Subjective Memory Problems and Availability of Emotional Support

Abstract

This study examines (1) whether subjective memory problems (SMP) influence perceived emotional support from and frequency of contact with family and friends; and, (2) the extent to which this relationship is moderated by gender, education, and functional limitations. We use the 2014 wave of the Health and Retirement Study, a nationally representative panel survey of adults aged 51 and over in the United States. While SMP does not affect perceived emotional support for younger group (YG; aged 51–64), in older group (OG; aged 65+), SMP is associated with reduced perceived support from friends. Also, SMP is predictive of fewer writing-based contact with children and friends among OG but not among YG. Lastly, we find that the effect of SMP on support from children is contingent upon activity of daily living (YG) and gender (OG), while the effect of SMP on writing-based contact with both children and friends is contingent upon education (YG only).

Keywords

subjective memory problems emotional support gender education functional limitations

Subjective memory problems (SMP)—which entail everyday forgetfulness and complaints about memory and cognition—refer to the perception, not objective measurement, of decline in memory (Mitchell, Kemp, Benito-León, & Reuber, 2014). SMP occurs commonly in older persons with the risk of it mounting with age (Brigola et al., 2015; Montejo, Montenegro, Fernandez, & Maestu, 2011). Research on SMP is consequential because SMP, for some, may mean increased risk of an objective memory decline, ranging from mild cognitive impairment to dementia (Mitchell et al., 2014; Mitchell & Shiri-Feshki, 2009). Dementia, in turn, requires substantial care resulting in health repercussions for caregivers. Also the perceptions of poor memory are tied to fears of developing dementia (Parikh, Troyer, Maione, & Murphy, 2016); and as such, there is mounting research connecting SMP to reduced mental health (Parikh et al., 2016) and lowered quality of life (Maki et al., 2014; Mol, van Boxtel, Williems, & Jolles, 2006).

What remains relatively underassessed, however, is the extent to which subjective evaluation of one’s memory is associated with social health, namely, the perceptions of emotional support from and frequency of contact (FOC) with family and friends. Research documents the negative impact of objective and severe cognitive impairment on social support. For example, Aartsen, Van Tilburg, Smits, and Knipscheer (2004) found that persons with lower mini-mental state examination (MMSE) scores experience loss of friends and neighbors. We are less aware, however, of whether the subjective assessment of one’s memory affects perceptions of support/contact, net of the effect of objective cognitive impairment. We extend research on cognitive health by (1) examining whether SMP influences perceptions of emotional support from and FOC with family and friends; and, (2) the extent to which the relationship between SMP and support/contact is moderated by (a) gender, (b) education, and, (c) functional limitations. Given that FOC likely is predicated on the mode of communication (M.J. Stern & Messer, 2009), we assess FOC using two separate outcome variables, namely, “in-person visit or telephone” and “writing-based” (e.g., mail, e-mail, and social media) interactions. Moreover, given that memory problems may differentially occur in and affect individuals based on age (Grady & Craik, 2000; Park & Festini, 2017), we examine our research questions using two separate models for individuals aged 51–64 (younger group [YG]) and those 65 and over (older group [OG]). Examining the social health consequences of SMP is critical, given that we live in an aging society and age-related cognitive complaints often progress to nonnormative cognitive degeneration (Mitchell & Shiri-Feshki, 2009). Moreover, knowing if SMP is negatively associated with support perceptions is important, given that emotional support and social contact, reciprocally, are predictive of overall cognitive health (Fratiglioni, Paillard-Borg, & Winblad, 2004; Glei et al., 2005).

Theoretical Perspectives

“Personal relationships feel most satisfying when both participants are perceived as contributing equally to the relationship” (Quadagno, 2017, p. 53). Exchange theory suggests that most relationships reach a point where resources are unequal and that the individuals with decreasing resources gradually disengage from relationships (Bengtson, Burgess, & Parrott, 1997). We utilize the exchange theory to posit that those with SMP likely withdraw from social interactions, which in turn adversely impacts their perceptions of support. However, the effect of SMP on support perceptions may vary depending on the source of support. For instance, parents invest countless resources in raising children; adult children, in turn, serve as primary source of support for elderly parents (Silverstein, Bengtson, & Lawton, 1997) even when parents in late life are unable to reciprocate. This “deferred” form of support, however, may or may not necessarily be available in all social relationships. As such, we examine the impact of SMP on perceptions of support from spouse, adult children, and friends.

We also rely on the stress process framework (Pearlin, Menaghan, Lieberman, & Mullan, 1981) to explain that while SMP may result in decreased perceived support, this relationship may be conditioned by individual resources. That is, the health ramifications of a stressor are contingent upon people’s ability to utilize available resources to cope with the stressor (Pearlin et al., 1981). Among these resources, we argue, are gender, education, and functional health.

SMP and Perceptions of Support From Family and Friends

Poor memory is a common problem that accompanies aging (Craik, Anderson, Kerr, & Li, 1995). The complications associated with memory loss—for example, difficulty in remembering names or finding words, forgetting instances from past or events planned in the future, or/and losing a train of thought—are likely to impact every day social life (Farias et al., 2006). Individuals when faced with such challenges may feel confused and frustrated. It may also bring mood disturbances and social withdrawal, indirectly driving off support and resulting in decreased perceptions of it (Meilak, Partridge, Willis, & Dhesi, 2016).

Research on auditory loss, for instance, suggests that those with hearing problems tend to disengage with significant others in an effort to prevent themselves from repeating things during conversations (Scarinci, Worrall, & Hickson, 2009). They disengage from social gatherings to prevent embarrassment for self and close others (Scarinci et al., 2009). Such efforts, we believe, aren’t limited to those with hearing loss; efforts taken by persons with SMP to disengage may signal loss of interest and ultimately, negatively impact perceptions of emotional support from and FOC with family and friends.

Compromised language skills that are often associated with memory loss (Folstein, Folstein, & McHugh, 1975) may interrupt not only in-person/phone conversations but also writing-based interactions via mail, e-mail, or/and social media. We posit that the impact of SMP would be less detrimental for the latter because writing-based communication may eliminate the need for spontaneous dialogue thereby allowing the “think time” necessary to recall, process, and express oneself without the feeling of being judged for ebbing memory (Moore Sohlberg, Fickas, Ehlhardt, & Todis, 2005). It also may be easier to conceal memory inadequacies in writing-based interactions as opposed to in-person/phone conversations (Scholl & Sabat, 2008).

Do Gender, Education, and Functional Limitations Moderate the Link Between SMP and Perceived Support?

We utilize the stress process framework (Pearlin et al., 1981) to posit that gender, education, and functional limitations moderate the consequences of SMP on perceptions of emotional support and FOC. Women compared to men generally report wider social circles and offer and receive more support, especially emotional support (Antonucci, Akiyama, & Takahashi, 2004; Fischer & Beresford, 2015; Hall, 2011; Liebler & Sandefur, 2002). Compared to men, women on most occasions also perceive their significant others to be more caring and helpful (Allen & Stoltenberg, 1995). Moreover, they report more varied sources of support, namely, adult children, relatives, and friends; men alternatively rely for support most heavily on their spouses (Stevens & Westerhof, 2006). Given that women have more diverse social relationships and sources of support to rely on in times of stress (Stevens & Westerhof, 2006), we expect SMP to more negatively impact men’s than women’s perceptions of support.

Women are somewhat more likely than men to pay closer attention to what and how they write (Pajares & Valiante, 2001; Xia, 2013); therefore, compromised language skills may more negatively hinder women’s than men’s writing-based FOC. Alternatively, given that writing-based interactions do not demand immediate response, the FOC based on this particular mode of communication may not be impacted by SMP either for women or men. When it comes to face-to-face and phone interactions, men with SMP may be more negatively impacted than women for two reasons. One, men compared to women already are less likely to talk over phone (Hannah & Murachver, 1999), and two, men in general tend to lead, facilitate, and interrupt conversations, whereas women tend toward patient listening, asking questions, and the use of body language for self-expression (Hannah & Murachver, 1999; Xia, 2013). Be it due to gender socialization, social situational demands/contexts, or/and biological predispositions, it is reasonable to assume that men are slightly more negatively impacted by SMP when it comes to in-person or/and phone conversations (Giri, 2004).

