Later Life as a Daring Experience: Factors Associated with Older Adults’ Risk Perception

ABSTRACT

Risk perception refers to people’s subjective judgments about the possibility of negative occurrences and the extent to which they are concerned with them. Previous studies have found that older adults who were exposed to ongoing terror threats developed later-life and terror risk perceptions. These studies showed that high risk perception has negative psychological and physiological consequences. This study aimed to identify the factors associated with the development of both later-life risk perception and terror risk perception in later life. Data were collected via an online survey with 306 Internet users aged 50 years and over, half resided in a high-risk zone while the remainder lived in a low-risk zone. The Perceived Risk Scale, measures of depressive symptoms, life satisfaction, social support, spirituality, internet use, and personal background were applied. Low self-rated health was associated with terror and later-life risk perceptions, regardless of the risk zone. After controlling for personal background, only depressive symptoms significantly correlated with high risk perceptions. These findings suggest that older adults with poorer self-rated health, secular beliefs, and elevated depressive symptoms may be susceptible to developing high risk perceptions. Clinicians should encourage older adults to identify preserving resources to improve adjustment to late life stressors.

KEYWORDS:

• Later life
• risk perception
• terror
• health
• depressive symptoms

Introduction

Risk perception refers to individuals’ subjective judgments about the likelihood of negative events such as injury, disease, death, etc. (Lifshitz et al., 2016b). It is an important determinant of protective behavior because it defines which risks people care about and how they cope with them. The literature regarding risk perception suggests several theoretical paradigms, of which the most prominent is the psychometric paradigm.

This perspective treats risk perception as a multidimensional construct and uses multidimensional scaling, clustering, and factor analysis to distinguish its underlying psychological dimensions (Slovic et al., 1986). In this paradigm, the psychological risk dimension can be identified by two categories. The first, dread, is defined by a perceived lack of control, feelings of dread, and perceived catastrophic potential. The second dimension, risk of the unknown, is defined as the extent to which a hazard is judged to be unobservable, unknown, new, or delayed in producing harmful impacts. It seems that risk perceptions in a wide range of countries are affected by both categories (Slovic, 2000). Yet, they differ according to specific threats associated with the circumstances in each national context (e.g., socioeconomic development, terror attacks).

The concept of hostile-world scenario (HWS) can be relevant to the potentially cumulative adversities in older adults’ life course. This concept is part of the pursuit of happiness in a hostile world model, proposed by Shmotkin (2005, Shmotkin & Shrira, 2012, 2013; Shmotkin, 2011), describing the dialectical perception of resilience and vulnerability in the face of life adversities along the adult life span. The HWS refers to the personal image that individuals have about actual or potential threats to their life. With age, the activation of the HWS is expected to increase by cumulative negatively perceived threats. The model also postulates that the HWS, if activated adaptively, helps the individual keep vigilant and prudent in the human quest to remain safe and well; yet, an extreme HWS generates a sense of struggling to survive in a disastrous world (Shrira, Palgi, Ben-Ezra, & Shmotkin, 2011).

Personal background characteristics and risk perception

The literature highlights several personal background characteristics associated with risk perception, three of which are particularly notable: demographics, socio-psychological variables, and structural variables (Sarafino, 2002). Higher risk judgments were linked to being a woman (Olofsson & Öhman, 2015; Slovic, 2000), being a member of a minority group (Slovic, 2000), being younger in age (Lidén & Olofsson, 2020; Pasion et al., 2020), living alone (Lidén & Olofsson, 2020), and having less education (Lidén & Olofsson, 2020). Sjöberg (2001) also postulated that certain individuals may demonstrate a greater sensitivity to risk depending on their culture, social evaluations, and structured conceptions of the world.

Previous experience with risk was found to be another predictor for risk perception (Slovic, 1986, 2000; Öhman, 2017). For example, following exposure to terror, terror-risk perception was found to be significantly higher in those living in a high-risk zone compared to those in a low-risk zone (Lifshitz et al., 2016b). Traditionally, risk perception frameworks have focused on cognitive, logical, and rule-based judgments concerning a specific risk. Over time, intuitive, experiential, and affective processes have been recognized as well (Ferrer et al., 2016). Affective risk perception refers to the positive vs. negative emotional responses (such as worry or fear) to the likelihood of facing a risk (Ferrer et al., 2016; Leventhal et al., 1980; Lidén & Olofsson, 2020). Öhman (2017) reported that there is a significant correlation between experience and perception of the same kind of risk. Moreover, social closeness with people affected by the same kind of risk was found to be correlated with higher risk perception (Liu et al., 2020).

