So Close and Yet So Irritating: Negative Relations and Implications for Well-being by Age and Closeness

So Close and Yet So Irritating: Negative Relations and Implications for Well-being by Age and... Abstract Objectives Negative social relationships are associated with poor health, chronic illness, and mortality. Yet, we know little about the dynamics of negative aspects of relationships within individual’s closest relationships over time, how those experiences vary by age, and the implications of those relationships for well-being. Method A total of 592 participants (ages 25–97; M = 57.5; 63.3% women) from the Social Relations Study completed monthly web surveys for up to 12 months. Each month they reported negative relationship quality with their three closest network members and multiple dimensions of well-being (positive affect, negative affect, self-rated health, and sleep quality). Results Multilevel models revealed older individuals reported less negativity in their relationships than younger people, but fewer age differences in the closest tie. Greater negative relationship quality predicted poor well-being (i.e., greater negative affect, sleep problems). Links between negative relations and well-being were less strong among older individuals; especially in the closest ties. Discussion Results were partially consistent with the strength and vulnerability integration (SAVI) model, which proposes fewer age-related improvements in emotion regulation when individuals are unable to avoid tensions. Despite feeling just as negative as younger individuals, older individuals may be more resilient to tensions in their closest relationships. Aging, Interpersonal tension, Negative relationship quality, Well-being Social relationships are key for multiple aspects of well-being, including psychological well-being, physical health, and survival. Indeed, social ties are often more highly associated with health than key health behaviors, including exercise, smoking, and body mass index (Holt-Lunstad, Smith, & Layton, 2010; House, Landis, & Umberson, 1988). Relationships, however, vary greatly in their positive and negative qualities. Negative aspects of relationships (e.g., irritations, demands) are generally more consequential for well-being than positive aspects (Newsom, Nishishiba, Morgan, & Rook, 2003; Rook, 2015), and change across the life span in ways that differ by the type of relationship. Parent–child ties, for example, become less negative over time, whereas relationships with spouses tend to become more negative as people age (Birditt, Jackey, & Antonucci, 2009). Further, research indicates that older adults are better able to regulate their emotional responses to interpersonal tensions than are younger adults (Birditt, Fingerman, & Almeida, 2005; Blanchard-Fields, 2007), especially in emotionally close relationships. Though negative relationship quality seems to vary by age and relationship type, it is unknown how age differences vary by relationship closeness. The present study examines negativity in close social ties and well-being using monthly web survey data from individuals ranging in age from young adulthood to old age. We specifically focused on negative quality relations with individuals’ three closest ties to understand whether age differences found in previous studies vary by relationship closeness. Theoretical Framework Negative aspects of relationships are defined by the extent to which they are irritating, demanding, critical, or get on one’s nerves. Research suggests that negative and positive aspects of relationships are not opposite ends of the same continuum, but represent two distinct dimensions of relationship quality (Fincham & Linfield, 1997; Uchino, 2004). We focus on negative qualities rather than positive because negativity often has greater variance, is more highly associated with well-being than positive dimensions of relationships (English & Carstensen, 2014; Rook, 2015), and varies significantly across the life span (Luong, Charles, & Fingerman, 2011). Life-span developmental theories, including socioemotional selectivity theory (SST) and the strength and vulnerability integration (SAVI) model, provide useful frameworks for understanding age differences in negative relations and their implications for well-being. According to SST, as people age, they perceive time as more limited. As a result, they become more motivated to achieve emotion focused goals (Carstensen, Isaacowitz, & Charles, 1999). Older individuals are more motivated to have emotionally meaningful relationships, and are less likely to attend to or remember negative information. SAVI emerged from SST theory and suggests that these age-related changes in negative quality relations only occur among individuals who are able to successfully avoid negative experiences (Charles, 2010). When tensions are difficult to avoid, there may be fewer age-related improvements in negative relationship quality and well-being. This study builds on these theoretical perspectives by examining age differences in negative relationship quality within the closest ties because such tensions are likely difficult to avoid. Feelings of negativity are common in the closest relationships, perhaps due in part to heightened emotions, close proximity, and/or frequent contact within these ties (Fingerman, Hay, & Birditt, 2004; Fung, Yeung, Li, & Lang, 2009; Uchino, Holt-Lunstad, Smith, & Bloor, 2004). As a consequence, it may be difficult for individuals to avoid tension and negativity in the closest relationships, especially as they age and become more invested in maintaining emotionally meaningful ties. Although older adults may experience negativity in their closest ties, the implications of negative relationship quality for well-being at this stage of the life span may be attenuated due to improved emotion regulation skills. Older adults report that interpersonal tensions are less stressful than do younger people and are more likely to use passive emotion regulation strategies such as avoidance that may preserve their well-being (Birditt et al., 2005). Indeed, older adults are most likely to regulate the expression of negative emotion in their closest and most emotionally salient ties (Blanchard-Fields, 2007; Emery & Hess, 2011). Thus, older adults may be more emotionally resilient to tensions within their closest ties due to age-related gains in the ability to regulate their emotional reactions to negative social interactions. Age Differences in Negative Relationship Quality Consistent with SST and the SAVI model, older individuals often report less negativity in their relationships than do younger people but the specific age differences vary by relationship type (Luong et al., 2011). For example, researchers often find that older adults rate ties with family and friends as less negative than younger adults, whereas negative relations in the spousal tie either show no age differences or increase over time (Akiyama, Antonucci, Takahashi, & Langfahl, 2003; Birditt et al., 2009; Walen & Lachman, 2000). As such, there may be fewer declines in negative relationship quality in the spousal tie because this relationship involves greater closeness and more difficulty with avoiding tensions relative to other ties. Notably, however, individuals do not universally have the same types of relationships across the life span. One way of addressing this issue is to examine closeness of ties rather than the type of social partner. English and Carstensen (2014) considered whether negative emotions toward social network members varied by age and closeness. Consistent with SST, but inconsistent with the SAVI model, they found that age was associated with lower negativity regarding social network members irrespective of closeness. The current study extends the literature by examining the experience of negativity within individuals’ three closest social relationships on a monthly basis. Negative Relationships and Well-being Negative aspects of relationships are linked with critical indicators of well-being across adulthood including psychological well-being, sleep, and physical health. These links may vary by both relationship closeness and age, and so it is critical to consider how these characteristics interact to shape well-being over the adult life span. Psychological Well-being Negative aspects of relationships tend to be more highly associated with psychological well-being outcomes than positive aspects of relationships (Rook, 2015). Rook (1984, 2001) found negative aspects of social ties, especially when chronic, are associated with increased psychological distress, depression, and decreased daily mood. Similarly, English and Carstensen (2014) found that negativity in social networks was associated with greater negative affect on a daily basis. There is conflicting evidence regarding if and how these links vary by age. Consistent with the SAVI model, older adults report better well-being when they are able to avoid irritations in their social ties but report similar or worse well-being when they are unable to avoid conflict. For example, Charles, Piazza, Luong, and Almeida (2009) and Birditt (2014) found that older adults report less negative affect than younger adults on days in which they avoided arguments or tensions, however there were no age differences in negative affect on days in which they reported arguments or tensions. Research that has examined close relationships (e.g., romantic partners, children) shows that older adults may be less adversely affected by negativity in their closest ties. Stafford, McMunn, Zaninotto, and Nazroo (2011), for instance, found that negative relationship quality with parents and children was less strongly associated with depressive symptoms among individuals aged 70 years and older compared with those aged 50–70 years. In the present study, we examine both positive and negative affect to gain a more nuanced understanding of links between negative relationship quality and well-being. Sleep Sleep is important to examine because poor sleep is associated with diminished physical and mental health (Irwin, 2015). Furthermore, sleep problems increase with age (Rodriguez, Dzierzewski, & Alessi, 2015). Researchers have found links between negative aspects of relationships and sleep quality. Individuals who report more strained family ties, for example, also report greater sleep problems (Ailshire & Burgard, 2012). Likewise, individuals who report greater negative quality relations with their spouse report more troubled sleep (Chen, Waite, & Lauderdale, 2015). These links may also vary by age but there is a lack of research in this area. Physical Health Researchers have established that negative aspects of relationships are linked with multiple indicators of physical health including biological indicators such as hypertension and increased allostatic load (Seeman, Gruenewald, Cohen, Williams, & Matthews, 2014; Sneed & Cohen, 2014) as well as poorer self-rated health (Croezen et al., 2012; Newsom, Mahan, Rook, & Krause, 2008; Walen & Lachman, 2000). Studies that have examined specific close ties such as relationships with children and spouses have also found these effects. For example, negative ties with children are associated with increased physical impairments over time (McGarrigle & Layte, 2015). Similarly, negative