We also expect education to shape the relationship between SMP and perceived support/FOC. Given the positive correlation between education and self-efficacy (House et al., 1994; Ross & Mirowsky, 2010) and the link between self-efficacy and the ability to more realistically appraise and manage circumstances (Ross & Mirowsky, 2010), persons with higher education may be better equipped to grapple with memory changes they experience. Research on factors associated with higher education such as reading ability, work complexity, and problem solving suggests that those with higher education likely cope better with cognitive decline than those with lower levels of education (Steffener & Stern, 2012). We argue that being able to cope effectively with memory problems could mean being able to remain socially engaged, which may maintain greater perceived support from and FOC with family and friends. Alternatively, given heightened awareness of the changes in their cognitive functioning, those with higher education may be more reluctant to engage in social relationships, thereby adversely impacting perceived support/contact. Such effects of education, we suspect, may be present regardless of the mode of communication.

Finally, we posit that the effect of SMP on perceived emotional support and FOC is contingent upon functional health. Specifically, we expect that individuals who experience both SMP and difficulty in activity of daily living (ADL) are more likely to report higher perceived support from/contact with spouse and adult children, but reduced perceived support from/contact with friends. Our expectation that those who have functional limitations in addition to SMP report higher perceived support from and contact with family emerges from extant literature revealing that close family members rally around and support older adults who have physical health problems (Hank, 2007; Silverstein et al., 1997). Adult children, for example, are more likely to have daily contact with older parents when parents suffer from chronic physical conditions (Hank, 2007). Functional limitations, however, may result in negative emotions of irritability and dependency (Hogerbrugge & Silverstein, 2015) which when combined with SMP can render those with both conditions to disengage from social activities, adversely affecting emotional support from and contact with those outside of immediate family, namely, friends. Comorbidity may also mean more care, which while family members might feel obligated to provide, friends may not.

Age Differences in the Effect of SMP

Given the differential susceptibility to memory changes based on age (Grady & Craik, 2000; Park & Festini, 2017), the effect of SMP on support perceptions and FOC likely varies based on the age of an individual. Compromised language and writing skills, for instance, might be more confusing and embarrassing for younger than older persons. Even the mildest of memory problems, for instance, may become more pronounced for those in their 50s compared to their peers in their 70s. It is also possible that a younger person with memory changes may be more easily dismissed, given the commonplace understanding that memory decline only happens in late life (Greenwood & Smith, 2016). Keeping the relevance of what’s normative and nonnormative at certain ages, we examine our proposed research questions using separate models for individuals aged 51–64 and those aged 65 and over.

Method

Data and Sampling

Analyses are based on the 2014 wave of the Health and Retirement Study (HRS), a nationally representative panel survey of adults aged 51 and over and their spouses/partners in the United States (Sonnega & Weir, 2014). The first wave of the HRS data collection occurred in 1992. Subsequent data collections occurred every 2 years through 2016, with new cohorts added in 1998 and 2004. From 2006, HRS administered a leave-behind questionnaire (LBQ) for the random half of the respondents who were eligible for the core survey to assess psychosocial outcomes, including support from spouse, children, and friends. We used data from the 2014 survey, which is the most recent wave of HRS available in public, in order to maximize the number of participants reporting SMP in our analytic sample and to utilize some of the new features in the 2014 survey. For example, 2014 survey assessed FOC via social media, which may be more frequently used than mail or e-mails among close friends or family members. Although HRS is a longitudinal survey, we decided to use cross-sectional data because the current study focuses on how different levels of subjective memory are associated with varying levels of social contact and perception of support rather than intraindividual changes in social relationships due to changes in memory.

For our analytic sample, we first selected respondents who participated in the core as well as LBQ surveys in 2014 (N = 7,477). Among these people, we excluded 71 respondents who lived in nursing homes and additional 402 respondents who have zero respondent weights in 2014. These 402 individuals had zero weights because they were not age eligible for the original HRS sampling scheme (aged 51 and older) or because they resided in a nursing home at the time of the survey. These exclusions resulted in 7,004 respondents. Of these respondents, we then selected those who had valid, nonproxy responses to questions on SMP (N = 3,417). There were missing data in dependent and control variables as well. However, because the size of missing data was less than 5% of the total sample, we chose not to impute these values. As the number of valid cases differed for each dependent variable, the number of observations used for each analysis is noted in the tables.

Measures

Dependent variables

We examined emotional support from various sources (i.e., spouse, children, and friends) and the FOC with children and friends as our outcome variables. Emotional support from a spouse or partner (α = .83) was assessed with the following seven questions about the spouse: “(a) How much do they really understand the way you feel about things, (b) How much can you rely on them if you have a serious problem, (c) How much can you open up to them if you need to talk about your worries, (d) How often do they make too many demands on you, (e) How much do they criticize you, (f) How much do they let you down when you are counting on them, and (g) How much do they get on your nerves?” These measures were adopted from Schuster, Kessler, and Aseltine (1990). Response categories included: 1 = not at all, 2 = a little, 3 = some, and 4 = a lot. Emotional support from children (α = .81) and emotional support from friends (α = .70) were assessed, respectively, using the same seven questions and response categories used in assessing spousal support. To construct our scales, we first dichotomized each item (1 = some or a lot of support, 0 = no or little support) and calculated the sum of 7 items for each scale. Negative items (d, e, f, g) were reverse coded so that higher scores reflect higher levels of support and lower levels of strain.

FOC with children and friends were assessed, respectively, with the questions asking how often the respondent (a) meets up, (b) speaks on the phone, (c) writes to or e-mails, and (d) communicates by Skype, Facebook, or other social media with the respective source of social support. Response categories to each question ranged from 1 = less than once a year or never to 6 = three or more times a week. We categorized these four modes of contact into two different modes—visit/phone versus writing-based interactions (mail, e-mail, and social media)—and calculated the mean scores of 2 items. The correlation between visit and telephone contact was .49 for both children and friends. The correlation between write/e-mail and social media contact was .55 for children and .59 for friends.

Independent variable

HRS asked about respondents’ subjective memory using the following question: “How would you rate your memory at the present time?” Response categories included 1 = excellent, 2 = very good, 3 = good, 4 = fair, and 5 = poor. Subjective memory measure was standardized with a mean of 0 and standard deviation of 1.

Moderating variables

Respondent’s gender (1 = female, 0 = male), education (1 = college or more, 0 = less than college), and functional limitations (1 = respondent has difficulty in performing at least one ADL, 0 = no limitation) were used as moderating variables. ADL included bathing, eating, dressing, walking across a room, and getting in or out of bed. Response categories for each item included “yes,” “no,” “don’t do,” and “can’t do.” Responses of “yes” and “can’t do” were coded as 1 (having some difficulty), whereas “no” and “don’t do” were coded 0 (having no difficulty).

Control variables

We controlled for respondent’s objective memory to separate out the effect of subjective memory. HRS administered a wide range of cognitive functioning measures based on the telephone interview for cognitive status (Brandt, Spencer, & Folstein, 1988). Among these measures, we chose three measures that capture memory: immediate word recall, delayed word recall, and serial 7’s test. For word recall tasks, interviewers read the respondents one of four possible lists of 10 nouns and asked to recall them immediately after reading and after 5 min of asking other survey questions. The number of correct answers (ranging from 0 to 10 for both tasks) is noted at the end of the recall. For serial 7’s test, interviewers asked the respondent to subtract 7 from 100, and continue to subtract 7 from each subsequent number. A total of five trials were done and the number of correct answers, ranging from 0 to 5, were noted. As in the case of subjective memory, objective memory was standardized with a mean of 0 and standard deviation of 1 in order to facilitate comparison of their effects. Whereas in the assessment of subjective memory, higher scores indicate SMP, in objective memory, higher scores reflect better cognitive functioning.

In addition, we controlled for respondents’ sociodemographic characteristics that may be correlated with both cognitive functioning of the respondent and the support that they receive from other sources. For all models, we included age (in years), race/ethnicity (1 = African Americans or other race/ethnicity; 0 = non-Hispanic White), depressive symptoms, and whether the respondent coresides with any child (1 = yes, 0 = no). Depressive symptoms were assessed with 8 items from the Center for Epidemiologic Stuides Depression (CES-D) scale (e.g., I felt depressed, I felt everything was an effort, I was happy), with response categories of 1 = yes and 0 = no. Positive items were reverse coded and then the scores of individual items were summed up to get a summary score. Information on whether the respondent coresides with any child was obtained from the coversheet. For models predicting support from and FOC with children and friends, we also controlled for respondent’s marital status (1 = married, 0 = not married).