Wellbeing and risk perception

The need and desire to understand wellbeing in old age have generated a significant volume of scientific research. “Over the course of gerontological research, numerous terminologies have emerged in an attempt to capture and describe the concept” (Poon & Cohen-Mansfield, 2011, p. 46). Measures of wellbeing width a large range of constructs and dimensions, from the more objective (e.g., quality of life, depressive symptoms) to the more subjective ones (e.g., life satisfaction).

The literature reports conflicting findings concerning the association between actual and perceived risks (specifically, exposure to extreme violence such as terror attacks(and wellbeing. Norris et al. (2002) found that over 60,000 individuals who experienced 102 different risk events exhibited different levels of psychological distress, behavioral changes, and physiological illness. Some studies reported a significant correlation between the exposure level to a specific risk and negative psychological and physiological reactions that followed (Benzion et al., 2009; Norris et al., 2002; Palgi et al., 2010). In a recent study, higher risk perception, including both terror and later-life risk perceptions, was associated with more depressive symptoms, and later-life risk perception was associated with lower life satisfaction (Lifshitz et al., 2016b). Additionally, risk perception was positively correlated with reported adoption of protective health behaviors during the COVID-19 pandemic (Guastafierro et al., 2021; Schneider et al., 2021). In contrast, studies conducted after the September 11 terror attacks in the U.S. found that stress reactions were not correlated with immediate exposure to terror, as high-risk perception was also found in remote areas (Cohen-Silver et al., 2002; Schlenger et al., 2002).

Coping resources, wellbeing and risk perception

Extensive research has been dedicated to identifying and understanding the coping resources that promote humans’ optimal functioning and wellbeing. Ryan and Deci (2001) identified several potential antecedents of wellbeing, such as personality traits, emotions, and social support. These resources are perceived as contributing to successful coping that can determine wellbeing (Galiana et al., 2020). Coping is defined as a set of cognitive and behavioral efforts that aim to manage the specific demands that exceed the resources of the individual (Lazarus & Folkman, 1984). According to Hobfoll’s Conservation of Resource Theory (Hobfoll & Wells, 1998), a loss of resources is a crucial factor associated with stress experience and symptoms (Jopp & Lampraski, 2018).

In previous studies, some internal and external coping resources were found to be correlated with wellbeing, especially during stressful situations. The current study focused on three representative resources found as particularly significant to wellbeing. The first resource is perceived social support, representing a combination of internal and external coping mechanisms.

Numerous studies have shown that social support reduces the stress level experienced by an individual (e.g., Harandi et al., 2017). Moreover, all sources of social support (from family, friends, and significant others) were associated with wellbeing among older adults experiencing risk situations (Lifshitz, 2016). This can be explained by describing the resource of social support as an indirect stress buffer (e.g., a stressful event is experienced as a lesser risk in the presence of social support), as well as directly promoting coping. In addition, while this study found that social support had an important role in preserving the wellbeing of older adults living in a high-risk zone by preventing depression, it did not increase their life satisfaction (Author, 2016).

The second coping resource is spirituality, an internal coping mechanism, which was found to be positively associated with wellbeing in later life (e.g., Kirby et al., 2004; Koenig et al., 2001; Lifshitz, Ifrah, et al., 2019; Reutter & Bigatti, 2014). Moreover, spirituality and religious practices were a protective factor during the COVID-19 pandemic, associated with physical health as well as with wellbeing (Coppola et al., 2021). However, by applying Fisher’s (2010) multidimensional approach to spirituality (including personal, communal, environmental, and transcendental spirituality) Lifshitz, Nimrod, et al. (2019) found that personal spirituality was the only domain positively associated with wellbeing (lower depressive symptoms and higher life satisfaction).

