The associations of pandemic-related difficulties with depressive symptoms and psychological growth among American older adults: Social support as moderators

Abstract

The COVID-19 pandemic brought social, health-related, and financial risks to older adults, yet their associations with depressive symptoms and posttraumatic growth (PTG) were not systematically examined. With 3504 respondents aged 60 and over from Health and Retirement Survey, this study found pandemic-related healthcare delay and financial hardship associated with elevated depressive symptoms and decreased PTG, whereas social disruption predicted greater PTG. When confronted with multidimensional difficulties, a higher level of social support buffered depressive symptoms and enhanced PTG following healthcare delay, while those from immediate family members carried the weighing of moderation. Additionally, the moderation effect varied between support types, as exclusive instrumental support engendered more depressive symptoms and squeezed PTG by stimulating a sense of incompetence for older adults. Inversely, receiving both instrumental and emotional support helped individuals of older age against financial-related depressive symptoms. These findings shed light on older adults’ mental health promotion in a pandemic context.

Keywords

depressive symptoms older adults pandemic-related difficulties posttraumatic growth social support

Introduction

The Coronavirus pandemic (COVID-19) arouses mental health challenges for the infected people and the general population associated with its preventive measures and socio-economic impacts (Pfefferbaum and North, 2020). This mental health crisis might be particularly worrisome among older adults, as they are vulnerable to more severe complications and higher mortality and often have more significant difficulties accessing healthcare and reentering the workforce (Vahia et al., 2020). A sizable of studies have investigated the psychological impacts of the pandemic on older adults, estimating an 8.3%–49.7% rate of anxiety, 14.6%–47.2% of depression, and 18.2%–26.4% of sleep disturbance (Rosenberg et al., 2021; Sepúlveda-Loyola et al., 2020). However, positive changes in individuals’ core beliefs (literally posttraumatic growth, PTG) also exist as a result of struggling with highly challenging events, but are less investigated (Menculini et al., 2022). Persons of older age often tend to de-emphasize negative events and have selective optimization of positive experiences, thus more likely to develop PTG (Nowlan et al., 2015). Nevertheless, one study pointed out that older adults living under the pandemic may perceive related threats as more fearful, thus making it harder to sustain PTG (Celdrán et al., 2021). PTG is important for supporting successful aging in modern societies (Taylor and Carr, 2021), yet whether and how older persons could gain psychological growth in this unprecedented pandemic is less known. Thus, to comprehensively investigate the mental health impacts of the COVID-19 pandemic on older adults, this study simultaneously examines depressive symptoms and PTG.

Often, depressive symptoms and PTG are more prevalent among people endorsing severer personal and property loss during adversities (Henson et al., 2021; Wilson-Genderson et al., 2018). As for the COVID-19 pandemic, the most pervasive difficulties for older adults apart from infectious risk are social disruption, healthcare delay, and financial hardship (Crimmins, 2020; Lee, 2020). In particular, seniors in the hard-hit United States suffer more incredible hardships than counterparts from other wealthy countries. Our previous study reveals that the proportion of American older adults with pandemic-related health and financial difficulties was 33%, and nearly all of the population experienced somewhat social disruption (Fu et al., 2022). Whereas more pandemic-related difficulties are often linked with increased depressive symptoms (Luo, 2021), its relationship with PTG is at least debatable. Existing studies across a broad spectrum of populations argued that greater pandemic-related risks enhanced or buffered PTG (Celdrán et al., 2021; Pietrzak et al., 2021) and sometimes demonstrated nonsignificant correlations (Ikizer et al., 2021). Inconsistent findings could be attributed to the rumination variance. Generally, PTG emerges when individuals perceive a high-level sense of personal control over the risks (Gouzman et al., 2022). However, the threshold of positive arousals varies over the life span (Spendelow et al., 2017). For older adults with different types and volumes of resources, there might also be distinct patterns in stress responses following social, health-related, and financial difficulties (Crimmins, 2020). Thus, to better support older adults navigating stressful situations, it is critical for this study to examine the associations of different types of pandemic-related challenges with mental health outcomes.

Moreover, social support may moderate the relationships between pandemic-related difficulties and mental health outcomes. Social support, as a combination of positive perception and experience of emotional and instrumental exchanges between individuals and their social ties (Antonucci and Jackson, 1987), often functions to regulate mental health in late life (Li et al., 2021). According to the cognitive activation theory of stress (Ursin and Eriksen, 2004), individuals’ mental health during adversities depends on the acquired expectancy of outcomes and available coping strategies associated with the stimuli. Correspondingly, social support could bear the moderation role with reappraisal and stress-coping strategies (Cobb, 1976). On the one hand, people with a higher level of social support tend to have a better sense of social safety. They are less likely to attribute the negative consequences of pandemic-related depravations to themselves, therefore, perceive the pandemic as less fearful (Armstrong et al., 2021). On the other hand, frequent social exchanges encourage older adults to cope with the pandemic-related difficulties with positive, negative, or avoidant strategies, which might help to moderate the initial stress arousals (Dominick et al., 2022).

