sesker A., Strickhouser J. E., Terracciano A., Sutin A. R. (2020). The trajectory of loneliness in response to COVID-19. American Psychologist, 75(7), 897–908. 10.1037/amp0000690 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Mathew J., Dunning C., Coats C., Whelan T. (2014). The mediating influence of hope on multidimensional perfectionism and depression. Personality and Individual Differences, 70, 66-71. 10.1016/j.paid.2014.06.008. [DOI] [Google Scholar]
  24. Morris W. L., Sinclair S., DePaulo B. M. (2007). No shelter for singles: The perceived legitimacy of marital status discrimination. Group Processes & Intergroup Relations, 10(4), 457–470. 10.1177/1368430207081535 [DOI] [Google Scholar]
  25. Muyan M., Chang E. C., Jilani Z., Yu T., Lin J., Hirsch J. K. (2016). Loneliness and negative affective conditions in adults: Is there any room for hope in predicting anxiety and depressive symptoms? The Journal of Psychology, 150(3), 333–341. 10.1080/00223980.2015.1039474 [DOI] [PubMed] [Google Scholar]
  26. Nguyen M. H., Gruber J., Marler W., Hunsaker A., Fuchs J., Hargittai E. (2021). Staying connected while physically apart: Digital communication when face-to-face interactions are limited. New Media & Society. 10.1177/1461444820985442. [DOI] [Google Scholar]
  27. Nowland R., Necka E. A., Cacioppo J. T. (2018). Loneliness and social internet use: Pathways to reconnection in a digital world? Perspectives on Psychological Science, 13(1), 70–87. 10.1177/1745691617713052 [DOI] [PubMed] [Google Scholar]
  28. Park A. L., Velez C. V., Kannan K., Chorpita B. F. (2020). Stress, functioning, and coping during the COVID-19 pandemic: Results from an online convenience sample. The Behavior Therapist, 42(6), 210–216. 10.31234/osf.io/jmctv [DOI] [Google Scholar]
  29. Pearman A., Hughes M. L., Smith E. L., Neupert S. D. (2020). Age differences in risk and resilience factors in COVID-19-related stress. The Journals of Gerontology: Series B, 76(2), e38–e44. 10.1093/geronb/gbaa120 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Ray C. D. (2021). The trajectory and determinants of loneliness during the early months of the COVID-19 pandemic in the United States. Journal of Social and Personal Relationships, 38(6), 1920–1938. 10.1177/02654075211016542 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Richardson T., Elliott P., Roberts R. (2017). Relationship between loneliness and mental health in students. Journal of Public Mental Health, 16(2), 48–54. 10.1108/JPMH-03-2016-0013 [DOI] [Google Scholar]
  32. Rodriguez-Llanes J. M., Vos F., Guha-Sapir D. (2013). Measuring psychological resilience to disasters: Are evidence-based indicators an achievable goal? Environmental Health, 12(1), 1–10. 10.1186/1476-069X-12-115 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Rosenberg M., Luetke M., Hensel D., Kianersi S., Fu T., Herbenick D. (2021). Depression and loneliness during April 2020 COVID-19 restrictions in the United States, and their associations with frequency of social and sexual connections. Social Psychiatry and Psychiatric Epidemiology, 56(7), 1221–1232. 10.1007/s00127-020-02002-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Russell D., Peplau L. A., Cutrona C. E. (1980). The revised UCLA loneliness scale: Concurrent and discriminant validity evidence. Journal of Personality and Social Psychology, 39(3), 472. 10.1037/0022-3514.39.3.472 [DOI] [PubMed] [Google Scholar]
  35. Ryff C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well- being. Journal of Personality and Social Psychology, 57(6), 1069. 10.1037/0022-3514.57.6.1069 [DOI] [Google Scholar]
  36. Ryff C. D., Keyes C. L. M. (1995). The structure of psychological well-being revisited. Journal of Personality and Social Psychology, 69(4), 719. 10.1037/0022-3514.69.4.719 [DOI] [PubMed] [Google Scholar]
