The Association Between Views of Aging and Subjective Cognitive Complaints in Older Adults: Findings From Two Samples

Abstract

This cross-sectional study examined whether views of aging (VoA) relate to subjective cognitive complaints in two separate cohorts of older adults. Ageist attitudes, attitudes to aging (psychological loss, physical change, and psychological growth), subjective age, and subjective successful aging were examined. A moderating effect of chronological age was also examined. Samples included 572 adults aged 50 or older (Sample 1; mean age = 67.63, SD = 11.39, 49.4% female) and 224 adults aged 65 or older (Sample 2; mean age = 81.50, SD = 6.61, 75.3% female). More negative VoA (higher ageist attitudes, lower psychological growth, lower physical change, older subjective age, and less successful aging) were associated with more subjective cognitive complaints after controlling for covariates. An increase in chronological age strengthened some of these associations. Findings suggest that improving dimensions of VoA may have a complementary positive effect on subjective cognitive complaints in older adults.

Keywords

views of aging subjective cognitive complaints older adults subjective age ageist attitudes

Population-based studies of subjective cognitive complaints (SCCs) suggest that 50–80% of older adults who perform within the normal range on objective cognitive tests endorse SCC (Jessen et al., 2020). A meta-analysis found that over four years, 26.6% of older people with subjective memory complaints will progress to mild cognitive impairment and 14.1% will progress to dementia (Mitchell et al., 2014; also see Mendonça et al., 2016). Even in the absence of dementia risk, SCC can have a negative impact on older adults’ well-being, contributing to fear of becoming demented, associated mood changes, and the implementation of behavioral changes in order to accommodate perceived difficulties or alleviate worries (Comijs et al., 2002). Thus, understanding the factors that associate with SCC outside of objective cognitive functioning is important to our attempt to support the well-being of individuals through the aging process.

Previous studies suggest that in individuals who do not show actual cognitive impairment, SCC may reflect psycho-affective or health problems (Burmester et al., 2016; Comijs et al., 2002; Reid & MacLullich, 2006). For example, in a meta-analysis by Reid and MacLullich (2006), the authors found subjective memory complaints to be consistently related to depression and neuroticism. In a study by Comijs et al. (2002) of older adults with no manifest cognitive decline, memory complaints associated with physical health problems, depressive and anxiety symptoms, low feelings of mastery, low perceived self-efficacy, and high neuroticism. The authors suggested that adequate intervention to address psycho-affective or health problems might improve quality of life in individuals with cognitive complaints as long as they have no objective cognitive impairment. In their meta-analysis, Burmester et al. (2016) discuss the possibility that beliefs about age-related declines may explain the link between depression and SCC.

Views of aging (VoA), or one’s introspective belief set about aging and older adults (Brown et al., 2020; Levy, 2009; Palgi et al., 2021), have been shown to predict various markers of health and well-being in old age, including physical health (B. R. Levy, M. D. Slade, & S. V. Kasl, 2002), mortality (B. R. Levy, M. D. Slade, S. R. Kunkel, et al., 2002; Sargent−Cox et al., 2014), and objective cognitive functioning (Brown et al., 2020; Robertson et al., 2016; Siebert et al., 2020). Age stereotype embodiment theory states that people internalize stereotypes about aging that they encounter over the years and this internalization causes them to develop negative VoA (Levy, 2009). According to Levy (2009), old-age cues at the interpersonal and institutional level prompt people to assign self-relevance to these age stereotypes. Longitudinal studies examining the trajectory of VoA have demonstrated that VoA become less positive as individuals age (Diehl et al., 2021; Miche et al., 2014). Given findings that negative VoA have about a threefold greater effect on behavior than positive VoA (Meisner, 2012), this raises the possibility that the influence of VoA on various health markers strengthens with increasing age. Consistent with this prediction, Siebert et al. (2020) found that attitudes to aging predicted objective cognitive changes over a 20-year period in older participants (over 60 years old) but not in younger participants (between 40 and 60 years old).

More recently, researchers in the field of VoA have proposed conceptual frameworks to encompass the different aspects of VoA (e.g., Diehl et al., 2014; Wurm et al., 2017). For example, a review by Wurm et al. (2017) divide VoA into two categories: “age stereotypes” which represent socially shared beliefs about the process of aging and thus reflect older adults’ more generalized views of older adults and the aging process; “subjective aging” which represents individual’s feelings regarding their own aging process and thus reflects older adults’ more personal views of the aging process. Both categories of VoA have been shown to have long-term effects on health, including cognitive, psychological, and physical health outcomes (for review, see Wurm et al., 2017). Few studies have investigated how VoA relate to SCC, and the studies that have looked at this association have examined the measure of subjective age specifically (Hülür et al., 2015; Segel-Karpas & Palgi, 2019; Stephan et al., 2020; for an exception, see Siebert et al., 2020). However, given the abovementioned studies, it stands to reason that various other indicators of VoA (encompassing both generalized and personal VoA, see below) may influence a person’s perceived cognitive abilities, and may do so more powerfully in older age groups.

In this regard, a well-known change associated with aging is age-related cognitive decline (Harada et al., 2013). The awareness of this fact is a source of great anxiety and stress for many older adults (Corner & Bond, 2004; Hodgson & Cutler, 1997). Individuals with negative VoA may be more attune to subtle cognitive changes that arise as part of the normal aging process. Similarly, such individuals may interpret neutral situations or minor cognitive mistakes that are common across all age groups as evidence of cognitive decline due to aging. This notion is supported by the finding that negative VoA is associated with a tendency to attribute physical health changes to the process of aging rather than to illnesses (Keller et al., 1989; Sarkisian et al., 2002), a tendency that has been associated with less adaptive psychological and health outcomes (Wurm et al., 2013). Similarly, individuals with negative VoA may show a tendency to interpret subtle cognitive changes or minor cognitive mistakes as a sign of cognitive decline due to inevitabilities of aging rather than due to other causes (e.g., stress and lack of sleep), thereby negatively influencing their own impressions of their cognitive abilities.

Using two separate cross-sectional samples, we examined the association between different VoA indicators, including generalized aspects of VoA (ageist attitudes) and personal aspects of VoA (subjective age, attitudes to aging, and subjective successful aging) on the one hand, and SCC on the other hand. We hypothesized that both generalized and personal aspects of negative VoA will associate with more SCC, after controlling for demographic covariates of sex, education, and economic status. Given evidence that VoA become more negative with increasing age (Diehl et al., 2021; Miche et al., 2014) and are therefore expected to have a stronger impact on health outcomes (Wurm et al., 2017), we additionally hypothesized that the association between generalized and personal VoA and SCC will be modified by chronological age and will be stronger in older individuals. Finally, we hypothesized that the association between VoA and SCC will persist after controlling for objective cognition. We addressed the first two hypotheses through two samples (Sample 1 and Sample 2) and examined the third hypothesis in a sample (Sample 2) that included a brief screening measure of objective cognition, the Mini-Mental State Examination (MMSE).

Method

Participants and Procedure

Sample 1. The sample included 572 participants over the age of 50, 565 of whom responded to the SCC questionnaire and were thus included in the current analyses (mean age = 67.63, SD = 11.39, range = 50–96, 49.4% female).