Up to date, a large number of studies have examined the buffering effect of social support aggregated across sources on older adults’ well-being in trauma contexts (Dominick et al., 2022; Yu et al., 2020). Nevertheless, it is not simply the level of social support but also its source matters (Henson et al., 2021). Older adults receive support mainly from their spouses, kids, immediate family members, and close friends (Gariépy et al., 2016), and earlier published studies suggested that spouse’s support is more strongly associated with psychological well-being for older adults with chronic distress (Gariépy et al., 2016; You et al., 2020). However, in this unprecedented pandemic, we have no idea about the sensitivity of older adults to source-specific social support; and if the supports from different social ties demonstrate distinct patterns in moderating mental health outcomes remain unknown. In addition, the relationships between pandemic-related difficulties and mental health might also depend on the type of received support. It’s highly possible that instrumental support will stimulate problem-focused coping for individuals, whereas emotional comforts activate more emotion-focused behaviors or avoidance (Schaefer and Moos, 1998), with their impacts on mental health being hotly debated by previous studies (Fuller and Huseth-Zosel, 2021; Yu et al., 2020). Therefore, this study aims to elaborate on existing studies regarding social support’s moderation with detailed speculation on different sources and types, which might be critical for promoting mental health for the aging population in similar public health emergencies.

Aims and hypothesis

The current study aims to examine the associations of pandemic-related difficulties with depressive symptoms and PTG among older adults. In addition, we would like to test whether and how social support could moderate the above relationships.

We propose that individuals with a larger number of pandemic-related difficulties tend to have higher levels of depressive symptoms and psychological growth. More detailed, the associations might differ across difficulty types in social disruption, healthcare delay, and financial hardship. The second hypothesis concerns the moderation effect of social support. We assume that individuals with multidimensional pandemic-related difficulties would have decreased depressive symptoms and increased psychological growth in case they had a higher level of social support. Moreover, we expect that support from spouses, kids, immediate family members, or close friends weighs the moderation effect differentially. Last, we investigate the moderation effects of different social support types, assuming older adults with emotional, instrumental, or both kinds of support would have distinct mental health outcomes from those who experienced pandemic-related difficulties but received no support.

Methods

Study design and data collection

Data in this study were retrieved from the 2020 COVID-19 Project (Early, Version 1.0) of the Health and Retirement Survey, which was conducted in the United States and examined the social, health, and economic indicators of the middle-aged and older adults in COVID-19 times (https://hrsdata.isr.umich.edu). From March 2020 to May 2021, the COVID-19 module administrated a 50% random subsample of the initially assigned households to enhance the interviewing. During the survey, most states, territorial, tribal, and local governments had implemented emergency declarations, lockdown, and other restrictions to slow the progression of the pandemic. In total, 15,723 respondents from 11,490 households participated in this study and achieved a response rate of 62%. As this study focused on the associations between pandemic-related difficulties, social support, and mental health outcomes among older adults, people aged below 60 years, without valid assessments on pandemic exposure, depressive symptoms, and PTG were excluded. In final, this study included a total of 3504 respondents.

This study was approved by the Institutional Review Board at the University of Michigan and all interviews provided verbal informed consent.

Measures

Independent variables

Pandemic-related difficulties were measured with references to previous studies estimating older adults’ vulnerability during adversities (Lee, 2020; Matias et al., 2020). A total of 18 items were included and divided into three categories: social disruption, healthcare delay, and financial hardship. Social disruption indicates the impacts on individuals’ interpersonal connections (Birditt et al., 2021), including 5 items such as “family celebrations canceled or restricted” and “unable to attend in-person or religious services for a family member or friend who died” et al. Healthcare delay consists of 6 items describing older adults’ vulnerability in accessing COVID tests, surgery, doctor visits, prescription, dental care, and other healthcare services. Financial hardship includes 7 typical financial deprivations for older adults such as income deduction, expenditure growth, missing payment on rent or mortgage, missing payments on credit cards, missing payments on utilities or insurance, inability to pay medical bills, and inability to afford food. Respondents were asked to report if they had experienced each of the items since March 2020, with alternative options as yes (1) or no (0). Social disruption, healthcare delay, and financial hardship were calculated as the sum of corresponding items, and three subscales were then summed to estimate the level of pandemic-related difficulties. Of note, if individuals experienced none of these 18 depravations, they would be categorized as the “difficulties = 0” group; otherwise, the “difficulties ⩾ 1” group. In our study, the estimated reliability in terms of Cronbach’s alpha was 0.773 for social disruption, 0.769 for healthcare delay, 0.727 for financial hardship, and 0.747 for the whole scale.

