Do Worries About Cognitive Functioning and Concerns About Developing Alzheimer’s Disease Affect Psychological Well-Being?

Abstract

Objective: The objective of this study is to determine if cognitive worries affect psychological well-being, if these effects are long-term, and if such concerns affect well-being more so among persons with a parent having Alzheimer’s disease (AD). Method: We used structural equation models with three waves of data collected from persons ages 40 to 60 at T₁. We created summative scores on five indicators of concerns about cognitive functioning and worries about dementia. Well-being measures included depression, life satisfaction, stress, and mastery. Results: We found (a) cognitive worries at Waves 1, 2, and 3 were generally associated with lower levels of psychological well-being at each of these waves; (b) there was no evidence of long-term, lagged effects, and (c) these relationships were statistically similar across groups of adult children and controls. Discussion: Because concerns about cognitive functioning and developing AD are pervasive among middle-aged and older persons, practitioners should be aware of their potentially deleterious effect on psychological well-being.

Keywords

anticipatory dementia dementia worries psychological well-being Alzheimer’s disease

Introduction

A number of factors have conspired to make Alzheimer’s disease (AD) an especially dreaded and costly condition. Although variable in manifestation and duration from one person to the next, AD’s characteristic progression leads inevitably to death. The time from diagnosis to death typically ranges from 2 to 4 years but in some cases may last as long as 20 years. AD is also widely considered to be untreatable, irreversible, and incurable (Daviglus et al., 2010; but see Bredesen et al., 2016; Leinenga & Götz, 2015; Prince, Albanese, Guerchet, & Prina, 2014, for more optimistic conclusions). For caregivers of persons with AD—those who have been referred to as second victims—the toll is also high. Research has generally demonstrated that AD caregivers have lower levels of psychological well-being and higher levels of morbidity and mortality than appropriately matched peers do (Alzheimer’s Association, 2016; Kim & Schulz, 2008; others—for example, Roth, Fredman, & Haley, 2015—have noted that informal caregiving may be accompanied by positive health effects).

In addition to such individual consequences of AD, its societal toll is also very high. For example, the best predictor of AD is age (Alzheimer’s Association, 2016; Meunier, 2016) and the implications of worldwide population aging (Bloom, Canning, & Lubet, 2015; He, Goodkind, & Kowal, 2016) are quite clear. Extrapolating from current figures, Alzheimer’s Disease International (ADI) estimated that population aging in North America is a major factor that will lead to an increase in the number of older persons (60+) with dementia (most of whom suffer from AD) from 4.8 million in 2015 to 11.7 million in 2050. The estimates for Europe are that the number of people aged 60+ with dementia will increase from 10.5 in 2015 to 18.7 million in 2050. And the most recent ADI projections suggest that the worldwide population of older persons with dementia will increase from 46.8 million in 2015 to 131.5 million in 2050, an increase of 181% (Prince et al., 2015). Although the precise magnitude of bottom line estimates may differ (e.g., compare Alzheimer’s Association [2016] with Prince et al. [2015]), there can be little doubt that population aging will bring with it a greater incidence and prevalence of cases of AD in particular and dementia more generally.

This brief portrait of the consequences of AD would be incomplete without some attention to its economic costs. Although estimates also vary here, they all converge on a common conclusion: Economically, AD is extraordinarily expensive. In the United States, for example, the Alzheimer’s Association has estimated that the total health care costs associated with AD in 2016 will amount to $236 billion (Alzheimer’s Association, 2016). And ADI has suggested that the worldwide costs attributed to dementia amounted to $817.9 billion in 2015 (Prince et al., 2015). Beyond the direct costs incurred by individuals and by families, there are also substantial indirect and opportunity costs associated with AD in particular and dementia more generally. With regard to employment, a 2016 survey of AD care contributors conducted by the Alzheimer’s Association showed that 27% had to shorten their work hours, 13% retired early, 11% took a different job, another 11% resigned from their job, and 5% lost their job (Alzheimer’s Association, 2016).

In light of the above, it should come as no surprise that AD has emerged as a particularly feared condition. Data from a five-country survey conducted by the Harvard School of Public Health and Alzheimer Europe (2011) showed that, among persons 60 years of age and older, AD was reported as the disease they most fear getting by 47% of respondents (Rs) in France, 35% in Spain, 32% in the United States, 30% in Germany, and 20% in Poland. Data from Great Britain showed that two thirds of Rs more than 50 years of age fear they will develop AD as compared with only 10% indicating they feared getting cancer (Huffington Post UK/PA, 2014). And a recent survey conducted in 2016 by “Grandparents.com” (2016) found that Alzheimer’s was the primary health concern of grandparents—one third (33%) of respondents cited it as the health condition that worried them most, followed by cancer (23.7%), chronic pain (15.9%), heart disease (10.8%), and diabetes (5.9%).