Participants in Sample 1 were part of a larger research study that examined VoA and well-being in adults over the age of 29 (Bodner et al., 2021; Shrira et al., 2015, 2020). Research assistants approached eligible participants by means such as snowball sampling and through online social media platforms. They asked them to take part in an online survey as volunteers. Inclusion criteria included being over 29 years old, speaking Hebrew, living in the community, and denying a diagnosis of severe cognitive impairment or dementia. All participants completed online booklets of questionnaires during a baseline assessment and at the end of the study, after 14 days. Only baseline measurements were considered in the present study.

Sample 2. This convenience sample included 224 older adults aged 65 or older who lived in the community or in nursing homes. Recruitment began by placing advertisements in the community, and approaching various nursing homes in Israel, ultimately leading to a snowball sampling approach. Inclusion criteria included being age 65 or older and Hebrew-speaking. A previous study investigating factors older adults consider to be important when rating subjective nearness to death has been published using this sample (Palgi et al., 2019). In the present study, one participant did not respond to the SCC questionnaire and thus was not included in the analyses, leaving a final sample of 223 participants (mean age = 81.50, SD = 6.61, range = 66–97, 75.3% female).

Questionnaires were administered to participants by trained research assistants. Participants were interviewed in their homes or in quiet areas of public spaces such as community centers. Interviews lasted approximately 1 hour.

Bar-Ilan University’s Institutional Review Board reviewed and approved all procedures of both studies, and all participants from both samples provided written consent to participate in the study.

Measures

Generalized VoA Measures

Ageist attitudes questionnaire

Participants from Sample 1 responded to a 20-item scale that assesses ageist attitudes based on the notion that older people are expected to relinquish both actual and symbolic resources so that younger age groups receive their turn (North & Fiske, 2013; see Koren et al., 2020 for the Hebrew version). The scale targets ageist attitudes across three prescriptive stereotypes: succession-based stereotypes (8 items) reflect the expectation that older adults will step aside so that younger adults can acquire enviable resources (e.g., employment and political opportunities; e.g., “Most older workers do not know when it is time to make way for the younger generation.”); consumption-based stereotypes (7 items) focus on the depletion of currently shared resources by older people (e.g., “Doctors spend too much time treating sickly older people.”); and identity-based stereotypes (5 items) reflect the expectation that participation of older adults in activities usually reserved for younger people should be limited (e.g., “Older people should not even try to act cool.”). Participants rated responses on a scale ranging from 1 (“strongly disagree”) to 6 (“strongly agree”). We calculated an average score across all items of all subscales. Possible scores ranged from 1 to 6, with higher scores indicating higher levels of ageist attitudes. This scale was considered as a whole as we were interested in overall negative feelings towards older adults, which all of the subscales capture. High reliability for this scale has been reported previously in lifespan cohorts (Koren et al., 2020; North & Fiske, 2013). Cronbach’s alpha in the current study was 0.91. This is in line with the high reliability (alpha = 0.90) of this measure reported in the literature (North & Fiske, 2013).

Personal VoA Measures

Subjective age

Participants from both Sample 1 and Sample 2 completed the Barak and Schiffman (1981) subjective age measure (see Hoffman et al., 2016 for the Hebrew version). Participants were asked to “please report how you feel most of the time during the day” in reference to four subjective age perceptions: mental age, physical age, appearance age, and behavior age. Responses were provided on a five-point scale, ranging from (1) “much younger than my age” to (5) “much older than my age.” We calculated the average score across the five items. Possible scores ranged from 1 to 5, with higher scores indicating higher subjective age. Cronbach’s alpha for Sample 1 was 0.79 and 0.72 for Sample 2. Past studies report alpha levels ranging from 0.83 to 0.97 (Avidor et al., 2016, 2018; Bodner et al., 2021).

Attitudes to aging

Participants in Sample 1 completed the 24-item Attitudes to Aging questionnaire (Laidlaw et al., 2018; see A. Shrira, L. Ayalon, et al., 2017 for the Hebrew version). Three subscales reflecting negative (psychological loss) and positive (physical change and psychological growth) attitudes to aging are derived from the questionnaire. The psychological loss subscale (8 items) refers to seeing old age as a negative experience, involving psychological and social losses (e.g., “I feel excluded from things because of my age”). The physical change subscale (8 items) focuses on health and exercise in the context of aging (e.g., “Growing old has been easier than I thought”). The psychological growth subscale (8 items) reflects positive gains that people attribute to themselves and to others (e.g., “I want to give a good example to younger people”). Participants rated items on a scale ranging from 1 (“completely disagree”) to 5 (“completely agree”). We calculated mean of ratings for each subscale and considered each scale separately in the present analyses. For each subscale, possible scores ranged from 1 to 5. We made the decision to consider subscales separately given evidence that a loss−related view of aging is more strongly associated with health compared to a gain−related view of aging (Brothers et al., 2017). For the overall measure, Cronbach’s alpha in the current study was 0.88. Cronbach’s alpha for each separate subscale was 0.90 for psychological loss, 0.79 for physical change, and 0.83 for psychological growth. Previous studies also reported alpha values in this range (e.g., 0.81–0.86 for psychological loss, 0.81–0.90 for physical change, and 0.74–0.82 for psychological growth; Laidlaw et al., 2010; A. Shrira, L. Ayalon, et al., 2017).

Subjective Successful Aging

Subjective successful aging (Pruchno et al., 2010) was assessed with three items (e.g., “I can say that I have reached my current age successfully”). Participants in Sample 2 rated each item on a five-point scale from one “completely disagree” to five “completely agree.” We calculated the average rating of all three items together, with higher scores indicating greater subjective successful aging. Possible scores ranged from 1 to 5. Cronbach’s alpha was 0.80, in line with previous studies reporting an alpha of 0.84 (A. Shrira, D. Shmotkin, et al., 2017) and 0.79 (Shrira, 2016).

Subjective Cognitive Complaints (SCC)

An adapted version of the Cognitive Status Questionnaire (Pearlin et al., 1990) served to measure SCC (Palgi et al., 2019) for both Sample 1 and Sample 2. The adapted questionnaire was comprised of eight items that reflect different cognitive abilities (e.g., “Remember recent events” and “Speak sentences”). Participants were asked to rate items according to the difficulty of each ability for them personally on a four-point scale, ranging from 1 (“not difficult at all”) to 4 (“very difficult”). A time span was not specified. We calculated an average score across all items, with higher scores reflecting greater cognitive complaints. Possible scores ranged from 1 to 4. Cronbach’s alpha was 0.78 for Sample 1 and 0.60 for Sample 2. Past studies by our group reported Cronbach’s alpha of 0.84 (Bodner et al., 2015) and 0.80 (Shrira, 2016).

The Mini-Mental State Examination (MMSE)

Participants in Sample 2 completed the MMSE (Folstein et al. 1975). The MMSE is a 30-item screening measure of global cognition. The Hebrew translation of the MMSE was used in this study (Werner et al., 1999). The test briefly examines functions of orientation, attention, calculation, recall, language, and visual construction. Scores range from 0 to 30, with higher scores indicating better cognitive functioning.

Chronological Age

Chronological age was calculated by subtracting participants’ year of birth from the year of the assessment.

