Abstract
Elder mistreatment is expected to rise with the aging of the American population. To date, the association between specific forms of mistreatment and decreased quality of life is poorly understood. The aim of the present study was to explore the association between verbal mistreatment among elderly individuals and depression and quality of life. A sample of 142 older adults (40% male) aged 65 or over was enrolled from a large medical practice and academic dental practice, mean (SD) = 74.88 (6.98) years. Thirty-eight percent of the sample reported verbal mistreatment. Controlling for socio-demographic characteristics and depression, verbal mistreatment was a significant predictor of social functioning (β = −.28, p<.001), mental health (β = −.25, p<.001), and role limitations OR = 3.02, 95% CI [1.34 – 6.77]. The present findings highlight the prevalence of verbal mistreatment in elderly individuals.
Keywords: elderly, verbal mistreatment, depression, quality of life
Introduction
Elder mistreatment is expected to exponentially rise in incidence and prevalence with the aging of America (Collins & Presnell, 2007). At the turn of the 19th century, the average life expectancy was about 40 years of age, and today, that expectancy has nearly doubled. With this incredible increase in longevity comes the societal responsibility of caring for older adults who may need help with their activities of daily living as they advance in age. Inadequate care may be associated with abuse, neglect, exploitation and abandonment, which have, in turn, been associated with increased morbidity and mortality in older persons in need of care (Lachs, Williams, O’Brien, Hurst, & Horwitz, 1997). Morbidity takes many forms, including both physical and mental states, which can create excess disability, increased care needs and suffering in older adults. The purpose of this paper is to examine the association of verbal mistreatment with decreased quality of life in older adults presenting at primary care clinics.
Elder mistreatment has been defined as “(a) intentional actions that cause harm or create a serious risk of harm (whether or not harm is intended) to a vulnerable elder by a caregiver or other person who stands in a trust relationship to the elder or (b) failure by a caregiver to satisfy the elder’s basic needs or to protect the elder from harm” (Bonnie & Wallace, 2003). In 2008, the first National Prevalence Study found that 9% of older adults reported verbal mistreatment, 3.5% financial mistreatment, and 0.2% physical mistreatment by a family member (Laumann, Leitsch, & Waite, 2008). The striking prevalence of verbal mistreatment, nearly 3 times greater than the next most frequent category (financial mistreatment) is illustrative of the prevalence of verbal mistreatment among the elderly.
Verbal mistreatment is, however, an overlooked form of elder mistreatment (Acierno et al., 2010; Comijs, Jonker, van Tilburg, & Smit, 1999; Vandeweerd, Paveza, & Fulmer, 2006). Many investigators have been reticent to label verbal abuse and mistreatment because of the subjective nature of the phenomenon and the difficulty of determining whether there has been a lifetime pattern of verbal abuse or new onset verbal abuse in older age. Cultural differences have also been cited as reasons for variance in labeling verbal mistreatment (Laumann et al., 2008), but mandatory reporting laws for elder mistreatment in this country consistently include verbal abuse indicators and research on this component of elder mistreatment is extremely important.