For these and other reasons, investigators have been turning their attention to worries about getting AD. Variously known as “anticipatory dementia” (Cutler & Hodgson, 1996) or “dementia worry” (Kessler, Bowen, Baer, Froelich, & Wahl, 2012), studies have shown that such concerns are widespread, especially among middle-aged and older people (Commisaris et al., 1996; Cutler & Hodgson, 2001; Roberts, McLaughlin, & Connell, 2014). This research has also provided insights into the factors that predict fear and concerns. We know, for instance, that worry is greater among persons who have a first-degree relative with a diagnosis of AD (Cutler, 2015). But studies have also shown that fears about developing AD are not restricted to those whose genealogy would seemingly make them most susceptible to developing AD (Green et al., 2002; Silverman et al., 1994). AD and its characteristic symptoms have become increasingly visible to the public—witness the outpouring of media attention on the occasion of the recent death from AD of Pat Summitt, the longtime, record-holding women’s basketball coach at the University of Tennessee—as has public knowledge of the major symptoms of AD (MetLife Foundation, 2011). In addition, the current scientific recognition that AD is inevitably fatal coupled with acknowledgments that there are no lifestyle or pharmacological treatments that have proven to be effective in stopping, curing, slowing, or reversing AD (Alzheimer’s Association, 2016; Daviglus et al., 2010) lead fear and worries to be widespread among the middle-aged and older populations (Cutler, 2015; Cutler & Hodgson, 2001). However, it is particularly evident among those who report negative changes in their cognitive functioning regardless of whether they have a first-degree relative with AD (Cutler, 2015; Cutler & Brăgaru, 2015).

Results for other predictors have been less consistent. Cutler (2015) and Roberts et al. (2014) found that worries decrease with advancing age among a sample of persons 50 years of age and older. On the contrary, Werner (2002) and Zeng et al. (2015) found non-significant relationships between age and concerns, while Cantegreil-Kallen and Pin (2012) found personal fear to be significantly higher among persons aged 65+ than among persons aged 35 to 64. Inconsistent results have also been reported for the effects of gender. Werner, Goldberg, Mandel, and Korczyn (2013) reported significant gender differences in worry about getting AD in Israel, with women expressing greater worry, but the studies reported by Roberts and colleagues (2014) and by Cutler (2015) based on a U.S. sample found gender to be a non-significant predictor of worry. Such variation in results may be due to different analysis designs or perhaps due to cultural differences in the respective countries from which samples have been drawn.

What have received only minimal attention thus far are the consequences of such fears and worries. To the best of our knowledge, very few studies have directly examined the effects of concerns about developing AD on relevant outcome measures (see, for example, Hodgson & Cutler, 2004). In work reported by Cutler and Hodgson (2013, 2014; see also Fastame, Penna, Rossetti, & Agus, 2013) that used multi-wave data, the findings suggested that fears and concerns were associated with diminished health and with poorer psychological well-being. A principal limitation of both studies, however, and one acknowledged by the authors, was the fact that neither used appropriate methodological techniques to take advantage of the multi-wave panel data.

In view of these major and continuing substantive and methodological gaps in the research literature, the present investigation used multi-wave data with structural equation modeling to pose three questions: (a) Do cognitive concerns and fear of developing AD affect psychological well-being? (b) Do such concerns and worries exert short-term effects, long-term effects, or both? (c) Do concerns and fears affect well-being more so among persons with a parental history of AD?

Method

Sample

The study is based on three waves of data collected in 2000, 2005, and 2011 from two samples of persons ages 40 to 60 at T₁: (a) adult children with a parent diagnosed with probable AD and (b) a control group, matched on age and sex, with no parental history of AD. These subsamples were selected because previous research has shown that adult children are more likely to develop AD themselves and they have higher levels of worry and concern than do persons with no parental history of AD (Cutler, 2015; Cutler & Brăgaru, 2015). The T₁ data were collected by telephone interviews with Rs residing in the New England states of the United States whereas the data gathered at T₂ and T₃ came from mailed questionnaires sent to the same Rs (see Cutler & Hodgson, 2013 for further information about these methodological procedures). For each wave of data collection, Table 1 gives the ns for each of the subsamples, the total Ns, and the follow-up response rates at T₂ and T₃. To assure that the T₂ and T₃ samples reflected the characteristics of the original T₁ sample, analyses (not shown here) were conducted comparing compositional distributions on gender, race, religion, marital status, employment status, educational attainment, and age. The 2000-2005, 2005-2011, and 2000-2011 comparisons on these distributional characteristics disclosed no significant differences.