Covariates

Covariates including sex, education, and economic status were selected for their known associations with SCC (e.g., Caracciolo et al., 2012; Lucas et al., 2016; Tomita et al., 2014). Sex included male (coded as 1) or female (coded as 2). Education was assessed using a five-point scale (0 = “no formal education” to 5 = “academic degree”). Economic status was assessed on a five-point scale (1 = “not good at all” to 5 = “very good”).

Statistical Analyses

All continuous variables were assessed for normality and outliers, and residuals of the regression models were examined for violation of the normality assumption.

Bivariate Spearman correlations were performed between each of the VoA variables (ageist attitudes, psychological loss, physical change, psychological growth, and subjective age in Sample 1; subjective age and subjective successful aging in Sample 2) and SCC. VoA variables that were significantly associated with SCC in bivariate analyses were entered into separate multiple linear regression models that adjusted for education, self-rated economic status, and sex. The MMSE was an additional covariate in analyses conducted using Sample 2. Continuous predictor variables were centered to the mean in all regression models. The main effects of age, the VoA variable, and the interaction of age by the VoA variable were examined for their association with SCC. Bonferroni corrections were used to adjust for multiple comparisons. As follow-up exploratory analyses, we investigated whether the VoA variables would differentially relate to the various items in the SCC questionnaire, which vary by both the types of cognitive functions (e.g., language and memory) assessed and the severity of the cognitive complaint (e.g., from severe - difficulty following simple instructions, to less severe - word finding difficulties). To this end, we performed bivariate Spearman correlations to examine the association between each VoA variable and each item on the SCC questionnaire.

Results

Participant Demographics

Tables 1 and 2 present descriptive statistics of demographic characteristics and variables of interest for Sample 1 and Sample 2, respectively. As for education in Sample 1, 23 participants (4.1%) reported no formal education, 37 (6.5%) reported elementary education, 64 (11.3%) reported incomplete high school education, 124 (21.9%) reported complete high school education, 87 (15.4%) reported several years of post-high school education with no academic degree, and 228 (40.4%) reported obtaining an academic degree. Two participants (0.4%) did not report their education level. As for education in Sample 2, six participants (2.7%) reported no formal education, five (2.2%) reported elementary education, 31 (13.9%) reported incomplete high school education, 30 (13.5%) reported complete high school education, 50 (22.4%) reported several years of post-high school education with no academic degree, and 100 (44.8%) reported obtaining an academic degree. One participant (0.4%) did not report education. With regard to self-reported economic status of Sample 1, 34 participants (6.0%) reported “not good at all,” 83 (14.7%) reported “not so good,” 188 (33.3%) reported “pretty good,” 189 (33.5%) reported “good,” and 61 (10.8%) reported “very good.” 10 participants (1.8%) did not report their economic status. With regard to self-reported economic status of Sample 2, two participants (0.9%) reported “not good at all,” 13 (5.8%) reported “not so good,” 49 (22.0%) reported “pretty good,” 126 (56.5%) reported “good,” and 31 (13.9%) reported “very good.” Two participants (0.9%) did not report their economic status.

Table 1.

Distribution of participant characteristics, views of aging indices, and subjective cognitive complaints in Sample 1.

	N	M	SD	Range
Age	565	67.63	11.39	50–96
Sex (% female)	565	49.40%	—	—
Education	563	3.60	1.47	0–5
Economic status	555	3.29	1.05	1–5
Ageist attitudes (mean)	435	2.40	0.78	1−5.05
Attitudes to aging
Psychological loss (sum)	561	2.12	0.86	1−4.88
Physical change (sum)	557	3.44	0.84	1−5
Psychological growth (sum)	559	3.74	0.70	1−5
Subjective age (mean)	560	2.36	0.63	1−4.50
SCC (mean)	565	1.27	0.40	1−4

Note. M = mean, SD = standard deviation; education was assessed on a five-point scale: (0 = “no formal education,” 1 = “elementary education,” 2 = “incomplete high school,” 3 = “complete high school,” 4 = “beyond high school,” and 5 = “academic degree”). Economic status was assessed on a five-point scale (1 = “not good at all,” 2 = “not so good,” 3 = “pretty good,” 4 = “good,” and 5 = “very good”). SCC = subjective cognitive complaints.

Table 2.

Distribution of participant characteristics, views of aging indices, and subjective cognitive complaints in Sample 2

	N	M	SD	Range
Age	222	81.50	6.61	66–97
Sex (% female)	223	75.30%	—	—
Education	222	4.86	1.33	1–6
Economic status	221	3.77	0.79	1–5
Mini-mental state examination	218	27.47	2.50	16–30
Subjective age (mean)	219	2.29	0.71	1–5
Subjective successful aging (mean)	215	4.08	0.80	1–5
SCC (mean)	223	1.35	0.29	1–2.63

Bivariate Associations of VoA Indices and SCC

A large number of participants from Sample 1 (n = 241, 42.7%) and from Sample 2 (n = 34, 15.2%) chose the “not difficult at all” response option for all items on the SCC questionnaire, reflecting no cognitive complaints and contributing to a positive skew of this variable. Thus, bivariate correlations were tested using Spearman’s rho and the variable was transformed to correct for non-normal residuals of the multiple regression models using a [ln(mean SCC score–0.25)] function.

Sample 1 correlations

Correlations were considered significant at a Bonferroni corrected p-value of .01. Significant correlations emerged between ageist attitudes and SCC (r_s = 0.178, p < .001). All three subscales of the Attitudes to Aging questionnaire correlated with SCC (psychological loss: r_s = 0.301, p < .001; physical change: r_s = −0.257, p < .001; psychological growth: r_s = −0.173, p < .001), as did the subjective age measure (r_s = 0.174, p < .001). In general, more negative VoA were associated with more SCC.

Sample 2 correlations

Spearman correlations were considered significant at a Bonferroni corrected p-value of .025. The correlation between subjective age and SCC was significant (r_s = 0.204, p = .002), as was the correlation between subjective successful aging and SCC (r_s = −0.233, p = .001). In both cases, more VoA were correlated with greater SCC.

Multiple Linear Regression Models Examining Associations between VoA Indices and SCC

To determine whether specific VoA indices are associated with SCC, separate multiple linear regression models were performed for each VoA index that was significantly correlated with SCC in the bivariate analyses (i.e., ageist attitudes, psychological loss, physical change, psychological growth, and subjective age in Sample 1; subjective age and subjective successful aging in Sample 2). Coefficients are reported in Tables 3 and 4 and are considered significant at a Bonferroni corrected p-value of .01 for Sample 1 and a p-value of .025 for Sample 2.

Table 3.

Association between the five different views of aging indices and subjective cognitive complaints in Sample 1.