  37. Sevari K., Pilram P., Farzadi F. (2020). The causal relationship between perceived social support and life satisfaction through hope, resilience and optimism. International Journal of Psychology, 14(1), 83–113 [Google Scholar]
  38. Shapiro A., Keyes C. L. M. (2008). Marital status and social well-being: Are the married always better off? Social Indicators Research, 88(2), 329–346. 10.1007/s11205-007-9194-3 [DOI] [Google Scholar]
  39. Simpson R. (2016). Singleness and self-identity: The significance of partnership status in the narratives of never-married women. Journal of Social and Personal Relationships, 33(3), 385–400. 10.1177/0265407515611884 [DOI] [Google Scholar]
  40. Slonim G., Gur-Yaish N., Katz R. (2015). By choice or by circumstance? Stereotypes of and feelings about single people. Studia Psychologica, 57(1), 35–50. 10.21909/sp.2015.01.672 [DOI] [Google Scholar]
  41. Smith K. J., Victor C. (2019). Typologies of loneliness, living alone and social isolation, and their associations with physical and mental health. Ageing & Society, 39(8), 1709–1730. 10.1017/s0144686x18000132 [DOI] [Google Scholar]
  42. Snyder C. R. (1994). The psychology of hope: You can get there from here. Simon & Schuster [Google Scholar]
  43. Snyder C. R., Harris C., Anderson J. R., Holleran S. A., Irving L. M., Sigmon S. T., Harney P. (1991). The will and the ways: Development and validation of an individual-differences measure of hope. Journal of Personality and Social Psychology, 60(4), 570–585. 10.1037/0022-3514.60.4.570 [DOI] [PubMed] [Google Scholar]
  44. Snyder C. R., Sympson S. C., Ybasco F. C., Borders T. F., Babyak M. A., Higgins R. L. (1996). Development and validation of the state hope scale. Journal of Personality and Social Psychology, 70(2), 321–335. 10.1037/0022-3514.70.2.321 [DOI] [PubMed] [Google Scholar]
  45. Stickley A., Koyanagi A. (2016). Loneliness, common mental disorders and suicidal behavior: Findings from a general population survey. Journal of Affective Disorders, 197, 81-87. 10.1016/j.jad.2016.02.054. [DOI] [PubMed] [Google Scholar]
  46. Twenge J. M., Spitzberg B. H., Campbell W. K. (2019). Less in-person social interaction with peers among U.S. adolescents in the 21st century and links to loneliness. Journal of Social and Personal Relationships, 36(6), 1892–1913. 10.1177/0265407519836170 [DOI] [Google Scholar]
  47. Waite L. J., Gallagher M. (2001). The case for marriage: Why married people are happier, healthier, and better off financially. Crown Publishing Group [Google Scholar]
  48. Wang J., Mann F., Lloyd-Evans B., Ma R., Johnson S. (2018). Associations between loneliness and perceived social support and outcomes of mental health problems: A systematic review. BMC Psychiatry, 18(1), 1–16. 10.1186/s12888-018-1736-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Williams K. (2003). Has the future of marriage arrived? A contemporary examination of gender, marriage, and psychological well-being. Journal of Health and Social Behavior, 44(4), 470. 10.2307/1519794 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. World Health Organization (2022). United States: WHO coronavirus disease (COVID-19). https://covid19.who.int/region/amro/country/us [Google Scholar]
  51. Yarcheski A., Mahon N. E., Yarcheski T. J. (2011). Stress, hope, and loneliness in young adolescents. Psychological Reports, 108(3), 919–922. 10.2466/02.07.09.pr0.108.3.919-922 [DOI] [PubMed] [Google Scholar]
  52. Ye Z., Yang X., Zeng C., Wang Y., Shen Z., Li X., Lin D. (2020). Resilience, social support, and coping as mediators between COVID‐19‐related stressful experiences and acute stress disorder among college students in China. Applied Psychology: Health and Well‐Being, 12(4), 1074–1094. 10.1111/aphw.12211 [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Journal of Family Issues are provided here courtesy of SAGE Publications

RESOURCES