Table 1.

Sample Sizes and Follow-Up Response Rates.

Year	Adult children (n)	Matched controls (n)	Total N	Follow-up response rate
2000 (T₁)	108	150	258
2005 (T₂)	106	100	206	79.8%
2011 (T₃)	89	88	177	85.9%^a/68.6%^b

2005-2011 response rate.

2000-2011 response rate.

Variables: Dependent Variables

In the analysis, we used four outcome measures: depression, life satisfaction, stress, and mastery. At each of the three waves, Rs were administered an 11-item version of the Center for Epidemiological Studies Depression Scale (the CESD-20 (Kohout, Berkman, Evans, & Cornoni-Huntley, 1993); a 10-item version of the Global Measure of Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983); Pearlin, Menaghan, Lieberman, and Mullan’s (1981) Mastery Scale; and a single item measure of life satisfaction asking Rs “All things considered, how would you say that you find life these days: very satisfying, somewhat satisfying, not very satisfying, or not at all satisfying?” Univariate distributions and psychometric characteristics for these (as well as the remaining) variables are presented in Tables 2 and 3.

Table 2.

Univariate Distributions.

	Time 1	Time 2	Time 3
Education (range = 9-18), M (n)	15.4 (258)
Age (range = 40-60), M (n)	49.7 (258)
Sex (range = 0-1), %female (n)	65.9 (258)
COGSUM (range = 0-5), M (n)	2.5 (258)	2.4 (205)	2.5 (169)
CESD (range = 1-4), M (n)	1.4 (257)	1.4 (198)	1.5 (170)
Life satisfaction (range = 1-4), M (n)	1.5 (257)	1.5 (205)	1.5 (172)
Stress (range = 1-5), M (n)	2.4 (258)	2.3 (206)	2.2 (173)
Mastery (range = 1-4), M (n)	3.1 (254)	3.2 (202)	3.2 (167)

Note. COGSUM= Cognitive Concern Summary Score; CESD = Center for Epidemiological Studies Depression Scale.

Table 3.

Psychometrics.

	Cronbach’s α	Number of items	n
Concerns and worries about cognition
COGSUM1^a	.647	5	258
COGSUM2	.664	5	205
COGSUM3	.730	5	169
Well-being
Depression1 (CESD1)	.832	11	257
Depression2 (CESD2)	.858	11	198
Depression3 (CESD3)	.870	11	170
Life satisfaction1^b		1	257
Life satisfaction2		1	205
Life satisfaction3		1	172
Stress1	.869	10	258
Stress2	.904	10	206
Stress3	.913	10	173
Mastery1	.819	7	258
Mastery2	.841	7	206
Mastery3	.863	7	167

Note. COGSUM= Cognitive Concern Summary Score; CESD = Center for Epidemiological Studies Depression Scale.

The numbers after each variable refer to the wave at which the data were gathered.

Cronbach’s alpha is a measure of multi-item reliability; its use with our single item measure of life satisfaction is inappropriate.

Variables: Predictor Variables

At each of the three waves, Rs were asked several questions about how they viewed their cognitive functioning, perceived changes in their cognitive functioning, and concerns about developing AD. Five of these variables were used to create a single summative variable in each wave, which for purposes of brevity are referred to here as COGSUM1, COGSUM2, and COGSUM3. Rs were asked how they would rate their memory at the present time along a 5-point scale from excellent to poor; the number of ways in which their memory had changed (if they perceive their memory to have changed); whether their ability to remember causes them any worry; composite scores on the 12-item Short Inventory of Memory Experiences (SIME; Herrmann, 1984); and a single item asking Rs, along a 4-point scale ranging from very to not at all, how concerned they are about developing AD. Distributional and psychometric characteristics of these primary predictor variables are also presented in Tables 2 and 3.

Variables: Control Variables

Based on prior studies (Cutler & Hodgson, 2013, 2014), we use three T₁ variables as controls: Rs’ educational attainment, age, and gender (coded 1 for males and 0 for females). Distributional characteristics for these three variables may also be found in Table 2.