aspects of the marital relationship (e.g., negative or hostile behaviors; overall strain) are linked with poorer self-rated health and greater functional limitations (Ryan, Wan, & Smith, 2014). Studies show that the links between negative social relations and physical health are stronger among older adults (Hakulinen et al., 2016) whereas others found no age differences (Walen & Lachman, 2000). Yet prior research has not examined whether age differences in links between negative relationship quality and multiple well-being indicators vary across level of relationship closeness. Present Study Using monthly survey data that includes repeated measures of negative relationship quality, this study builds on current theoretical and empirical work by addressing two research questions: (a) Does negative relationship quality reported on a monthly basis vary by age and closeness? (b) Is negative relationship quality associated with multiple dimensions of well-being, and do those links vary by age and closeness? Consistent with the SAVI model, we predicted that older individuals would report lower negative relationship quality than younger individuals but that there would be fewer age differences in negative relationship quality ratings in the closest tie compared to ties that are less close. However, because older adults are better able to regulate their emotions in close relationships, we predicted that older individuals would show fewer links between negative relationship quality and well-being, especially in their closest ties. Method The participants are from the longitudinal Social Relations Study (SRS; Antonucci, PI). All waves of data were collected by the Survey Research Operations unit at the Institute for Social Research. The Wave 1 SRS sample was drawn from the tri-county Detroit metropolitan area. A two-stage area probability sample design was used to select an equal probability sample of housing units. The design included an oversampling for people aged 60 years and older. Field interviewers visited each selected housing unit, completed a household roster, and selected a random adult for face-to-face interviews (N = 1,703; response rate = 72% in 1992). Wave 2, completed in 2005, using both telephone and face-to-face interviewing, included 1,076 of the original participants with 320 identified as deceased (N = 1,076, follow-up response rate = 78%). Wave 3, completed in 2015, using telephone interviews included 720 of the original participants with 63 deceased, 27 disabled and 2 incarcerated (follow-up response rate = 73%). Research indicates few data quality differences using face to face versus phone (Herzog & Rodgers, 1988; Soldo, Hurd, Rodgers, & Wallace, 1997). See Table 1 for a description of the Wave 3 sample used in the present study. Table 1. Description of Sample M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) Note: CNM = Core network member. View Large Table 1. Description of Sample M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) Note: CNM = Core network member. View Large Participants completed a social network diagram in Wave 3 in which they were asked to list the people they felt closest to in order of closeness in three concentric circles (Kahn & Antonucci, 1980). The people respondents could not imagine life without are placed in the first circle followed by those that are less close in the second and third circles. After completing the interview, Wave 3 participants were invited to provide contact information for the first three people listed in their social networks. These network members (referred to hereafter as the core network sample) were then invited to participate in the study. After completing their interviews, both the panel and the core network sample were asked to complete monthly web surveys. The analytic sample includes 362 panel respondents and 230 of their core network members who completed at least one web survey. There were a total of 2,203 web surveys completed by panel respondents and a total of 1,367 web surveys completed by core network members. A description of the analytic sample is provided in Table 1. An analysis was conducted to examine whether individuals who completed the web surveys were different from those who did not complete web surveys. We examined whether age, respondent type (panel vs core), gender, marital status, having children, education, self-rated health, and depressive symptoms predicted completing one or more web surveys versus none in a logistic regression. Findings revealed that older respondents, core network members, females, those who were married, those without children, and those with higher education were more likely to complete at least one web survey. Panel respondents received $25 and core network members received $20 dollars for participating in the main interview. All respondents then received $5 for each monthly survey they completed; an additional $5 incentive if the respondent completed 6 web surveys, an additional $10 if the respondent completed 9, and an additional $15 if the respondent completed all 12. The web survey was offered over 15 months (October 1, 2014 to December 10, 2015). The respondents who completed their baseline interviews between July 2014 and December 2014 were eligible for 12 monthly surveys. To ensure that participants had at least 6 months possible to complete surveys, the decision was made to stop conducting additional web surveys starting in May 2015 and participants received the maximum allowable money if they completed all the surveys available to them. Measures Negative relationship quality To assess the negative qualities of their three closest network members, participants completed four widely used, reliable, and validated items (Birditt, Newton, Cranford, & Ryan, 2015; Birditt, Newton, Cranford, & Webster, 2016; Schuster, Kessler, & Aseltine Jr, 1990; Walen & Lachman, 2000): gets on my nerves, makes too many demands, lets me down when I am counting on them, and criticizes me on a scale from 1 (disagree) to 5 (agree). A mean of the items was created for each network member separately. All scale reliability alphas were computed using the method outlined by Cranford et al. (2006). For each scale, a between-person alpha (which treats month of completion as random), as well as a within person alpha, was calculated. The between-person alpha for negative relations with core network member 1, 2, and 3 ranged from .70 to .74 and the within-person alpha (which reflects the reliabilities for detecting systematic change over time) ranged from .56 to .59. The within person reliabilities were somewhat lower than Cranford et al.’s within person alphas for daily mood (.62–.88). This difference may be due to variation in constructs; as relationship quality measured at monthly intervals is likely more stable than daily mood. Age Participants reported their date of birth and four categories were created including: young adults (25–39), middle age (40–59), young-old (60–79), and oldest- old (80–97). Closeness Each network member was coded in terms of the order in which they were nominated by the respondent with 1 being the closest tie followed by network members 2 and 3. Well-being Each month participants rated their emotional and physical well-being. Negative and positive affect items were from the National Study of Daily Experiences (Almeida 1996–1997). Negative affect included 14 items such as feeling ashamed, nervous, and afraid. Participants rated the extent to which they experienced each emotion in the past month from 1 (not at all) to 5 (extremely). The between person alpha was .75 and the within-person alpha was .79. Positive affect included 11 items such as feeling attentive, cheerful, and extremely happy. The between-person alpha was .71 and the within-person alpha was .82. Self-rated health was rated from 1 (poor) to 5 (excellent). Sleep problems included four items from the Midlife in the United States Survey (MIDUS) regarding sleep quality over the past month (e.g., have trouble falling asleep, wake up during the night (Stephan, Sutin, Bayard, & Terracciano, 2017). These items were rated from 1 (never) to 5 (almost always). The between-person alpha was .75 and the within-person alpha was .64. Covariates We controlled for whether the respondent was a panel respondent or core network member (aka respondent type), relationship type, the month of survey, gender, marital status, whether they had a child, years of education, and depressive symptoms. Panel was coded as 1 and core network members as 0. Month of survey was coded as 1 through 12. Relationship type included 6 categories: 1 (spouse/partner), 2 (child), 3(parent), 4 (sibling), 5 (step/extended family), and 6 (friend/peripheral tie) and spouse/partner was the comparison group. Gender was coded as 1 (man) and 2 (woman). Marital status was coded as 0 (not married) or 1 (married). Whether participants had a child was coded as 1(yes) or 0 (no). Years of education coded from 1 (first grade) to 17 (more than four years of college). The 20-item Center for Epidemiological Studies Depression (CESD) scale (Radloff, 1977) was administered to assess depressive symptoms. Participants reported their experience of depressive symptoms in the past week from 0 (rarely/none of the time) to 3 (most of the time). The items are summed to create a total score (Cronbach’s α = .90), with higher scores representing more frequent depressive symptoms. Analysis Strategy To examine whether negative ties varied by age group, we estimated a multilevel model in SAS Proc Mixed. The model accounted for four levels of nested data. Social network was the upper level because principal respondents may have had up to three network members who participated, the participant was the third level, core network member number (1–3) the second level because each respondent could report on three network members, and month was the first level because each core network member could include up to 12 months of negative quality ratings. Negative relationship quality was the outcome and age group, closeness (i.e., core network number/position), and the age group by closeness interaction were entered as predictors. Age group was entered as a categorical variable with three dummy coded variables and the oldest-old age group was the reference group. The models controlled for relationship type, respondent type (e.g., panel or core network member), month of survey, gender, marital status, parental status, years of education, and depressive symptoms. Continuous variables were centered on the participant’s mean. Significant interactions were explored with tests of simple slopes and comparisons of simple slopes with a Bonferroni correction (i.e., adjustment of the p value for the 66 comparisons). To test whether there were associations between negative relationships and well-being and whether those links varied by age group, we estimated a series of multilevel models with each well-being indicator as the outcome (positive affect, negative affect, sleep problems, and self-rated heath). These models included three levels in which social network was the upper level, participant was the second level, and month was the lowest level. These models were estimated separately for each network member (first, second, third). In each model, the predictors included negative relationship quality, age