Acierno et al (2010) reported on a representative sample using random digit dialing across geographic strata, analyzing 5,777 respondents. They reported a prevalence of 4.6% for emotional abuse, 1.6% for physical abuse, 0.6% for sexual abuse, 5.1% for potential neglect, and 5.2% for financial abuse (Acierno et al., 2010). Approximately, 1 in 10 respondents reported some mistreatment in the past year (Acierno et al., 2010). In this study emotional mistreatment included verbal abuse, humiliation, harassment/coercing, or being ignored, and the lifetime prevalence of verbal abuse, thus included as a form of verbal mistreatment, accounted for 528 of the 1,250 cases (42%). The categories of mistreatment assessed were not exclusive, meaning that participants might report both verbal abuse and humiliation, harassment/coercion or being ignored, however emotional mistreatment was by far the most prevalent form reported (Acierno et al., 2010). The 2009 national prevalence survey in the United Kingdom described lower rates of frequent verbal mistreatment with 0.4% of respondents reporting psychological abuse (Biggs, Manthorpe, Tinker, Doyle, & Erens, 2009) which included verbal mistreatment, assessed using an item of the conflict tactics scale (CTS) (Straus & Brown, 1978). Verbal mistreatment was considered to be present if someone had “insulted you, called you names, or swore at you; threatened you; undermined or belittled what you do; excluded you or repeatedly ignored you; threatened to harm others that you care about; prevented you from seeing others that you care about” at a frequency of at least “10 or more instances in the past year.” The high frequency cutoff employed in this study likely accounted for the lower prevalence of psychological abuse found among their sample. Systematic reviews have suggested that these discrepancies in the literature may stem from methodological disparities. A systematic review of the prevalence of elder abuse and neglect using multiple databases and independent raters identified 49 studies meeting the inclusion criteria, of which only 7 used measures for which reliability and validity had been assessed and established (Cooper, Selwood, & Livingston, 2008). These findings highlighted the variability of approaches for operationalizing verbal abuse and further, the lack of consensus regarding the existence of verbal abuse as a specific category of mistreatment (Cooper et al., 2008). Daly and colleagues (2011) conducted a second systematic review, resulting in a sample of 590 studies. Their work further underscored the discord regarding the operationalization of verbal mistreatment as well as paucity of intervention studies (Daly et al., 2011).
A third systematic review, focusing on the psychological correlates of elder abuse, identified 25 studies examining the psychological consequences of elder abuse, and concluded that the effects of elder abuse may be more severe and longer-lasting than those of physical abuse (Dong, Chen, Chang, & Simon, 2012). Interestingly, the authors also documented 16 studies exploring psychological distress as a risk factor for elder abuse, suggesting that the relationship between these two factors may be complex. Despite evidence of the prevalence, of verbal mistreatment as a form of abuse, there is a dearth of literature examining the impact of verbal mistreatment on the well-being of elderly individuals. Recently, authors have called for research focusing on the consequences of specific types of elder abuse (Dong, Chen, et al., 2012), highlighting the need for further research using consistent measures for verbal abuse and expanding our understanding of the relationship between verbal abuse as a form of elder mistreatment and psychological distress. The little research available has suggested that verbal mistreatment is associated with severe physical and mental health consequences. In a sample of 842 community-dwelling women over the age of 60, psychological/emotional abuse, which included verbal abuse, was associated with an increased number of health conditions (defined as having previously been diagnosed by a doctor) including anxiety and depression (Fisher & Regan, 2006). Among an observational cohort study of 93,676 postmenopausal women aged 50–75, women reporting physical and verbal abuse were more likely to have poorer mental health and depressive symptoms (Mouton, Rodabough, Rovi, Brzyski, & Katerndahl, 2010). Thus the existing literature on the relationship between verbal mistreatment and psychological distress has a number of methodological limitations, and has rarely included males. Furthermore, while verbal abuse has been shown to be the strongest predictor of psychological distress among elderly individuals (Dong, Simon, & Evans, 2012), little data exist on its repercussions on quality of life.
In light of the prevalence of elder mistreatment of all types in this country and specifically, verbal mistreatment, we analyzed data collected from older adults during visits to primary care clinics to better understand the prevalence of verbal mistreatment and to determine the associations with quality of life. As depression and quality of life have been shown to be tightly related (e.g. Gallegos-Carrillo, García-Peña, Mudgal, Romero, Durán-Arenas, & Salmerón, 2009; Gurman, 1992), we explored these relationships controlling for depression. We hypothesized that verbal abuse would be associated with lower mental and physical quality of life.
Methods
Participants
Participants for this study were recruited and enrolled from a large urban medical practice and academic dental practice in a large, diverse metropolitan setting (Fulmer & Cabrera, 2012; Russell et al., 2012). We enrolled 142 older adults (40% male) aged 65 or over. The mean (SD) age of participants was 74.88 (6.98) years, and 45% of the sample was 75 years of age or older. The sample was very diverse with 33.3% of the sample self-identifying as White, 16.9% as Black or African American, 4.3% as Asian, 41.6% as Latino and 3.9% as other. Less than half the sample (38%) was married, 27.4% was widowed, 19.5% separated or divorced, 11.6% never married, and 3.5% were living together as married. A total of 21.6% had competed 8th grade or lower at school, 36.5% had some high school education and 41.9% had gone beyond high school.
