The Factors Associated With Anxiety Symptom Severity in Older Adults Living in Nursing Homes and Other Residential Aged Care Facilities

Abstract

Objective: This study aimed to identify the biopsychosocial factors associated with anxiety among a residential aged care sample. Method: A total of 178 residents (M age = 85.4 years, SD = 7.4 years) with mild cognitive impairment or normal cognition participated. Participants completed the Geriatric Anxiety Inventory (GAI) and a set of measures assessing cognition, depression, self-perceived health, mastery, attachment, perceived social support, social engagement, functional status, the experience of a fall, and other negative life events. Results: Unique correlates of GAI scores were depression, a preoccupied attachment style, lower mastery, cognitive impairment, and lower self-perceived health. Discussion: Most correlates that were uniquely associated with anxiety had little to do with the current environment. More variance was accounted for by stable and lifelong factors. This provides new insights into the characteristics of anxiety within aged care populations, and although preliminary, provides possible targets to prevent and treat anxiety within this setting.

Keywords

anxiety aged care correlates older adults nursing home

Introduction

Anxiety is one of the most common psychiatric issues in later life (Gonçalves, Pachana, & Byrne, 2011) and is particularly prevalent among older adults living in residential aged care facilities (RACFs; also known as nursing homes, hostels, assisted-living facilities, and long-term care/residential homes). Specifically, prevalence rates of anxiety symptoms within RACFs are reported to range from 6.5% to 58.4% (see Creighton, Davison, & Kissane, 2015, for a review), and with our population rapidly aging and people living longer than ever before (United Nations Population Fund, 2012), this issue is likely to increase considerably over the coming years.

Despite this, research on the risk factors and correlates of anxiety within RACF residents is only starting to emerge, with current knowledge primarily derived from community- and population-based elderly samples. Our limited understanding of the factors associated with late-life anxiety among RACF residents was highlighted in a review by Creighton, Davison, and Kissane (2016), where many studies were found to be secondary analyses of data. Nonetheless, the review indicated that factors such as female sex, younger age, higher educational level, lower functional ability, number of medical conditions, self-perceived health, level of cognitive impairment, depression, lower perceived social support, and the experience of negative life events have all been found to be associated with anxiety disorders or symptoms in RACF residents (Creighton et al., 2016). Although these findings are similar to the results of studies conducted with community-based elderly samples (e.g., Byers, Yaffe, Covinsky, Friedman, & Bruce, 2010; Gonçalves et al., 2011; Zhang et al., 2015), it is important to note that the majority of factors have only been assessed in one or two aged care studies, often with inconsistent results. Thus, many of the associations between anxiety and a number of factors within RACFs remain unclear. However, given that many of the abovementioned variables are ubiquitous among RACF residents, it is possible that the presence of these factors contributes to the higher prevalence rate of anxiety within this setting. Furthermore, research is needed to determine if this is the case, with a simultaneous comparison of multiple factors also enabling us to determine which factors are most important in understanding anxiety among older adults in RACFs.

Compared with demographic and health-related variables, only a limited number of psychosocial factors associated with anxiety have previously been investigated within RACF samples. For instance, to date very little or no research has examined the association between anxiety and global attachment style, residents’ sense of mastery (i.e., personal control and sense of competence in mastering one’s day-to-day activities and environment), level of social engagement (i.e., having connections with others and being involved in group activities), or experience of a fall. Previous late-life research examining these variables have found significant associations between depression and lower levels of mastery (Davison, McCabe, Knight, & Mellor, 2012) and social engagement (Kang, 2012; Resnick, Fries, & Verbrugge, 1997) among RACF residents, whereas community-based studies have found an association between anxiety and the experience of a fall (Holloway et al., 2016; Menant et al., 2013) and an anxious attachment style (Kafetsios & Sideridis, 2006). Given that attachment behavior continues throughout the life span and impacts on well-being (Bowlby, 1980), and RACF residents are at particular risk of low social engagement, low perceived mastery, and increased risk of falls, research examining these factors and their association with anxiety is warranted. Addressing this gap in knowledge is important, given that a number of these psychosocial variables are potentially modifiable and could, therefore, be used in prevention and intervention strategies aimed at reducing anxiety within this frail and growing population.