	Ageist attitudes (N = 424)				Psychological loss (N = 548)				Physical change (N = 544)				Psychological growth (N = 546)				Subjective Age (N = 547)
	Model 1 $R_{a d j}^{2}$ = 0.170		Model 2 $R_{a d j}^{2} = 0.174$		Model 1 $R_{a d j}^{2} = 0.182$		Model 2 $R_{a d j}^{2} = 0.191$		Model 1 $R_{a d j}^{2} = 0.169$		Model 2 $R_{a d j}^{2} = 0.181$		Model 1 $R_{a d j}^{2} = 0.154$		Model 2 $R_{a d j}^{2} = 0.161$		Model 1 $R_{a d j}^{2} = 0.147$		Model 2 $R_{a d j}^{2}$ = 0.170
	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE
Sex	−0.021	0.026	−0.027	0.026	−0.018	0.024	−0.020	0.024	−0.011	0.024	−0.020	0.024	−0.021	0.024	−0.019	0.024	−0.015	0.024	−0.017	0.024
Education	−0.013	0.010	−0.018	0.010	−0.085	0.009	−0.078	0.009	−0.068	0.009	−0.062	0.009	−0.090	0.009	−0.086	0.009	−0.094	0.009	−0.075	0.009
Economic status	−0.172*	0.015	−0.168**	0.015	−0.029	0.012	−0.024	0.012	−0.036	0.012	−0.036	0.012	−0.055	0.012	−0.057	0.012	−0.047	0.012	−0.045	0.012
Age	0.324**	0.001	0.322**	0.001	0.294**	0.001	0.275**	0.001	0.283**	0.001	0.276**	0.001	0.310**	0.001	0.307**	0.001	0.304**	0.001	0.291**	0.001
VoA index	0.157****	0.017	0.152*	0.017	0.231**	0.014	0.223**	0.014	−0.211**	0.015	−0.185**	0.015	−0.156**	0.017	−0.145**	0.017	0.124*	0.020	0.109*	0.019
Age * VoA index			0.077	0.001			0.104*	0.001			−0.117*	0.001			−0.092	0.002			0.158**	0.002

Note. Model 1 regressed covariates, age, and the specific VoA index under investigation on subjective cognitive complaints. Model 2 added the age by VoA interaction term. VoA = views of aging; R²_adj = adjusted R²; SE = standard error; Males are coded as 1 and females as 2.

p < .01; p < .001.

Table 4.

Association between views of aging indices and subjective cognitive complaints in Sample 2

	Subjective age (N = 210)						Subjective successful aging (N = 206)
	Model 1 $R_{a d j}^{2}$ = 0.030		Model 2 $R_{a d j}^{2}$ = 0.039		Model 3 $R_{a d j}^{2}$ = 0.058		Model 1 $R_{a d j}^{2}$ = 0.045		Model 2 $R_{a d j}^{2}$ = 0.051		Model 3 $R_{a d j}^{2}$ = 0.051
	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE	$β$	SE
	Sex	−0.053	0.040	−0.044	0.040	−0.046	0.039	−0.018	0.039	−0.007	0.039	−0.014	0.039
Education	−0.022	0.014	−0.004	0.015	−0.002	0.014	−0.003	0.015	0.014	0.015	0.018	0.015
Economic status	−0.049	0.022	−0.037	0.022	−0.036	0.022	−0.013	0.023	−0.006	0.023	−0.008	0.023
Age	0.108	0.003	0.089	0.003	−0.411	0.008	0.174*	0.003	0.159*	0.003	0.495	0.013
VoA index	0.178*	0.024	0.178*	0.024	−1.699+	0.285	−0.218**	0.023	−0.205**	0.023	0.604	0.256
MMSE			−0.118	0.007	−0.122	0.007			−0.108	0.008	−0.121	0.008
Age * VoA index					1.997*	0.004					−0.923	0.003

Note. Model 1 regressed covariates, age, and the specific VoA index on SCC. Model 2 added the MMSE. Model 3 added the age by VoA interaction term. VoA = views of aging; R²_adj = adjusted R²; SE = standard error; MMSE = Mini-Mental State Examination. Males are coded as 1 and females as 2.

p < .05p < .025; p < .01.

Sample 1 Regressions

After adjusting for covariates (sex, education, and self-reported economic status), ageist attitudes, psychological loss, physical change, psychological growth, and subjective age were significantly associated with SCC in separate models (Table 3, Model 1). The main effect of age was also significant for all models (Table 3, Model 1). Furthermore, chronological age significantly moderated the relationship between specific indices of VoA and SCC, including psychological loss, physical change, and subjective age in separate models (Table 3, Model 2; all p ≤ .01). There was a marginal trend toward an interaction with chronological age for the ageist attitudes scale (p = .084) and the psychological growth subscale of the Attitudes to Aging questionnaire (p = .020).

We further explored the nature of the significant interactions using the PROCESS macro for SPSS (Hayes, 2018). To do so, we examined the conditional effects of the VoA indices at three different chronological age groups: participants whose chronological age fell below one standard deviation (SD) of the mean (−1SD), participants whose chronological age was within one SD of the mean (within 1SD), and those whose chronological age was above one SD of the mean (+1SD). All models adjusted for covariates of sex, education, and economic status. These analyses revealed that as chronological age increases, the association between the VoA indices and SCC strengthens. For psychological loss, the main effect was significant across all three age groups (−1SD: b = 0.04, SE = 0.02, p = .03; within 1SD: b = 0.08, SE = 0.01, p $\leq$ .001; +1SD: $b$ = .11, SE = 0.02, p $\leq$ .001). The main effect of physical change was not significant for those whose age was −1SD or below (p = .26) but was significant for those whose ages were within 1SD or greater (within 1SD: $b$ = −0.07, SE = 0.02, p $\leq$ .001; +1SD: $b$ = −0.11, SE = 0.02, p $\leq$ .001). Finally, the main effect of subjective age was not significant in those whose age was −1SD or below (p = .46), but it was significant in those whose age was within 1SD ( $b$ = 0.05, SE = 0.02, p = .007), as well as those whose age was +1SD or greater ( $b$ = 0.13, SE = 0.03, p < .001). Figures 1a−c depicts the interaction effect of age and VoA on SCC.

Figure 1.

Graphical displays of the significant age by VoA interaction effect on subjective cognitive complaints (SCC) in Sample 1, specifically for VoA indices of (a) psychological loss, (b) physical change, and (c) subjective age. For visualization purposes, the association between each VoA index and SCC is displayed for participants whose age fell below one standard deviation of the mean (−1SD), those whose age was within one standard deviation of the mean (within 1SD), and those whose age was above one standard deviation of the mean (+1SD).

Sample 2

After adjusting for education, self-reported economic status, and sex, the main effect of subjective age on SCC was significant (p = .012; Table 4, Model 1), but the main effect of chronological age was not significant (p = .15). After adding the MMSE scores to the model (Table 4, Model 2), subjective age remained significantly associated with SCC (p = .012); however, the main effect of MMSE was not significant (p = .097). In a subsequent model that included an interaction term, chronological age significantly moderated the association between subjective age and SCC (p = .023; Table 4, Model 3).

In the model examining the association between subjective successful aging and SCC, the main effects of subjective successful aging (p = .003) and of chronological age (p = .023) were significant after adjusting for sex, education, and economic status (Table 4, Model 1). The main effects remained significant after adding MMSE scores to the model (ps ≤ .039; Table 4, Model 2). In this model, MMSE scores also did not significantly associate with SCC (p = .09; Table 4, Model 2). The interaction between successful aging and age was not significant (p = .504; Table 4, Model 3).