The Overall and source-specific social supports are originally described by Schuster et al. (1990), estimating the level of individuals perceiving themselves to be cared for and understood by social ties. The current study constructed perceived social support for each of the following relationships: spouse, kids, immediate family members (excluding spouse and kids), and close friends (Kutschke et al., 2018). For source-specific support, respondents were asked three questions: “How much do they understand the way you feel about things?” “How much can you rely on them if you have a serious problem?” and “How much can you open up to them if you need to talk about your worries?” Items were scored from 1 (not at all) to 4 (a lot) and then summed up to estimate the level of specific social support. Individuals’ overall social support was calculated as the mean score of four source-specific supports, with a higher score for greater social support. In this study, the Cronbach’s alpha for overall social support and that from spouse, kids, immediate family members, and friends were 0.819, 0.811, 0.835, 0.862, and 0.844, respectively.

The type of social support was assessed with two questions, asking if respondents had received instrumental assistance (e.g. food, medications, emergency household repairs) or emotional support (e.g. suggestions, encouragement, moral support) since the outbroke of the COVID-19 pandemic. In the current study, social support type was constructed as a categorical variable, with four alternatives: none, instrumental support, emotional support, and two-tier support (instrumental and emotional support).

Outcome variables

Depressive symptoms were evaluated by the 8-item version of the Center for Epidemiology Studies Depression Scale (CESD-D), which was widely used to estimate late-life depression and demonstrated good psychometric properties worldwide (Zivin et al., 2010). Respondents answered the eight items such as “much of the time during the past week, I felt depressed,” “I felt everything I did was an effort,” “My sleep was restless,” “I was happy,” “I felt lonely,” “I enjoyed life,” “I felt sad,” and “I could not get going” with response options of yes or no. The depressive symptom score was calculated by counting the number of “no” responses to questions “I was happy” and “I enjoyed life” plus the number of “yes” for the other six items. The total score of this scale ranges from 0 to 8, with a higher score representing severer depressive symptoms. Cronbach’s alpha for the CESD-D in this study was 0.801.

PTG refers to enduring positive psychological changes experienced after adversities, and we in this study adopted a pre-versus-post strategy to estimate the degree of personality growth from the pandemic (Jayawickreme et al., 2021). Respondents were asked to rank the extent to which they agree with the following statement: “I tend to recover quickly after difficult times like this one,” “I have learned some positive things from this situation about myself,” “I found greater meaning in work or my other activities and hobbies,” “I now feel more in touch with people in my local community,” “I found new ways to connect socially with other people,” and “I am now more appreciative of things that I had taken for granted before.” Alternatives for each item are based on a 6-point Likert scale ranging from strongly disagree (1) to agree strongly (6). The scores were then summed to an overall score ranging from 6 to 36, with a higher score referring to more significant psychological growth. The Cronbach’s alpha for PTG in this study was 0.809.

Covariates include sociodemographic variables such as gender (male/female), race (Hispanic/non-Hispanic white/non-Hispanic black/others), marital status (married or partnered /single), education (high school or below/get high school diplomacy/some college or above), Medicaid eligibility (yes/no), quartile household wealth (lower than ordinary level/ordinary level/ordinary to advanced level/advanced level or above) and age. Besides, health status and behavioral variables in particular of chronic disease (yes /no, including stroke, diabetes, heart disease, hypertension, lung disease, and cancer), cognition (continuous variable determined by the telephone interview for cognitive status, TICS), difficulty in activities of daily living (yes /no, ADL, including eating, getting in and out of bed, toileting, dressing, walking across a room), difficulty in instrumental activities of daily living (yes /no, IADL, including preparing meals, grocery shopping, making phone calls, taking medications and managing money), drinking (yes/no) and smoking (yes/no) were also included. These variables were examined to be associated with older adults’ mental health in previous studies (Andrew et al., 2012; Zivin et al., 2010).

Statistical analyses

Descriptive analyses were conducted for all variables in this study. To compare the characteristics of older adults with different levels of pandemic-related difficulties (difficulties = 0; difficulties ⩾ 1), we performed chi-square tests for categorical variables and Welch’s t-test for continuous variables. Then, multivariate linear regressions were employed to examine the relationships between pandemic-related difficulties, social support, and mental health in depressive symptoms and PTG. We used the continuous overall and sub-scaled scores in this stage to assess the pandemic-related difficulties, respectively. In final exploratory analyses, interaction variables indicating the moderation effect of social support on relationships between sub-scaled pandemic-related difficulties and mental health were examined via linear regressions. We computed standardized beta (abbreviated as β henceforth) that could compare these predictions. All regressions had adjusted for a broad spectrum of covariates such as gender, age, education, race, marital status, Medicaid eligibility, chronic disease, ADL difficulties, IADL difficulties, cognitive functioning, smoking, and drinking. All analyses were conducted in Stata version 17.0.