Thus, to further our current limited understanding of the factors associated with anxiety in RACFs, this study aimed to determine the correlates of anxiety symptoms among a sample of RACF residents using the biopsychosocial model as a framework. Specifically, demographic variables (age, sex, educational level, and marital status), biological/health-related variables (cognitive impairment, functional ability, number of physical health conditions, and self-perceived health), and psychosocial variables (perceived social support, social engagement, attachment style, mastery, depression, experience of negative life events, and experience of a recent fall) were all examined within this study. Given the conceptual overlap between anxiety and depression (Beekman et al., 2000; Schoevers, Beekman, Deeg, Jonker, & van Tilburg, 2003) and the finding that depression is also a consequence of living with anxiety (Wetherell, Gatz, & Pedersen, 2001), a hierarchical regression analysis was conducted with depression entered at the first step. This then enabled the assessment of whether other biopsychosocial variables accounted for additional variance in self-rated anxiety.

Method

Study Design

This study utilized a cross-sectional, observational design. Ethics approval was granted by the Monash University Human Research Ethics Committee (project number: CF14/3346–2014001779).

Participants

Between March 2015 and November 2016, residents were recruited from 12 randomly selected RACFs across southern and eastern metropolitan Melbourne. To be eligible to participate, residents had to (a) be ≥ 65 years of age, (b) have resided at the RACF for a minimum of 3 months, and (c) scored ≥ 18 on the Mini-Mental State Examination (MMSE). Residents were excluded if they (a) had a diagnosis of schizophrenia or bipolar affective disorder, or (b) were unable to complete clinical assessments because of illness, medication, sensory or speech impairment, intellectual disability, or lack of language fluency. Figure 1 outlines participant recruitment with reasons for exclusion from the study and statistical analyses indicated.

Figure 1.

Participant recruitment flowchart.

Measures

Anxiety

Anxiety symptoms were assessed using the Geriatric Anxiety Inventory (GAI; Pachana et al., 2007), a 20-item self-report measure of general anxiety symptoms in older adults over the past week. Using a dichotomous agree/disagree format to ensure ease of understanding, each item utilizes language commonly employed by older adults to describe anxiety and worry (e.g., “butterflies in my stomach”). Total scores range from 0 to 20, with higher scores indicating greater anxiety levels. Research examining the psychometric appropriateness of the GAI in RACF samples have reported excellent reliability and validity within this context (Boddice, Pachana, & Byrne, 2008; Gerolimatos, Gregg, & Edelstein, 2013). For the current sample, the GAI’s Cronbach’s alpha was found to be .94.

Demographic characteristics

Each participant’s age, sex, marital status, and educational level (i.e., years of formal education) was derived from their file held at the facility. To ensure the accuracy of information, educational level and marital status was verbally confirmed with each participant during the interview.

Biological/health-related characteristics

Four health-related variables were assessed in the current study:

Cognitive impairment

Level of cognitive impairment was assessed using the MMSE (Folstein, Folstein, & McHugh, 1975), a commonly used, brief cognitive screening instrument comprising 11 items assessing orientation, memory recall, attention, language, comprehension, and visuospatial skills. Scores range from 0 to 30, with commonly accepted cutoff points being the following: 24 to 30 for normal cognition, 18 to 23 for mild cognitive impairment (MCI), and 0 to 17 for moderate to severe cognitive impairment (Tombaugh & McIntyre, 1992).

Presence and number of physical health conditions

To assess the number and type of chronic illnesses recorded in participants’ files, the Functional Comorbidity Index (FCI; Groll, To, Bombardier, & Wright, 2005) was used. The FCI provides a sum of 18 predefined comorbid conditions (e.g., arthritis, stroke), with scores ranging from 0 to 18 (higher scores indicate greater comorbidity). In the present study, the FCI was used as a checklist, with the researcher (A.C.) examining participants’ files and recording which conditions were present. The three items measuring anxiety, depression, and body mass index were excluded in this study, as anxiety was the outcome variable, depression was assessed using a diagnostic interview, and the ability to ascertain an accurate measurement of participants’ current weight and height to calculate body mass index was considered unfeasible. Thus, a total of 15 comorbid conditions were assessed (with a possible maximum score of 15).