Measures
Verbal mistreatment
Verbal mistreatment was assessed using the verbal aggression subscale of the Conflict Tactics Scale (CTS) (Straus, 1990). Respondents were required to think about the person who helped them the most with their care needs, and to then indicate how frequently each of the 6 items occurred in the previous year on a Likert-like scale ranging from “0 = never happened” to “6 = more than 20 times in the past year.” An example item is “Threatened to hit or throw something at him/her”. In the present sample the alpha value was α = .70.
Quality of Life
The SF-36 (Ware & Sherbourne, 1992) is a 36-item measure assessing eight parameters of health status: physical functioning (10 items), role limitations due to emotional problems (3 items), role limitations due to physical problems (4 items), social functioning (2 items), mental health (5 items), bodily pain (2 items), vitality (4 items), and general health perceptions (5 items). For each parameter, scores are coded, summed, and transformed to a scale from 0 to 100, with higher scores indicating better health. The two role-limitations subscales are scored by participants on a dichotomous scale, while the other six subscales are scored on Likert-like scales with responses options ranging from (1) to (3), to (1) to (6). The SF-36 scoring algorithm handles missing data using proration. If one half or fewer items in each scale are missing, a person-specific estimate (mean of the non-missing items) is substituted; otherwise, the scale is assigned a missing value. The SF-36 has been used successfully in elderly population with internal reliability coefficients for the subscales ranging from α = .82 to α = .94 (Lyons, Perry, & Littlepage, 1994). In the present sample the alpha values were α = .92 for physical functioning, α = .87 for role emotional, α = .86 for role physical, α = .73 for social functioning, α = .76 for mental health, α = .76 for bodily pain, α = .82 for vitality, and α = .70 for general health.
Depressive Symptoms
Depressive symptoms were assessed using the 20-item self-report Center for Epidemiological Studies-Depression Scale (CES-D) (Radloff, 1977), which focuses on negative affect and depressed mood. Answers are rated on a 4-point scale, from 0 (rarely or none of the time) to 3 (most or all of the time), with possible scores ranging from 0 to 60 and higher scores indicating higher levels of depressive symptoms. An example item is “During the past week, I had crying spells.” This scale has been previously successfully used in elderly populations (Fulmer et al., 2005; Lachs et al., 1997), in the present study, the alpha value was α = .71
Procedure
The procedure of the present study has been described in detail elsewhere (Fulmer & Cabrera, 2012). The study was approved by the university Institutional Review Board. Briefly, a convenience sample of 142 patients of 65 years of age or older, attending either a medical clinic (42%) or a dental clinic were enrolled. Patients were administered the Mini Mental Status Examination (Folstein, Folstein, & McHugh, 1975) in person and excluded if their score was <18. Data were collected using audio-assisted computer self-interview.
Statistical Analyses
Verbal mistreatment groups were created on the basis of scores obtained on the CTS verbal aggression, by dichotomizing the sample into a first group reporting no incidents of verbal mistreatment, and a second group reporting at least 1 incident of verbal mistreatment. Group differences were explored using t-tests and non-parametric equivalents. Hierarchical linear regression analyses and binary logistic regression analyses were conducted with verbal mistreatment as a predictor of depression and quality of life, controlling for socio-demographic variables. All analyses were conducted using SPSS 20.0 with a significance level set at .05. A search for outliers was conducted by examining Mahalanobis distance for the regression analyses. One outlier whose value was consistently over 3 times the relevant critical chi value was removed from the analysis.
Results
Prevalence of verbal mistreatment and demographic characteristics
When using a cutoff of at least one incidence of verbal mistreatment, 38% (n = 90) of the sample scored positive (Table 1). Patients reporting verbal mistreatment differed in terms of education (χ2 (2) = 6.81, p<.05) and income (χ2 (3) = 15.11, p<.01) from those reporting no verbal mistreatment. Patients reporting verbal mistreatment were more likely to have a high-level of education and report a higher income. No differences were found regarding age, gender, ethnicity or marital status.
Table 1.