Results

Descriptive analyses

Table 1 demonstrates the descriptive information of 3504 respondents and those with (n = 3132, 89.38%) or without (n = 372, 10.62%) pandemic-related difficulties, respectively. The mean score was 2 for social disruption (SD = 1.56), 0.59 for healthcare delay (SD = 0.96) and 0.39 for financial hardship (SD = 0.82). Comparatively, respondents with pandemic-related difficulties were likely to perceive a higher level of social support, t (3499) = 2.85, p = 0.004, while those without difficulties were less likely to receive assistance from others, X² (3, N = 3469) = 87.04, p < 0.001. Noteworthy, the average score of depressive symptoms (M = 1.33, SD = 1.92), t (3502) = 2.80, p = 0.005 and psychological growth (M = 25.03, SD = 5.88), t (3502) = 2.42, p = 0.016 was significantly higher among individuals with pandemic-related difficulties. Details on respondents’ socioeconomic and health characteristics are shown in Table 1.

Table 1.

Descriptive analysis of sample characteristics by different level of pandemic-related difficulties.

	Total (N = 3504)	Difficulties = 0 (n = 372)	Difficulties ⩾ 1 (n = 3132)	X²	p
	n (%)	n (%)	n (%)	X²	p
Gender				4.93	0.026*
Male	1240 (35.39)	151 (40.59)	1089 (34.77)
Female	2264 (64.61)	221 (59.41)	2043 (65.23)
Race				18.42	<0.001*
Hispanic	378 (13.08)	23 (7.93)	355 (13.65)
Non-Hispanic White	1858 (64.29)	207 (71.38)	1651 (63.50)
Non-Hispanic Black	541 (18.72)	41 (14.14)	500 (19.23)
Others	113 (3.91)	19 (6.55)	94 (3.62)
Marital status				1.84	0.174
Married or partnered	2176 (62.10)	219 (58.87)	62.48 (1957)
Single	1328 (37.90)	153 (41.13)	1175 (37.52)
Education level				9.06	0.011*
High school or below	465 (13.27)	59 (15.86)	406 (12.96)
Get high school Diplomacy	1333 (38.04)	159 (42.74)	1174 (37.48)
Some college or above	1706 (48.69)	154 (41.40)	1552 (49.55)
Medicaid eligibility				0.99	0.320
No	3071 (87.64)	332 (89.25)	2739 (87.45)
Yes	433 (12.36)	40 (10.75)	393 (12.55)
Household\|net-worth				16.08	0.001*
Lower than ordinary level	439 (12.53)	49 (13.17)	390 (12.45)
Ordinary level	1799 (51.34)	223 (59.95)	1576 (50.32)
Ordinary to advanced level	563 (16.07)	49 (13.17)	514 (16.41)
Advanced level or above	703 (20.06)	51 (13.71)	652 (20.82)
Chronic disease				1.37	0.241
None	653 (18.64)	61 (16.40)	592 (18.90)
One or more	2851 (81.36)	311 (83.60)	2540 (81.10)
ADL difficulties				1.79	0.180
None	2949 (84.16)	322 (86.56)	2627 (83.88)
One or more	555 (15.84)	50 (13.44)	505 (16.12)
IADL difficulties				5.92	0.015*
None	3086 (88.07)	342 (91.94)	2744 (87.61)
One or more	418 (11.93)	30 (8.06)	388 (12.39)
Smoking				1.04	0.308
No	3222 (91.95)	337 (90.59)	2885 (92.11)
Yes	282 (8.05)	35 (9.41)	247 (7.89)
Drinking				3.52	0.061
No	602 (17.18)	51 (13.71)	551 (17.59)
Yes	2902 (82.82)	321 (86.29)	2581 (82.41)
Social support type				87.04	<0.001*
None	1920 (55.35)	286 (78.14)	1634 (52.66)
Instrumental only	165 (4.76)	10 (2.73)	155 (5.00)
Emotional only	786 (22.66)	45 (12.30)	741 (23.88)
Instrumental and emotional	598 (17.24)	25 (6.83)	573 (18.47)
	M (SD)	M (SD)	M (SD)	t	p
Age	72.30 (8.63)	75.21 (9.02)	71.96 (8.52)	6.86	<0.001*
Cognitive functioning	16.60 (4.04)	15.62 (4.13)	16.71 (4.01)	4.36	<0.001*
Social support level	8.08 (2.27)	7.76 (2.36)	8.12 (2.27)	2.85	0.004*
Spouse support	6.71 (5.26)	6.58 (5.39)	6.72 (5.24)	0.46	0.410
Kids support	8.89 (3.67)	8.39 (4.04)	8.94 (3.62)	2.69	0.003*
Family member support	8.36 (3.24)	7.89 (3.58)	8.41 (3.20)	2.91	0.002*
Friend support	8.40 (3.48)	8.27 (3.45)	8.42 (3.48)	0.74	0.076
Depressive symptoms	1.30 (1.89)	1.03 (1.63)	1.33 (1.92)	2.80	0.005*
Psychological growth	24.94 (5.95)	24.24 (6.45)	25.03 (5.88)	2.42	0.016*
Difficulty types
Social disruption	2 (1.56)		2.24 (1.48)
Healthcare delay	0.59 (0.96)		0.66 (0.99)
Financial hardship	0.39 (0.82)		0.44 (0.85)

n (%) indicates the number (percentage) of categorical items. M (SD) indicates the mean (standard deviation) of continuous variables. X² indicates chi-square statistic value, t indicates t-test value (absolute), p indicates their statistical significance, * denotes statistically significant differences of the concern between difficulty types.