Activities of daily living (ADLs)

The Katz Index of ADLs (Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963) was used to assess functional ability and participants’ capacity to perform basic ADLs (e.g., bathing, dressing) independently. This measure was administered to an RACF staff member who was involved in the participant’s care activities, and involved rating the participant as either fully independent or dependent across six skills. Total scores can range from 0 to 6, with a maximum score of 6 points indicating full independence, 4 points moderate impairment, and 2 points severe impairment. Overall, the psychometric properties of this index have been found to be good, with evidence of high levels of reliability and validity in elderly populations (Arik et al., 2015; Brorsson & Asberg, 1984). In the current study, this measure had a Cronbach’s alpha of .80.

Self-perceived health

Participants’ subjective perception of their physical health was assessed via one item (“How would you rate your overall health at the present time?”). Participants rated their current health using a 4-point Likert-type scale from 1 (poor) to 4 (excellent), with a higher rating indicating greater self-perceived health.

Psychosocial characteristics

A total of seven psychosocial variables were assessed within this study.

Social engagement

Participants’ individual level of social engagement was assessed via the Revised Index for Social Engagement (RISE; Gerritsen et al., 2008). This observational scale consists of six dichotomous yes/no items and was specifically developed to measure positive features of RACF residents’ social behavior (e.g., “Does the resident accept invitations to most group activities?”). Scores range from 0 to 6, with higher scores representing greater social engagement. The RISE was completed with a staff member who was familiar with the resident and had worked closely with them for at least the previous 2 weeks. The RISE has been widely used to assess social engagement in RACFs among residents with cognitive impairment (e.g., de Boer, Hamer, Zwakhalen, Tan, & Verbeek, 2017; van Kooten et al., 2015). Cronbach’s alpha for the scale within the present sample was found to be .80.

Perceived social support

Perceived social support was assessed using the Multidimensional Scale of Perceived Social Support (MSPSS; Zimet, Dahlem, Zimet, & Farley, 1988). This self-report measure comprises 12 questions that assess perceptions of support from three sources: family (e.g., “I can talk about my problems with my family”), friends (e.g., “I can count on my friends when things go wrong”), and a significant other (“I have a special person who is a real source of comfort to me”). Each item is answered using a 7-point Likert-type scale from 1 (very strong disagree) to 7 (very strongly agree). Total scores can range from 7 to 84, with higher scores indicating greater perceived social support. Good levels of reliability and validity for the MSPSS within older adult populations have been found (Stanley, Beck, & Zebb, 1998). In the present study, Cronbach’s alpha for the total score of the MSPSS was .83.

Attachment style

Global attachment style was measured using the Experience in Close Relationships–Relationship Structures (ECR-RS) Adult Attachment Questionnaire (Fraley, Waller, & Brennan, 2000). This nine-item self-report measure was designed to assess two underlying global attachment patterns: avoidance (six items that assess discomfort with emotional closeness to and dependency on partners) and anxiety (three items that measure excessive worry and concern that a partner will not be available when support is needed). Each item is rated on a 7-point Likert-type scale from 1 (strongly disagree) to 7 (strongly agree), with two separate total scores for the avoidance and anxiety dimensions provided. Each subscale score ranges from 1 to 7, with low scores on both these dimensions reflecting attachment security, whereas higher scores represent higher attachment avoidance and anxiety, respectively. In the current study, participants were instructed to rate each item with respect to how they feel about “close relationships in general” to identify their general attachment style. Cronbach’s alpha for the avoidant and anxiety attachment dimensions in the current sample were .58 and .75, respectively.

Mastery

The coping resource of perceived level of mastery (i.e., the extent to which an individual perceives they have control of events and ongoing situations) was assessed using Pearlin and Schooler’s (1978) seven-item self-report scale. Each item is rated using a 4-point Likert-type scale from 1 (strongly disagree) to 4 (strongly agree). Total scores can range from 7 to 28, with higher scores indicating greater levels of mastery. In the current study Cronbach’s alpha for the scale was .61.

Depression

The presence of a Major Depressive Disorder (MDD) was assessed using the MINI-International Neuropsychiatric Interview version 7.0.0 (MINI; Sheehan et al., 1998). The MINI is a structured clinical interview that generates diagnoses according to Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA], 2013) criteria, and although it wasn’t specifically developed for older adults, it has been frequently used with both community (e.g., Byrne et al., 2010; Cheung, Patrick, Sullivan, Cooray, & Chang, 2012) and RACF (e.g., Arvaniti et al., 2005; Dozeman et al., 2012; Pachana et al., 2007) samples.