We further investigated the interactive effect of chronological age on the association between subjective age and SCC, using the PROCESS macro for SPSS (Hayes, 2018). As was the case for Sample 1, the conditional effect of subjective age on SCC was examined at three separate chronological age groups: chronological age below one SD (SD) of the mean (−1SD), chronological age within one SD of the mean (within 1SD), and chronological age above one SD of the mean (+1SD). All models adjusted for sex, education, economic status, and MMSE scores. Similar to Sample 1, as chronological age increased, the association between subjective age and SCC also increased. Specifically, the association between subjective age and SCC was not significant in those whose age was −1SD or below (p = .73), but it was significant for those whose age was within 1SD or greater (within 1SD: b = 0.07, SE = 0.02, p $=$ .007; +1SD: $b$ = .12, SE = 0.03, p $\leq$ .001). Figure 2 depicts the effect of the interaction between chronological age and subjective age on SCC.

Figure 2.

Graphical display of the significant age by subjective age interaction effect on subjective cognitive complaints (SCC) in Sample 2. For visualization purposes, the association between subjective age and SCC is displayed for participants whose age fell below one standard deviation of the mean (−1SD), those whose age was within one standard deviation of the mean (within 1SD), and those whose age was above one standard deviation of the mean (+1SD).

Exploratory Analyses by Item

To examine whether different VoA are more strongly related to specific subjective cognitive abilities, we ran separate Spearman correlations between the VoA variables and each item on the SCC questionnaire for each of the two samples. Results can be viewed in Table 5. In general, there were no apparent patterns observed between the VoA variables and the different SCC variables. Associations appear stronger in Sample 1 relative to Sample 2. We briefly discuss implications of this in the general discussion section.

Table 5.

Spearman correlation coefficients of the association between each view of aging measure and each item on the questionnaire.

	Sample 1					Sample 2
	Subjective age	Psychological loss^a	Physical change^a	Psychological growth^a	Ageist attitudes	Subjective age	Successful aging
Ability to remember past events	.248**	.295**	−.315**	−.170**	0.062	.238**	−.168*
Ability to recall the day of the week	.245**	.277**	−.248**	−.115**	.158**	0.092	−0.108
Ability to remember names and details	0.062	.152**	−.147**	−.127**	.118*	.154*	−0.073
Ability to remember words (for example, within a sentence)	0.047	.160**	−.118**	−.106*	.142**	0.089	−0.098
Ability to understand simple instructions	.139**	.236**	−.184**	−.137**	.143**	0.024	−.147^c
Ability to find your way in different locations	.133**	.225**	−.221**	−.140**	.160**	0.068	−.205**
Ability to speak in full sentences	.168**	.156**	−.248**	−.153**	.133**	.169*	−.184**
Ability to recognize people you have already met	.107*	.164**	−.130**	−0.077	.142**	0.123	−0.052

^aPsychological loss, physical change, and psychological growth are part of the Attitudes to Aging questionnaire.

**Correlation is significant at the 0.01 level (2-tailed).

*Correlation is significant at the 0.05 level (2-tailed).

General Discussion

Findings from two separate cross-sectional samples of older adult participants confirmed our first hypothesis for most indices of VoA, including those indices conceptualized as generalized or personal aspects of VoA (Wurm et al., 2017). Specifically, individuals who reported more ageist views, worse attitudes to aging, less successful aging, and older subjective age also reported more SCC. Furthermore, in line with our second hypothesis, chronological age moderated some of these associations such that, in general, the association between VoA and SCC strengthened with increasing age. This was true for subjective age (both Sample 1 and Sample 2), and the psychological loss and physical change subscales of the Attitudes to Aging questionnaire (Sample 1). As for our third hypothesis that these associations would be independent of objective cognition, subjective age and subjective successful aging remained significantly associated with SCC after including the MMSE score as a covariate in analyses conducted with Sample 2. Importantly findings from this research are cross-sectional, and thus we are unable to determine causality between VoA and SCC.

The fact that more negative generalized and personal aspects of VoA associated with more SCC is consistent with previous studies that reported an association between older subjective age (Hülür et al., 2015; Segel−Karpas & Palgi, 2019; Siebert et al., 2020; Stephan et al., 2020) and worse subjective cognition. These associations between VoA and more SCC can be explained at least partially by the age stereotype embodiment theory (Levy, 2009). The theory states that aging stereotypes are present throughout one’s life and are eventually targeted toward the self in older age due to cues from the environment at the interpersonal and institutional level (Levy, 2009). At the point in which the age stereotypes are directed toward oneself in old age, VoA are generated. More negative generalized aspects of VoA including ageist views may also lead to a tendency to expect outcomes consistent with age stereotypes (Wurm et al., 2013), such as worse cognitive functioning with increasing age. It is thus possible that individuals with more negative VoA have an increased awareness of subtle cognitive changes and notice their personal cognitive shortcomings even if those are common in the general population. Such individuals may over-interpret these occurrences as signs of cognitive decline due to aging, thereby contributing to lower subjective ratings of cognition. Future studies should directly test over-interpretation to better identify the mechanisms that underlie the associations between negative VoA and SCC. Importantly, the mechanisms underlying the relationship between VoA and SCC may differ based on the types of VoA under investigation (i.e., generalized vs. personal aspects of VoA). This is also an important direction for future research.

VoA may indirectly contribute to ratings of SCC via effects on psychological and physical health (Wurm et al., 2013), factors that can influence SCC (Burmester et al., 2016). A study by Stephan et al. (2015) reported an association between subjective age and biological aging (e.g., pulmonary and muscular function and lower central adiposity). The authors discuss that subjective age may represent a condensed summary of information related to cognitive and physical functioning. Physical health has been shown to directly impact SCC (Burmester et al., 2016), and it may also do so indirectly via its effect on objective cognition (MacDonald et al., 2011).

VoA may also indirectly contribute to greater SCC through possible effects on objective cognition. Studies have reported an association between VoA and worse objective cognitive functioning both cross-sectionally and longitudinally (Brown et al., 2020; Robertson et al., 2016; Siebert et al., 2020). In a study by Stephan et al. (2016) that examined longitudinal data from the Health and Retirement Study, lower baseline subjective age was associated with better memory performances at baseline and slower decline at follow-up assessments. In the present study, we found that the associations between personal indices of VoA (subjective age, attitudes toward aging, and subjective successful aging) and SCC persisted after controlling for objective cognition (Sample 2). In Sample 1, we were unable to test whether associations between our indices of VoA and SCC were independent of objective cognition. It remains possible that generalized aspects of VoA examined in this study (e.g., ageist attitudes) are related to SCC via effects on objective cognition. Consistent with this, Levy et al. (2012) found negative age stereotypes to be associated with worse memory performance over 38 years and greater memory decline over time.

Nevertheless, in Sample 2, we found VoA to be associated with SCC independent of objective cognition. It is possible that individuals recognize subtle changes to their cognitive functioning despite performing within the normal range on cognitive testing (McAlister & Schmitter-Edgecombe, 2016). These subtle changes may directly impact an individual’s VoA (Stephan et al., 2016). Additionally, individuals with greater objective cognitive impairment may not necessarily report more SCC, as awareness may be compromised once individuals begin to develop mild cognitive impairment or dementia (Bregman et al., 2019, 2020). In these individuals, VoA may be a stronger predictor of their self-impressions of cognition than objective cognition. Given that SCC has been shown to negatively impact the well-being of older adults, including contributing to fear of becoming demented, associated mood changes, and behavioral changes to accommodate perceived difficulties (Comijs et al., 2002), improving negative VoA may serve as a point of intervention for mitigating the negative impact of SCC on well-being in older adulthood.