ADL: activities of daily living; IADL: instrumental activities of daily living.

Table 2 shows the associations between pandemic-related difficulties, social support, and depressive symptoms. With a wide spectrum of variables controlled, individuals with a higher level of pandemic-related difficulties tended to have greater depressive symptoms (β = 0.13, se = 0.02, p < 0.001). More detailed, a larger number of healthcare delay predicted a substantially higher level of depressive symptoms (β = 0.11, se = 0.03, p < 0.001), and to a lesser extent, financial hardship was associated with depressive symptoms (β = 0.08, se = 0.04, p < 0.001). On the contrary, social disruption presented no significant association with depressive symptoms. When confronted with multidimensional difficulties, older adults perceiving a higher level of social support were likely to have fewer depressive symptoms (β = −0.18, se = 0.02, p < 0.001), with the strongest prediction from spouse’s support (β = −0.22, se = 0.01, p < 0.001) followed by that from friends (β = -0.08, se = 0.01, p < 0.001), kids (β = −0.07, se = 0.01, p = 0.001) and immediate family members (β = −0.04, se = 0.01, p = 0.044). However, getting support from others associated with more depressive symptoms among older adults (β = 0.05, se = 0.15, p = 0.011 for instrumental support; β = 0.06, se = 0.09, p = 0.004 for emotional support; β = 0.05, se = 0.10, p = 0.009 for two-tier support).

Table 2.

Associations of pandemic-related difficulties and social support with depressive symptoms.

	Model 1			p	Model 2			p	Model 3			p
	B	se	β	p	B	se	β	p	B	se	β	p
Difficulties	0.11	0.02	0.13	<0.001***
Social disruption					0.04	0.02	0.04	0.079	0.04	0.02	0.03	0.079
Healthcare delay					0.19	0.03	0.11	<0.001***	0.19	0.03	0.11	<0.001***
Financial hardship					0.16	0.04	0.08	<0.001***	0.17	0.04	0.08	<0.001***
Support level	−0.16	0.02	-0.20	<0.001***	−0.15	0.02	−0.18	<0.001***
Spouse support level									−0.08	0.01	−0.22	<0.001***
Kid support level									−0.03	0.01	−0.07	0.001***
Family member support level									−0.02	0.01	-0.04	0.044*
Friend support level									−0.04	0.01	−0.08	<0.001***
Support type (ref: None)
Instrumental only	0.32	0.15	0.04	0.033*	0.30	0.14	0.04	0.036*	0.39	0.15	0.05	0.011*
Emotional only	0.25	0.08	0.06	0.003**	0.24	0.08	0.06	0.002**	0.25	0.09	0.06	0.004**
Instrumental and emotional	0.23	0.09	0.05	0.014*	0.23	0.09	0.05	0.009*	0.25	0.10	0.05	0.009**

B represents unstandardized regression coefficients, se indicates the standard error, β indicates the standardized regression coefficients. p value indicates the significance of associations between listed variables and depressive symptoms, ***p < 0.001, **p < 0.01, *p < 0.05.

Variables including gender, race, age, marital status, education level, Medicaid eligibility, household net-worth, cognitive functioning, chronic disease condition, ADL difficulties, IADL difficulties, drinking and smoking behaviors were controlled. List-wise strategy was used for missing values.

As shown in Table 3, the total number of pandemic-related difficulties demonstrated no significant relationship with post-pandemic growth. Yet, greater social disruption predicted a higher level of PTG (β = 0.06, se = 0.08, p = 0.004), whereas more healthcare delays (β = −0.04, se = 0.11, p = 0.031) and financial hardships (β = −0.05, se = 0.14, p = 0.026) were associated with lesser PTG. Social support contributed to positive psychological changes as respondents perceiving a higher level of support were likely to have greater PTG (β = 0.17, se = 0.06, p < 0.001), with the greatest effect from friends (β = 0.11, se = 0.04, p < 0.001) then kids (β = 0.07, se = 0.03, p < 0.001) and immediate family members (β = 0.05, se = 0.03, p = 0.022). In addition, emotional support (β = 0.04, se = 0.28, p = 0.045) and two-tier support (β = 0.11, se = 0.32, p < 0.001) predicted greater psychological growth associated with the pandemic.

Table 3.

Associations of pandemic-related difficulties and social support with psychological growth.