group, and the interaction between negative relationship quality and age group. Negative relationship quality was group mean centered on respondents’ average negative quality with each network member. Models included the covariates described above as well as well-being in the previous month. Continuous variables were centered (either on the grand mean or the participant’s mean). Significant interactions were explored with tests of simple slopes and comparisons of simple slopes with a Bonferroni correction (i.e., adjustment of the p value for the six comparisons). Results Description Participants reported that their relationships were moderately negative with average ratings of 2.01 (SD = 1.01), 1.85 (SD = 0.94), and 1.82 (SD = 0.95) for core network members 1 through 3, respectively (Table 1). As presented in Supplementary Table 1, core network member 1 was most likely to be a spouse/partner followed by a child and a parent. Core network member 2 was most likely to be a child followed by a parent and a sibling. Core network member 3 was most likely to be a child followed by a sibling and a friend. The composition of the network members also varied by age group such that older individuals, for example, did not list parents. There was significant variance within participants over time in their reports of negative relationship quality. We provide an illustrative figure (Supplementary Figure 1) to show negative relationship quality with network member 1 by month among participants who completed all 12 of their web surveys. Each line represents a different participant and the figure shows that there is a great amount of both within-person and between-person variation in the reports of negative relationship quality over the 12 months. Unconditional models were estimated to determine the amount of within- and between-person variance in negative relationship quality and well-being. For negative relationship quality, 18.2% of the variance was between networks, 14.5% was between respondents, 39.0% between core network members, and 28.3% of the variance was within respondents. For negative affect, 15.8% of the variance was between networks, 59.4% was between respondents, and 24.8% of the variance was within respondents. For positive affect, 17.8% of the variance was between networks, 52.7% was between respondents, and 29.5% of the variance was within respondents. For sleep problems, 5.4% of the variance was between networks, 69.3% was between respondents, and 25.3% of the variance was within respondents. For self-rated health, 7.7% of the variance was between networks, 51.7% was between respondents, and 40.5% of the variance was within respondents. A covariate only model was estimated to assess variation in negative relationship quality by relationship type, respondent type, month of survey, gender, marital status, parental status, years of education, and depressive symptoms. As predicted, individuals reported greater negative relationship quality with spouse than with children (b = −.44, SE = .05, p < .001), parents (b = −.20, SE = .06, p < .01), siblings (b = −.41, SE = .07, p < .001), other family (b = −.67, SE = .08, p < .001), and friend/peripheral ties (b = −.63, SE = .08, p < .001). Individuals also reported greater negative relationship quality when they reported greater depressive symptoms (b = .02, SE = .00, p < .001). Covariate only models were estimated to assess variation in well-being by respondent type, month of survey, gender, marital status, parental status, years of education, depressive symptoms, and well-being in the previous month. With the exception of self-rated health, well-being in the previous month was positively associated with well-being in the current month. These results are not shown due to space limitations. Negative affect was negatively associated with the month of the survey (b = −.01, SE = .00, p < .01), positively related to depressive symptoms (b = .04, SE = .00, p < .001). Positive affect was negatively associated with depressive symptoms (b = −.04, SE = .00, p < .001). Sleep problems were negatively associated with the month of the survey (b = −.01, SE = .00, p < .001), positively related to depressive symptoms (b = .05, SE =. 00, p < .001). Self-rated health was negatively associated with depressive symptoms (b = −.04, SE = .00, p < .01). Does Negative Relationship Quality Vary by Age and Closeness? Models estimated whether negative relationship quality with core network members varied by age group (Table 2). Models revealed that negativity with core networks varied significantly by age and closeness, and that there was also a significant age by closeness interaction (Figure 1). Consistent with our hypothesis, there were no age differences in negative relationship quality with the closest tie (network member 1). In contrast, oldest-old participants reported their relationships with network members 2 and 3 were less negative than middle-aged and young-adult participants. Also, young-old participants reported their relationship with network member 3 was less negative than middle-aged participants. Table 2. Multilevel Model Predicting Negative Relationship Quality as a Function of Age Group and Closeness Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Note: CNM = Core network member; Model controlled for Panel versus CNM, Survey month, gender, married, children, education, CESD, and relationship to CNM. *p < .05, **p < .01, ***p < .001. View Large Table 2. Multilevel Model Predicting Negative Relationship Quality as a Function of Age Group and Closeness Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Note: CNM = Core network member; Model controlled for Panel versus CNM, Survey month, gender, married, children, education, CESD, and relationship to CNM. *p < .05, **p < .01, ***p < .001. View Large Figure 1. View largeDownload slide Negative relationship quality by age group and closeness. Figure 1. View largeDownload slide Negative relationship quality by age group and closeness. Are Negative Relations Associated With Well-being Differently by Age and Closeness? Next, multilevel models assessed whether negative relationship quality with each network member was associated with well-being and whether there were significant interactions between age and negative relationship quality predicting well-being. Negative affect When individuals reported greater negative relationship quality they also reported greater negative affect during the same month (Model 1; Supplementary Table 2). There was a significant interaction between negative relationship quality with network member 1 and age group when predicting negative affect (Model 2; Supplementary Table 2). Negative quality with the closest network member was associated with increased negative affect among all four age groups but the strength of the association varied by age (Figure 2). Comparisons of the slopes revealed that the link between negative relationship quality with network member 1 and negative affect was greater among young adults compared to middle-aged (contrast = .11, SE = .03, p < .01) and young-old adults (contrast = .10, SE = .03, p < .05) (Figure 1). The interaction between negative quality with less close network members (i.e., network members 2 and 3) and age predicting negative affect was not significant. This finding indicates that older adults (with the exception of the oldest-old) appeared better able to regulate the implications of negative relationship quality on negative affect only in the closest tie but not in the less close ties which was consistent with our hypothesis. Figure 2. View largeDownload slide Negative affect as a function of relationship quality with core network member 1 and age group. Figure 2. View largeDownload slide Negative affect as a function of relationship quality with core network member 1 and age group. Positive affect Individuals who reported greater negative relationship quality reported lower positive affect during the same month (Model 1; Supplementary Table 3). There was a significant interaction between negative relationship quality with network members 1 and 2 and age group predicting positive affect. Greater negative quality relations with network member 1 predicted lower positive affect among all age groups with the exception of the oldest-old (Figure 3). Comparison of the slopes showed that the association was stronger among young adults compared to young-old adults (contrast = .12, SE = .04, p < .05). Greater negative quality relations with network member 2 predicted lower positive affect among young adults and oldest-old adults (Supplementary Figure 3). Comparisons of the slopes with a showed that the association between negative quality relations and positive affect was greater among oldest-old adults than among middle-aged and young-old adults (contrast = .19, SE = .07, p < .05; contrast = .17, SE = .07, p < .05, respectively). Overall these findings showed that there were more age differences in the closest tie which is consistent with the hypothesis that older individuals (with the exception of the oldest-old) may be better able to regulate their reactions to their closest ties than younger individuals. Figure 3. View largeDownload slide Positive affect as a function of negative relationship quality with core network member 1 and age group. Figure 3. View largeDownload slide Positive affect as a function of negative relationship quality with core network member 1 and age group. Sleep problems Individuals who reported greater negative relationship quality reported more sleep problems (Model 1; Supplementary Table 4). There was a significant interaction between negative relationship quality with network member 3 and age group when predicting sleep problems. More negative relations with network member 3 predicted greater sleep problems among young adults and middle-aged adults but not among young-old or oldest-old adults (Supplementary Figure 4). Comparisons of the slopes with a revealed the association was greater among young adults than among young-old adults (contrast = .17, SE = .05, p < .01). These finding only provide partial support of our hypothesis. Self-rated health The association between negative quality relations and self-rated health was not significant. There was a significant interaction between negative relationship quality with network member 1 and age group predicting self-rated health (Model 2; Supplementary Table 5). Greater negative relations with network member 1 predicted worse self-rated health among young adults but were not predictive of self-rated health among the other three age groups (Supplementary Figure 5). Comparisons of slopes showed that the association was stronger among young adults compared to the middle-aged adults (contrast = .18, SE = .07, p < .05). Again this finding was consistent with the hypothesis that there would be fewer age differences in the closest tie. Post hoc Models Because the core network members varied in terms of relationship types, we estimated all of the models again to address whether findings varied by relationship type. We collapsed relationship type into spouse, parent-child tie, and all other in order to account for variation in the types of relationships by age group. First, we estimated models predicting negative relationship quality as a function of relationship type, closeness, and