The third coping resource found in the literature is internet use. This resource, considered to be an external resource, has showed an overall positive association with wellbeing in old age (e.g., Forsman & Nordmyr, 2017). Yet, a recent study that focused on the purpose of internet use found that among the four use purposes (communication, information, task performance, and leisure), only leisure use was associated significantly with wellbeing (Lifshitz et al., 2016a). Moreover, in a study conducted during the COVID-19 pandemic, stress was significantly and positively associated with an increase in internet use for interpersonal communications and online errands. However, using the internet for leisure was the only use found to be associated significantly with older adults’ wellbeing (Nimrod, 2020).

Studying risk perception may be beneficial in many ways, especially in later life. The cumulative inequality theory (Ferraro & Shippee, 2009) claims that cumulative adversity shapes functioning in old age and possibly leads to accelerated aging. The human tendency is to reduce the exposure to risk and in so doing, maintain wellbeing. Therefore, it is important to provide an empirical analysis of how risk is perceived and what factors affect its perception to enable older adults, who face various and continues potential risks, to monitor for detection of developing adversities, find and activate resources within themselves and in their environment, and thus preserve wellbeing.

Understanding how risk perception is related to various situational and personal resources may enable the development of successful strategies for coping and for interventions. However, among the different studies that described the factors related to risk perception, only a few focused on older adults. These studies examined only one predicting factor at a time, either decreasing negative psychological consequences or improving positive ones (e.g., Dural et al., 2021; Nimrod, 2020; Reutter & Bigatti, 2014). Therefore, the current study aimed at expanding our knowledge by identifying correlates of risk perception (including terror risk perception and later-life risk perception) in later life simultaneously with the three variable groups/categories that were identified in previous research: (1) background characteristics, (2) two measures of wellbeing: Life satisfaction (subjective measure) and depressive symptoms (objective measure), and (3) three representatives of coping resources: internal, external and a combination of internal and external.

The study hypotheses

Based on the literature reviewed above, the study tests five main hypotheses:

Hypothesis 1:

Terror risk perception and later-life risk perception will vary among older adults 50+ years with different background characteristics.

Hypothesis 2:

Terror risk perception and later-life risk perception will be associated with measures of wellbeing: positively with depressive symptoms and negatively with life satisfaction.

Hypothesis 3:

High levels of spirituality, specifically personal spirituality, will be associated with lower terror risk perception and later-life risk perception.

Hypothesis 4:

High levels of social support will be associated with lower terror risk perception and later-life risk perception.

Hypothesis 5:

Internet use, specifically the use for leisure, will be associated with lower terror risk perception and later-life risk perception.

Methods

Data collection and sample

Data were collected within the framework of a research project that explored the wellbeing of individuals aged 50 years and over residing in residing in Israel which is involved in an ongoing military conflict with a neighboring country. Three hundred and six individuals completed an online survey. In line with the project’s goal, about half (144) resided in a high-risk zone, consisting of areas close to the border, while the remainder (162) lived in a low-risk zone (for more information, see Lifshitz et al., 2016b). This sample was derived from a commercial panel comprised of 50,000 registered participants. The commercial online panel hosted the survey on its website and enabled the researchers to reach numerous people with the relevnt demographic information for the study (e.g., age and place of residence). Two hundred participants were randomly sampled from each residential area (i.e., the response rate was 306/400; 76.5%). Participants were contacted by e-mail with a link to a survey. Completion of the survey constituted an informed consent. The study was approved by the Ethics Committee of the Faculty of Humanities and Social Sciences at the second and third authors’ Academic Institute.

Measurement

Personal background

The questionnaire included demographic and socio-demographic questions regarding age (years), gender (man/woman), religious orientation (secular/religious) and self-rated health on a five-point Likert scale ranging from 1 (very bad) to 5 (very good). Place of residence (i.e., high/low risk zone) was also used as a background variable.

Risk perception

The Perceived Risk Scale (Lifshitz et al., 2016b) was used to measure risk perception. This scale refers to two types of risk: Later life risks, consisting of five items (experiencing disability, being chronically ill, experiencing a fall, being involved in a traffic accident, experiencing financial loss) and terror risks, which includes three items (being physically harmed in a terror attack, being emotionally harmed in a terror attack, having property harmed in a terror attack). Participants were asked to evaluate the likelihood of their experiencing each of the eight items (each representing a risk) in the coming year on a scale ranging from 0% (“highly unlikely”) to 100% (“very likely”), with a higher score representing a higher perceived risk. Cronbach’s alpha for the total scale was α = 0.92, and α = 0.88 and α = 0.91 for the two subscales, respectively.