Analytic Plan

First, descriptive statistics are presented to show the sample characteristics. Next, ordinary least squares hierarchical regression models are used to estimate the effect of respondent’s SMP on their various sources of support and the moderating effects of gender, education, and functional limitations. In Model 1, we included respondent’s SMP along with moderating and control variables. In Model 2, we included interaction terms between respondents’ SMP and three moderating variables (i.e., gender, education, and functional limitations). In conducting regression analyses, we adjusted for person-level weights and the clustered structure of the HRS survey by using the SVY command in STATA. Also, we checked the variance inflation factor (VIF) of variables in each regression model to check possible collinearity problems. VIF scores were close to 1, suggesting there is no significant collinearity among independent variables.

Results

Descriptive Statistics

Table 1 shows the characteristics of the sample. The mean levels of support from various sources ranged from 5.73 to 5.98 on a 0–7 scale. Average FOC of visit and phone were above 4, indicating that on average respondents made contacts more than “once or twice a month” for both children and friends. Average FOC in writing was lower, with 2.60 for friends and 3.04 for children. Mean age of the respondents was 66.6 and about 49% were female; 59% had college education or more; 11% of the respondents had some difficulty at least in one of the activities of daily living; and 87% of the respondents were non-Hispanic White and 13% were African Americans or of other racial/ethnic origins. Average count of depressive symptoms was 1, and 96% were married; 21% had at least one child living with the respondent.

Table 1.
Descriptive Statistics.

Variables N Mean SD Minimum Maximum

Dependent variables

Support from spouse 3,373 5.81 1.64 0 7

Support from children 3,132 5.73 1.70 0 7

Support from friends 3,124 5.98 1.30 0 7

FOC with children (visit or phone) 3,081 4.39 1.10 1 6

FOC with children (writing-based) 3,042 3.04 1.65 1 6

FOC with friends (visit or phone) 3,135 4.15 1.08 1 6

FOC with friends (writing-based) 3,090 2.60 1.53 1 6

Independent variables

Subjective memory (higher scores = poorer memory)^a 3,417 −0.09 0.99 −2.32 2.16

Objective memory (higher scores = better memory)^a 3,417 0.18 0.96 −3.38 2.73

Age 3,417 66.63 8.48 54 97

Gender (1 = female) 3,417 0.49 0.50 0 1

Education (1 = college or more) 3,402 0.59 0.49 0 1

At least one ADL problem (1 = yes, 0 = no) 3,417 0.11 0.31 0 1

Race (1 = non-White; 0 = White) 3,417 0.13 0.34 0 1

Depressive symptoms 3,417 1.00 1.64 0 8

Marital status 3,416 0.96 0.19 0 1

Has a coresiding child (1 = yes, 0 = no) 3,417 0.21 0.41 0 1

Note. FOC = frequency of contact; ADL = activity of daily living.

^a Standardized; analyses are weighted.

Effect of SMP on Support From Various Sources

Table 2 (panel A: YG and panel B: OG) shows the extent to which levels of SMP affect the respondents’ perceived support from spouse, children, and friends. Contrary to our hypothesis, SMP had no significant main effects on any of these outcomes among YG (see Table 2, panel A: Model 1). Among OG (Table 2, panel B: Model 1), poorer subjective memory was associated with lower support from friends.

Table 2.
Regression Models Predicting Support From Various Sources.

Support From Spouse Support From Children Support From Friends

Variables Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

A. YG

SMP (higher scores = poorer memory)^a 0.07 0.11 −0.06 −0.25 −0.01 0.08

(0.06) (0.10) (0.08) (0.13) (0.05) (0.12)

Objective memory (higher scores = better memory)^a 0.09 0.09 0.11 0.11 0.07 0.07

(0.07) (0.07) (0.10) (0.10) (0.06) (0.06)

Age 0.01 0.01 −0.02 −0.02 −0.01 −0.02

(0.01) (0.01) (0.02) (0.02) (0.01) (0.01)

Gender (1= female) −0.21 −0.23 0.19 0.24 0.52* 0.51*

(0.12) (0.13) (0.12) (0.12) (0.09) (0.10)

Education (1= college or more) 0.07 0.07 −0.12 −0.12 0.19 0.17

(0.12) (0.13) (0.13) (0.13) (0.10) (0.09)

At least one ADL problem (1=yes, 0 = no) 0.21 0.30 −0.65 −1.14 −0.52 −0.45*

(0.23) (0.26) (0.43) (0.37) (0.18) (0.20)

Race (1 = non-White, 0 = White) −0.22 −0.23 0.39* 0.37* −0.08 −0.09

(0.16) (0.16) (0.18) (0.17) (0.12) (0.11)

Depressive symtoms −0.27* −0.27* −0.25* −0.26* −0.07** −0.07*

(0.04) (0.04) (0.05) (0.05) (0.02) (0.03)

Marital status 0.06 0.07 0.06 0.04

(0.40) (0.35) (0.18) (0.18)

Has a coresiding child (1 = yes) −0.16 −0.17 −0.52* −0.49* 0.10 0.09

(0.12) (0.12) (0.13) (0.13) (0.10) (0.10)

SMP x Gender (1= female) −0.06 0.15 −0.03

(0.13) (0.10) (0.11)

SMP x Education (1 = college or more) 0.01 0.00 −0.09

(0.10) (0.13) (0.10)

SMP x ADL problem (1 = yes) −0.25 1.11* −0.22

(0.19) (0.20) (0.18)

Constant 5.43* 5.50* 6.97* 6.73* 6.52* 6.59***

(0.78) (0.79) (1.30) (1.28) (0.81) (0.80)

Observations 1,146 1,146 1,083 1,083 1,128 1,128

B. OG

SMP (higher scores = poorer memory)^a 0.01 −0.06 −0.03 −0.14* −0.06 −0.06

(0.04) (0.06) (0.03) (0.07) (0.03) (0.05)

Objective memory (higher scores = better memory)^a 0.09 0.09 0.03 0.04 0.00 0.00

(0.04) (0.04) (0.06) (0.06) (0.04) (0.05)

Age 0.01 0.01 0.04* 0.04* −0.00 −0.00

(0.01) (0.01) (0.01) (0.01) (0.00) (0.00)

Gender (1= female) −0.14* −0.14* 0.35* 0.34* 0.50* 0.50*

(0.07) (0.07) (0.06) (0.06) (0.07) (0.07)

Education (1= college or more) 0.08 0.08 0.02 0.02 0.08 0.08

(0.08) (0.08) (0.09) (0.09) (0.08) (0.08)

At least one ADL problem (1=yes, 0 = no) −0.12 −0.14 −0.16 −0.19 0.10 0.12

(0.14) (0.14) (0.15) (0.16) (0.09) (0.09)

Race (1 = non-White, 0 = White) −0.20 −0.20 0.24* 0.24* −0.22 −0.23

(0.11) (0.11) (0.10) (0.09) (0.16) (0.16)

Depressive symtoms −0.26* −0.26* −0.18* −0.18* −0.10** −0.10*

(0.03) (0.03) (0.03) (0.03) (0.04) (0.04)

Marital status 0.55 0.56 0.50* 0.50*

(0.34) (0.34) (0.25) (0.24)

Has a coresiding child (1 = yes) −0.01 −0.02 −0.17 −0.18 −0.16 −0.16

(0.12) (0.12) (0.14) (0.14) (0.11) (0.11)

SMP x Gender (1= female) 0.15 0.16* 0.02

(0.09) (0.08) (0.06)

SMP x Education (1 = college or more) −0.03 0.05 0.01

(0.06) (0.08) (0.06)

SMP x ADL problem (1 = yes) 0.12 0.09 −0.10

(0.14) (0.11) (0.07)

Constant 5.69* 5.68* 2.25* 2.24* 5.59* 5.59*

(0.41) (0.41) (0.60) (0.60) (0.41) (0.41)

Observations 2,058 2,058 1,998 1,998 1,984 1,984

Note. Standard errors are in parentheses. SMP = subjective memory problems; ADL = activity of daily living.

^a Standardized.

p < .05.

p < .01.

p < .001.

Looking at Table 2, panel A: Model 2, significant moderating effects of functional limitations were found in predicting the effect of SMP on support from children among YG. For those who have at least one functional limitation in ADL, SMP had a positive effect on support from children; however, for those who do not have any functional limitation, SMP was associated with lower support from children (see Figure 1a). Among OG (Table 2, panel B: Model 2), gender was a significant moderator in the relationship between subjective memory and support from children. Compared to their female counterparts, older men received much lowered support from children when they have SMP (see Figure 1b).

Figure 1.
Moderating effects of activity of daily living (younger group) and gender (older group) in the relationship between subjective memory problems and perceived support from children. Significance level for a is 0.001 and for b is 0.05.