Analysis Methods

The analysis proceeded in two steps. First, using structural equation modeling via Stata/IC 13.1 (Acock, 2013), we tested the model presented in Figure 1. This model allowed us to answer the first two questions that informed this study: (a) Do concerns about cognitive functioning and worries about developing AD affect psychological well-being? and (b) do such concerns exert short-term effects, long-term effects, or both? Several goodness of fit measures were also examined to assess the fit of the data to the models: chi-square, comparative fit index [CFI], and root mean square error of approximation [RMSEA]. Second, using multiple group analysis within a structural equation modeling framework, we examined data related to the third question: If concerns do affect psychological well-being, do these concerns affect well-being more so among persons with a parental history of AD? Specifically, we investigated whether the effects are different across groups (see Acock, 2013; Tufiș, 2012, pp. 54-58) by simultaneously running two models having the effects constrained to be equal between two groups: persons with a parental history of AD and persons without a parental history of AD.

Figure 1.

Conceptual model.

Results

Findings related to the first two questions posed in this study are presented in Table 4. To reduce clutter, Table 4 presents only the statistically significant standardized regression coefficients that were obtained from the structural equation models. R²s are also presented as are the various goodness of fit statistics that were used to evaluate the overall adequacy of the fit of the models to the data.

Table 4.

Statistically Significant Standardized Regression Coefficients, R²s, and Goodness of Fit Statistics for Primary Modeled Relationships.

	COGSUM1	COGSUM2	COGSUM3	EDUCATION	GENDER	AGE
CESD1	.269***			−.179**	ns	ns
R² = .098
CESD2	ns	.338***		−.135*	ns	ns
R² = .148
CESD3	ns	ns	.245**	−.198**	ns	ns
R² = .176
χ² = 6.644, df = 3, p = .084; CFI = .981; RMSEA = .069
LIFE SATIS1	.293***			−.185**	ns	ns
R² = .112
LIFE SATIS2	ns	.216*		ns	ns	ns
R² = .081
LIFE SATIS3	ns	ns	ns	ns	ns	ns
R² = .047
χ² = 7.499, df = 3, p = .058; CFI = .943; RMSEA = .076
STRESS1	.383***			−.164*	ns	ns
R² = .179
STRESS2	ns	.384***		−.128*	ns	ns
R² = .202
STRESS3	ns	ns	.243**	ns	ns	ns
R² = .185
χ² = 4.549, df = 3, p = .208; CFI = .994; RMSEA = .045
MASTERY1	−.177**			.222***	ns	ns
R² = .077
MASTERY2	ns	−.174*		ns	ns	ns
R² = .092
MASTERY3	ns	ns	−.200*	.181**	ns	ns
R² = .132
χ² = 7.307, df = 3, p = .063; CFI = .979; RMSEA = .075

Note. COGSUM= Cognitive Concern Summary Score; CESD = Center for Epidemiological Studies Depression Scale; CFI = comparative fit index; RMSEA = root mean square error of approximation; LIFE SATIS = life satisfaction.

p < .05. **p < .01. ***p < .001.

Focusing on the predictor of primary interest, a somewhat repetitive pattern of relationships emerged. COGSUM1, our summated version of cognitive concerns and worries about developing AD at T₁, was significantly related to each of the four psychological well-being outcome variables at T₁. Likewise, COGSUM2 was significantly related to each of the outcomes as measured at T₂. And in three of the four cases—CESD3, STRESS3, and MASTERY3—COGSUM3 was significantly related to these outcomes at T₃. In other words, the preponderance of evidence suggested that our COGSUM measures do exert a significant effect on psychological well-being. The greater the concerns one has about one’s cognitive functioning and the greater the worries about developing AD at a particular time, the lower is the person’s psychological well-being at that time.

The data in Table 4 also suggest that the effects of COGSUM on psychological well-being were restricted to contemporaneous effects. In no instance was there evidence of a COGSUM variable at a given time having a lagged effect on a measure of psychological well-being at a later time. To take one illustration of this more general pattern, there was a statistically significant relationship between COGSUM1 and CESD1, but the relationships between COGSUM1 and CESD2 and between COGSUM1 and CESD3 were not significant. In most cases, then, our COGSUM variables exerted significant effects on the various measures of psychological well-being, but those effects were in all instances current and in no instances were they lagged.

Net of the effects of other variables in the models, only education of the three control variables bears relationships to the psychological well-being outcome variables at all three times. Higher levels of educational attainment resulted in lower levels of depression in each of the three waves, higher life satisfaction only in the first wave, lower stress only in Waves 1 and 2, and higher levels of mastery in Waves 1 and 3. The net effects of neither gender nor age were statistically significant at any wave for any of the outcome variables.