The recent experience of negative life events

Based on the findings of previous literature (e.g., Beekman et al., 1998; Beekman et al., 2000; De Beurs et al., 2001), an eight-item dichotomous (yes/no) scale was used to assess whether each participant had experienced any of the following life events within the past 12 months: the death of a partner or family member, partner or family member becoming ill, or conflict with partner, family member, other RACF residents, or nursing staff. Total scores ranged from 0 to 8, with higher scores indicating that the participant experienced more of the assessed life events within the past year.

The eight events mentioned above were selected as they were likely to have occurred recently, and have previously been found to be associated with the onset of depression and anxiety in later life (De Beurs et al., 2001). Other stressful life events found to be associated with a reduction in well-being (e.g., change in financial state, being fired from work, losing driver’s license) were excluded as they were not considered relevant for RACF residents.

The recent experience of a fall

Participants’ experience of a fall within the last 6 months was determined using a single dichotomous (yes/no) item (“Have you had a fall in the last 6 months?”).

Procedure

Using a random number generator, 19 RACFs were randomly selected from a list of all facilities within southern and eastern metropolitan Melbourne, Australia, and invited to participate via phone call and e-mail. Twelve facilities agreed to participate, including private companies, not-for-profit and religious organizations, and government-funded facilities. Screening and identification of potential participants was completed with the assistance of the manager and/or director of nursing of each participating facility. Eligible residents were then approached by the first author (A.C.) and completed a process developed by Warner, McCarney, Griffin, Hill, and Fisher (2008) to determine their capacity to provide informed consent. If deemed able to provide informed consent, they were invited to participate in the study and sign the consent form. For those considered unable to provide consent themselves, the “person responsible” was approached to provide written informed consent. The MMSE was then administered, with residents scoring <18 excluded from the study as well as residents who met other exclusion criteria. All eligible participants were then administered all measures listed above in an interview format to ensure good understanding and comprehension of each item. Each participant’s file held at the facility was also screened to obtain demographic and health-related information. Finally, a staff member familiar with the participant was then approached and completed the RISE and Katz Index of Independence in ADLs in an interview format with the researcher.

Statistical Analyses

Data were collated and analyzed using version 22 of the Statistical Package for the Social Sciences (SPSS). Descriptive statistics (proportions or means and standard deviations) were used to describe the demographic and clinical characteristics of the sample. Due to the exploratory nature of this study, the correlates of anxiety were investigated in two phases. In the first phase, bivariate correlations were conducted to determine which continuous variables were associated with scores on the GAI, with nonparametric Spearman correlations being used due to positive skewness on the GAI. The relationship between anxiety score and categorical variables were examined using Mann–Whitney U or Kruskal–Wallis tests. In phase two, all variables which showed significance at an alpha of .05 were entered into a hierarchical multiple regression to determine which factors were most closely associated with anxiety. The presence of an MDD diagnosis was entered as a first step, with all other variables were then entered in a subsequent step to determine if they accounted for any additional variance in anxiety scores.

Results

Sample Characteristics

A total of 180 residents completed the study; however, two cases were excluded from analysis. One case was a multivariate outlier, with Mahalanobis distance exceeding χ²(12) = 32.909, p < .001, and one case had a standardized residual in excess of ±3.30; indicating undue influence on the model (Tabachnick & Fidell, 2007). The study, therefore, comprised 178 participants from 12 RACFs, 60 males and 118 females (M age = 85.4 years). Table 1 provides an overview of the demographic and clinical characteristics of the final sample.

Table 1.

Demographic and Clinical Characteristics of the Sample (N = 178).