In the current study, we also found an interactive effect of age on the associations between VoA and SCC. Generally, we found that as age increased, the association between specific VoA indices (the psychological loss and physical change subscales of the Attitudes to Aging questionnaire, as well as subjective age) and SCC strengthened. These findings suggest that as individuals age, VoA may exert a stronger effect on self-assessments of cognitive functioning. Longitudinal studies have shown that VoA become more negative as individuals age (Diehl et al., 2021; Miche et al., 2014). Moreover, a meta-analysis of age stereotyping priming effects found that the effect of negative age stereotype priming on behaviors is greater than that of positive age stereotype priming (Meisner, 2012). Thus, with increasing age, the effect of negative VoA on health perceptions and behaviors, including subjective cognition, is likely to grow. The increase in negative VoA with increasing age could reflect the fact that cues about old age at the interpersonal and institutional level become more common or noticeable with increasing age, thereby strengthening the self-relevance of certain age stereotypes (Diehl et al., 2021; Levy, 2009). For example, older adults may encounter stereotypes directly related to cognition such as the expression “senior moment” more frequently and may thus be more likely to incorporate such stereotypes into their own self-image.

There are many ways to measure SCC, and we used a brief measure that captures several domains rather than focusing on specific domains separately. Individuals with objective cognitive decline show different levels of awareness to specific cognitive domains (Bregman et al., 2019), and it is therefore possible that domain specificity has an effect on the association between VoA and SCC in cognitively healthy individuals as well. Additionally, our measure of SCC includes both functions that commonly decline with normal cognitive aging (e.g., remembering names and details and word finding difficulties), as well as functions that generally remain intact with normal cognitive aging (e.g., understanding simple instructions; Harada et al., 2013). In our exploratory item analyses in which we correlated VoA variables with each item from the SCC questionnaire, we did not find strong evidence for domain specificity or for differential relationships with VoA based on the severity of the cognitive complaint. In fact, almost all VoA measures correlated with almost all of the SCC items in Sample 1. In general, subjective age and subjective successful aging variables from Sample 2 showed less significant associations with the SCC items relative to VoA variables from Sample 1. This could be a power issue in that the sample size of Sample 1 was about 2.5 times larger than that of Sample 2. Given the brevity of our measure of SCC, and the fact that most individuals in both samples endorsed very few cognitive complaints, future studies examining associations of VoA with SCC may consider investigating cognitive domains in greater breadth and detail.

We acknowledge that the current study has some limitations. First, the study is cross-sectional and thus causality cannot be established. Although we discuss findings with a focus on the impact of VoA on SCC, it has been previously shown that SCC contributes to VoA and that some relationships are bidirectional (e.g., see Siebert et al., 2020). Future longitudinal studies may further explore the directionality of these associations, as well as mechanisms underlying the associations. For example, it is possible that negative VoA contributes to increased age awareness which may in turn result in overinterpretation of cognitive changes due to aging, thereby contributing to more SCC. The Awareness of Age-Related Change (AARC) questionnaire (Diehl & Wahl, 2010) measures the tendency to attribute physical and cognitive changes to age and may be a useful future measure to explore in this regard. Second, a more comprehensive measure of objective cognition will help to elucidate the role of negative VoA on SCC, independent of its association with objective cognition. This is an important area of study given the fact that many older adults experience SCC yet do not show objective impairments (Jessen et al., 2020) and do not go on to develop dementia (Mendonça et al., 2016; Mitchell et al., 2014). Finally, both samples were convenience samples and thus not representative of the larger older adult population in Israel. Sample 2 included nursing home residents, which may have affected the findings in unknown ways (e.g., see Seifert & Schelling, 2018). Future studies may consider investigating the moderating role of living situation on the association between VoA and SCC.

Negative self-perceptions of cognitive functioning can be a source of great anxiety in older adulthood (Corner & Bond, 2004; Hodgson & Cutler, 1997). Thus, elucidating the factors that contribute to SCC in older adults who do not eventually develop dementia will aid in establishing ways to mitigate this source of stress in older adulthood, ultimately improving the quality of life of older adults. Our study found that specific indices of VoA including ageist attitudes, attitudes to aging, subjective successful aging, and subjective age associate with SCC. Findings also suggest that these associations may be independent of objective cognitive functioning. Thus, helping older adults view aging more positively may have a complementary positive effect on their self-ratings of cognitive functioning.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study from which Sample 2 was derived was supported by the Israel Science Foundation (ISF; grant number 1234/14).

ORCID iDs

Gali H. Weissberger

Ehud Bodner

Author Biography

Gali H. Weissberger, Ph.D., is a senior lecturer at Bar-Ilan University in Israel in the Interdisciplinary Department of Social Sciences.

Ehud Bodner, Ph.D., is a full professor at Bar-Ilan University in Israel in the Interdisciplinary Department of Social Sciences and the Department of Music.

Yuval Palgi, Ph.D., is an associate professor at the University of Haifa, Haifa, Israel in the Department of Gerontology.

Gitit Kavé, Ph.D., is a full professor at the Open University in Israel in the Department of Education and Psychology.

Dov Shmotkin, Ph.D., is professor emeritus at Tel Aviv University in Israel in the School of Psychological Sciences and the Herczeg Institute on Aging.

Amit Shrira, Ph.D., is a full professor at Bar−Ilan University in Israel in the Interdisciplinary Department of Social Sciences.

References

Avidor

Benyamini

Solomon

(2016). Subjective age and health in later life: The role of posttraumatic symptoms. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 71(3), 415−424. https://doi.org/10.1093/geronb/gbu150.

Avidor

Levin

Solomon

(2018). Guilt as a mediator between depressive symptoms and subjective age: A 17−year longitudinal study of Israeli ex−prisoners of war. American Journal of Orthopsychiatry, 88(2), 199−210. https://doi.org/10.1037/ort0000212.

Barak

Schiffman

L. G.

(1981). Cognitive age: A nonchronological age variable. ACR North American Advances, 8, 602−606.

Bodner

Shrira

Bergman

Y. S.

Cohen−Fridel

(2015). Anxieties about aging and death and psychological distress: The protective role of emotional complexity. Personality and Individual Differences, 83, 91−96. https://doi.org/10.1016/j.paid.2015.03.052.

Bodner

Shrira

Hoffman

Bergman

Y. S.

(2021). Day-to-day variability in subjective age and ageist attitudes and their association with depressive symptoms. The Journals of Gerontology: Series B, 76(5), 836−844. https://doi.org/10.1093/geronb/gbaa125.

Bregman

Kavé

Shiner

Biran

(2019). Dissociation in awareness of memory and language decline in alzheimer's disease. International Journal of Geriatric Psychiatry, 34(4), 548−554. https://doi.org/10.1002/gps.5049.

Bregman

Kavé

Zeltzer

Biran

(2020). Memory impairment and alzheimer’s disease pathlogy in individuals with MCI who underestimate or overestimate their decline. International Journal of Geriatric Psychiatry, 35(5), 581−588. https://doi.org/10.1002/gps.5274.

Brothers

Miche

Wahl

H.−W.