Among control variables, objective measure of memory, like SMP, was not significantly associated with any of the outcomes in either sample. Further, more depressive symptoms were associated with lower levels of support from all sources regardless of age-group. Women received greater support from children (OG only) and friends. Having ADL problem was associated with lower support from friends among YG. Compared to Whites, older non-Whites received less support from spouse and friends but more support from children. Younger non-Whites received greater support from children than Whites. Married older adults also received greater support from children and friends compared to their nonmarried peers.

Effect of Subjective Memory on FOC With Children and Friends

Table 3 (panel A: YG and panel B: OG) shows the effects of SMP on FOC with children and friends. SMP was not significantly associated with any of the outcomes among YG. Among OG (Table 3, panel B: Model 1), SMP was associated with fewer writing-based contact with children and friends.

Table 3.
Regression Models Predicting Frequency of Contact With Various Sources.

FOC With Children FOC With Friends

Visit or Phone Writing-Based Visit or Phone Writing-Based

Variables Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

A. YG

SMP (higher scores = poorer memory)^a −0.06 −0.12 −0.12 −0.02 0.03 0.09 −0.01 0.21*

(0.05) (0.09) (0.08) (0.12) (0.05) (0.10) (0.07) (0.10)

Objective memory (higher scores = better memory)^a 0.01 0.01 0.15* 0.15* 0.04 0.04 0.18 0.18

(0.05) (0.05) (0.07) (0.07) (0.06) (0.06) (0.07) (0.07)

Age −0.01 −0.01 −0.00 −0.00 −0.01 −0.01 −0.04 −0.04

(0.01) (0.01) (0.02) (0.02) (0.01) (0.01) (0.02) (0.02)

Gender (1= female) 0.36* 0.39* 0.26 0.27 0.26* 0.25* 0.51* 0.49*

(0.08) (0.09) (0.09) (0.10) (0.06) (0.06) (0.08) (0.09)

Education (1= college or more) −0.05 −0.06 0.61* 0.58* 0.05 0.04 0.56* 0.52*

(0.10) (0.10) (0.15) (0.14) (0.08) (0.08) (0.12) (0.12)

At least one ADL problem (1 = yes) 0.08 −0.00 −0.06 −0.05 −0.05 −0.10 0.03 0.07

(0.21) (0.25) (0.26) (0.29) (0.15) (0.18) (0.21) (0.22)

Race (1 = non-White, 0 = White) 0.15 0.14 −0.29 −0.30 0.10 0.09 −0.50* −0.51*

(0.12) (0.11) (0.18) (0.18) (0.09) (0.09) (0.14) (0.13)

Depressive symptoms −0.08 −0.09 −0.05 −0.05 −0.05* −0.06* −0.08* −0.08*

(0.03) (0.03) (0.04) (0.04) (0.03) (0.03) (0.03) (0.03)

Marital status 0.53* 0.52* 0.40 0.38 −0.00 0.00 0.27 0.25

(0.26) (0.24) (0.39) (0.37) (0.22) (0.23) (0.26) (0.26)

Has a coresiding child (1 = yes) −0.11 −0.10 0.00 −0.01 −0.01 −0.01 −0.07 −0.07

(0.09) (0.09) (0.13) (0.13) (0.09) (0.09) (0.13) (0.13)

SMP × Gender (1 = female) 0.15 0.08 −0.01 −0.08

(0.08) (0.11) (0.09) (0.10)

SMP × Education (1 = college or more) −0.05 −0.23* −0.10 −0.25*

(0.08) (0.11) (0.09) (0.11)

SMP × ADL problem (1 = yes) 0.21 −0.06 0.08 −0.20

(0.17) (0.23) (0.15) (0.14)

Constant 4.57* 4.48* 2.73* 2.77* 4.54* 4.52* 4.22 4.28

(0.86) (0.87) (1.15) (1.17) (0.87) (0.87) (1.26) (1.25)

Observations 1,053 1,053 1,045 1,045 1,130 1,130 1,121 1,121

B. OG

SMP (higher scores = poorer memory)^a −0.02 0.01 −0.09* −0.02 0.03 −0.02 −0.08* −0.04

(0.03) (0.06) (0.04) (0.08) (0.04) (0.06) (0.04) (0.06)

Objective memory (higher scores = better memory)^a −0.01 −0.01 0.16* 0.16* 0.08* 0.08* 0.17* 0.17*

(0.03) (0.03) (0.04) (0.04) (0.04) (0.04) (0.04) (0.04)

Age 0.00 0.00 −0.04* −0.04* 0.00 0.00 −0.03* −0.03*

(0.00) (0.00) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01)

Gender (1 = female) 0.32* 0.32* 0.43* 0.43* 0.27* 0.27* 0.44* 0.44*

(0.05) (0.05) (0.07) (0.07) (0.05) (0.05) (0.07) (0.07)

Education (1 = college or more) −0.11* −0.10* 0.66* 0.66* 0.03 0.02 0.49* 0.49*

(0.05) (0.05) (0.10) (0.09) (0.06) (0.06) (0.09) (0.09)

At least one ADL problem (1 = yes) −0.03 −0.02 −0.10 −0.12 −0.06 −0.07 0.10 0.06

(0.10) (0.11) (0.14) (0.16) (0.10) (0.11) (0.13) (0.13)

Race (1 = non-White, 0 = White) 0.14 0.14 −0.36* −0.35* −0.16 −0.16 −0.46* −0.45*

(0.08) (0.08) (0.14) (0.15) (0.08) (0.08) (0.10) (0.10)

Depressive symptoms −0.04 −0.04 −0.05 −0.05 −0.04* −0.04* −0.03 −0.03

(0.02) (0.02) (0.04) (0.04) (0.02) (0.02) (0.03) (0.03)

Marital status 0.37 0.36 0.30 0.32 −0.34 −0.33 0.28 0.26

(0.21) (0.20) (0.26) (0.26) (0.20) (0.20) (0.25) (0.24)

Has a coresiding child (1 = yes) −0.08 −0.08 −0.30* −0.29* −0.13 −0.14 −0.04 −0.03

(0.11) (0.11) (0.13) (0.13) (0.10) (0.09) (0.13) (0.13)

SMP × Gender (1 = female) 0.03 −0.06 0.06 −0.07

(0.06) (0.08) (0.05) (0.06)

SMP × Education (1 = college or more) −0.05 −0.11 0.04 −0.06

(0.06) (0.09) (0.06) (0.08)

SMP × ADL problem (1 = yes) −0.07 0.10 0.03 0.18

(0.11) (0.12) (0.10) (0.10)

Constant 3.92* 3.92* 4.74* 4.72* 4.46* 4.46* 4.04* 4.05*

(0.42) (0.42) (0.50) (0.50) (0.40) (0.40) (0.50) (0.50)

Observations 1,980 1,980 1,949 1,949 1,993 1,993 1,957 1,957

Note. Standard errors are in parentheses. SMP = subjective memory problems; ADL = activity of daily living.

^a Standardized.

p < .05.

p < .01.

p < .001.

Looking at Table 3, panel A: Model 2, education was a significant moderator in predicting writing-based contact with both children and friends among YG. Negative effect of SMP on writing-based FOC with children and friends was more pronounced among those who are college educated than those with lower education. That is, among YG, SMP had a more detrimental effect on writing-based contact with children and friends when the respondent has higher education (see Figure 2a and b).

Figure 2.
Moderating effects of education in the relationship between subjective memory problems and writing-based interactions with children and friends (younger group). Significance level for a and b is 0.05.

Although SMP was not associated with FOC, better objective memory was associated with significantly more frequent writing-based contacts with both children and friends among both YG and OG. It was also associated with more frequent visits and phone calls with friends among OG. Other than memory, gender, education, race, and depressive symptoms were significantly associated with some or all of the outcomes in both samples. Marital status was a significant predictor of more frequent visit/call with children among YG, whereas having a coresiding children was associated with fewer e-mails/social media contact with children among OG. More depressive symptoms were associated with fewer visits and phone calls with both sources and fewer writing-based contact with friends among YG, whereas they were associated with fewer visits and phone calls with friends among OG.

Discussion

We draw on data from the HRS to examine (1) whether SMP is associated with perceived emotional support from and FOC with family and friends; and (2) the extent to which the relationship between SMP and support is moderated by (a) gender, (b) education, and (c) functional limitations. Our analyses revealed four findings that help us understand how subjective assessment of one’s memory can influence perceptions of support. First, we did not find SMP to affect perceptions of support for YG; among OG, however, SMP is associated with reduced perceived support from friends. Second, among YG, ADL positively moderates the association between SMP and support from children, whereas among OG, gender positively moderate the association between SMP and support from children. Third, we find no significant effect of SMP on FOC for YG. Among OG, however, SMP is predictive of reduced writing-based contact with children and friends. Fourth, we find that for YG, the effect of SMP on writing-based contact with both children and friends is contingent upon education.