Characteristic	n	%	M	SD	Range
Age (years)			85.4	7.4	66-101
Sex
Male	60	33.7
Female	118	66.3
Years of education			10.7	3.3	1-22
Marital status
Widowed	94	52.8
Divorced/separated	36	20.2
Married	34	19.1
Never married/single	12	6.7
Other	2	1.1
Length of stay at RACF (years)			2.6	2.5	0.2-12.6
Social engagement (RISE score)			4.0	1.9	0-6
Cognitive functioning (MMSE score)			24.7	3.6	18-30
Mild impairment (18-23)	64	36.0
No impairment (24-30)	114	64.0
Number of physical illnesses (FCI score)			3.6	1.7	0-10
Functional impairment (Katz Index of ADLs score)			3.5	1.9	0-6
Self-perceived health (“How would you rate your overall health at the present time?”)
Excellent	13	7.3
Good	84	47.2
Fair	55	30.9
Poor	26	14.6
Global attachment (ECR-RS score)
Anxious attachment			2.9	1.3	1-7
Avoidant attachment			4.0	1.1	1-7
Perceived social support (MSPSS score)			62.0	11.7	25-84
Mastery			17.5	3.9	8-28
Number of negative life events experienced in past 12 months			1.1	1.1	0-4
Family member became ill^a	47	26.4
Death of a family member^a	38	21.3
Conflict with RACF staff^a	34	19.1
Conflict with a family member^a	24	13.5
Conflict with other residents^a	22	12.4
Partner became ill^a	16	9.0
Death of partner^a	10	5.6
Conflict with partner^a	4	2.2
Experienced a fall in last 6 months
Yes	49	27.5
No	129	72.5
MDD diagnosis
Yes	15	8.4
No	163	91.6
Anxiety (GAI score)			4.4	5.7	0-20

Note. RACF = Residential Aged Care Facility; RISE = Revised Index for Social Engagement; MMSE = Mini-Mental State Examination; FCI = Functional Comorbidity Index; ADL = activities of daily living; ECR-RS = Experience in Close Relationships–Relationship Structures; MSPSS = Multidimensional Scale of Perceived Social Support; MDD = Major Depressive Disorder; GAI = Geriatric Anxiety Inventory.

Count and percentages provided are of those participants who had experienced the life event in the last 12 months.

Association of Self-Rated Anxiety With Biopsychosocial Variables

The association between anxiety symptoms, as measured by the GAI (Pachana et al., 2007), and all variables across the six stages of the model were examined, with the correlations presented in Table 2. Cognitive impairment, mastery, self-perceived health, social engagement, negative life events, perceived social support, and an anxious attachment style were all found to be significantly correlated with GAI scores. Out of the categorical variables, the presence of an MDD diagnosis, z = −5.005, p < .001, and the experience of a fall, z = −3.838, p < .001, were both found to be significantly associated with higher GAI scores. No significant association was found between GAI score and sex, z = –.123, p = .902, or marital status, χ²(4) = 7.947, p = .094.

Table 2.

Spearman Correlations of Self-Rated Anxiety and Continuous Health-Related and Psychosocial Variables.

Variables	Self-rated anxiety (rs)
Demographics
Years of education	−.13
Age (years)	−.04
Health-related variables
Self-perceived health	−.32**
Cognitive impairment	−.16*
Number of physical illnesses	−.02
Functioning in basic ADLs	.07
Psychosocial variables
Anxious attachment	.42**
Mastery	−.39**
Social engagement	−.18*
Perceived social support	−.18*
Experience of negative life events in the last 12 months	.18*
Avoidant attachment	−.07

Note. ADL = activities of daily living.

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

To determine which factors had the strongest association with anxiety, those variables which were significantly associated with self-rated anxiety were entered into a hierarchical multiple regression. The presence/absence of an MDD diagnosis was entered at the first step, with social engagement, attachment, mastery, self-perceived health, perceived social support, cognitive impairment, the experience of negative life events within the past 12 months, and the experience of a fall within the past 6 months entered in a subsequent step. Although avoidant attachment was not significantly associated with GAI scores in the bivariate correlations, it was included in the regression as this allowed the two-dimensional model of attachment to be accurately represented, and enabled the results to be conceptually interpreted in accordance with Bartholomew and Horowitz’s (1991) commonly used four attachment styles (secure, dismissive, fearful, and anxious/preoccupied; Fraley, 2012).

The presence of an MDD diagnosis was significantly associated self-rated anxiety score, F(1, 176) = 62.786, p < .001, explaining 26.30% of the variance in GAI scores (R² = .259). Entry of the remaining variables significantly increased the association with anxiety scores, ∆F(11, 165) = 6.226, p < .001, with the final model explaining 47.90% of the variance in GAI scores (R² = .479). The significant unique correlates in the final model were MDD diagnosis, attachment style, level of mastery, self-perceived health, and cognitive impairment (see Table 3). Life events, the experience of a fall, perceived social support, and social engagement did not contribute unique variance in anxiety scores.