Acock (2013) suggested that goodness of fit values of CFI > .95, RMSEA < .05, and a p value of >.001 associated with chi-square constitute models that are a “good” fit to the data. Goodness of fit values of CFI > .9, RMSEA < .08, and a p value of >.001 associated with chi-square constitute a “reasonably close” fit to the data. In these terms, the chi-square values indicated that the fit of the data to the models is “good” for all four outcome variables; the CFI values suggest “good” fits for depression, stress, and mastery and a “reasonably good” fit in the case of life satisfaction; and RMSEA indicated a “good” fit to the data for the stress model and a “reasonably good” fit for the other models.

We noted above that our index measuring cognitive concerns and worries about developing AD had for the most part significant effects on the outcome variables, but only at the same time of measurement. The final question we ask in this study is whether these modeled relationships occurred similarly across both of the major subgroups comprising the sample—that is, adult children with at least one parent who had been diagnosed as having AD and matched controls with no parental history of AD—or are the relationships particularly strong and evident in one of the subgroups but not in the other. Using a multiple group analysis option within the structural equation model framework, we constrained the effects to be equal across the two groups and investigated whether this hypothesis was supported. The results of these analyses showed that the effects were similar across the groups with the constrained model not being a poorer fitting model than the unconstrained one (for CESD, the χ² for the model comparison across groups was 15.019, df = 15, p = .450; for LIFESAT, χ² = 21.746, df = 15, p = .115; for STRESS, χ² = 12.088, df = 15, p = .672; and for MASTERY, χ² = 11.133, df = 15, p = .743).

Discussion

The major objective of this study was to determine whether concerns about cognitive functioning and anxiety about developing AD have an impact on psychological well-being. A second objective was to consider whether any such effects were short-term or long-standing. And, third, we sought to examine whether any such effects might be evident both among a group of Rs with a parent who had been diagnosed as having probable AD as well as a matched group of Rs with no parental history of AD.

Given the increased visibility of AD and widespread public understanding of the defining characteristics of AD (Alzheimer’s Association, 2016), it is not at all surprising that researchers have become interested in what has been variously referred to as anticipatory dementia (Cutler & Hodgson, 1996) or dementia worries (Kessler et al., 2012). Memory lapses, the tip of the tongue phenomenon (Salthouse & Mandell, 2013), forgetting where one has left something or why one has come into a room, and other common cognitive problems widely experienced by middle-aged and older adults can set in motion a negative spiral of concerns about whether such occurrences are early warning signals of the impending emergence of full-blown dementia. The work of several authors has demonstrated that worries about developing AD are common and prevalent (e.g., Roberts et al., 2014). Although found more often among persons who have a first-degree relative with AD, studies have repeatedly shown that fears and anxieties were not restricted to persons having a close genetic or other connection to someone with AD (Cutler, 2015).

What have received far less attention in the research literature are the consequences of these fears. Using structural equation modeling on a three-wave data set, we found that our available measures of psychological well-being (depression, life satisfaction, stress, and mastery) were related to our composite indicator of concerns about cognitive functioning and worries about developing AD. The greater the concerns about one’s cognitive functioning and the more one worries about developing AD, the higher the level of depression, the lower the level of life satisfaction, the higher the level of stress, and the lower the level of mastery. However, our results showed strong evidence that these effects were not lagged. Cognitive concerns and worries affected psychological well-being at the time both are measured, but in no instance did we find that concerns and worries measured at an early time affected psychological well-being at a later time. It is in this sense that we conclude that these effects are significant, strong, and contemporary but neither lagged nor enduring. Finally, the results of multi-group analyses show that the pattern of these effects was similar across the two groups of Rs comprising the sample—middle-aged and older children with a parent diagnosed with AD and a matched group with no parental history of AD. To the extent that our sample permits generalization, we conclude that concerns about cognitive functioning and worries about developing dementia have generally equal effects on psychological well-being among persons with and without a parent who had been diagnosed as having AD. Put another way, any effects of concerns and worries on well-being are due less to being a first-degree relative of someone diagnosed with AD than to having and expressing worries and concerns.