age group to test whether the closeness by age finding varied by type of relationship. There was no significant three-way interaction indicating there was not significant variation by type of relationship. Next, we estimated models to assess the effects of negative relationship quality on well-being outcomes by core network member and relationship type. There were no significant interactions between negative quality and relationship type predicting well-being outcomes (negative affect, sleep, physical health) with one exception. When predicting positive affect with negative quality with the closest network member (network member 1) the interaction between negative quality, relationship type, and age revealed the age difference was significant for parent–child and other ties but not the spousal relationship. Thus, the spousal tie may incur unique effects. Nevertheless, findings generally showed that the closeness of the tie was independently associated with negative relationship quality and its implications for well-being beyond the type of relationship partner. Discussion The present study examined monthly reports of negative relationship quality regarding individuals’ three closest relationships among a life-span sample. Interestingly, findings only partially supported the SAVI model, which suggests fewer age related improvements in emotion regulation when conflict or stress is unavoidable. Although older people perceived their closest relationship to be just as irritating as younger individuals, they appear to be better able to regulate the effects of those ties on their well-being. Variations in Negative Relationship Quality by Age and Closeness Age differences in negative relationship quality varied by relationship closeness. Consistent with the SAVI model and our hypothesis, there were fewer age differences in reports of negative relationship quality in the closest tie compared to relationships that were less close. It is possible that there are fewer age differences in the closest tie because having negative interactions in the closest ties is less avoidable. It is also more common to have simultaneously positive and negative relationships with people who are considered closest (Fingerman et al., 2004). This is consistent with the literature showing that there are fewer age-related decreases in the negative aspects of the spousal tie, which is often the closest tie with the most contact, compared to relationships with children and with friends (Birditt et al., 2009). This study extends prior research by showing that there may be fewer age differences in the negative aspects of individuals’ closest relationships regardless of the relationship type (e.g., spouse, child). Age differences in reports of negative relationship quality were in the expected direction in the relationships that were less close suggesting that older adults are better able to regulate the perception of negative relationship quality in relationships that may provide greater opportunities to use avoidance. Variations in the Negative Relations-Well-being Link by Age and Closeness Negative relationship quality predicted poorer well-being (greater negative affect, lower positive affect, and poorer sleep), which is consistent with the previous literature (Ailshire & Burgard, 2012; English & Carstensen, 2014), but those links varied by age and relationship closeness. Inconsistent with the SAVI model (but consistent with SST), older individuals showed fewer negative implications of negative ties for well-being when those negative experiences were in the closest ties compared to the less close ties. As predicted, these findings suggest that when older people experience negative quality relations in their closest tie, their well-being is less impacted by those negative relations compared to young adults. With regards to the closest network member there were age differences in the link between negative relationship quality and negative affect, positive affect, and physical health. Young adults who reported greater negative relationship quality reported greater negative affect, lower positive affect, and poorer health compared to middle-aged and/or young-old adults. However, oldest-old adults did not show less reactivity compared to younger age groups. Findings regarding negative quality in less close network members and well-being were not as consistent. The link between negative relationship quality with core network member 2 and positive affect was less pronounced among older adults than younger people. Further, the link between negative relationship quality with core network member 3 and sleep problems was lower among older adults than among younger people. Thus, the age differences were in the expected direction with older individuals being less detrimentally affected by negative relationship quality. However, there was more evidence of age-related improvements in the closest tie. It is possible that as people age they use more adaptive types of emotion regulation strategies in their closest ties (Blanchard-Fields, 2007), which in turn may differentially impact their well-being. In their closest relationships, older individuals tend to use avoidant coping and expressive regulation strategies (e.g., emotional suppression) that are employed after the emotion is experienced and these strategies are typically more successful in preserving their well-being (Birditt, 2014; Birditt et al., 2005; Charles et al., 2009). Older individuals are also less likely to use direct destructive strategies such as insults and yelling. Thus, while older adults still find their closest ties irritating, they are able to use more effective strategies than younger adults to offset the detrimental implications of negativity in those ties, and thus their well-being is less impacted. However, further research is needed to understand the specific mechanisms accounting for these effects. Overall, there was more evidence of links between negative relationship quality and psychological well-being (negative and positive affect) than between negative relationship quality and the outcomes of sleep and physical health. Further, there was more evidence of age-related improvements in links between negative quality and well-being with psychological well-being than with sleep and physical health. It is possible that age-related improvements in emotion regulation strategies have a greater impact on psychological well-being on a monthly basis, whereas adverse consequences for physical health and sleep may take longer to develop. It is also most likely more feasible to regulate the impact of relationships on emotional health than it is to regulate the impact of relationships on health and sleep. Directions for Future Research There are limitations to this study that should be addressed in future research. First, the range of web surveys that participants were invited to participate in varied from 6 to 12 surveys. The models did control for the month of participation, which did not appear to affect findings, yet future studies would benefit from ensuring all participants completed the same number of web surveys. In addition, the sample that completed web surveys differed from those who did not complete these surveys in key ways (e.g., the web sample was more educated and older). Future studies should include more representative samples to assess the generalizability of the findings. Further, the measure of negative relationship quality included only four items, and future research may benefit from a more comprehensive assessment. The data also do not include ratings of relationship quality with individuals beyond the three closest network members. Examining whether the age difference in relationship quality varies by closeness across the full range of network members would enhance our understanding of the ways that age influences the experience of negative relationships. Future research should also examine more objective indicators of well-being. For instance, previous studies have shown important links between negative aspects of relationships and biological indicators including blood pressure, cortisol, and waist circumference (Birditt, Manalel, Kim, Zarit, & Fingerman, 2017; Sneed & Cohen, 2014). In addition, we acknowledge that the examination of negativity in close relationships is similar to the concept of ambivalence, which has been defined as simultaneous positive and negative feelings about a social partner (Fingerman et al., 2004; Fung et al., 2009; Uchino et al., 2004). According to Uchino and colleagues, ambivalence is particularly detrimental for well-being because ambivalent relationships can be stressful and unpredictable. Our findings suggest that, although simultaneous feelings of closeness and negativity are common among older adults, it is not necessarily associated with poorer well-being. Future work should consider how perceptions of negativity in close relationships are similar to or different from measures of ambivalence that are typically assessed in the literature (i.e., feeling torn; concurrent positive and negative sentiments). The present study makes a significant contribution to the literature by examining negative relationship quality and well-being over time on a short term monthly basis, rather than over years or days. This type of design allowed us to examine how short-term variations in negative relationship quality are associated with changes in well-being by controlling for well-being in the previous month. This study is also novel because it examined relationship quality with identified close others rather than focusing only on specific relationship types. Study findings revealed that older individuals appear to experience negative relationship quality differently than younger individuals. However, these age differences varied by relationship closeness. Findings imply that there may be age-related improvements in emotion regulation in the context of social ties that vary by relationship closeness. We hope that this study inspires future research regarding the complexity of negative relationship quality across the adult life span. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences online. Funding This study was funded by a grant from the National Institute on Aging (Antonucci, PI; AG045423). C. A. Polenick was supported by training grant T32 MH073553-11 from the National Institute of Mental Health (Stephen J. Bartels, Principal Investigator). Conflict of Interest None reported. Acknowledgment We would like to thank Angela Turkelson for her assistance with the analysis. A previous version of this paper was presented at the International Association of Gerontology and Geriatrics (IAGG) conference in July 2017. References Ailshire , J. A. , & Burgard , S. A . ( 2012 ). 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Abstract