Table 3.

Hierarchical Multiple Regression Analysis for Variables Predicting GAI Score (N = 178).

Variables	Self-rated anxiety (GAI score)
	Model 1			Model 2
	B	β	sr ²	B	β	sr ²
Health-related variables
Cognitive impairment				−0.31	−.20**	.033
Self-perceived health
Excellent versus poor				−3.55	−.16*	.016
Good versus poor				−1.50	−.13
Fair versus poor				−0.87	−.07
Psychosocial variables
Anxious attachment				1.19	.27***	.053
Avoidant attachment				−0.69	−.13*	.013
Mastery				−0.24	−.16*	.019
Social engagement				0.12	.04
Perceived social support				−0.04	−.08
Experience of negative life events in last 12 months				0.33	.06
Experience of a fall in the last 6 months				1.09	.09
MDD diagnosis	10.49	.51***	.26	6.29	.31***	.073
R ²	.263			.479
Adjusted R²	.259			.441
F	62.79***			12.65***
ΔR²				.216
ΔF				6.23***

Note. Ratings of self-perceived health were represented as three dummy variables, with poor self-perceived health serving as the reference group. GAI = Geriatric Anxiety Inventory; MDD = major depressive disorder.

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

Discussion

The current study aimed to examine the relationship between self-rated anxiety and a range of demographic, health-related, and psychosocial variables. Using the biopsychosocial model as a framework, the overall model accounted for 47.9% of the total variance in anxiety scores, with the introduction of the psychosocial variables explaining an additional 21.60% after the effects of MDD were controlled for. Specifically, attachment style, lower levels of mastery, higher levels of cognitive impairment, and the perception that physical health was poor rather than excellent all made significant contributions to the model and were all strongly associated with higher levels of self-reported anxiety within the RACF sample.

Consistent with previous aged care research (e.g., Cheok, Snowdon, Miller, & Vaughan, 1996; Haugan, Innstrand, & Moksnes, 2013; Neville & Teri, 2011; Smalbrugge, Pot, Jongenelis, Beekman, & Eefsting, 2005), MDD was found to have a strong and significant association with anxiety symptoms. Within the current sample, when all other variables were held constant, the predicted GAI score was 6.29 times greater for participants with an MDD diagnosis than for those without MDD. This came as no surprise, given the conceptual overlap between the conditions and the fact that anxiety has been found to be a significant precursor and perpetuating factor to depression (Wetherell et al., 2001). As suggested by Schoevers et al. (2003), the strong association found in this study might indicate that both disorders should be considered as different representations of the same disorder, rather than distinct diagnostic entities as defined by the DSM-5 (APA, 2013).

After controlling for the influence of MDD, both attachment dimensions were found to be significantly associated with anxiety. Specifically, the more anxious and less avoidant residents were, with respect to their attachment style, the higher their levels of self-rated anxiety. This pattern of anxiety and avoidance indicates that high levels of anxiety were associated with a preoccupied attachment style, which is consistent with studies examining the association between anxiety and attachment in adult populations (e.g., Eng, Heimberg, Hart, Scheier, & Liebowitz, 2001; Fonagy et al., 1996). As an individual with a preoccupied attachment style is characterized by an excessive dependence and high need for approval from others, anxiety about rejection and abandonment, and a negative view of the self (Bartholomew & Horowitz, 1991), it is likely that this attachment style affects their self-belief in their ability to cope and adjust. Anxiety and feelings of insecurity are likely to be heightened for these individuals within an RACF environment; where there are significant barriers to forming meaningful relationships (Casey, Low, Jeon, & Brodaty, 2016), such as frequent shift changes, high rates of staff and resident turnover (Castle, 2006; Castle & Engberg, 2005), and an overemphasis on staff providing clinical services and completing documentation rather than nurturing social interactions (Walker & Paliadelis, 2016).