We conclude by noting some important weaknesses of this study, weaknesses that we hope may be rectified by subsequent research. First, our primary emphasis has been on whether concerns about cognitive functioning and worries about developing AD have demonstrable implications for psychological well-being. We have devoted little attention to discussing the possible mechanisms underlying this relationship. One potential mechanism is stress (Rickenbach, Almeida, Seeman, & Lachman, 2014). To the extent that fears and concerns are truly stressful, prior work indicates that there ought to be a measurable impact on individuals (Diener, Suh, Lucas, & Smith, 1999; Dupre, George, Liu, & Peterson, 2015; George, 2001; Kulmala et al., 2013; Steverink, Veenstra, Oldehinkel, Gans, & Rosmalen, 2011). Then, too, we have also been constrained by the absence of data on the effects on well-being of such psychological variables as neuroticism, anxiety, and other personality variables (see, for example, Pearman & Storandt, 2005; Steinberg et al., 2013).

Second, the sample has the advantage of following Rs 3 times over 11 years, but it is small and non-representative in important respects. For instance, Rs are principally from the New England states of the United States. And the sample has a higher proportion of women and of Rs who are more highly educated than would be the case from a random sample of age peers. Although nationally representative samples of middle-aged and older Rs may have some of the outcome variables in which we were interested (e.g., The Health and Retirement Study or the Survey of Health, Ageing and Retirement in Europe), we know of none that has measures of concerns and worries that are as extensive and asked as repeatedly as those we use here. Adding such measures to ongoing national, longitudinal studies of the older population would be an important advance. Similarly, we can speak with confidence only about the effects of concerns and worries in the United States. We expect that the basic relationships shown here would exist in other nations, but only comparative research would shed light on any cultural differences that may influence the relationships (Kessler et al., 2012). A final design consideration is that it is possible the intervals between waves of data gathering may be too long for enduring effects to emerge with clarity.

Third, we are confident from an examination of the psychometric properties of our measures that they are validly tapping the concerns and anxieties people have. Yet, our COGSUM measures were developed from existing measures in an ad hoc manner. To the extent that anticipatory dementia and dementia worries are important concepts in understanding AD and related conditions, it would be well for psychometricians to devote their energies to the development and assessment of valid and reliable measures of these concerns.

Finally, although all the models are satisfactory in terms of the goodness of fit measures, there remains a great deal of unaccounted variance. The data in Table 4 show that the models we have used in this analysis accounted anywhere from .047 to .202 of the variance (the average of the R²s at T₁ is .117, at T₂ is .131, and at T₃ is .135). Knowledge of a person’s cognitive concerns and worries about developing AD is of clear significance in understanding psychological well-being, but much of the variance in the outcome measures was unaccounted for by our models.

In conclusion, the data reported on in this study lead us to suggest that practitioners should pay careful attention to the concerns and worries about cognitive changes that their patients and clients may bring with them. We found no evidence of long-term effects of worries about cognitive functioning, but we did find substantial contemporary effects. That cognitive concerns and worries do affect psychological well-being regardless of parental AD status should alert practitioners to their deleterious effects on the well-being of their patients and clients. It is all too easy to dismiss these concerns as being inconsequential; to the contrary, our results suggest that these concerns have demonstrable consequences and must be taken seriously.

Footnotes

Acknowledgements

The authors express their gratitude to Professor Lynne Hodgson of Quinnipiac University who collected the Wave 3 data used in this research and collaborated with one of the authors (S.J.C.) in earlier phases of this study. They also express their appreciation to the two anonymous reviewers whose comments and suggestions appreciably strengthened the research reported here.

Authors’ Note

An earlier version of this article was presented at the 26th Alzheimer Europe Conference in Copenhagen, Denmark, on November 2, 2016.

Declaration of Conflicting Interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for the Wave 1 data collection in 2000 was provided by a grant from the Alzheimer’s Association. Neither the subsequent waves of data collection nor the research reported in this article has received any further funding.

References

Acock

A. C.

(2013). Discovering structural equation modeling using Stata (Rev. ed.) [eBook]. College Station, TX: Stata Press.

Alzheimer’s Association. (2016). 2016 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 12, 459-509.

Bloom

D. E.

Canning

Lubet

(2015). Global population aging: Facts, challenges, solutions, & perspectives. Daedalus, 144(2), 80-92.

Bredesen

D. E.

Amos

E. C.

Canick

Ackerly

Raji

Fiala

Ahdidan

(2016). Reversal of cognitive decline in Alzheimer’s disease. Aging, 8, 1250-1258.

Cantegreil-Kallen

(2012). Fear of Alzheimer’s disease in the French population: Impact of age and proximity to the disease. International Psychogeriatrics, 24, 108-116.

Cohen

Kamarck

Mermelstein

(1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 385-396.

Commisaris

Jolles

Verhey

Ponds

Damoiseaux

Kok

(1996). Forgetfulness or dementia? Who is worried and why? European Journal of Public Health, 6, 297-299.