Abstract Objectives Negative social relationships are associated with poor health, chronic illness, and mortality. Yet, we know little about the dynamics of negative aspects of relationships within individual’s closest relationships over time, how those experiences vary by age, and the implications of those relationships for well-being. Method A total of 592 participants (ages 25–97; M = 57.5; 63.3% women) from the Social Relations Study completed monthly web surveys for up to 12 months. Each month they reported negative relationship quality with their three closest network members and multiple dimensions of well-being (positive affect, negative affect, self-rated health, and sleep quality). Results Multilevel models revealed older individuals reported less negativity in their relationships than younger people, but fewer age differences in the closest tie. Greater negative relationship quality predicted poor well-being (i.e., greater negative affect, sleep problems). Links between negative relations and well-being were less strong among older individuals; especially in the closest ties. Discussion Results were partially consistent with the strength and vulnerability integration (SAVI) model, which proposes fewer age-related improvements in emotion regulation when individuals are unable to avoid tensions. Despite feeling just as negative as younger individuals, older individuals may be more resilient to tensions in their closest relationships. Aging, Interpersonal tension, Negative relationship quality, Well-being Social relationships are key for multiple aspects of well-being, including psychological well-being, physical health, and survival. Indeed, social ties are often more highly associated with health than key health behaviors, including exercise, smoking, and body mass index (Holt-Lunstad, Smith, & Layton, 2010; House, Landis, & Umberson, 1988). Relationships, however, vary greatly in their positive and negative qualities. Negative aspects of relationships (e.g., irritations, demands) are generally more consequential for well-being than positive aspects (Newsom, Nishishiba, Morgan, & Rook, 2003; Rook, 2015), and change across the life span in ways that differ by the type of relationship. Parent–child ties, for example, become less negative over time, whereas relationships with spouses tend to become more negative as people age (Birditt, Jackey, & Antonucci, 2009). Further, research indicates that older adults are better able to regulate their emotional responses to interpersonal tensions than are younger adults (Birditt, Fingerman, & Almeida, 2005; Blanchard-Fields, 2007), especially in emotionally close relationships. Though negative relationship quality seems to vary by age and relationship type, it is unknown how age differences vary by relationship closeness. The present study examines negativity in close social ties and well-being using monthly web survey data from individuals ranging in age from young adulthood to old age. We specifically focused on negative quality relations with individuals’ three closest ties to understand whether age differences found in previous studies vary by relationship closeness. Theoretical Framework Negative aspects of relationships are defined by the extent to which they are irritating, demanding, critical, or get on one’s nerves. Research suggests that negative and positive aspects of relationships are not opposite ends of the same continuum, but represent two distinct dimensions of relationship quality (Fincham & Linfield, 1997; Uchino, 2004). We focus on negative qualities rather than positive because negativity often has greater variance, is more highly associated with well-being than positive dimensions of relationships (English & Carstensen, 2014; Rook, 2015), and varies significantly across the life span (Luong, Charles, & Fingerman, 2011). Life-span developmental theories, including socioemotional selectivity theory (SST) and the strength and vulnerability integration (SAVI) model, provide useful frameworks for understanding age differences in negative relations and their implications for well-being. According to SST, as people age, they perceive time as more limited. As a result, they become more motivated to achieve emotion focused goals (Carstensen, Isaacowitz, & Charles, 1999). Older individuals are more motivated to have emotionally meaningful relationships, and are less likely to attend to or remember negative information. SAVI emerged from SST theory and suggests that these age-related changes in negative quality relations only occur among individuals who are able to successfully avoid negative experiences (Charles, 2010). When tensions are difficult to avoid, there may be fewer age-related improvements in negative relationship quality and well-being. This study builds on these theoretical perspectives by examining age differences in negative relationship quality within the closest ties because such tensions are likely difficult to avoid. Feelings of negativity are common in the closest relationships, perhaps due in part to heightened emotions, close proximity, and/or frequent contact within these ties (Fingerman, Hay, & Birditt, 2004; Fung, Yeung, Li, & Lang, 2009; Uchino, Holt-Lunstad, Smith, & Bloor, 2004). As a consequence, it may be difficult for individuals to avoid tension and negativity in the closest relationships, especially as they age and become more invested in maintaining emotionally meaningful ties. Although older adults may experience negativity in their closest ties, the implications of negative relationship quality for well-being at this stage of the life span may be attenuated due to improved emotion regulation skills. Older adults report that interpersonal tensions are less stressful than do younger people and are more likely to use passive emotion regulation strategies such as avoidance that may preserve their well-being (Birditt et al., 2005). Indeed, older adults are most likely to regulate the expression of negative emotion in their closest and most emotionally salient ties (Blanchard-Fields, 2007; Emery & Hess, 2011). Thus, older adults may be more emotionally resilient to tensions within their closest ties due to age-related gains in the ability to regulate their emotional reactions to negative social interactions. Age Differences in Negative Relationship Quality Consistent with SST and the SAVI model, older individuals often report less negativity in their relationships than do younger people but the specific age differences vary by relationship type (Luong et al., 2011). For example, researchers often find that older adults rate ties with family and friends as less negative than younger adults, whereas negative relations in the spousal tie either show no age differences or increase over time (Akiyama, Antonucci, Takahashi, & Langfahl, 2003; Birditt et al., 2009; Walen & Lachman, 2000). As such, there may be fewer declines in negative relationship quality in the spousal tie because this relationship involves greater closeness and more difficulty with avoiding tensions relative to other ties. Notably, however, individuals do not universally have the same types of relationships across the life span. One way of addressing this issue is to examine closeness of ties rather than the type of social partner. English and Carstensen (2014) considered whether negative emotions toward social network members varied by age and closeness. Consistent with SST, but inconsistent with the SAVI model, they found that age was associated with lower negativity regarding social network members irrespective of closeness. The current study extends the literature by examining the experience of negativity within individuals’ three closest social relationships on a monthly basis. Negative Relationships and Well-being Negative aspects of relationships are linked with critical indicators of well-being across adulthood including psychological well-being, sleep, and physical health. These links may vary by both relationship closeness and age, and so it is critical to consider how these characteristics interact to shape well-being over the adult life span. Psychological Well-being Negative aspects of relationships tend to be more highly associated with psychological well-being outcomes than positive aspects of relationships (Rook, 2015). Rook (1984, 2001) found negative aspects of social ties, especially when chronic, are associated with increased psychological distress, depression, and decreased daily mood. Similarly, English and Carstensen (2014) found that negativity in social networks was associated with greater negative affect on a daily basis. There is conflicting evidence regarding if and how these links vary by age. Consistent with the SAVI model, older adults report better well-being when they are able to avoid irritations in their social ties but report similar or worse well-being when they are unable to avoid conflict. For example, Charles, Piazza, Luong, and Almeida (2009) and Birditt (2014) found that older adults report less negative affect than younger adults on days in which they avoided arguments or tensions, however there were no age differences in negative affect on days in which they reported arguments or tensions. Research that has examined close relationships (e.g., romantic partners, children) shows that older adults may be less adversely affected by negativity in their closest ties. Stafford, McMunn, Zaninotto, and Nazroo (2011), for instance, found that negative relationship quality with parents and children was less strongly associated with depressive symptoms among individuals aged 70 years and older compared with those aged 50–70 years. In the present study, we examine both positive and negative affect to gain a more nuanced understanding of links between negative relationship quality and well-being. Sleep Sleep is important to examine because poor sleep is associated with diminished physical and mental health (Irwin, 2015). Furthermore, sleep problems increase with age (Rodriguez, Dzierzewski, & Alessi, 2015). Researchers have found links between negative aspects of relationships and sleep quality. Individuals who report more strained family ties, for example, also report greater sleep problems (Ailshire & Burgard, 2012). Likewise, individuals who report greater negative quality relations with their spouse report more troubled sleep (Chen, Waite, & Lauderdale, 2015). These links may also vary by age but there is a lack of research in this area. Physical Health Researchers have established that negative aspects of relationships are linked with multiple indicators of physical health including biological indicators such as hypertension and increased allostatic load (Seeman, Gruenewald, Cohen, Williams, & Matthews, 2014; Sneed & Cohen, 2014) as well as poorer self-rated health (Croezen et al., 2012; Newsom, Mahan, Rook, & Krause, 2008; Walen & Lachman, 2000). Studies that have examined specific close ties such as relationships with children and spouses have also found these effects. For example, negative ties with children are associated with increased physical impairments over time (McGarrigle & Layte, 2015). Similarly, negative aspects of the marital relationship (e.g., negative or hostile behaviors; overall strain) are linked with poorer self-rated health and greater functional limitations (Ryan, Wan, & Smith, 2014). Studies show that the links between negative social relations and physical health are stronger among older adults (Hakulinen et al., 2016) whereas others found no age differences (Walen & Lachman, 2000). Yet prior research has not examined whether age differences in links between negative relationship quality and multiple well-being indicators vary across level of relationship closeness. Present Study Using monthly survey data that includes repeated measures of negative relationship quality, this study builds