Effect of SMP on Perceived Support From Family and Friends

While SMP did not significantly affect perceptions of support for the YG, among OG, SMP was associated with reduced perceived support from friends. While this finding is not consistent with our hypothesis that SMP will have a more detrimental effect on YG than OG because it is a nonnormative stressor for YG, it is possible that OG is more negatively affected by SMP because they have smaller network of friends (Van Tilburg, 1998). In addition, based on the exchange theory (Bengtson et al., 1997), it is logical to assume that older individuals with SMP, compared to their peers without memory problems, are more likely to perceive inequity of resources and consequently reduce social activities and disengage from relationships. Perceived support from adult children and spouse, however, may not be affected because family members tend to serve as their primary caregivers (Van Tilburg, 1998). Interesting to note is that depressive symptoms were negatively associated with perceptions of support from all sources in both YG and OG. This may suggest that it is not the SMP per se, but the depressive symptoms that often accompany memory problems (Solfrizzi et al., 2007), are a greater source of perceived deficiency in emotional support.

Functional Limitations Moderate Association Between SMP and Support From Adult Children

While SMP did not directly influence support from adult children among YG, we find that for those who have at least one difficulty in ADL, SMP had a positive effect on perceived support from children. Children may be more proactive in providing support to a parent who faces comorbidity (Reinhardt, 1996). For instance, if children think that SMP interferes with their parents’ ability to function or it adds to the already existing physical limitation, they may feel doubly obligated to offer support. Alternatively, given that adult children provide more support to parents with ADL needs (Hank, 2007; Kim et al., 2017; Silverstein et al., 1997), it is possible that support systems (e.g., regular visits and phone calls) already are in place for persons with a functional limitation and consequently, readily available to them in face of SMP.

Gender Moderates Association Between SMP and Support From Adult Children Among OG

Older women compared to older men, when experiencing SMP, report greater perceived support from adult children. We expected this, given that women, often socialized to be kin keepers (Cherlin, 2010), are involved not just in rearing children but in being their constant source of emotional support. Men, alternatively, are socialized to value professional achievements (Sheppard, 2018). In light of such gender variations, women may be in a better position to muster, solicit, and consequently receive support from their children when they have SMP. The actual receipt of support, in turn, could result in greater perceptions of it. Women, compared to men, may also feel more comfortable discussing memory changes, making it easier for them to maintain support and consequently perceive the availability of it. Moreover, “because of women’s kin-keeping roles, it is likely that their physical and psychological needs are more visible to their children than those of men” (Djundeva, Mills, Wittek, & Steverink, 2015, p. 984).

Effect of SMP on FOC With Friends and Family

While SMP did not significantly affect FOC for the YG, among OG, SMP led to reduced writing-based contact with both adult children and friends. As argued above in the case of the outcome of perceived support, we posit here that older individuals compared to their younger peers probably are more likely to reconfigure social networks and prioritize interactions based on a variety of factors, including changes in personal and heath resources (Carstensen, 1993; Van Tilburg, 1998). Changes in social engagement may consequently mean changes in FOC. What is interesting is that the changes in perceived FOC are limited to writing-based interactions. This probably is reflective of the fact that older adults may find it more comfortable to communicate face-to-face or via phone interactions with family and friends. Using computers to communicate (e.g., e-mails or social media) may be especially challenging with SMP (Meilak et al., 2016). In addition, writing-based communication may provide the opportunity to slow down and regulate interactions, consequently feeling reduced FOC. Alternatively, it also could be that both adult children and friends are more diligent about making in-person visits and phone calls while reducing writing-based contact.

Education Moderates the Association Between SMP and Contact With Children and Friends Among YG

We find that the negative effect of SMP on writing-based contact with both children and friends is more pronounced for those who have college education among YG. Although those who have college education in general show more frequent writing-based contact than those who have less education, the decline in the FOC that is associated with SMP is greater for those with college education. This is surprising because those with more education are more likely to utilize preexisting cognitive mechanisms or/and learn new ones to cope with memory changes (Steffener & Stern, 2012). This ability to actively cope with memory changes, we considered, may help those with more education to maintain continuity in the ways in which they interacted with family and friends. Clearly, our finding parts ways with our thinking on this matter. It is conceivable that those who are more educated may feel more stigmatized by and conceal their mental health problems (Borecki, Gozdzik-Zelazny, & Pokorski, 2010) and consequently disengage to avoid embarrassment and protect their self-worth. Alternatively, because highly educated persons are more resilient to age-related brain changes, by the time highly educated persons perceive signs of memory decline, the underlying pathology of cognitive decline may have progressed more than among those with lower education (Y. Stern, 2012), prohibiting them from engaging in writing-based interactions.

Several of the findings in our study support the stress process framework which suggests that context matters when assessing the impact of a stressor. In particular, among OG, the negative effect of SMP is significantly reduced for women compared to men, suggesting that women probably are better positioned to cope with SMP by soliciting support from children. Interestingly, having functional limitations is a facilitator (or protective factor) in YG’s getting support in the face of SMP. However, contrary to our expectation, education does not serve as a resource that mitigates the negative impact of SMP. Rather, our findings suggest that those who are highly educated may be more vulnerable to stigma associated with SMP and require more attention from health professionals. Our study also suggests the relevance of examining the link between SMP and support perceptions within the context of age. Research on dementia, for example, shows that while this health condition is devastating to all involved, the challenges associated with it vary based on age at diagnosis (Roach, Drummond, & Keady, 2016). Challenges associated with SMP similarly may be idiosyncratic based on the age—consequently differentially influencing perceptions of support and FOC based on the age of an individual.

The present study also highlights the importance of examining varied forms of support, given that different relationship types tend to provide different types of social support (Messeri, Silverstein, & Litwak, 1993). Looking at how SMP affects perceptions of support is even more important now than before given the shifting family structures, increasing childlessness, and consequently, changing social support systems (Ajrouch, Akiyama, & Antonnuci, 2007; Suanet, Van Tilburg, & Broese van Groenou, 2013). We are now more than ever before likely to see the growing significance of nonkin members in terms of support systems.

Limitations and Future Directions

Our study has a few limitations. First, we did not use longitudinal data because this study focuses on how different levels of subjective memory are associated with varying levels of social contact and support rather than intraindividual changes in social relationships due to changes in memory. Future studies, utilizing different data, would be well-advised to assess the impact of changes in subjective memory on changes in support. Second, because we included in the sample only those who can self-evaluate their memory, those who are more severely affected by memory problems and cannot complete the survey by themselves were excluded from our study. The effects of SMP may be underestimated due to such restrictions. Third, SMP can be tied to more than changes in memory itself. Like dementia, it can be tied to mood conditions/disorders, such as depression and anxiety (Ganguli, Du, Dodge, Ratcliff, & Chang, 2006; Hwang, Masterman, Ortiz, Fairbanks, & Cummings, 2004; Oi, 2017; Solfrizzi et al., 2007). While we control for depressive symptoms in our work, future studies on SMP and support perceptions should further examine this relationship by considering other mood conditions, such as major depressive disorder and anxiety.

While future research is needed to replicate our efforts, the findings here have clinical and policy implications. To date, focus of clinicians and researchers is on examining factors that predict dementia and objective memory decline. However, our study shows that SMP, which is not tantamount to dementia but remains highly correlated with objective memory decline, could potentially affect social health of individuals by altering their perceptions of support. Perceived social support, in turn, is predictive of enhanced mental, physical health, and cognitive health (Koropeckyj-Cox, 2002).