Although social factors are given much attention in models of well-being (e.g., Young, Frick, & Phelan, 2009), the current findings indicated that perceived social support, social engagement, and the experience of negative, socially oriented life events (e.g., death, illness, or conflict with their partner or family member) were not associated with anxiety when included in the multivariate model. Instead, the results suggest that long-standing factors (such as attachment style) are more strongly associated with anxiety. This suggests that rather than the social environment being the key contributing factor to the experience of anxiety in RACF settings, it appears some residents are predisposed to cope better or worse with the social changes associated with this stage of life (e.g., forming new relationships within the facility, and the experience of loved ones becoming sick or dying). Given that most previous research into anxiety in RACFs have examined only age-related (e.g., cognitive impairment) or current social/environmental factors (e.g., loneliness, social support) associated with anxiety (Drageset, Eide, & Ranhoff, 2013; Smalbrugge et al., 2005), further research investigating possible predisposing factors (such as attachment style) is needed.

A low level of mastery was found to have a significant independent association with anxiety, with residents who perceived they lacked control over their lives experiencing higher levels of anxiety. This is consistent with the findings reported by the only other RACF study to examine the association between mastery and anxiety (Keister, 2006), and is in line with previous research examining the relationship between environmental mastery and depression within this context (Davison et al., 2012; Knight, Davison, McCabe, & Mellor, 2011). The impact of an overall perceived lack of control on psychological well-being appears to be significant within RACFs, and is likely heightened by the strict regimented routines and limited opportunity to ascribe control and choice over everyday issues (Hillcoat-Nallétamby, 2014; Kane et al., 1997).

With regard to health-related variables, both cognitive impairment and a lower level of self-perceived health were found to be independently associated with self-rated anxiety. Despite excluding residents with moderate to severe cognitive impairment, lower cognitive functioning was found to be independently associated with higher anxiety within the RACF sample, which is consistent with Parmelee, Katz, and Lawton (1993) and Zuidema, Derksen, Verhey, and Koopmans (2007). Although causal inferences cannot be made due to the cross-sectional nature of the study, it may be that residents with MCI still retain a level of insight and awareness of their decreasing cognitive function. However, increased anxiety may lead to or exacerbate poor cognitive performance. Although an association between anxiety and cognition has been consistently found in community-dwelling samples (Beaudreau & O’hara, 2008), some RACF studies have found either a positive relationship (Smalbrugge et al., 2005) or no significant association (Cheok et al., 1996; Neville & Teri, 2011) between cognitive function and anxiety. Given that more than half of RACF residents have some level of cognitive dysfunction (Björk et al., 2016), prospective longitudinal research is needed to clarify the association between these two variables and help determine whether cognition is a potential risk factor for the development of anxiety.

Although objective physical health (i.e., number of physical illnesses) had no association with anxiety, residents’ perception that their health was poor (compared with excellent) was found to be significantly associated with higher levels of anxiety. Previous research in RACFs have found subjective health to be significantly poorer in residents with higher death anxiety (Moreno, de la Fuente Solana, Rico, & Fernandez, 2009; Mullins & Lopez, 1982) and depression (Cummings, 2002), whereas worse self-rated health has been found to be significantly correlated with anxiety symptoms and disorders within community-dwelling elderly samples (Beekman et al., 1998; De Beurs, Beekman, Deeg, Van Dyck, & Van Tilburg, 2000; De Beurs et al., 2001; De Beurs et al., 1999). The reasons for this association may be bidirectional, with poorer subjective health potentially leading to an increase in anxiety, and the presence of anxiety possibly leading to poorer perceptions of health.

Anxiety was not found to be associated with any demographic variables, functional ability, or the experience of a fall. Although the finding that no significant relationship exists between demographic characteristics and anxiety is consistent with most previous RACF research (e.g., Baldacchino & Bonello, 2013; Drageset et al., 2013; Neville & Teri, 2011), for some variables the lack of a statistical finding may be due to lack of contrast. For example, functional impairment is a common reason for admission into RACFs (Gaugler, Duval, Anderson, & Kane, 2007), meaning that it may be somewhat “normalized” within the aged care environment and, therefore, be less anxiety-inducing. However, the lack of a significant association between anxiety and more recent and age-related variables (e.g., reduced functional ability as well as age itself) suggests that the experience of anxiety in RACFs may not be an acute response to factors specifically associated with older age or the nursing home setting, but instead is a chronic lifelong condition that residents have had to cope with throughout their lives. This has been found to be the case for depression, with McSweeney and O’Connor (2008) finding that most RACF residents were depressed on entry. To date, no research has examined the trajectory of anxiety within this context; thus, future studies examining the course of anxiety in newly admitted RACF residents using a prospective, longitudinal design are needed.