on current theoretical and empirical work by addressing two research questions: (a) Does negative relationship quality reported on a monthly basis vary by age and closeness? (b) Is negative relationship quality associated with multiple dimensions of well-being, and do those links vary by age and closeness? Consistent with the SAVI model, we predicted that older individuals would report lower negative relationship quality than younger individuals but that there would be fewer age differences in negative relationship quality ratings in the closest tie compared to ties that are less close. However, because older adults are better able to regulate their emotions in close relationships, we predicted that older individuals would show fewer links between negative relationship quality and well-being, especially in their closest ties. Method The participants are from the longitudinal Social Relations Study (SRS; Antonucci, PI). All waves of data were collected by the Survey Research Operations unit at the Institute for Social Research. The Wave 1 SRS sample was drawn from the tri-county Detroit metropolitan area. A two-stage area probability sample design was used to select an equal probability sample of housing units. The design included an oversampling for people aged 60 years and older. Field interviewers visited each selected housing unit, completed a household roster, and selected a random adult for face-to-face interviews (N = 1,703; response rate = 72% in 1992). Wave 2, completed in 2005, using both telephone and face-to-face interviewing, included 1,076 of the original participants with 320 identified as deceased (N = 1,076, follow-up response rate = 78%). Wave 3, completed in 2015, using telephone interviews included 720 of the original participants with 63 deceased, 27 disabled and 2 incarcerated (follow-up response rate = 73%). Research indicates few data quality differences using face to face versus phone (Herzog & Rodgers, 1988; Soldo, Hurd, Rodgers, & Wallace, 1997). See Table 1 for a description of the Wave 3 sample used in the present study. Table 1. Description of Sample M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) Note: CNM = Core network member. View Large Table 1. Description of Sample M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) M (SD) % (n) Age 57.5 (15.8) Age group  25–39 18.8 (111)  40–59 34.1 (202)  60–79 38.0 (225)  80–97 9.1 (54) Panel 61.1 (362) Female 63.3 (375) Married 62.2 (368) Children 79.1 (468) Education 14.3 (2.5) Depressive symptoms 9.1 (9.0) Negative relations CNM1 2.0 (1.0) Negative relations CNM2 1.8 (0.9) Negative relations CNM3 1.8 (1.0) Negative affect 1.7 (0.6) Positive affect 3.2 (0.8) Sleep problems 2.4 (1.0) Self-rated Health 3.7 (0.9) Note: CNM = Core network member. View Large Participants completed a social network diagram in Wave 3 in which they were asked to list the people they felt closest to in order of closeness in three concentric circles (Kahn & Antonucci, 1980). The people respondents could not imagine life without are placed in the first circle followed by those that are less close in the second and third circles. After completing the interview, Wave 3 participants were invited to provide contact information for the first three people listed in their social networks. These network members (referred to hereafter as the core network sample) were then invited to participate in the study. After completing their interviews, both the panel and the core network sample were asked to complete monthly web surveys. The analytic sample includes 362 panel respondents and 230 of their core network members who completed at least one web survey. There were a total of 2,203 web surveys completed by panel respondents and a total of 1,367 web surveys completed by core network members. A description of the analytic sample is provided in Table 1. An analysis was conducted to examine whether individuals who completed the web surveys were different from those who did not complete web surveys. We examined whether age, respondent type (panel vs core), gender, marital status, having children, education, self-rated health, and depressive symptoms predicted completing one or more web surveys versus none in a logistic regression. Findings revealed that older respondents, core network members, females, those who were married, those without children, and those with higher education were more likely to complete at least one web survey. Panel respondents received $25 and core network members received $20 dollars for participating in the main interview. All respondents then received $5 for each monthly survey they completed; an additional $5 incentive if the respondent completed 6 web surveys, an additional $10 if the respondent completed 9, and an additional $15 if the respondent completed all 12. The web survey was offered over 15 months (October 1, 2014 to December 10, 2015). The respondents who completed their baseline interviews between July 2014 and December 2014 were eligible for 12 monthly surveys. To ensure that participants had at least 6 months possible to complete surveys, the decision was made to stop conducting additional web surveys starting in May 2015 and participants received the maximum allowable money if they completed all the surveys available to them. Measures Negative relationship quality To assess the negative qualities of their three closest network members, participants completed four widely used, reliable, and validated items (Birditt, Newton, Cranford, & Ryan, 2015; Birditt, Newton, Cranford, & Webster, 2016; Schuster, Kessler, & Aseltine Jr, 1990; Walen & Lachman, 2000): gets on my nerves, makes too many demands, lets me down when I am counting on them, and criticizes me on a scale from 1 (disagree) to 5 (agree). A mean of the items was created for each network member separately. All scale reliability alphas were computed using the method outlined by Cranford et al. (2006). For each scale, a between-person alpha (which treats month of completion as random), as well as a within person alpha, was calculated. The between-person alpha for negative relations with core network member 1, 2, and 3 ranged from .70 to .74 and the within-person alpha (which reflects the reliabilities for detecting systematic change over time) ranged from .56 to .59. The within person reliabilities were somewhat lower than Cranford et al.’s within person alphas for daily mood (.62–.88). This difference may be due to variation in constructs; as relationship quality measured at monthly intervals is likely more stable than daily mood. Age Participants reported their date of birth and four categories were created including: young adults (25–39), middle age (40–59), young-old (60–79), and oldest- old (80–97). Closeness Each network member was coded in terms of the order in which they were nominated by the respondent with 1 being the closest tie followed by network members 2 and 3. Well-being Each month participants rated their emotional and physical well-being. Negative and positive affect items were from the National Study of Daily Experiences (Almeida 1996–1997). Negative affect included 14 items such as feeling ashamed, nervous, and afraid. Participants rated the extent to which they experienced each emotion in the past month from 1 (not at all) to 5 (extremely). The between person alpha was .75 and the within-person alpha was .79. Positive affect included 11 items such as feeling attentive, cheerful, and extremely happy. The between-person alpha was .71 and the within-person alpha was .82. Self-rated health was rated from 1 (poor) to 5 (excellent). Sleep problems included four items from the Midlife in the United States Survey (MIDUS) regarding sleep quality over the past month (e.g., have trouble falling asleep, wake up during the night (Stephan, Sutin, Bayard, & Terracciano, 2017). These items were rated from 1 (never) to 5 (almost always). The between-person alpha was .75 and the within-person alpha was .64. Covariates We controlled for whether the respondent was a panel respondent or core network member (aka respondent type), relationship type, the month of survey, gender, marital status, whether they had a child, years of education, and depressive symptoms. Panel was coded as 1 and core network members as 0. Month of survey was coded as 1 through 12. Relationship type included 6 categories: 1 (spouse/partner), 2 (child), 3(parent), 4 (sibling), 5 (step/extended family), and 6 (friend/peripheral tie) and spouse/partner was the comparison group. Gender was coded as 1 (man) and 2 (woman). Marital status was coded as 0 (not married) or 1 (married). Whether participants had a child was coded as 1(yes) or 0 (no). Years of education coded from 1 (first grade) to 17 (more than four years of college). The 20-item Center for Epidemiological Studies Depression (CESD) scale (Radloff, 1977) was administered to assess depressive symptoms. Participants reported their experience of depressive symptoms in the past week from 0 (rarely/none of the time) to 3 (most of the time). The items are summed to create a total score (Cronbach’s α = .90), with higher scores representing more frequent depressive symptoms. Analysis Strategy To examine whether negative ties varied by age group, we estimated a multilevel model in SAS Proc Mixed. The model accounted for four levels of nested data. Social network was the upper level because principal respondents may have had up to three network members who participated, the participant was the third level, core network member number (1–3) the second level because each respondent could report on three network members, and month was the first level because each core network member could include up to 12 months of negative quality ratings. Negative relationship quality was the outcome and age group, closeness (i.e., core network number/position), and the age group by closeness interaction were entered as predictors. Age group was entered as a categorical variable with three dummy coded variables and the oldest-old age group was the reference group. The models controlled for relationship type, respondent type (e.g., panel or core network member), month of survey, gender, marital status, parental status, years of education, and depressive symptoms. Continuous variables were centered on the participant’s mean. Significant interactions were explored with tests of simple slopes and comparisons of simple slopes with a Bonferroni correction (i.e., adjustment of the p value for the 66 comparisons). To test whether there were associations between negative relationships and well-being and whether those links varied by age group, we estimated a series of multilevel models with each well-being indicator as the outcome (positive affect, negative affect, sleep problems, and self-rated heath). These models included three levels in which social network was the upper level, participant was the second level, and month was the lowest level. These models were estimated separately for each network member (first, second, third). In each model, the predictors included negative relationship quality, age group, and the interaction between negative relationship quality and age group. Negative relationship quality was group mean centered on respondents’ average negative quality with each network member. Models included the covariates described above as well as well-being