Demographic Comparisons Between Elderly Reporting at Least One Instance of Verbal Mistreatment and Those Reporting None
| Verbal mistreatment (N = 90) | No verbal mistreatment (N = 148) | |||
|---|---|---|---|---|
| Age | Mean (SD) | 74.14 (6.51) | 75.32 (7.22) | t(236) = 1.27, ns |
| Gender | 54% female | 63% female | χ2 (1) = 1.64, ns | |
| Ethnicity | χ2 (4) = 6.49, ns | |||
| White | 40% | 28% | ||
| Latino | 34% | 46% | ||
| Black | 18% | 13% | ||
| Asian | 2% | 4% | ||
| Pacific Islander | 0% | 1% | ||
| Other | 6% | 8% | ||
| Marital status | χ2 (3) = 4.12, ns | |||
| Married | 49% | 37% | ||
| Widowed | 21% | 31% | ||
| Separated/divorced | 20% | 20% | ||
| Never married | 10% | 12% | ||
| Education | χ2 (2) = 6.81, p<.05 | |||
| 8th grade or less | 17% | 24% | ||
| High-school | 31% | 41% | ||
| Above high-school | 52% | 35% | ||
| Income | χ2 (3) = 15.11, p<.01 | |||
| Less than $9,999 | 27% | 33% | ||
| $10.000 – $19.999 | 17% | 35% | ||
| $20.000 – $39.999 | 22% | 21% | ||
| $40.000 – more | 33% | 12% |
Table 2 presents the descriptive statistics for depressive symptoms and quality of life among elderly individuals according to age and as well as the norms established for the SF-36 among corresponding age-groups (Thalji, Haggerty, Rubin, Berckermans, & Pardee, 1991). As the role-limitations subscales are coded on a dichotomous scale, the median is presented as opposed to the mean. Furthermore for the remaining analyses, responses to these subscales were dichotomized so as to create two groups: those reporting no role limitations and those reporting at least some role limitations. T-tests and Chi-square tests were conducted to compare levels of quality of life reported in the present sample to the norms for the corresponding age group. Overall, the present sample reported higher levels of quality of life compared to the norms for their age group, particularly among the older participants. Participants aged between 65 and 74 reported higher levels of vitality compared to the norms for their age group (p<.05). Participants aged 75 and over reported higher levels of physical functioning, general health and social functioning and less bodily pain compared to the norms for their age group (all p<.001).
Table 2.
Descriptive Statistics for Depression and Quality of Life among Elderly Individuals According to Age and Comparison with Group-Norms
| 65–74 years old | 75 years and older | |||
|---|---|---|---|---|
| The present sample (N = 126) | Norms (N = 442) | The present sample (N = 115) | Norms (N = 264) | |
| Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | |
| Depression Quality of life domains | 9.50 (10.10) | 9.03 (8.10) | ||
| Physical functioning | 75.31 (25.93) | 69.38 (26.26)* | 65.24 (27.99) | 53.20 (29.98)** |
| Bodily Pain | 70.47 (26.48) | 68.49 (26.42) | 70.98 (26.59) | 60.88 (26.01)** |
| General Health | 66.42 (20.23) | 62.56 (22.42) | 64.69 (22.32) | 56.66 (21.21)** |
| Vitality | 65.71 (22.84) | 59.4 (22.12)* | 60.27 (22.81) | 50.41 (23.62) |
| Social functioning | 84.27 (24.11) | 80.61 (25.63) | 85.36 (19.06) | 73.89 (28.75)** |
| Mental Health | 75.86 (19.88) | 76.87 (18.08) | 78.43 (17.43) | 73.99 (20.23) |
| Median | Median | Median | Median | |
| Role-physical | 100.00 | 75.00 | 100.00 | 25.00 |
| Role-emotional | 100.00 | 100.00 | 100.00 | 100 |
p< .05
p<.001
Relationship between verbal mistreatment, depression and quality of life
A series of hierarchical linear regression analyses were conducted entering the socio-demographic variables (age, gender, ethnicity, marital status, education, and income) into a first step, depression into a second step, and the dichotomous verbal mistreatment variable into a third step in order to predict the six quality of life subscales scored on a Likert-like scale (Table 3). In the first step, age was a significant predictor of (β = −.16, p<.05) of physical functioning. Furthermore, female gender (β = −.17, p<.05), being widowed (β = −.24 p<.01) and being separated (β = −.22, p<.01) were predictors of increased bodily pain. Findings revealed that controlling for socio-demographic characteristics and depression, verbal mistreatment was a significant negative predictor of social functioning (β = −.22, p<.005), and mental health (β = −.22, p<.05). The relationships with bodily pain (β = −.13, p = .096). and vitality (β = −.14, p = .059) just failed to meet significance. Verbal mistreatment was not a significant predictor of physical functioning, or general health.