One way to help those struggling with SMP is to move away from looking at memory loss as a loss of self and intelligence because societal labels and attitudes pertaining to memory conditions—namely, dementia—likely and negatively shape the views individuals with SMP develop about themselves (Beard & Neary, 2013). While there may be fears associated with memory loss and reluctance to interact with persons with memory problems, learning about cognitive functioning can help potential support givers better understand loved ones with SMP. Subjective memory assessment also can be utilized to guide individuals with SMP to cognitive rehabilitation or alternative cognitive behavioral interventions, which would come handy when recognizing and coping with any further cognitive decline (Fyock & Hampstead, 2015). Those in the early stage of dementia, research shows, are much more malleable to learning new ways of coping with changes in their lives (Flood & Buckwalter, 2009). Those with SMP also may show similar willingness to learning new coping strategies in order to continue maintaining activities and relationships they enjoyed prior to their experience of memory problems. The efforts to cope with SMP, however, must be crafted based on sociopersonal characteristics of an individual. Our study, couched in the stress process framework, highlights that the association between SMP and support perceptions is far from uniform in nature. Instead, the impact of SMP on perceived support is to a great extent conditioned by personal resources such as gender, educational attainment, and functional health. Finally, social workers and therapists can help individuals with SMP to emotionally grapple with their experience; this is critical, given that older adults with poor memory often worry about developing dementia (Parikh et al., 2016). Being able to emotionally deal with memory changes can help with both alleviating fears of further memory decline and maintaining a stable perception of one’s social support.

Variables	N	Mean	SD	Minimum	Maximum
Dependent variables
Support from spouse	3,373	5.81	1.64	0	7
Support from children	3,132	5.73	1.70	0	7
Support from friends	3,124	5.98	1.30	0	7
FOC with children (visit or phone)	3,081	4.39	1.10	1	6
FOC with children (writing-based)	3,042	3.04	1.65	1	6
FOC with friends (visit or phone)	3,135	4.15	1.08	1	6
FOC with friends (writing-based)	3,090	2.60	1.53	1	6
Independent variables
Subjective memory (higher scores = poorer memory)^a	3,417	−0.09	0.99	−2.32	2.16
Objective memory (higher scores = better memory)^a	3,417	0.18	0.96	−3.38	2.73
Age	3,417	66.63	8.48	54	97
Gender (1 = female)	3,417	0.49	0.50	0	1
Education (1 = college or more)	3,402	0.59	0.49	0	1
At least one ADL problem (1 = yes, 0 = no)	3,417	0.11	0.31	0	1
Race (1 = non-White; 0 = White)	3,417	0.13	0.34	0	1
Depressive symptoms	3,417	1.00	1.64	0	8
Marital status	3,416	0.96	0.19	0	1
Has a coresiding child (1 = yes, 0 = no)	3,417	0.21	0.41	0	1

	Support From Spouse	Support From Children	Support From Friends
A. YG
SMP (higher scores = poorer memory)^a	0.07	0.11	−0.06	−0.25	−0.01	0.08
	(0.06)	(0.10)	(0.08)	(0.13)	(0.05)	(0.12)
Objective memory (higher scores = better memory)^a	0.09	0.09	0.11	0.11	0.07	0.07
	(0.07)	(0.07)	(0.10)	(0.10)	(0.06)	(0.06)
Age	0.01	0.01	−0.02	−0.02	−0.01	−0.02
	(0.01)	(0.01)	(0.02)	(0.02)	(0.01)	(0.01)
Gender (1= female)	−0.21	−0.23	0.19	0.24	0.52***	0.51***
	(0.12)	(0.13)	(0.12)	(0.12)	(0.09)	(0.10)
Education (1= college or more)	0.07	0.07	−0.12	−0.12	0.19	0.17
	(0.12)	(0.13)	(0.13)	(0.13)	(0.10)	(0.09)
At least one ADL problem (1=yes, 0 = no)	0.21	0.30	−0.65	−1.14**	−0.52**	−0.45*
	(0.23)	(0.26)	(0.43)	(0.37)	(0.18)	(0.20)
Race (1 = non-White, 0 = White)	−0.22	−0.23	0.39*	0.37*	−0.08	−0.09
	(0.16)	(0.16)	(0.18)	(0.17)	(0.12)	(0.11)
Depressive symtoms	−0.27***	−0.27***	−0.25***	−0.26***	−0.07**	−0.07*
	(0.04)	(0.04)	(0.05)	(0.05)	(0.02)	(0.03)
Marital status			0.06	0.07	0.06	0.04
			(0.40)	(0.35)	(0.18)	(0.18)
Has a coresiding child (1 = yes)	−0.16	−0.17	−0.52***	−0.49***	0.10	0.09
	(0.12)	(0.12)	(0.13)	(0.13)	(0.10)	(0.10)
SMP x Gender (1= female)		−0.06		0.15		−0.03
		(0.13)		(0.10)		(0.11)
SMP x Education (1 = college or more)		0.01		0.00		−0.09
		(0.10)		(0.13)		(0.10)
SMP x ADL problem (1 = yes)		−0.25		1.11***		−0.22
		(0.19)		(0.20)		(0.18)
Constant	5.43***	5.50***	6.97***	6.73***	6.52***	6.59***
	(0.78)	(0.79)	(1.30)	(1.28)	(0.81)	(0.80)
Observations	1,146	1,146	1,083	1,083	1,128	1,128

B. OG
SMP (higher scores = poorer memory)^a	0.01	−0.06	−0.03	−0.14*	−0.06	−0.06
	(0.04)	(0.06)	(0.03)	(0.07)	(0.03)	(0.05)
Objective memory (higher scores = better memory)^a	0.09	0.09	0.03	0.04	0.00	0.00
	(0.04)	(0.04)	(0.06)	(0.06)	(0.04)	(0.05)
Age	0.01	0.01	0.04***	0.04***	−0.00	−0.00
	(0.01)	(0.01)	(0.01)	(0.01)	(0.00)	(0.00)
Gender (1= female)	−0.14*	−0.14*	0.35***	0.34***	0.50***	0.50***
	(0.07)	(0.07)	(0.06)	(0.06)	(0.07)	(0.07)
Education (1= college or more)	0.08	0.08	0.02	0.02	0.08	0.08
	(0.08)	(0.08)	(0.09)	(0.09)	(0.08)	(0.08)
At least one ADL problem (1=yes, 0 = no)	−0.12	−0.14	−0.16	−0.19	0.10	0.12
	(0.14)	(0.14)	(0.15)	(0.16)	(0.09)	(0.09)
Race (1 = non-White, 0 = White)	−0.20	−0.20	0.24*	0.24*	−0.22	−0.23
	(0.11)	(0.11)	(0.10)	(0.09)	(0.16)	(0.16)
Depressive symtoms	−0.26***	−0.26***	−0.18***	−0.18***	−0.10**	−0.10*
	(0.03)	(0.03)	(0.03)	(0.03)	(0.04)	(0.04)
Marital status			0.55	0.56	0.50*	0.50*
			(0.34)	(0.34)	(0.25)	(0.24)
Has a coresiding child (1 = yes)	−0.01	−0.02	−0.17	−0.18	−0.16	−0.16
	(0.12)	(0.12)	(0.14)	(0.14)	(0.11)	(0.11)
SMP x Gender (1= female)		0.15		0.16*		0.02
		(0.09)		(0.08)		(0.06)
SMP x Education (1 = college or more)		−0.03		0.05		0.01
		(0.06)		(0.08)		(0.06)
SMP x ADL problem (1 = yes)		0.12		0.09		−0.10
		(0.14)		(0.11)		(0.07)
Constant	5.69***	5.68***	2.25***	2.24***	5.59***	5.59***
	(0.41)	(0.41)	(0.60)	(0.60)	(0.41)	(0.41)
Observations	2,058	2,058	1,998	1,998	1,984	1,984