in the previous month. Continuous variables were centered (either on the grand mean or the participant’s mean). Significant interactions were explored with tests of simple slopes and comparisons of simple slopes with a Bonferroni correction (i.e., adjustment of the p value for the six comparisons). Results Description Participants reported that their relationships were moderately negative with average ratings of 2.01 (SD = 1.01), 1.85 (SD = 0.94), and 1.82 (SD = 0.95) for core network members 1 through 3, respectively (Table 1). As presented in Supplementary Table 1, core network member 1 was most likely to be a spouse/partner followed by a child and a parent. Core network member 2 was most likely to be a child followed by a parent and a sibling. Core network member 3 was most likely to be a child followed by a sibling and a friend. The composition of the network members also varied by age group such that older individuals, for example, did not list parents. There was significant variance within participants over time in their reports of negative relationship quality. We provide an illustrative figure (Supplementary Figure 1) to show negative relationship quality with network member 1 by month among participants who completed all 12 of their web surveys. Each line represents a different participant and the figure shows that there is a great amount of both within-person and between-person variation in the reports of negative relationship quality over the 12 months. Unconditional models were estimated to determine the amount of within- and between-person variance in negative relationship quality and well-being. For negative relationship quality, 18.2% of the variance was between networks, 14.5% was between respondents, 39.0% between core network members, and 28.3% of the variance was within respondents. For negative affect, 15.8% of the variance was between networks, 59.4% was between respondents, and 24.8% of the variance was within respondents. For positive affect, 17.8% of the variance was between networks, 52.7% was between respondents, and 29.5% of the variance was within respondents. For sleep problems, 5.4% of the variance was between networks, 69.3% was between respondents, and 25.3% of the variance was within respondents. For self-rated health, 7.7% of the variance was between networks, 51.7% was between respondents, and 40.5% of the variance was within respondents. A covariate only model was estimated to assess variation in negative relationship quality by relationship type, respondent type, month of survey, gender, marital status, parental status, years of education, and depressive symptoms. As predicted, individuals reported greater negative relationship quality with spouse than with children (b = −.44, SE = .05, p < .001), parents (b = −.20, SE = .06, p < .01), siblings (b = −.41, SE = .07, p < .001), other family (b = −.67, SE = .08, p < .001), and friend/peripheral ties (b = −.63, SE = .08, p < .001). Individuals also reported greater negative relationship quality when they reported greater depressive symptoms (b = .02, SE = .00, p < .001). Covariate only models were estimated to assess variation in well-being by respondent type, month of survey, gender, marital status, parental status, years of education, depressive symptoms, and well-being in the previous month. With the exception of self-rated health, well-being in the previous month was positively associated with well-being in the current month. These results are not shown due to space limitations. Negative affect was negatively associated with the month of the survey (b = −.01, SE = .00, p < .01), positively related to depressive symptoms (b = .04, SE = .00, p < .001). Positive affect was negatively associated with depressive symptoms (b = −.04, SE = .00, p < .001). Sleep problems were negatively associated with the month of the survey (b = −.01, SE = .00, p < .001), positively related to depressive symptoms (b = .05, SE =. 00, p < .001). Self-rated health was negatively associated with depressive symptoms (b = −.04, SE = .00, p < .01). Does Negative Relationship Quality Vary by Age and Closeness? Models estimated whether negative relationship quality with core network members varied by age group (Table 2). Models revealed that negativity with core networks varied significantly by age and closeness, and that there was also a significant age by closeness interaction (Figure 1). Consistent with our hypothesis, there were no age differences in negative relationship quality with the closest tie (network member 1). In contrast, oldest-old participants reported their relationships with network members 2 and 3 were less negative than middle-aged and young-adult participants. Also, young-old participants reported their relationship with network member 3 was less negative than middle-aged participants. Table 2. Multilevel Model Predicting Negative Relationship Quality as a Function of Age Group and Closeness Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Note: CNM = Core network member; Model controlled for Panel versus CNM, Survey month, gender, married, children, education, CESD, and relationship to CNM. *p < .05, **p < .01, ***p < .001. View Large Table 2. Multilevel Model Predicting Negative Relationship Quality as a Function of Age Group and Closeness Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Predictor B (SE) Age 25–39 (young adults) .54 (.15)*** Age 40–59 (middle age) .62 (.13)*** Age 60–79 (young-old) .34 (.13)** Age 80–97 (oldest-old) REF CNM1 .07 (.13) CNM2 -.03 (.13) CNM3 REF Age 25–39 *CNM1 -.44 (.16)** Age 25–39*CNM2 .05 (.16) Age 40–59*CNM1 -.54 (.14)*** Age 40–59*CNM2 -.12 (.14) Age 60–79*CNM1 -.29 (.14)* Age 60–79*CNM2 .01 (.14) Variance Estimates  Between Network .16 (.03)***  Between Person .10 (.03)***  Between Core Network Member .31 (.02)***  Within person .27 (.00)*** Note: CNM = Core network member; Model controlled for Panel versus CNM, Survey month, gender, married, children, education, CESD, and relationship to CNM. *p < .05, **p < .01, ***p < .001. View Large Figure 1. View largeDownload slide Negative relationship quality by age group and closeness. Figure 1. View largeDownload slide Negative relationship quality by age group and closeness. Are Negative Relations Associated With Well-being Differently by Age and Closeness? Next, multilevel models assessed whether negative relationship quality with each network member was associated with well-being and whether there were significant interactions between age and negative relationship quality predicting well-being. Negative affect When individuals reported greater negative relationship quality they also reported greater negative affect during the same month (Model 1; Supplementary Table 2). There was a significant interaction between negative relationship quality with network member 1 and age group when predicting negative affect (Model 2; Supplementary Table 2). Negative quality with the closest network member was associated with increased negative affect among all four age groups but the strength of the association varied by age (Figure 2). Comparisons of the slopes revealed that the link between negative relationship quality with network member 1 and negative affect was greater among young adults compared to middle-aged (contrast = .11, SE = .03, p < .01) and young-old adults (contrast = .10, SE = .03, p < .05) (Figure 1). The interaction between negative quality with less close network members (i.e., network members 2 and 3) and age predicting negative affect was not significant. This finding indicates that older adults (with the exception of the oldest-old) appeared better able to regulate the implications of negative relationship quality on negative affect only in the closest tie but not in the less close ties which was consistent with our hypothesis. Figure 2. View largeDownload slide Negative affect as a function of relationship quality with core network member 1 and age group. Figure 2. View largeDownload slide Negative affect as a function of relationship quality with core network member 1 and age group. Positive affect Individuals who reported greater negative relationship quality reported lower positive affect during the same month (Model 1; Supplementary Table 3). There was a significant interaction between negative relationship quality with network members 1 and 2 and age group predicting positive affect. Greater negative quality relations with network member 1 predicted lower positive affect among all age groups with the exception of the oldest-old (Figure 3). Comparison of the slopes showed that the association was stronger among young adults compared to young-old adults (contrast = .12, SE = .04, p < .05). Greater negative quality relations with network member 2 predicted lower positive affect among young adults and oldest-old adults (Supplementary Figure 3). Comparisons of the slopes with a showed that the association between negative quality relations and positive affect was greater among oldest-old adults than among middle-aged and young-old adults (contrast = .19, SE = .07, p < .05; contrast = .17, SE = .07, p < .05, respectively). Overall these findings showed that there were more age differences in the closest tie which is consistent with the hypothesis that older individuals (with the exception of the oldest-old) may be better able to regulate their reactions to their closest ties than younger individuals. Figure 3. View largeDownload slide Positive affect as a function of negative relationship quality with core network member 1 and age group. Figure 3. View largeDownload slide Positive affect as a function of negative relationship quality with core network member 1 and age group. Sleep problems Individuals who reported greater negative relationship quality reported more sleep problems (Model 1; Supplementary Table 4). There was a significant interaction between negative relationship quality with network member 3 and age group when predicting sleep problems. More negative relations with network member 3 predicted greater sleep problems among young adults and middle-aged adults but not among young-old or oldest-old adults (Supplementary Figure 4). Comparisons of the slopes with a revealed the association was greater among young adults than among young-old adults (contrast = .17, SE = .05, p < .01). These finding only provide partial support of our hypothesis. Self-rated health The association between negative quality relations and self-rated health was not significant. There was a significant interaction between negative relationship quality with network member 1 and age group predicting self-rated health (Model 2; Supplementary Table 5). Greater negative relations with network member 1 predicted worse self-rated health among young adults but were not predictive of self-rated health among the other three age groups (Supplementary Figure 5). Comparisons of slopes showed that the association was stronger among young adults compared to the middle-aged adults (contrast = .18, SE = .07, p < .05). Again this finding was consistent with the hypothesis that there would be fewer age differences in the closest tie. Post hoc Models Because the core network members varied in terms of relationship types, we estimated all of the models again to address whether findings varied by relationship type. We collapsed relationship type into