Wellbeing

Two commonly used measures were applied to measure wellbeing: Depressive symptoms, representing a more objective measure, and life satisfaction, representing a more subjective measure. The short version of the Center for Epidemiological Studies Depression Scale (Radloff, 1977) was used. It consists of 11 statements regarding depressive symptoms felt over the past week, and ranked by participants on a Likert scale ranging from 1 (rarely or never) to 3 (most of the time). Sample questions include items such as “In the past week I felt depressed,” “In the past week I felt lonely,” and “In the past week, I enjoyed life” (reverse coded). Cronbach’s alpha was found to be high: α = 0.86.

Life satisfaction was assessed with the Satisfaction with Life Scale (Diener et al., 1985), comprising five statements ranked on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Sample questions include items such as “In most ways my life is close to my ideal,” and “If I could live my life over, I would change almost nothing.” Cronbach’s alpha was found to be high: α = 0.91.

Social support

The commonly used Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988) was applied. This 12-item self-reporting instrument asks respondents to evaluate how they feel about each statement regarding three sources of support: family (e.g., “I get the emotional help and support I need from my family”), friends (e.g., “My friends really try to help me”), and significant others (e.g., “There is a special person that is around when I am in need”) on a Likert scale ranging from 1 (very strongly disagree) to 7 (very strongly agree). Cronbach’s alpha for the total scale was found to be high: α = 0.95.

Spirituality

The Spiritual Health and Life-Orientation Measure (SHALOM; Fisher, 2010) was used to measure spirituality. This scale is comprised of 20 items, five items for each of its four domains: personal (e.g., sense of identity), communal (e.g., forgiveness toward others), environmental (e.g., connection with nature), and transcendental (e.g., feeling close to God). Each item requires the respondents to consider how this is reflected in their daily personal experience on a Likert scale ranging from 1 (very low) to 5 (very high). Internal consistency of the four dimensions was found to be very high (0.85 < α < 0.96).

Internet use

A four-item scale developed and tested by Dahan and Nimrod (2014) was used to assess internet use. Participants were asked to rank their intensity of use for each of the four main online functions (interpersonal communication, information, task performance, leisure) during the week preceding the survey on a Likert scale ranging from 1 (very rarely) to 5 (very frequently). Each online use was accompanied by relevant examples such as “banking, shopping, and scheduling appointments” for task performance and “games, films, music, and photo albums” for leisure.

Data analysis

After performing descriptive statistics, the associations between continuous variables were tested using Pearson correlation. Then two series of hierarchical multiple regression analyses were conducted for each of the risk perceptions. In each regression analyses, Step 1 included the socio-demographic characteristics. In Step 2, depressive symptoms were added, in Step 3 life satisfaction, and in Step 4 the independent variables representing the coping resources. Only variables found to be significantly correlated with the dependent variables in the bivariate analyses were included in the regression models. All continuous variables were standardized before being entered into the analyses. Data were analyzed using SPSS statistical software, PC version 27.0.

Results

Sample characteristics

As shown in Table 1, the study sample’s mean age was 58.8 (SD = 6.03, range 50–77) and no significant effect was found for risk area, t(304) = −.84, p = .084); 57% were female; 36% classified themselves as religious; 75% rated their health as good, very good, or excellent; and 47% lived in a high-risk zone. Participants reported an average level of depressive symptoms (M = 16.64, lower than 21 – the cutoff for depression, SD = 4.37) and a high level of life satisfaction (M = 4.86, SD = 1.30). Additionally, the most used resources were social support from significant others (M = 6.01), personal and communal spirituality (M = 3.76, M = 3.80, respectively), and using the internet for interpersonal communication and information (M = 4.01, M = 3.97, respectively).

Table 1. Means, standard deviations, and correlations between main study variables.