Clinical Implications of Findings

Based on the findings of this article, the following clinical implications are noted. First, a key implication of the study is the finding that the variables with the highest association with anxiety symptoms were generally not modifiable (e.g., attachment style, cognitive impairment). Although these factors may not be specific targets for intervention, staff should remain aware of them to ensure the best possible care is provided to residents and those individuals at risk of experiencing anxiety are detected as early as possible. Second, the confirmation of the association between anxiety and depression within aged care residents is important, as the presence of depressive symptoms—which are typically more frequently assessed for within this context—could potentially be used by staff to alert them that a resident is at higher risk of also experiencing anxiety. Third, although further research within an aged care setting is needed to confirm findings, the association between the presence of anxiety symptoms and a preoccupied attachment style aids in furthering our understanding of the characteristics of anxiety in aged care residents, and may also help with the development of more effective and personalized day-to-day care. For instance, the identification that a preoccupied attachment style may help staff identify residents who are at risk of anxiety and suggests that fostering a sense of acceptance of the residents and encouraging the formation of social relationships in their new environment may help reduce anxiety symptoms. Fourth, increasing perceived mastery by providing residents with an opportunity to be involved in decisions and accomplish small but achievable challenges (e.g., physical exercise; Olsen, Telenius, Engedal, & Bergland, 2015) may help increase a sense of control and empowerment and reduce anxiety within the aged care context. Last, although further research is needed, the finding that lower self-perceived health was associated with higher levels of anxiety symptoms suggests that routine assessment of self-perceived health in RACF settings may be useful in identifying residents at risk of poor mental health. In addition, interventions aimed at increasing residents’ self-perceived health may help reduce anxiety and improve emotional well-being, particularly given that objective health status was not found to be a significant correlate.

Study Limitations

There are a number of limitations of this study that warrant noting. First, although the exclusion of individuals with moderate and severe cognitive impairment was done to ensure included residents had the capacity to reliably understand and complete the measures, their omission from the sample limits the generalizability of the findings to the broader aged care population. Second, although the use of only one item to assess self-perceived health is common in geriatric research (e.g., Chou, Mackenzie, Liang, & Sareen, 2011; De Beurs et al., 2001), this may be seen as a limitation due to the lack of detail provided. Third, it is important to note that the low Cronbach’s alphas for the measures assessing mastery and avoidant attachment may have impacted on the current findings and contributed to the lack of a significant association between mastery and anxiety in the regression analyses. Future research using these tools in a RACF sample should, therefore, attempt to ascertain their reliability through the completion of other reliability analyses (e.g., confirmatory factor analysis). Last, the study utilized a cross-sectional design, meaning that causal inferences cannot be made between anxiety and the factors assessed. Prospective longitudinal studies that utilize a large sample size and include residents with more severe levels of cognitive impairment would enable a more comprehensive understanding of the relationships between anxiety and biopsychosocial factors in RACF residents. Similarly, as our knowledge of the correlates of anxiety improves, it would also be helpful for future research to consider issues such as potential mediating factors. The current study ensured that a diagnosis of depression was entered as a first step in the hierarchical regression, and it would beneficial for future research to expand on this by taking other potential mediating factors into consideration.

Conclusion

In sum, findings from the current study highlight the importance that attachment style, mastery, self-perceived health, cognitive impairment, and depression have on the experience of anxiety among older RACF residents. Based on the results, the presence of depression and/or a decline in cognitive functioning could be used by staff to identify residents at risk of experiencing anxiety, whereas interventions or programs aimed at enhancing mastery, self-perceived health, and increasing opportunities to build meaningful relationships may help reduce the high anxiety rates within this growing frail and vulnerable population.

Footnotes

Authors’ Note

With the assistance of T.D. and D.K., A.C. designed the study and wrote the protocol, undertook the statistical analysis and interpretation, and wrote the first draft of the manuscript. T.D. and D.K. read and provided comments and suggestions for all further drafts. All authors have contributed to and approved the final manuscript.

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: A.C. would like to acknowledge the financial support received through an Australian Government Research Training Program Scholarship. This funding had no involvement in the design, collection, analysis, or interpretation of data; writing of the report; or decision to submit the article for publication.

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