	Model 1			p	Model 2			p	Model 3			p
	B	se	β	p	B	se	β	p	B	se	β	p
Difficulties	−0.05	0.05	-0.01	0.900
Social disruption					0.22	0.08	0.06	0.004**	0.23	0.08	0.06	0.004**
Healthcare delay					−0.24	0.11	−0.04	0.031*	−0.24	0.11	−0.04	0.029*
Financial hardship					−0.31	0.14	−0.05	0.026*	−0.34	0.14	−0.05	0.019*
Support level	0.43	0.06	0.17	<0.001***	0.42	0.06	0.17	<0.001***
Spouse support level									0.02	0.04	0.02	0.604
Kid support level									0.11	0.03	0.07	<0.001***
Family member support level									0.08	0.03	0.05	0.022*
Friend support level									0.19	0.04	0.11	<0.001***
Support type (ref: None)
Instrumental only	0.53	0.50	0.02	0.281	0.55	0.49	0.02	0.267	0.50	0.51	0.02	0.325
Emotional only	0.74	0.28	0.05	0.008**	0.71	0.28	0.05	0.011*	0.58	0.28	0.04	0.045*
Instrumental and emotional	1.65	0.31	0.11	<0.001***	1.60	0.31	0.11	<0.001***	1.64	0.32	0.11	<0.001***

B represents unstandardized regression coefficients, se indicates the standard error, β indicates the standardized regression coefficients. p value indicates the significance of associations between listed variables and psychological growth, ***p < 0.001, **p < 0.01, *p < 0.05.

Table 4 focuses on the role of perceived social support in moderating mental health outcomes following pandemic-related difficulties. Accordingly, the interactions of support with social disruption and financial hardship were nonsignificant. However, a higher level of social support would buffer depressive symptoms (β = −0.23, se = 0.01, p < 0.001) and promote PTG (β = 0.17, se = 0.05, p = 0.034) in case older adults had healthcare delay. Moreover, the moderation effects of social support on the relationships between healthcare delay and mental health were varied between sources. Immediate family members offered the strongest support against depressive symptoms (β = −0.11, se = 0.01, p = 0.047) and promoting psychological growth (β = 0.12, se = 0.03, p = 0.043). To a lesser extent, older adults with support from friends (β = −0.10, se = 0.01, p = 0.031) and spouse (β = −0.07, se = 0.01, p = 0.035) also had a lower level of depressive symptoms in the face of healthcare delay.

Table 4.

Interaction effects of pandemic-related difficulties and perceived social support predicting mental health outcomes.

	Depressive symptoms								Psychological growth
	Model 1				Model 2				Model 1				Model 2
	B	se	β	p	B	se	β	p	B	se	β	p	B	se	β	p
Difficulty types # Support level
Social # support level	−0.01	0.01	−0.06	0.371					−0.01	0.03	−0.03	0.738
Health # support level	−0.05	0.01	−0.23	< 0.001***					0.12	0.05	0.17	0.034*
Financial # support level	−0.02	0.02	−0.06	0.157					0.01	0.05	0.01	0.545
Health # Source-specific support level
Health # Spouse support					−0.01	0.01	−0.07	0.035*					0.03	0.02	0.05	0.112
Health # Kids support					−0.02	0.01	−0.08	0.135					0.03	0.03	0.05	0.174
Health # Family members support					−0.02	0.01	−0.11	0.047*					0.07	0.03	0.12	0.043*
Health # Friend support					−0.02	0.01	−0.10	0.031*					0.02	0.03	0.01	0.847

Interaction variables were examined separately, and all models have controlled for social disruption, healthcare delay, financial hardship, support type, gender, race, age, marital status, education level, Medicaid eligibility, household net-worth, cognitive functioning, chronic disease condition, ADL difficulties, IADL difficulties, drinking and smoking behaviors. List-wise strategy was used for missing values.

Table 5 demonstrates the interactions between pandemic-related difficulties and the received support on mental health outcomes. Compared with the isolated counterparts, older adults with exclusive instrumental support were likely to have elevated depressive symptoms (β = 0.09, se = 0.14, p < 0.001) and decreased PTG (β = −0.05, se = 0.45, p = 0.041) after healthcare delay. Alike, exclusively receiving instrumental support exacerbated depressive symptoms associated with financial hardship (β = 0.04, se = 0.16, p = 0.013), but two-tier support helped older adults alleviate the depressive arousals (β = −0.06, se = 0.10, p = 0.017). However, the relationships of social disruption with mental health outcomes demonstrated no significant differences between individuals receiving different types of support.

Table 5.

Interaction effects of pandemic-related difficulties and received social support predicting mental health outcomes.