	Variables	M	SD	Terror Risk Perception	Later-Life Risk Perception
1.	Terror risk perception	29.63	22.71	1	.61**
2.	Later-life risk perception	31.60	23.02	. 61**	1
3.	Age	58.80	6.03	.00	.11*
4.	Gender ͣ	.57	.49	.00	.00
5.	Religiosity^b	.36	.48	.00	−.11*
6.	Self-rated health	3.20	1.08	−.15**	−.47**
7.	Place of residence^c	.47	.49	.27**	.10
8.	Depressive symptoms	16.64	4.37	.30**	.32**
9.	Life satisfaction	4.86	1.30	−.12**	−.22**
10.	Social support from family	5.76	1.26	−.03	−.09
11.	Social support from friends	5.37	1.31	−.01	−.10
12.	Social support from significant others	6.01	1.02	−.04	−.16**
13.	Personal spirituality	3.76	.77	−.05	−.15**
14.	Communal spirituality	3.80	.69	.01	−.06
15.	Environmental spirituality	3.45	.85	.06	−.09
16.	Transcendental spirituality	2.42	1.30	.02	−.08
17.	Internet use for interpersonal communication	4.01	1.02	−.04	−.01
18.	Internet use for information	3.97	.88	−.00	−.03
19.	Internet use for task performance	3.11	1.25	−.15**	−.05
20.	Internet use for leisure	2.80	1.25	.04	−.02

N = 306, Correlation values present Pearson coefficients (gender and area of risk present point-biserial coefficients). Gender was coded 0 = man, 1 = woman, ^bReligiosity orientation was coded 0=secular,1=religious, ^cPlace of residence was coded 0=low risk zone, 1=high risk zone.

* p < .05. ** p < .01.

Associations between personal background, wellbeing, coping resources, and risk perceptions

The analysis identified a number of significant correlations between the various variables and risk perception (see Table 1). Significant negative correlations were found between terror risk perception and self-rated health (r = −.15, p < .01), life satisfaction (r = −.12, p < .01) and using the internet for task performance (r =-.15, p < .01). Significant positive correlations were found with place of residence (living in a high-risk zone was positively correlated with terror risk perception; (r = .27, p < .01) and depressive symptoms (r = .30, p < .01). Later-life risk perception was associated negatively and significantly with levels of religiosity (r = −.11, p < .05), self-rated health (r = −.47, p < .01), life satisfaction (r = −.22, p < .01), receiving social support from significant others (r = −.16, p < .01), and personal spirituality (r = −.15, p < .01). It also had positive correlations with age (r = .11, p < .05) and depressive symptoms (r = .32, p < .01). (The full correlation matrix is available from the first author upon request).

Factors associated with risk perception

Results of the two regression analyses are presented in Table 2. In the first hierarchical multiple regression with terror risk perception as the dependent variable, personal background characteristics were entered in the first block into the equation. Two variables emerged as significant predictors of terror risk perception: self-rated health (β = −.153, t = −2.803, p < .01) and place of residence (β =.275, t = 5.034, p < .001). The model explained a modest percentage (9.8%) of the observed variance and was found to be significant, F (2, 303) = 16.441, p < .001. Depressive symptoms were entered into the equation in the second block. This resulted in a significant change in R² (∆R² = 5.4%). Together, the variables in the equation explained 15.2% of the observed variance, F (5, 300) = 11.601, p < .001. Depressive symptoms emerged as significant predictors of terror risk perception (β =.253, t = 4.391, p < .001). Life satisfaction was entered in the third block, and internet use for task performance was entered in the fourth block. These steps did not result in significant changes in R².

Table 2. Factors associated with terror and later-life risk perceptions: a linear regression analysis.

Variables	Terror Risk Perception	Later-Life Risk Perception
Step 1 (∆R^2)	.098***	.240***
Age	-	.057
Religiosity^b	-	−.114*
Self-rated health	−.153**	−.466***
Place of residence^c	.275***	-
Step 2 (∆R^2)	.054***	.033***
Depressive symptoms	.253***	.199***
Step 3 (∆R^2)	.001	.000
Life satisfaction	−.028	.017
Step 4 (∆R^2)	.009	.000
Social support from significant others	-	−.011
Personal spirituality	-	.034
Internet use for task performance	−.100	-
R^2	.152	.273
F	11.601***	16.115***
df	(5,300)	(7,298)