Diehl

(2017). Examination of associations among three distinct subjective aging constructs and their relevance for predicting developmental correlates. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 72(4), 547−560. https://doi.org/10.1093/geronb/gbv085.

Brown

K. E.

Kim

Stewart

Fulton

McCarrey

A. C.

(2020). Positive, but not negative, self−perceptions of aging predict cognitive function among older adults. The International Journal of Aging and Human Development, 93(1), 543–561.

10.

Burmester

Leathem

Merrick

(2016). Subjective cognitive complaints and objective cognitive function in aging: A systematic review and meta−analysis of recent cross-sectional findings. Neuropsychology Review, 26(4), 376−393. https://doi.org/10.1007/s11065−016−9332−2.

11.

Caracciolo

Gatz

Pedersen

N. L.

Fratiglioni

(2012). Differential distribution of subjective and objective cognitive impairment in the population: A nation-wide twin-study. Journal of Alzheimer’s Disease, 29(2), 393−403. https://doi.org/10.3233/JAD−2011−111904.

12.

Comijs

Deeg

Dik

Twisk

Jonker

(2002). Memory complaints; The association with psycho−affective and health problems and the role of personality characteristics: A 6-year follow-up study. Journal of Affective Disorders, 72(2), 157−165. https://doi.org/10.1016/s0165−0327(01)00453−0.

13.

Corner

Bond

(2004). Being at risk of dementia: Fears and anxieties of older adults. Journal of Aging Studies, 16(5), 143−155. https://doi.org/10.7748/nop.16.5.8.s9.

14.

Diehl

M. K.

Wahl

H.−W.

(2010). Awareness of age−related change: Examination of a (mostly) unexplored concept. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65(3), 340−350. https://doi.org/10.1093/geronb/gbp110.

15.

Diehl

Wahl

H.−W.

Barrett

A. E.

Brothers

A. F.

Miche

Montepare

J. M.

Westerhof

G. J.

Wurm

(2014). Awareness of aging: Theoretical considerations on an emerging concept. Developmental Review, 34(2), 93−113. https://doi.org/10.1016/j.dr.2014.01.001.

16.

Diehl

Wettstein

Spuling

S. M.

Wurm

(2021). Age-related change in self-perceptions of aging: Longitudinal trajectories and predictors of change. Psychology and Aging, 36(3), 344–359. https://doi.org/10.1037/pag0000585.

17.

Folstein

McHugh

(1975). ‘Mini-mental state (MMSE)’ A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189−198. https://doi.org/10.1016/0022−3956(75)90026−6.

18.

Harada

C. N.

Love

M. C. N.

Triebel

K. L.

(2013). Normal cognitive aging. Clinics in Geriatric Medicine, 29(4), 737−752. https://doi.org/10.1016/j.cger.2013.07.002.

19.

Hayes

A. F.

(2018). Introduction to mediation, moderation, and conditional process analysis: A regression−based approach. Guilford publications.

20.

Hodgson

L. G.

Cutler

S. J.

(1997). Anticipatory dementia and well-being lynne gershenson Hodgson, PhD. American Journal of Alzheimer's Disease, 12(2), 62−66. https://doi.org/10.1177/153331759701200203.

21.

Hoffman

Y. S.

Shrira

Cohen−Fridel

Grossman

E. S.

Bodner

(2016). Posttraumatic stress disorder symptoms as a function of the interactive effect of subjective age and subjective nearness to death. Personality and Individual Differences, 102, 245−251. https://doi.org/10.1016/j.paid.2016.07.017.

22.

Hülür

Hertzog

Pearman

A. M.

Gerstorf

(2015). Correlates and moderators of change in subjective memory and memory performance: Findings from the health and retirement study. Gerontology, 61(3), 232−240. https://doi.org/10.1159/000369010.

23.

Jessen

Amariglio

R. E.

Buckley

R. F.

van der Flier

W. M.

Han

Molinuevo

J. L.

Rabin

Rentz

D. M.

Rodriguez−Gomez

Saykin

A. J.

Sikkes

S. A. M.

Smart

C. M.

Wolfsgruber

Wagner

(2020). The characterisation of subjective cognitive decline. Lancet Neurology, 19(3), 271−278. https://doi.org/10.1016/S1474−4422(19)30368−0.

24.

Keller

M. L.

Leventhal

Prohaska

T. R.

Leventhal

E. A.

(1989). Beliefs about aging and illness in a community sample. Research in Nursing & Health, 12(4), 247−255. https://doi.org/10.1002/nur.4770120407.

25.

Koren

Shrira

Bodner

Bergman

Y. S.

(2020). Subjective nearness−to−death and negative attitudes toward persons with disability: Attachment patterns moderate. Death Studies, 44(5), 312−318. https://doi.org/10.1080/07481187.2018.1544949.

26.

Laidlaw

Kishita

Shenkin

S. D.

Power

M. J.

(2018). Development of a short form of the attitudes to ageing questionnaire (AAQ). International Journal of Geriatric Psychiatry, 33(1), 113−121. https://doi.org/10.1002/gps.4687.

27.

Laidlaw

Wang

Coelho

Power

(2010). Attitudes to ageing and expectations for filial piety across Chinese and British cultures: A pilot exploratory evaluation. Aging & Mental Health, 14(3), 283–−292. https://doi.org/10.1080/13607860903483060.

28.

Levy

B. R.

(2009). Stereotype embodiment: A psychosocial approach to aging. Current Directions in Psychological Science, 18(6), 332−336. https://doi.org/10.1111/j.1467−8721.2009.01662.x.

29.

Levy

B. R.

Slade

M. D.

Kasl

S. V.

(2002). Longitudinal benefit of positive self-perceptions of aging on functional health. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 57(5), P409−P417. https://doi.org/10.1093/geronb/57.5.p409.

30.

Levy

B. R.

Slade

M. D.

Kunkel

S. R.

Kasl

S. V.

(2002). Longevity increased by positive self-perceptions of aging. Journal of Personality and Social Psychology, 83(2), 261. https://doi.org/10.1037//0022−3514.83.2.261.

31.

Levy

B. R.

Zonderman

A. B.

Slade

M. D.

Ferrucci

(2012). Memory shaped by age stereotypes over time. Journals of Gerontology: Series B, 67(4), 432−436. https://doi.org/10.1093/geronb/gbr120.

32.

Lucas

H. D.

Monti

J. M.

McAuley

Watson

P. D.

Kramer

A. F.

Cohen

N. J.

(2016). Relational memory and self-efficacy measures reveal distinct profiles of subjective memory concerns in older adults. Neuropsychology, 30(5), 568−578. https://doi.org/10.1037/neu0000275.

33.

MacDonald

S. W.

DeCarlo

C. A.

Dixon

R. A.

(2011). Linking biological and cognitive aging: Toward improving characterizations of developmental time. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 66(suppl_1), i59−i70. https://doi.org/10.1093/geronb/gbr039.

34.

McAlister

Schmitter-Edgecombe

(2016). Everyday functioning and cognitive correlates in healthy older adults with subjective cognitive concerns. The Clinical Neuropsychologist, 30(7), 1087−1103. https://doi.org/10.1080/13854046.2016.1190404.

35.