	FOC With Children	FOC With Friends
A. YG
SMP (higher scores = poorer memory)^a	−0.06	−0.12	−0.12	−0.02	0.03	0.09	−0.01	0.21*
	(0.05)	(0.09)	(0.08)	(0.12)	(0.05)	(0.10)	(0.07)	(0.10)
Objective memory (higher scores = better memory)^a	0.01	0.01	0.15*	0.15*	0.04	0.04	0.18**	0.18**
(0.05)	(0.05)	(0.07)	(0.07)	(0.06)	(0.06)	(0.07)	(0.07)
Age	−0.01	−0.01	−0.00	−0.00	−0.01	−0.01	−0.04	−0.04
	(0.01)	(0.01)	(0.02)	(0.02)	(0.01)	(0.01)	(0.02)	(0.02)
Gender (1= female)	0.36***	0.39***	0.26**	0.27**	0.26***	0.25***	0.51***	0.49***
	(0.08)	(0.09)	(0.09)	(0.10)	(0.06)	(0.06)	(0.08)	(0.09)
Education (1= college or more)	−0.05	−0.06	0.61***	0.58***	0.05	0.04	0.56***	0.52***
	(0.10)	(0.10)	(0.15)	(0.14)	(0.08)	(0.08)	(0.12)	(0.12)
At least one ADL problem (1 = yes)	0.08	−0.00	−0.06	−0.05	−0.05	−0.10	0.03	0.07
	(0.21)	(0.25)	(0.26)	(0.29)	(0.15)	(0.18)	(0.21)	(0.22)
Race (1 = non-White, 0 = White)	0.15	0.14	−0.29	−0.30	0.10	0.09	−0.50***	−0.51***
	(0.12)	(0.11)	(0.18)	(0.18)	(0.09)	(0.09)	(0.14)	(0.13)
Depressive symptoms	−0.08**	−0.09**	−0.05	−0.05	−0.05*	−0.06*	−0.08*	−0.08*
	(0.03)	(0.03)	(0.04)	(0.04)	(0.03)	(0.03)	(0.03)	(0.03)
Marital status	0.53*	0.52*	0.40	0.38	−0.00	0.00	0.27	0.25
	(0.26)	(0.24)	(0.39)	(0.37)	(0.22)	(0.23)	(0.26)	(0.26)
Has a coresiding child (1 = yes)	−0.11	−0.10	0.00	−0.01	−0.01	−0.01	−0.07	−0.07
	(0.09)	(0.09)	(0.13)	(0.13)	(0.09)	(0.09)	(0.13)	(0.13)
SMP × Gender (1 = female)		0.15		0.08		−0.01		−0.08
		(0.08)		(0.11)		(0.09)		(0.10)
SMP × Education (1 = college or more)		−0.05		−0.23*		−0.10		−0.25*
		(0.08)		(0.11)		(0.09)		(0.11)
SMP × ADL problem (1 = yes)		0.21		−0.06		0.08		−0.20
		(0.17)		(0.23)		(0.15)		(0.14)
Constant	4.57***	4.48***	2.73*	2.77*	4.54***	4.52***	4.22**	4.28**
	(0.86)	(0.87)	(1.15)	(1.17)	(0.87)	(0.87)	(1.26)	(1.25)
Observations	1,053	1,053	1,045	1,045	1,130	1,130	1,121	1,121
B. OG
SMP (higher scores = poorer memory)^a	−0.02	0.01	−0.09*	−0.02	0.03	−0.02	−0.08*	−0.04
	(0.03)	(0.06)	(0.04)	(0.08)	(0.04)	(0.06)	(0.04)	(0.06)
Objective memory (higher scores = better memory)^a	−0.01	−0.01	0.16***	0.16***	0.08*	0.08*	0.17***	0.17***
	(0.03)	(0.03)	(0.04)	(0.04)	(0.04)	(0.04)	(0.04)	(0.04)
Age	0.00	0.00	−0.04***	−0.04***	0.00	0.00	−0.03***	−0.03***
	(0.00)	(0.00)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
Gender (1 = female)	0.32***	0.32***	0.43***	0.43***	0.27***	0.27***	0.44***	0.44***
	(0.05)	(0.05)	(0.07)	(0.07)	(0.05)	(0.05)	(0.07)	(0.07)
Education (1 = college or more)	−0.11*	−0.10*	0.66***	0.66***	0.03	0.02	0.49***	0.49***
	(0.05)	(0.05)	(0.10)	(0.09)	(0.06)	(0.06)	(0.09)	(0.09)
At least one ADL problem (1 = yes)	−0.03	−0.02	−0.10	−0.12	−0.06	−0.07	0.10	0.06
	(0.10)	(0.11)	(0.14)	(0.16)	(0.10)	(0.11)	(0.13)	(0.13)
Race (1 = non-White, 0 = White)	0.14	0.14	−0.36*	−0.35*	−0.16	−0.16	−0.46***	−0.45***
	(0.08)	(0.08)	(0.14)	(0.15)	(0.08)	(0.08)	(0.10)	(0.10)
Depressive symptoms	−0.04	−0.04	−0.05	−0.05	−0.04*	−0.04*	−0.03	−0.03
	(0.02)	(0.02)	(0.04)	(0.04)	(0.02)	(0.02)	(0.03)	(0.03)
Marital status	0.37	0.36	0.30	0.32	−0.34	−0.33	0.28	0.26
	(0.21)	(0.20)	(0.26)	(0.26)	(0.20)	(0.20)	(0.25)	(0.24)
Has a coresiding child (1 = yes)	−0.08	−0.08	−0.30*	−0.29*	−0.13	−0.14	−0.04	−0.03
	(0.11)	(0.11)	(0.13)	(0.13)	(0.10)	(0.09)	(0.13)	(0.13)
SMP × Gender (1 = female)		0.03		−0.06		0.06		−0.07
		(0.06)		(0.08)		(0.05)		(0.06)
SMP × Education (1 = college or more)		−0.05		−0.11		0.04		−0.06
		(0.06)		(0.09)		(0.06)		(0.08)
SMP × ADL problem (1 = yes)		−0.07		0.10		0.03		0.18
		(0.11)		(0.12)		(0.10)		(0.10)
Constant	3.92***	3.92***	4.74***	4.72***	4.46***	4.46***	4.04***	4.05***
	(0.42)	(0.42)	(0.50)	(0.50)	(0.40)	(0.40)	(0.50)	(0.50)
Observations	1,980	1,980	1,949	1,949	1,993	1,993	1,957	1,957

Footnotes

Acknowledgments

The authors would like to thank Yumi Shin for her research assistance.

Author Contributions

Jung-Hwa Ha and Manacy Pai have contributed equally to this work.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014S1A5A8016774).

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	Support From Spouse		Support From Children		Support From Friends
Variables	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2
A. YG
SMP (higher scores = poorer memory)^a	0.07	0.11	−0.06	−0.25	−0.01	0.08
	(0.06)	(0.10)	(0.08)	(0.13)	(0.05)	(0.12)
Objective memory (higher scores = better memory)^a	0.09	0.09	0.11	0.11	0.07	0.07
	(0.07)	(0.07)	(0.10)	(0.10)	(0.06)	(0.06)
Age	0.01	0.01	−0.02	−0.02	−0.01	−0.02
	(0.01)	(0.01)	(0.02)	(0.02)	(0.01)	(0.01)
Gender (1= female)	−0.21	−0.23	0.19	0.24	0.52***	0.51***
	(0.12)	(0.13)	(0.12)	(0.12)	(0.09)	(0.10)
Education (1= college or more)	0.07	0.07	−0.12	−0.12	0.19	0.17
	(0.12)	(0.13)	(0.13)	(0.13)	(0.10)	(0.09)
At least one ADL problem (1=yes, 0 = no)	0.21	0.30	−0.65	−1.14**	−0.52**	−0.45*
	(0.23)	(0.26)	(0.43)	(0.37)	(0.18)	(0.20)
Race (1 = non-White, 0 = White)	−0.22	−0.23	0.39*	0.37*	−0.08	−0.09
	(0.16)	(0.16)	(0.18)	(0.17)	(0.12)	(0.11)
Depressive symtoms	−0.27***	−0.27***	−0.25***	−0.26***	−0.07**	−0.07*
	(0.04)	(0.04)	(0.05)	(0.05)	(0.02)	(0.03)
Marital status			0.06	0.07	0.06	0.04
			(0.40)	(0.35)	(0.18)	(0.18)
Has a coresiding child (1 = yes)	−0.16	−0.17	−0.52***	−0.49***	0.10	0.09
	(0.12)	(0.12)	(0.13)	(0.13)	(0.10)	(0.10)
SMP x Gender (1= female)		−0.06		0.15		−0.03
		(0.13)		(0.10)		(0.11)
SMP x Education (1 = college or more)		0.01		0.00		−0.09
		(0.10)		(0.13)		(0.10)
SMP x ADL problem (1 = yes)		−0.25		1.11***		−0.22
		(0.19)		(0.20)		(0.18)
Constant	5.43***	5.50***	6.97***	6.73***	6.52***	6.59***
	(0.78)	(0.79)	(1.30)	(1.28)	(0.81)	(0.80)
Observations	1,146	1,146	1,083	1,083	1,128	1,128