In the second hierarchical multiple regression with later-life risk perception as the dependent variable, personal background characteristics were entered in the first block into the equation. Two variables emerged as significant predictors of later-life risk perception: religiosity (β =-.114, t = −2.266, p < .05) and self-rated health (β = −.466, t = −9.222, p < .001). The model explained a modest percentage (24%) of the observed variance and was found to be significant, F (3, 302) = 31.831, p < .001. Depressive symptoms were entered into the equation in the second block. This resulted in a significant change in R² (∆R² = 3.3%). Together, the variables in the equation explained 27.3% of the observed variance, F (7, 298) = 16.115, p < .001. Depressive symptoms emerged as a significant predictor of later-life risk perception (β =.199, t = 3.704, p < .001). Life satisfaction was entered in the third block, and social support from significant others and personal spirituality were entered in the fourth block. These steps did not result in significant changes in R² (Full hierarchical tables are available from the first author upon request).

The results indicate that self-rated health was the only background variable negatively associated with both terror and later-life risk perceptions, while residing in a high-risk zone was positively associated only with terror risk perception, and religiosity was negatively associated only with later-life risk perception. Additionally, after controlling for the background characteristics associated with each risk perception, depressive symptoms were positively associated with both terror risk perception and later-life risk perception, but life satisfaction was not correlated significantly with either the risk perception.

Discussion

This study aimed at identifying the factors associated with older adults’ risk perceptions. Its innovation lies in the simultaneous evaluation of the associations of three types of variables explored separately in previous research (i.e., personal background, two measures of wellbeing, and three coping resources representing external and internal mechanisms) with two types of risk perceptions, namely, later-life and terror risk perceptions. This approach enabled an in depth understanding of older adults’ characteristics associated with risk perception and revealed their potential vulnerability.

Our findings indicate that study participants who lived in a high-risk zone were more prone to develop terror risk perception compared to participants who lived in a low-risk zone. This finding is in accordance with previous studies that suggested that there is a clear relationship between experience and perception of the same kind of risk (e.g., Öhman, 2017). The findings also suggest that vulnerability, manifested in lower health and lower usage of coping resources, is correlated with higher risk perceptions. Low self-rated health, as well as low frequency of using the internet for task performance were associated with higher terror risk perception, while low self-rated health and older age, as well as low perceived social support from significant others and personal spirituality were associated with higher later-life risk perception. Moreover, being secular was associated with higher later-life risk perception, suggesting that religiosity may be an important coping resource in later life. It may thus be concluded that Hypothesis 1 was confirmed and that terror risk perception and later-life perception vary among older adults with different background characteristics.

In this vein, significant correlations were found between participants’ wellbeing, as postulated in depressive symptoms and life satisfaction, and both terror and later-life risk perceptions. However, it was somewhat surprising to note that after controlling for personal background, depressive symptoms were the only factor associated with both terror and later-life risk perceptions. Therefore, the results were only partially supportive of Hypothesis 2. These findings conform with the extensive literature regarding the association between risk perception and negative psychological reactions (Norris et al., 2002). The finding that life satisfaction was not a significant factor associated with both risk perceptions may be explained by the study participants’ characteristics as manifested in high life satisfaction and good self-reported health. Nevertheless, these correlations should be interpreted cautiously, as they are bilateral in nature: While previous studies have established that people exposed to risks may be harmed psychologically, the current study demonstrates that people with a high level of depressive symptoms and lower life satisfaction may develop high risk perceptions. Moreover, as this study focused specifically on older adults, this may implies that poor psychological wellbeing is related to people’s subjective judgments of stress situations in later life.

A major conclusion of the present study is that older adults may be susceptible to develop later-life risk perception due to their vulnerability, as manifested in this study in poorer self-rated health, a low level of religiosity, and more depressive symptoms. This conclusion is based on the concept of the perception of control (Brug et al., 2004), which claims that people feel themselves more at risk from threats they cannot control (e.g., Nordgren et al., 2007). Based on previous research suggesting an ongoing reciprocal correlations between perceived control with health and wellbeing with age, older adults may perceive themselves as having less control of their lives (Robinson & Lachman, 2017). In our study, feeling vulnerable, physically and mentally, may have contributed to a decrease in their perception of control, and this was apparent in higher terror and later-life risk perceptions.