Meisner

B. A.

(2012). A meta-analysis of positive and negative age stereotype priming effects on behavior among older adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 67(1), 13−17. https://doi.org/10.1093/geronb/gbr062.

36.

Mendonça

M. D.

Alves

Bugalho

(2016). From subjective cognitive complaints to dementia: Who is at risk?: A systematic review. American Journal of Alzheimer’s Disease & Other Dementias®, 31(2), 105−114.

37.

Miche

Elsässer

V. C.

Schilling

O. K.

Wahl

H.−W.

(2014). Attitude toward own aging in midlife and early old age over a 12-year period: Examination of measurement equivalence and developmental trajectories. Psychology and Aging, 29(3), 588−600. https://doi.org/10.1037/a0037259.

38.

Mitchell

Beaumont

Ferguson

Yadegarfar

Stubbs

(2014). Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: Meta‐analysis. Acta Psychiatrica Scandinavica, 130(6), 439−451. https://doi.org/10.1111/acps.12336.

39.

North

M. S.

Fiske

S. T.

(2013). A prescriptive intergenerational-tension ageism scale: Succession, identity, and consumption (SIC). Psychological Assessment, 25(3), 706−713. https://doi.org/10.1037/a0032367.

40.

Palgi

Shrira

Kavé

Rubinstein

Shmotkin

(2019). Which factors do older adults consider when estimating the time left for them to live? The Journals of Gerontology: Series B, 74(1), 69−73. https://doi.org/10.1093/geronb/gby048.

41.

Palgi

Shrira

Neupert

S. D.

(2021). Views on aging and health: A multidimensional and multitemporal perspective. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 76(5), 821−824. https://doi.org/10.1093/geronb/gbab026.

42.

Pearlin

L. I.

Mullan

J. T.

Semple

S. J.

Skaff

M. M.

(1990). Caregiving and the stress process: An overview of concepts and their measures. The Gerontologist, 30(5), 583−594. https://doi.org/10.1093/geront/30.5.583.

43.

Pruchno

R. A.

Wilson−Genderson

Cartwright

(2010). A two-factor model of successful aging. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65(6), 671−679. https://doi.org/10.1093/geronb/gbq051.

44.

Reid

L. M.

MacLullich

A. M.

(2006). Subjective memory complaints and cognitive impairment in older people. Dementia and Geriatric Cognitive Disorders, 22(5−6), 471−485. https://doi.org/10.1159/000096295.

45.

Robertson

D. A.

King−Kallimanis

B. L.

Kenny

R. A.

(2016). Negative perceptions of aging predict longitudinal decline in cognitive function. Psychology and Aging, 31(1), 71−81. https://doi.org/10.1037/pag0000061.

46.

Sargent−Cox

K. A.

Anstey

K. J.

Luszcz

M. A.

(2014). Longitudinal change of self−perceptions of aging and mortality. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 69(2), 168−173. https://doi.org/10.1093/geronb/gbt005.

47.

Sarkisian

C. A.

Hays

R. D.

Mangione

C. M.

(2002). Do older adults expect to age successfully? The association between expectations regarding aging and beliefs regarding healthcare seeking among older adults. Journal of the American Geriatrics Society, 50(11), 1837−1843. https://doi.org/10.1046/j.1532−5415.2002.50513.x.

48.

Segel−Karpas

Palgi

(2019). ‘It is nothing more than a senior moment’: The moderating role of subjective age in the effect of change in memory on self−rated memory. Aging & Mental Health, 23(2), 272−276. https://doi.org/10.1080/13607863.2017.1399350.

49.

Seifert

Schelling

H. R.

(2018). Attitudes toward aging and retirment homes before and after entry into a retirement home. Journal of Housing for the Elderly, 32(1), 12−25. https://doi.org/10.1080/02763893.2017.1393484.

50.

Shrira

(2016). Perceptions of aging among middle-aged offspring of traumatized parents: The effects of parental holocaust-related communication and secondary traumatization. Aging & Mental Health, 20(1), 65−73. https://doi.org/10.1080/13607863.2015.1013921.

51.

Shrira

Ayalon

Bensimon

Bodner

Rosenbloom

Yadid

(2017). Parental post−traumatic stress disorder symptoms are related to successful aging in offspring of holocaust survivors. Frontiers in Psychology, 8(1099). https://doi.org/10.3389/fpsyg.2017.01099.

52.

Shrira

Bodner

Palgi

(2015). Emotional complexity and its effect on psychological distress as a function of chronological age and subjective distance-to-death. Aging & Mental Health, 19(12), 1056−1062. https://doi.org/10.1080/13607863.2014.995592.

53.

Shrira

Segel−Karpas

Bodner

Palgi

(2020). Subjective age and emotion covariation: Findings from two daily experience studies. The Journals of Gerontology: Series B, 75(5), 991−1000. https://doi.org/10.1093/geronb/gby125.

54.

Shrira

Shmotkin

Palgi

Hoffman

Bodner

Ben−Ezra

Litwin

(2017). Older adults exposed to ongoing versus intense time-limited missile attacks: Differences in symptoms of posttraumatic stress disorder. Psychiatry, 80(1), 64−78. https://doi.org/10.1080/00332747.2016.1178028.

55.

Siebert

J. S.

Braun

Wahl

H.−W.

(2020). Change in attitudes toward aging: Cognitive complaints matter more than objective performance. Psychology and Aging, 35(3), 357–368. https://doi.org/10.1037/pag0000451.

56.

Stephan

Sutin

A. R.

Caudroit

Terracciano

(2016). Subjective age and changes in memory in older adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 71(4), 675−683. https://doi.org/10.1093/geronb/gbv010.

57.

Stephan

Sutin

A. R.

Luchetti

Terracciano

(2020). Subjective age and informant-rated cognition and function: A prospective study. Psychology and Aging, 36(3), 338–343. https://doi.org/10.1037/pag0000566.

58.

Stephan

Sutin

A. R.

Terracciano

(2015). How old do you feel? The role of age discrimination and biological aging in subjective age. Plos One, 10(3), e0119293. https://doi.org/10.1371/journal.pone.0119293.

59.

Tomita

Sugawara

Kaneda

Okubo

Iwane

Takahashi

Kaneko

Yasui‐Furukori

(2014). Sex‐specific effects of subjective memory complaints with respect to cognitive impairment or depressive symptoms. Psychiatry and Clinical Neurosciences, 68(3), 176−181. https://doi.org/10.1111/pcn.12102.

60.

Werner

Heinik

Mendel

Reicher

Bleich

(1999). Examining the reliability and validity of the Hebrew version of the mini mental state examination. Aging Clinical and Experimental Research, 11(5), 329−334. https://doi.org/10.1007/BF03339808.

61.

Wurm

Diehl

Kornadt

A. E.

Westerhof

G. J.

Wahl

H.−W.

(2017). How do views on aging affect health outcomes in adulthood and late life? Explanations for an established connection. Developmental Review, 46, 27−43. https://doi.org/10.1016/j.dr.2017.08.002.

62.

Wurm

Warner

L. M.

Ziegelmann

J. P.

Wolff

J. K.

Schüz

(2013). How do negative self-perceptions of aging become a self-fulfilling prophecy? Psychology and Aging, 28(4), 1088−1097. https://doi.org/10.1037/a0032845.