spouse, parent-child tie, and all other in order to account for variation in the types of relationships by age group. First, we estimated models predicting negative relationship quality as a function of relationship type, closeness, and age group to test whether the closeness by age finding varied by type of relationship. There was no significant three-way interaction indicating there was not significant variation by type of relationship. Next, we estimated models to assess the effects of negative relationship quality on well-being outcomes by core network member and relationship type. There were no significant interactions between negative quality and relationship type predicting well-being outcomes (negative affect, sleep, physical health) with one exception. When predicting positive affect with negative quality with the closest network member (network member 1) the interaction between negative quality, relationship type, and age revealed the age difference was significant for parent–child and other ties but not the spousal relationship. Thus, the spousal tie may incur unique effects. Nevertheless, findings generally showed that the closeness of the tie was independently associated with negative relationship quality and its implications for well-being beyond the type of relationship partner. Discussion The present study examined monthly reports of negative relationship quality regarding individuals’ three closest relationships among a life-span sample. Interestingly, findings only partially supported the SAVI model, which suggests fewer age related improvements in emotion regulation when conflict or stress is unavoidable. Although older people perceived their closest relationship to be just as irritating as younger individuals, they appear to be better able to regulate the effects of those ties on their well-being. Variations in Negative Relationship Quality by Age and Closeness Age differences in negative relationship quality varied by relationship closeness. Consistent with the SAVI model and our hypothesis, there were fewer age differences in reports of negative relationship quality in the closest tie compared to relationships that were less close. It is possible that there are fewer age differences in the closest tie because having negative interactions in the closest ties is less avoidable. It is also more common to have simultaneously positive and negative relationships with people who are considered closest (Fingerman et al., 2004). This is consistent with the literature showing that there are fewer age-related decreases in the negative aspects of the spousal tie, which is often the closest tie with the most contact, compared to relationships with children and with friends (Birditt et al., 2009). This study extends prior research by showing that there may be fewer age differences in the negative aspects of individuals’ closest relationships regardless of the relationship type (e.g., spouse, child). Age differences in reports of negative relationship quality were in the expected direction in the relationships that were less close suggesting that older adults are better able to regulate the perception of negative relationship quality in relationships that may provide greater opportunities to use avoidance. Variations in the Negative Relations-Well-being Link by Age and Closeness Negative relationship quality predicted poorer well-being (greater negative affect, lower positive affect, and poorer sleep), which is consistent with the previous literature (Ailshire & Burgard, 2012; English & Carstensen, 2014), but those links varied by age and relationship closeness. Inconsistent with the SAVI model (but consistent with SST), older individuals showed fewer negative implications of negative ties for well-being when those negative experiences were in the closest ties compared to the less close ties. As predicted, these findings suggest that when older people experience negative quality relations in their closest tie, their well-being is less impacted by those negative relations compared to young adults. With regards to the closest network member there were age differences in the link between negative relationship quality and negative affect, positive affect, and physical health. Young adults who reported greater negative relationship quality reported greater negative affect, lower positive affect, and poorer health compared to middle-aged and/or young-old adults. However, oldest-old adults did not show less reactivity compared to younger age groups. Findings regarding negative quality in less close network members and well-being were not as consistent. The link between negative relationship quality with core network member 2 and positive affect was less pronounced among older adults than younger people. Further, the link between negative relationship quality with core network member 3 and sleep problems was lower among older adults than among younger people. Thus, the age differences were in the expected direction with older individuals being less detrimentally affected by negative relationship quality. However, there was more evidence of age-related improvements in the closest tie. It is possible that as people age they use more adaptive types of emotion regulation strategies in their closest ties (Blanchard-Fields, 2007), which in turn may differentially impact their well-being. In their closest relationships, older individuals tend to use avoidant coping and expressive regulation strategies (e.g., emotional suppression) that are employed after the emotion is experienced and these strategies are typically more successful in preserving their well-being (Birditt, 2014; Birditt et al., 2005; Charles et al., 2009). Older individuals are also less likely to use direct destructive strategies such as insults and yelling. Thus, while older adults still find their closest ties irritating, they are able to use more effective strategies than younger adults to offset the detrimental implications of negativity in those ties, and thus their well-being is less impacted. However, further research is needed to understand the specific mechanisms accounting for these effects. Overall, there was more evidence of links between negative relationship quality and psychological well-being (negative and positive affect) than between negative relationship quality and the outcomes of sleep and physical health. Further, there was more evidence of age-related improvements in links between negative quality and well-being with psychological well-being than with sleep and physical health. It is possible that age-related improvements in emotion regulation strategies have a greater impact on psychological well-being on a monthly basis, whereas adverse consequences for physical health and sleep may take longer to develop. It is also most likely more feasible to regulate the impact of relationships on emotional health than it is to regulate the impact of relationships on health and sleep. Directions for Future Research There are limitations to this study that should be addressed in future research. First, the range of web surveys that participants were invited to participate in varied from 6 to 12 surveys. The models did control for the month of participation, which did not appear to affect findings, yet future studies would benefit from ensuring all participants completed the same number of web surveys. In addition, the sample that completed web surveys differed from those who did not complete these surveys in key ways (e.g., the web sample was more educated and older). Future studies should include more representative samples to assess the generalizability of the findings. Further, the measure of negative relationship quality included only four items, and future research may benefit from a more comprehensive assessment. The data also do not include ratings of relationship quality with individuals beyond the three closest network members. Examining whether the age difference in relationship quality varies by closeness across the full range of network members would enhance our understanding of the ways that age influences the experience of negative relationships. Future research should also examine more objective indicators of well-being. For instance, previous studies have shown important links between negative aspects of relationships and biological indicators including blood pressure, cortisol, and waist circumference (Birditt, Manalel, Kim, Zarit, & Fingerman, 2017; Sneed & Cohen, 2014). In addition, we acknowledge that the examination of negativity in close relationships is similar to the concept of ambivalence, which has been defined as simultaneous positive and negative feelings about a social partner (Fingerman et al., 2004; Fung et al., 2009; Uchino et al., 2004). According to Uchino and colleagues, ambivalence is particularly detrimental for well-being because ambivalent relationships can be stressful and unpredictable. Our findings suggest that, although simultaneous feelings of closeness and negativity are common among older adults, it is not necessarily associated with poorer well-being. Future work should consider how perceptions of negativity in close relationships are similar to or different from measures of ambivalence that are typically assessed in the literature (i.e., feeling torn; concurrent positive and negative sentiments). The present study makes a significant contribution to the literature by examining negative relationship quality and well-being over time on a short term monthly basis, rather than over years or days. This type of design allowed us to examine how short-term variations in negative relationship quality are associated with changes in well-being by controlling for well-being in the previous month. This study is also novel because it examined relationship quality with identified close others rather than focusing only on specific relationship types. Study findings revealed that older individuals appear to experience negative relationship quality differently than younger individuals. However, these age differences varied by relationship closeness. Findings imply that there may be age-related improvements in emotion regulation in the context of social ties that vary by relationship closeness. We hope that this study inspires future research regarding the complexity of negative relationship quality across the adult life span. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences online. Funding This study was funded by a grant from the National Institute on Aging (Antonucci, PI; AG045423). C. A. Polenick was supported by training grant T32 MH073553-11 from the National Institute of Mental Health (Stephen J. Bartels, Principal Investigator). Conflict of Interest None reported. Acknowledgment We would like to thank Angela Turkelson for her assistance with the analysis. A previous version of this paper was presented at the International Association of Gerontology and Geriatrics (IAGG) conference in July 2017. References Ailshire , J. A. , & Burgard , S. A . ( 2012 ). 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Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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The Journals of Gerontology Series B: Psychological Sciences and Social SciencesOxford University Press

Published: Mar 27, 2018

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