Cutler

S. J.

(2015). Worries about getting Alzheimer’s: Who’s concerned? American Journal of Alzheimer’s Disease & Other Dementias, 30, 591-598.

Cutler

S. J.

Brăgaru

(2015). Long-term and short-term predictors of worries about getting Alzheimer’s disease. European Journal of Ageing, 12, 341-351.

10.

Cutler

S. J.

Hodgson

L. G.

(1996). Anticipatory dementia: A link between memory appraisals and concerns about developing Alzheimer’s disease. The Gerontologist, 36, 657-664.

11.

Cutler

S. J.

Hodgson

L. G.

(2001). Correlates of personal concerns about developing Alzheimer’s disease among middle-aged persons. American Journal of Alzheimer’s Disease & Other Dementias, 16, 335-343.

12.

Cutler

S. J.

Hodgson

L. G.

(2013). Concerns about cognitive functioning, dementia worries, and psychological well-being. Revista de Asistenţă Socială/Social Work Review, 12(3), 77-86.

13.

Cutler

S. J.

Hodgson

L. G.

(2014). Is health affected by dementia worries and concerns about cognitive functioning? Revista de Asistenţă Socială/Social Work Review, 13(3), 7-15.

14.

Daviglus

M. L.

Bell

C. C.

Berrettini

Bowen

P. E.

Connolly

E. S.

Cox

N. J.

. . . Trevisan

(2010). National Institutes of Health state-of-the-science conference statement: Preventing Alzheimer disease and cognitive decline. Annals of Internal Medicine, 153, 176-181.

15.

Diener

Suh

E. M.

Lucas

R. E.

Smith

H. L.

(1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125, 276-302.

16.

Dupre

M. E.

George

L. K.

Liu

Peterson

E. D.

(2015). Association between divorce and risks for acute myocardial infarction. Circulation: Cardiovascular Quality and Outcomes, 8, 244-251.

17.

Fastame

M. C.

Penna

M. P.

Rossetti

E. S.

Agus

(2013). Perceived well-being and metacognitive efficiency in life course: A developmental perspective. Research on Aging, 35, 736-749.

18.

George

L. K.

(2001). The social psychology of health. In Binstock

R. H.

George

L. K.

(Eds.), Handbook of aging and the social sciences (5th ed., pp. 217-237). San Diego, CA: Academic Press.

19.

Grandparents.com research finds Alzheimer’s is the number one health concern among older Americans. (2016, July 18). PR Newswire. Retrieved from http://www.prnewswire.com/news-releases/grandparentscom-research-finds-alzheimers-is-the-number-one-health-concern-among-older-americans-300300213.html

20.

Green

R. C.

Cupples

L. A.

Benke

K. S.

Edeki

Griffith

P. A.

. . . Farrer

(2002). Risk of dementia among White and African American relatives of patients with Alzheimer disease. Journal of the American Medical Association, 287, 329-336.

21.

Harvard School of Public Health and Alzheimer Europe. (2011). Five-country Alzheimer’s disease survey. Retrieved from https://www.hsph.harvard.edu/news/press-releases/alzheimers-international-survey/

22.

Goodkind

D. E.

Kowal

(2016). An aging world: 2015 (U.S. Census Bureau, International Population Reports, P95/16-11). Washington, DC: U.S. Government Publishing Office.

23.

Herrmann

(1984). Questionnaires about memory. In Harris

Morris

(Eds.), Everyday memory, actions, and absentmindedness (pp. 133-151). New York, NY: Academic Press.

24.

Hodgson

L. G.

Cutler

S. J.

(2004). Help-seeking for personal concerns about developing Alzheimer’s disease. Journal of Applied Gerontology, 23, 385-410.

25.

Huffington Post UK/PA. (2014, August 4). Why people fear dementia more than they do cancer. The Huffington Post UK. Retrieved from http://www.huffingtonpost.co.uk/2014/08/04/dementia-more-feared-than-cancer_n_5646872.html

26.

Kessler

E.-M.

Bowen

Baer

Froelich

Wahl

H.-W.

(2012). Dementia worry: A psychological examination of an unexplored phenomenon. European Journal of Ageing, 9, 275-284.

27.

Kim

Schulz

(2008). Family caregivers’ strains: Comparative analysis of cancer caregiving with dementia, diabetes, and frail elderly. Journal of Aging and Health, 20, 483-503.

28.