Table 3.
Summary of the Results from the Linear Regression Analyses Exploring Verbal Mistreatment as a Predictor of Depression and Quality of Life, Controlling for Socio-Demographic Variables.
| Quality of life#
|
|||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PF | BP | GH | VT | SF | MH | ||||||||
| R2 | β | R2 | β | R2 | β | R2 | β | R2 | β | R2 | β | ||
| Step1 | Control variables | .09** | .08* | .01 | .04¶ | .00 | .03 | ||||||
| Step 2 | Depression | .09 | .07 | .00 | .04 | .00 | .03 | ||||||
| Step2 | Verbal mistreatment | .08 | .08¶ | .00 | .05¶ | .04** | .07** | ||||||
| −.01 | −.13¶ | −.07 | −.14¶ | −.22** | −.22** | ||||||||
p<.05
p<.01
p<.001
p<.10
Note: PF: SF-36 Physical Functioning; RP: SF-36 Role Physical; BP: SF-36 Bodily Pain; GH: SF-36 General Health; VT: Vitality; SF: SF-36 Social Functioning; MH: SF-36 Mental Health.
Significance values refer to increases in the explained variance.
Two binary logistic regression analyses were conducted, entering the socio-demographic control variables and depression in a first step and verbal mistreatment in a second step, in order to predict the dichotomous physical and emotional role limitations variables. The first model predicting role limitations due to physical problems was not significant, chi2 (17) = 22.06, ns, and none of the included variables were significant predictors. The second model predicting role limitations due to emotional problems was also overall non-significant chi2 (17) = 22.20, ns, however verbal mistreatment was a significant predictor with elderly individuals reporting verbal mistreatment 3 times more likely to also report role limitations due to emotional problems, OR = 3.02, 95% CI [1.34 – 6.77].
Discussion
The aim of the present study was to explore the association between verbal mistreatment among elderly individuals and depression and quality of life. Overall, our findings support our main hypothesis, in that elderly individuals reporting verbal abuse also reported higher levels of depression and poorer quality of life compared to elderly individuals reporting no verbal abuse.
Our sample, when stratified by age, reported higher levels of quality of life and functioning than national norms. This seems reasonable in that these patients were ambulatory and able to get to a primary care visit, and further, had a primary care provider and felt well enough to enroll in the study. This higher level of self-reported quality of life, vitality and functioning might be the reason these patients would feel empowered enough to report verbal mistreatment. Despite this high level of functioning, the rate of reported verbal mistreatment in our sample was 38%. While our definition was somewhat inclusive, and encompassed all reports of at least one incidence of verbal mistreatment, this is a compelling finding, especially given the risk for under-reporting any kind of elder mistreatment (Liao, Jayawardena, Bufalini, & Wiglesworth, 2009). It further underscores the importance of screening for verbal mistreatment among elderly individuals.
Our data indicated that after controlling for socio-demographic factors and depression, verbal mistreatment was a significant negative predictor of social functioning and mental health. These findings are in line with previous reports among women and expand the evidence of an association between verbal mistreatment and depression and poor quality of life (Fisher & Regan, 2006; Mouton et al., 2010). The cross-sectional nature of our study as well as the existing literature does not allow the directionality of the relationship between verbal mistreatment, depression and poorer quality of life to be explored, and it would be important for future research to focus on better understanding the relationships between these factors. It may be that these relationships are complex and that depression and poor quality of life are both risk factors and the consequences of elder mistreatment, thus contributing to a circular process. When considering the impact of depression and quality of life on successful aging, it is imperative that we develop and evaluate effective interventions for elder mistreatment. To date, interventions have mainly included advocacy service interventions, support groups or family conferences and demonstrated limited success (Daly et al., 2011; Dong, Simon, et al., 2012). However, cognitive-behavioral interventions that can change the communication patterns in elder-caregiver dyads have not yet been evaluated and may have a higher potential for success. Others have documented programs of “pattern -changing” for abused women, focused on intervening with women (Goodman & Fallon, 1995). We posit that a dyadic approach that fosters a couple’s therapy model can be developed and evaluation of such a program can help the field progress from screening and detection to intervention. Intervention for all types of elder mistreatment, and for verbal mistreatment in particular, are desperately needed along with the concomitant evaluation methodologies to systematically document the efficacy of interventions addressing this serious issue.