	Depressive symptoms				Psychological growth
	B	se	β	p	B	se	β	p
Social # Support type (Ref: None)
Social # instrumental only	0.04	0.11	0.03	0.533	−0.31	0.88	−0.03	0.392
Social # emotional only	0.02	0.06	0.01	0.688	−0.02	0.49	−0.01	0.916
Social # instrumental and emotional	0.05	0.06	0.03	0.725	−0.10	0.55	−0.02	0.620
Health# Support type (Ref: None)
Health # instrumental only	0.54	0.14	0.09	<0.001***	−0.92	0.45	−0.05	0.041*
Health # emotional only	0.04	0.08	0.01	0.617	−0.14	0.28	−0.01	0.609
Health # instrumental and emotional	−0.09	0.09	−0.03	0.295	−0.31	0.28	−0.03	0.269
Financial # Support Type (Ref: None)
Financial # instrumental only	0.33	0.16	0.04	0.013*	−0.81	0.54	−0.03	0.131
Financial # emotional only	0.04	0.10	0.01	0.946	0.01	0.35	0.01	0.975
Financial # instrumental and emotional	−0.23	0.10	−0.06	0.017*	−0.03	0.32	−0.01	0.931

Interaction variables were examined separately, and all models have controlled for social disruption, healthcare delay, financial hardships, support type, gender, race, age, marital status, education level, Medicaid eligibility, household net-worth, cognitive functioning, chronic disease condition, ADL difficulties, IADL difficulties, drinking and smoking behaviors. List-wise strategy was used for missing values.

Discussion

The COVID-19 pandemic and associated socio-economic impacts engender positive and negative psychological responses for older adults, to whom social support from close ties is of growing importance. With cutoff points recommended by previous studies (Rodríguez-Rey and Alonso-Tapia, 2017; Zivin et al., 2010), we estimate a 16.44% prevalence of depression and 62.24% rate of PTG in this study, revealing noteworthy mental health changes for older adults in the COVID-19 era. Moreover, this study provides novel evidence unraveling the associations between pandemic-related difficulties and mental health outcomes, with an in-depth investigation of the moderation effects of social support.

Several findings of this study warrant further discussion. First, we find a larger number of healthcare delays and financial hardships were associated with elevated depressive symptoms and lower PTG, and experiencing social disruption stimulated psychological growth for older adults. Our findings support the conservation of resources stress theory with COVID-19 evidence (Hobfoll and Freedy, 1993), suggesting that an actual resource loss would lead to psychological stress and decreased psychological growth among older adults. In line with previous studies (Pietrzak et al., 2021; Wamser-Nanney et al., 2018), more significant losses associated with health-related and financial risks enlarge the extent to which the pandemic is perceived to be integral to individuals’ life, which is predictive of stronger depressive arousals. Meanwhile, existing studies estimated that about 13 million (38%) adults aged 50 and over in the United States were inexperienced with telemedicine (Lam et al., 2020), and about half of the disadvantaged elderly were living without emergency savings (Dushi et al., 2017). With such limited monetary and capital reservation, older adults are harder to accommodate their compelling health and financial demands and become more susceptible to internal ageism and poor self-acceptance, thereby more likely to suppress personal strength afterward (Wong and Jensen, 2020). On the contrary, if individuals have some alternative resources to compensate for the actual losses, such as an over 80% utilization of telecommunication technologies for social connectedness (Kakulla, 2021), stress responses from social disruption might be buffered to some extent (Hobfoll and Freedy, 1993). Also, adaptative coping behaviors with sufficient resource reservation would probably stimulate a sense of competence among older adults and enhance their positive psychological changes (Tedeschi and Calhoun, 2004). Given the findings above, it is critical to suggest that older adults are relatively resilient in social connectedness. Nevertheless, losses associated with healthcare delay and financial hardship might pose severer challenges to older adults’ mental health, which are worthy of more attention and timely interventions in possible future emergencies.

Second, individuals perceiving a higher level of social support were found to have better mental health, and to a lesser extent, those receiving more actual support were associated with elevated depressive symptoms and psychological growth. Consistent with previous research (Gariépy et al., 2016), this study reveals strong positive associations between perceived social support and psychological well-being among older adults. Comparatively, the spouse provides the most robust support in reducing depressive symptoms, and that from friends is of utmost importance for PTG promotion. Possibly, a sense of safeness from the spouse’s support is likely to counterbalance initial negative arousals, whereas a sense of social coherence from friends’ support is more predictive of psychological growth (Koelen et al., 2017). Besides, emotional and instrumental supports help older adults positively cope with pandemic-related difficulties and contribute to greater psychological growth (Dominick et al., 2022). However, contrary to our hypothesis, older adults receiving more support seemed to have a higher level of depressive symptoms. One possible explanation goes to the stress contagion phenomenon (Liu and Doan, 2020). There might be a crossover of negative affection such as fear, anxiety, and stress in the social exchange process, which forces individuals to perceive the pandemic as more fearful and exacerbates their depressive symptoms. Noteworthy, as the access to social support is often objectively hindered during the COVID-19 lockdowns (Saltzman et al., 2020), received support (the type of social support) is relatively less weighing than perceived support (the level of support) in predicting mental health outcomes. Thus, it is reasonable for this study to urge that improving the relationship between older adults and their social ties is critical for mental health promotion during the pandemic, and practitioners should pay attention to the stress contagion risk when offering support to older adults.