Kohout

F. J.

Berkman

L. F.

Evans

D. A.

Cornoni-Huntley

(1993). Two shorter forms of the CES-D depression symptoms index. Journal of Aging and Health, 5, 179-193.

29.

Kulmala

von Bonsdorff

M. B.

Stenholm

Törmäkangas

von Bonsdorff

M. E.

Nygård

C.-H.

. . . Rantanen

(2013). Perceived stress symptoms in midlife predict disability in old age: A 28-year prospective cohort study. The Journals of Gerontology, Series A: Biological Sciences & Medical Sciences, 68, 984-991.

30.

Leinenga

Götz

(2015). Scanning ultrasound removes amyloid-β and restores memory in an Alzheimer’s disease mouse model. Science Translational Medicine, 7(278), Article 278ra33.

31.

MetLife Foundation. (2011). What America thinks: MetLife Foundation Alzheimer’s survey. Retrieved from https://www.metlife.com/metlife-foundation/reports-research/index.html?WT.ac=GN_metlife-foundation_reports-research

32.

Meunier

(2016). Age and Alzheimer’s disease. Nutrients, 8, 372.

33.

Pearlin

L. I.

Menaghan

E. G.

Lieberman

M. A.

Mullan

J. T.

(1981). The stress process. Journal of Health and Social behavior, 22, 337-356.

34.

Pearman

Storandt

(2005). Self-discipline and self-consciousness predict subjective memory in older adults. The Journals of Gerontology, Series B: Psychological Sciences & Social Sciences, 60, 153-157.

35.

Prince

Albanese

Guerchet

Prina

(2014). World Alzheimer report 2014: Dementia and risk reduction, an analysis of protective and modifiable factors. London, England: Alzheimer’s Disease International.

36.

Prince

Wimo

Guerchet

Ali

G.-C.

Y.-T.

Prina

(2015). World Alzheimer report 2015: The global impact of dementia, an analysis of prevalence, incidence, cost and trends. London, England: Alzheimer’s Disease International.

37.

Rickenbach

E. H.

Almeida

D. M.

Seeman

T. E.

Lachman

M. E.

(2014). Daily stress magnifies the association between cognitive decline and everyday memory problems: An integration of longitudinal and diary methods. Psychology and Aging, 29, 852-862.

38.

Roberts

J. S.

McLaughlin

S. J.

Connell

C. M.

(2014). Public beliefs and knowledge about risk and protective factors for Alzheimer’s disease. Alzheimer’s & Dementia, 10(5, Suppl.), S381-S389.

39.

Roth

D. L.

Fredman

Haley

W. E.

(2015). Informal caregiving and its impact on health: A reappraisal from population-based studies. The Gerontologist, 55, 309-319.

40.

Salthouse

T. A.

Mandell

A. R.

(2013). Do age-related increases in tip-of-the-tongue experiences signify episodic memory impairments? Psychological Science, 24, 2489-2497.

41.

Silverman

J. M.

Zaccario

M. L.

Smith

C. J.

Schmeidler

Mohs

R. C.

Davis

K. L.

(1994). Patterns of risk in first-degree relatives of patients with Alzheimer’s disease. Archives of General Psychiatry, 51, 577-586.

42.

Steinberg

S. I.

Negash

Sammel

Bogner

Harel

Livney

M. G.

. . . Arnold

S. E.

(2013). Subjective memory complaints, cognitive performance, and psychological factors in healthy older adults. American Journal of Alzheimer’s Disease & Other Dementias, 28, 776-783.

43.

Steverink

Veenstra

Oldehinkel

A. J.

Gans

R. O. B.

Rosmalen

J. G. M.

(2011). Is social stress in the first half of life detrimental to later physical and mental health in both men and women? European Journal of Ageing, 8, 21-30.

44.

Tufiș

(2012). Status attainment: Predictable patterns or trendless fluctuation? Iași, Romania: Institutul European.

45.

Werner

(2002). Assessing correlates of concern about developing Alzheimer’s dementia among adults with no family history of the disease. American Journal of Alzheimer’s Disease & Other Dementias, 17, 331-337.

46.

Werner.

Goldberg

Mandel

Korczyn

A. D

. (2013). Gender differences in lay persons’ beliefs and knowledge about Alzheimer’s disease (AD): A national representative study of Israeli adults. Archives of Gerontology and Geriatrics, 56, 400-404.

47.

Zeng

Xie

Wang

Luo

Shi

Zou

. . . Lian

(2015). General public perceptions and attitudes toward Alzheimer’s disease from five cities in China. Journal of Alzheimer’s Disease, 43, 511-518.