B. OG
SMP (higher scores = poorer memory)^a	0.01	−0.06	−0.03	−0.14*	−0.06	−0.06
	(0.04)	(0.06)	(0.03)	(0.07)	(0.03)	(0.05)
Objective memory (higher scores = better memory)^a	0.09	0.09	0.03	0.04	0.00	0.00
	(0.04)	(0.04)	(0.06)	(0.06)	(0.04)	(0.05)
Age	0.01	0.01	0.04***	0.04***	−0.00	−0.00
	(0.01)	(0.01)	(0.01)	(0.01)	(0.00)	(0.00)
Gender (1= female)	−0.14*	−0.14*	0.35***	0.34***	0.50***	0.50***
	(0.07)	(0.07)	(0.06)	(0.06)	(0.07)	(0.07)
Education (1= college or more)	0.08	0.08	0.02	0.02	0.08	0.08
	(0.08)	(0.08)	(0.09)	(0.09)	(0.08)	(0.08)
At least one ADL problem (1=yes, 0 = no)	−0.12	−0.14	−0.16	−0.19	0.10	0.12
	(0.14)	(0.14)	(0.15)	(0.16)	(0.09)	(0.09)
Race (1 = non-White, 0 = White)	−0.20	−0.20	0.24*	0.24*	−0.22	−0.23
	(0.11)	(0.11)	(0.10)	(0.09)	(0.16)	(0.16)
Depressive symtoms	−0.26***	−0.26***	−0.18***	−0.18***	−0.10**	−0.10*
	(0.03)	(0.03)	(0.03)	(0.03)	(0.04)	(0.04)
Marital status			0.55	0.56	0.50*	0.50*
			(0.34)	(0.34)	(0.25)	(0.24)
Has a coresiding child (1 = yes)	−0.01	−0.02	−0.17	−0.18	−0.16	−0.16
	(0.12)	(0.12)	(0.14)	(0.14)	(0.11)	(0.11)
SMP x Gender (1= female)		0.15		0.16*		0.02
		(0.09)		(0.08)		(0.06)
SMP x Education (1 = college or more)		−0.03		0.05		0.01
		(0.06)		(0.08)		(0.06)
SMP x ADL problem (1 = yes)		0.12		0.09		−0.10
		(0.14)		(0.11)		(0.07)
Constant	5.69***	5.68***	2.25***	2.24***	5.59***	5.59***
	(0.41)	(0.41)	(0.60)	(0.60)	(0.41)	(0.41)
Observations	2,058	2,058	1,998	1,998	1,984	1,984

	FOC With Children				FOC With Friends
	Visit or Phone		Writing-Based		Visit or Phone		Writing-Based
Variables	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2
A. YG
SMP (higher scores = poorer memory)^a	−0.06	−0.12	−0.12	−0.02	0.03	0.09	−0.01	0.21*
	(0.05)	(0.09)	(0.08)	(0.12)	(0.05)	(0.10)	(0.07)	(0.10)
Objective memory (higher scores = better memory)^a	0.01	0.01	0.15*	0.15*	0.04	0.04	0.18**	0.18**
Objective memory (higher scores = better memory)^a	(0.05)	(0.05)	(0.07)	(0.07)	(0.06)	(0.06)	(0.07)	(0.07)
Age	−0.01	−0.01	−0.00	−0.00	−0.01	−0.01	−0.04	−0.04
	(0.01)	(0.01)	(0.02)	(0.02)	(0.01)	(0.01)	(0.02)	(0.02)
Gender (1= female)	0.36***	0.39***	0.26**	0.27**	0.26***	0.25***	0.51***	0.49***
	(0.08)	(0.09)	(0.09)	(0.10)	(0.06)	(0.06)	(0.08)	(0.09)
Education (1= college or more)	−0.05	−0.06	0.61***	0.58***	0.05	0.04	0.56***	0.52***
	(0.10)	(0.10)	(0.15)	(0.14)	(0.08)	(0.08)	(0.12)	(0.12)
At least one ADL problem (1 = yes)	0.08	−0.00	−0.06	−0.05	−0.05	−0.10	0.03	0.07
	(0.21)	(0.25)	(0.26)	(0.29)	(0.15)	(0.18)	(0.21)	(0.22)
Race (1 = non-White, 0 = White)	0.15	0.14	−0.29	−0.30	0.10	0.09	−0.50***	−0.51***
	(0.12)	(0.11)	(0.18)	(0.18)	(0.09)	(0.09)	(0.14)	(0.13)
Depressive symptoms	−0.08**	−0.09**	−0.05	−0.05	−0.05*	−0.06*	−0.08*	−0.08*
	(0.03)	(0.03)	(0.04)	(0.04)	(0.03)	(0.03)	(0.03)	(0.03)
Marital status	0.53*	0.52*	0.40	0.38	−0.00	0.00	0.27	0.25
	(0.26)	(0.24)	(0.39)	(0.37)	(0.22)	(0.23)	(0.26)	(0.26)
Has a coresiding child (1 = yes)	−0.11	−0.10	0.00	−0.01	−0.01	−0.01	−0.07	−0.07
	(0.09)	(0.09)	(0.13)	(0.13)	(0.09)	(0.09)	(0.13)	(0.13)
SMP × Gender (1 = female)		0.15		0.08		−0.01		−0.08
		(0.08)		(0.11)		(0.09)		(0.10)
SMP × Education (1 = college or more)		−0.05		−0.23*		−0.10		−0.25*
		(0.08)		(0.11)		(0.09)		(0.11)
SMP × ADL problem (1 = yes)		0.21		−0.06		0.08		−0.20
		(0.17)		(0.23)		(0.15)		(0.14)
Constant	4.57***	4.48***	2.73*	2.77*	4.54***	4.52***	4.22**	4.28**
	(0.86)	(0.87)	(1.15)	(1.17)	(0.87)	(0.87)	(1.26)	(1.25)
Observations	1,053	1,053	1,045	1,045	1,130	1,130	1,121	1,121
B. OG
SMP (higher scores = poorer memory)^a	−0.02	0.01	−0.09*	−0.02	0.03	−0.02	−0.08*	−0.04
	(0.03)	(0.06)	(0.04)	(0.08)	(0.04)	(0.06)	(0.04)	(0.06)
Objective memory (higher scores = better memory)^a	−0.01	−0.01	0.16***	0.16***	0.08*	0.08*	0.17***	0.17***
	(0.03)	(0.03)	(0.04)	(0.04)	(0.04)	(0.04)	(0.04)	(0.04)
Age	0.00	0.00	−0.04***	−0.04***	0.00	0.00	−0.03***	−0.03***
	(0.00)	(0.00)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
Gender (1 = female)	0.32***	0.32***	0.43***	0.43***	0.27***	0.27***	0.44***	0.44***
	(0.05)	(0.05)	(0.07)	(0.07)	(0.05)	(0.05)	(0.07)	(0.07)
Education (1 = college or more)	−0.11*	−0.10*	0.66***	0.66***	0.03	0.02	0.49***	0.49***
	(0.05)	(0.05)	(0.10)	(0.09)	(0.06)	(0.06)	(0.09)	(0.09)
At least one ADL problem (1 = yes)	−0.03	−0.02	−0.10	−0.12	−0.06	−0.07	0.10	0.06
	(0.10)	(0.11)	(0.14)	(0.16)	(0.10)	(0.11)	(0.13)	(0.13)
Race (1 = non-White, 0 = White)	0.14	0.14	−0.36*	−0.35*	−0.16	−0.16	−0.46***	−0.45***
	(0.08)	(0.08)	(0.14)	(0.15)	(0.08)	(0.08)	(0.10)	(0.10)
Depressive symptoms	−0.04	−0.04	−0.05	−0.05	−0.04*	−0.04*	−0.03	−0.03
	(0.02)	(0.02)	(0.04)	(0.04)	(0.02)	(0.02)	(0.03)	(0.03)
Marital status	0.37	0.36	0.30	0.32	−0.34	−0.33	0.28	0.26
	(0.21)	(0.20)	(0.26)	(0.26)	(0.20)	(0.20)	(0.25)	(0.24)
Has a coresiding child (1 = yes)	−0.08	−0.08	−0.30*	−0.29*	−0.13	−0.14	−0.04	−0.03
	(0.11)	(0.11)	(0.13)	(0.13)	(0.10)	(0.09)	(0.13)	(0.13)
SMP × Gender (1 = female)		0.03		−0.06		0.06		−0.07
		(0.06)		(0.08)		(0.05)		(0.06)
SMP × Education (1 = college or more)		−0.05		−0.11		0.04		−0.06
		(0.06)		(0.09)		(0.06)		(0.08)
SMP × ADL problem (1 = yes)		−0.07		0.10		0.03		0.18
		(0.11)		(0.12)		(0.10)		(0.10)
Constant	3.92***	3.92***	4.74***	4.72***	4.46***	4.46***	4.04***	4.05***
	(0.42)	(0.42)	(0.50)	(0.50)	(0.40)	(0.40)	(0.50)	(0.50)
Observations	1,980	1,980	1,949	1,949	1,993	1,993	1,957	1,957