Third, it is a novelty for the current study to say that perceived social support moderates the relationship between healthcare delay and mental health, and that of immediate family members carries the weight of the moderating role. As previous research may overlook the differences across stress types (Dominick et al., 2022), the results of this study reveal that perceived social support is more likely to regulate stress responses from the COVID-related healthcare delay other than social and financial difficulties. As Weiner (2006) postulated, social support as a positive cognitive factor is critical for coping with traumatic losses that being attributed to internal deficiency, yielding far-reaching impacts, and inducing more personal responsibilities. In a pandemic context, older adults are more likely to attribute the social and financial difficulties to external factors as nearly all the society is afflicted with similar threats. In contrast, healthcare delay is more likely to be perceived as a result of older adults’ vulnerability to poorer health status and inexperience with telemedicine (D’cruz and Banerjee, 2020). Besides, adults of older age are more motivated to struggle with healthcare delay as they tend to ascribe its highly-risked consequences to themselves, but that of financial risks to the family or government (Rajkumar, 2020). Thus, compared with social disruption and financial hardship, rumination on healthcare delay is more likely to engender self-ageism, depreciation, and a sense of unfairness for older adults (Banerjee, 2020), to which social support is of growing importance. Additionally, inconsistent with previous studies (Gariépy et al., 2016; You et al., 2020), older adults with healthcare delays are more sensitive to support from immediate family members and friends. It’s possible that many of the mechanisms for individuals to navigate healthcare services became difficult during the pandemic, and older adults disproportionally rely on close social ties beyond the household to access new information and recommendations in this highly dynamic situation (Chen et al., 2021). Thus, we are prudent to conclude that social support is critical for older adults experiencing health-related difficulties during the pandemic, particularly those from immediate family members and friends.

Finally, this study reveals a reverse buffering effect of exclusive instrumental support on older adults’ mental health, despite two-tier support alleviating depressive symptoms following financial hardships. As noted by one previous study (D’cruz and Banerjee, 2020), instrumental exchanges during adversities might stimulate upward comparisons between older adults and their social ties. During this process, older adults would perceive themselves as less competent than the support providers and have a reduced self-efficacy to cope with pandemic-related difficulties, which enhances the relationships between stress and depressive symptoms and squeezes the space for psychological growth. Inversely, older adults receiving two-tier support are more likely to sustain positive internal schema and contribute to alleviated psychological distress (Lakey and Cassady, 1990). As the broaden-and-build theory suggests, instrumental support together with emotional comforts might spark individuals’ urge to explore within a socially safe environment and promote novel actions to build psychological resources (Fredrickson, 2004). However, the salutary effect of two-tier support on PTG is nonsignificant because older adults are harder to quickly construct a powerful self-image in such a pandemic-specific context with increasing uncertainties. Given the variance in moderation effects across support types, it is reasonable for this study to urge that two-tier support, that is, simultaneous instrumental and emotional assistance, is of greater importance for older adults’ mental health promotion during the pandemic.

Strengths and limitations

The findings of this study enlighten older adults and the public to navigate the stressful pandemic situation better. However, some limitations should be mentioned. A first limitation is that we cannot infer causality based on cross-sectional data, although it seems plausible enough in the temporal sequence that pandemic-related difficulties are first, social support as moderator, depressive symptoms and PTG being the outcomes. Second, there might be some confounding that was not controlled. For example, differences in political responses of states, territories, and counties possibly contribute to variance in pandemic-related difficulties and related stress responses. However, residence information is lacking in this data. Also, pre-pandemic mental health was not measured in this study, which might present anchoring effects on depressive symptoms and psychological growth during and after the pandemic. Third, nearly 90% of the respondents in this study had experienced one or more pandemic-related difficulties; hence the between-group comparisons in the descriptive analyses might be biased given the uneven sample distribution. Last, when discussing the moderation effect across different support types, we have no idea concerning the sources of the received support. It is of interest for further study to use multiple sources of information to investigate the role of source-specific received support in moderating mental health after trauma losses.

Conclusion

This study suggests that healthcare delay and financial hardship during the pandemic were associated with elevated depressive symptoms and decreased PTG due to resource losses. On the contrary, social disruption contributed to psychological growth as older adults reserved alternative resources for social connectedness. In addition, a higher level of perceived social support helped adults of older age to sustain well-being in the aftermath of healthcare delay, while that from immediate family members outside of the household weighed the moderating role. Also, we find the moderation effect varied between social support types, as exclusively receiving instrumental assistance engendered poorer mental health, whereas two-tier support buffered depressive symptoms associated with financial hardship. The findings of this study shed light on mental health promotion for older adults in a pandemic context.

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Footnotes

Data sharing statement

The current article is accompanied by the relevant raw data generated during and/or analysed during the study, including files detailing the analyses and either the complete database or other relevant raw data. These files are available in the Figshare repository and accessible as Supplemental Material via the SAGE Journals platform. Ethics approval, participant permissions, and all other relevant approvals were granted for this data sharing.

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: This study was supported by the National Social Science Fund of China (20VYJ030).

ORCID iD

Mingqi Fu

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