Another somewhat disturbing implication of the above conclusion is the potential development of risk perception in the face of continuing exposure to adversities in later life. Although the majority of older adults seem resilient to lifetime adversities and may even demonstrate post-traumatic growth (Tedeschi & Calhoun, 2004), some people may still be mentally more vulnerable to the effects of adversity than others (Lifshitz, Ifrah, et al., 2019). Continuous exposure to lifetime adversity is known to have a detrimental effect on late-life mental health (Seery et al., 2010; Shmotkin & Litwin, 2009) and to increase psychological difficulties among older adults (Palgi et al., 2015). This emerging cycle may activate the Hostile-World Scenario (HWS) which creates an image of actual or potential threats to one’s physical and mental integrity. Every individual has such an image of threats in mind, which practically constitutes a system of self- beliefs about possible catastrophes and inflictions such as accidents, wars, illness, loss of loved ones, aging, and death (Shmotkin & Shrira, 2012, 2013; Shmotkin, 2005, 2011).

With age, the activation of the HWS is expected to increase due to threats associated with old age (e.g., deteriorating health, the death of one’s spouse and close friends, loss of independence, cognitive impairment, elder abuse), but an extreme HWS generates a sense of struggling to survive in a disastrous world (Shrira et al., 2011). Thus, vulnerability, as exhibited in the current study by poorer self-rated health and more depressive symptoms in later life, contributes to higher risk perceptions and continuous late-life stressors may lead to an extreme HWS.

Furthermore, although significant negative correlations were found between terror risk perception and using the internet for task performance and between later-life risk perception and receiving social support from significant others and with personal spirituality, and while previous studies have suggested otherwise, after controlling for the backgrounds variables, the coping resources selected in this study did not correlate with risk perceptions. Therefore, these results were not in line with Hypotheses 3,4,5. Individuals need to react to emerging threats based on their potential resources, and older adults may need help to learn how to effectively adopt problem-solving, emotional, and action-oriented coping mechanisms to preserve their health (Rana et al., 2021). Thus, it is important to encourage them to find and activate resources within themselves and in their environment that can help them to preserve wellbeing facing stressful encounters (Lazarus & Folkman, 1984), thus, decreasing risk perceptions.

Limitations and future research

There are several limitations in this study that should be acknowledged. First, the sample consisted of older internet users who were relatively young, healthy, and secular. Moreover, considering the sampling method employed, the sample was not representative of the country’s older population. Additionally, the self-report nature of the data may have biased the associations between the major study variables. Moreover, as the data were gathered in a country involved in a military conflict, the study conclusions may not be generalizable to peaceful countries. Furthermore, the survey was conducted during periods of calm and confrontation alike, a situation that may have affected the participants’ perception of risks. Finally, the study design was cross-sectional, which does not allow for causal interpretations.

Considering the above limitations, this study should be seen as a preliminary examination of the factors associated with risk perception. Future studies should further examine risk perception with other socio-demographics, cultures, various stressful situational variables, different internal and external coping resources and different measures of wellbeing (e.g., anxiety). The application of longitudinal methods in such studies will underscore causality.

Clinical implications

With caution needed in regard to the above potential limitations (e.g., relatively young sample of older adults), the current study offers an initial outlook on a potentially bothersome situation whereby older adults, regardless of the risk zone in which they live (high/low terror risk), may be prone to develop risk perception from later-life risks (e.g., illness) as their wellbeing weakens. Moreover, those residing in a high-risk zone and/or who are physically and mentally vulnerable may be more susceptible to develop terror risk perception.

While this naturally reflects vulnerability, we also suggest new directions for improving resilience: Public health practitioners and researchers should encourage older adults to identify and embrace psychological, social, and cognitive resources that will improve adjustment to late-life stressors and may help ensure positive health-promoting behaviors, especially in times of stress and loss of age-related resources, to diminish the potential of developing risk perception. Moreover, we encourage field experts to develop and implement more innovative interventions (e.g., mindfulness, nature, performance art) for older adults to strengthen their resilience while facing risks.

Author contribution

All three authors contributed equally to the conceptualization of the study and the interpretation of the results. Rinat Lifshitz collected the data, analyzed it, and wrote most of the manuscript. Galit Nimrod and Yaacov Bachner wrote parts of the manuscript, revised the manuscript, and finalized it.

Compliance with ethical standards

All procedures involving human participants were performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.