The high rate of verbal mistreatment that was found in our study has important implications for future research as well as policy decision-making. Future research should be directed at determining the best methods of intervening for patients who have reported verbal mistreatment. Sensitive and valid screening methods should also be developed to identify the patients who may be at risk for verbal mistreatment and identify patients that are currently experiencing some form of verbal mistreatment (Fulmer, Guadagno, Bitondo dyer, & Connolly, 2004). Screening methods are important in light of research that has suggested elder mistreatment is grossly under-reported (Liao et al., 2009).
Conclusions
Verbal mistreatment is a serious and understudied form of elder abuse, which may be associated with decreases in both mental and physical health. Our findings suggest that verbal mistreatment is a highly prevalent concern (38%) among elderly individuals in primary care clinics, and is related with negative outcomes. Further research is needed to better understand the relationship between verbal mistreatment and poor mental health and quality of life. In addition, efforts should be made to develop feasible, acceptable and effective interventions that could contribute to preventing mistreatment in the elderly.
Limitations
Our study includes a number of limitations. Firstly, we recruited in primary care clinics, which may render our sample less generalizable. Our sample had somewhat higher levels of functioning that the norms for their age group, while elder mistreatment has been shown to be more likely among individuals with low levels of functioning (Lachs et al., 1997). This may have led to the present sample reporting lower rates of the prevalence of verbal mistreatment than those which are present in the general population. Furthermore, the relationships between verbal mistreatment and depression and poor quality of life may vary among individuals with greater impairment, in particular cognitive impairment. In addition, even larger samples would allow for greater statistical power and the use of more complex logistical models to explore the impact of verbal mistreatment on levels of quality of life. Finally, importantly, our study was cross-sectional and therefore failed to clarify the directionality of the relationship between verbal mistreatment, depression and poor quality of life. This is an important issue, as better understanding both the risk factors and the consequences of elder mistreatment will contribute to identifying targets for intervention, and inform effective intervention strategies.
Table 4.
Summary of the Results from the Logistic Regression Analyses Exploring Verbal Mistreatment as a Predictor of Role Limitations, Controlling for Socio-Demographic Variable.
| Role limitations physical | Role limitations emotional | |||||||
|---|---|---|---|---|---|---|---|---|
| Wald | Exp (β) | p | 95% CI | Wald | Exp (β) | p | 95% CI | |
| Age | 1.94 | 1.04 | ns | .98 – 1.09 | .32 | ns | .95–1.08 | |
| Gender | 2.96 | .54 | ns | .26 – 1.09 | 3.39 | ns | .156–1.06 | |
| Ethnicity | 4.81 | ns | .35 | ns | ||||
| Education | .20 | ns | .23 | ns | ||||
| Income | 4.67 | ns | 7.05 | ns | ||||
| Marital Status | 4.85 | ns | .45 | ns | ||||
| Depression | 1.77 | 1.01 | ns | .99–1.01 | .02 | 1.00 | ns | .99–1.01 |
| Verbal mistreatment | .55 | 1.29 | ns | .66 – 2.51 | 7.15 | 3.02 | .007 | 1.34 – 6.77 |
Acknowledgments
The authors would like to gratefully acknowledge funding support from the National Institute on Aging: 1R21AG030664.
Contributor Information
Terry Fulmer, Email: t.fulmer@neu.edu.
Rachel F. Rodgers, Email: r.rodgers@neu.edu.
Allison Pelger, Email: pelger.a@husky.neu.edu.
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