Depression is very common among nursing home residents (Rosen, Mulsant, & Pollock, 2000). In addition to the 10% to 22% of nursing home residents diagnosed with depression, another 15% to 50% experience significant depressive symptoms without meeting the diagnostic criteria for major depression (Burrows, Morris, Simon, Hirdes, & Phillips, 2000). Elderly individuals with depression experience increased morbidity and mortality (Gazewood & Mehr, 1998; O'Connor & Vallerand, 1998; Parmelee, Katz, & Lawton, 1992; Penninx et al., 1999; Rovner, 1993). Depression is thought to result from both biological phenomena such as drugs and disease, and experiential phenomena such as loss - particularly losses resulting in self-reproach or diminished self-esteem (Dugan et al., 2000). Specific phenomena placing an elderly person at risk for depression include personal vulnerability, social factors such as bereavement, and health related factors such as disability and cognitive impairment (Jorm, 1995). Additional risk factors for development of depression in elderly individuals include (Commerford & Reznikoff, 1996; Doyle, 1995; Dugan et al., 2000; Hagerty & Williams, 1999; McCurren, Dowe, Rattle, & Looney, 1999):
* Stressful life events.
* Interference with daily routines.
* Lack of supportive social network.
* Lack of a sense of belonging.
* Decrease in life satisfaction.
* Co-occurrence of physical conditions and functional decline.
Depression leads to despair, suffering, isolation, and loss of personal happiness (McCurren et al., 1999). When compared with younger individuals, elderly individuals with depression have an increased risk of suicidal ideation and a decreased likelihood of being treated (Uncapher & Arean, 2000). Although depression in elderly adults can be successfully treated with a variety of modalities (e.g., medication, psychotherapy, electroconvulsive therapy), depression in this group is difficult to diagnose and, therefore, often goes untreated (Beck, Koenig, & Beck, 1998; Lander, Wilson, & Chochinov, 2000; Onega & Abraham, 1998; Rovner, 1993). The lack of recognition and treatment of depression in elderly individuals occurs despite evidence that the benefits of treatment outweigh potential risks (Mulsant & Ganguli, 1999).
A positive correlation between depression and cognitive impairment has been noted among both individuals with cognitive impairment and those without cognitive impairment (Forsell & Winblad, 1998; Kauhanen et al., 1999). Among elderly women without dementia, depression was associated with poor cognitive performance and ensuing cognitive deterioration (Yaffe et al., 1999). Treatment for depression has been shown to improve cognitive impairment-related behavioral symptoms (Pollock & Mulsant, 1998).
Although the nature of the link between depression and communication impairment is unclear, cognitive impairment increases the probability of depression in elderly adults with communication impairment. Among aphasie stroke patients, those with cognitive impairment are more likely to experience major depression (Kauhanen et al., 1999). In elderly nursing home residents, presence of depressive symptoms is associated with significandy more disruptive vocalization independent of cognitive impairment, age, and sex (Dwyer & Byrne, 2000). Verbally aggressive behaviors are positively correlated with depression in nursing home residents with cognitive impairment (Menon et al., 2001). Verbally disruptive behavior is positively correlated with depression (Draper et al., 2000). Verbal agitation in patients with dementia is decreased after treatment with antidepressant selective serotinin reuptake inhibitors, suggesting that depression may be a cause of verbal agitation in individuals with cognitive impairment (Ramadan, Naughton, & Bassanelli, 2000).
Pain in elderly individuals is common, underestimated, and undertreated - especially in individuals with cognitive impairment (Huffman & Kunik, 2000). Claims that individuals with advanced dementia do not experience pain are hard to evaluate because a person's ability to communicate pain also diminishes with advancing dementia. Nursing home resident self-report of pain intensity correlates positively with higher cognitive functioning as measured by the Mini-Mental State Exam (MMSE) (Folstein, Folstein, & McHugh, 1975) and with self-report of depression as measured by the Geriatric Depression Scale (Fisher et al., 2000). Positive correlations between pain and depression in elderly adults have been found in many settings (CohenMansfield & Marx, 1993; Desbiens et al., 1997; Koenig, 1997; Parmelee, Katz, & Lawton, 1991; Ross & Crook, 1998; Won et al., 1999). It is theorized that disease causes pain, pain causes depression, and depression, in turn, sensitizes the individual to pain (Harkins, 1996).
In an investigational setting, individuals with depression complained of more frequent, more intense, and more unpleasant responses to experimentally induced pain than did healthy control subjects, even though the individuals with depression had significandy higher pain thresholds that did the control subjects (Lautenbacher, Spernal, Schreiber, & Krieg, 1999). In nursing home residents, verbal self-report of pain intensity was positively correlated with self-report of depression (Fisher et al., 2000). Pain and depression are seen as coexisting in elderly adults. Treatment for one requires adequate treatment of the other (Gloth, 2000).
Cognitive impairment and communication difficulties make pain measurement difficult. In addition, although there is general belief that individuals with advanced dementia are able to experience pain (Hurley, Volicer, Hanrahan, Houde, & Volker, 1992; Marzinski, 1991), there is also evidence that some individuals with advanced dementia of the Alzheimer's type do not appear to experience pain (Fisher-Morris & Gellatly, 1997).
A descriptive correlational post hoc design was used to examine the relationships among cognitive impairment, communication impairment, depression, and pain in elderly nursing home residents. The research questions posed by this study were:
MINIMUM DATA SET (MDS) SUBSCALES USED AS DATA SOURCES
* What is the relationship between depression and age, pain, cognition, and communication?
* Do significant differences in depression exist between groups defined by age, cognition, communication, and pain?
* How much of the variance in depression can be explained by variance in age, cognition, communication, and pain?
Setting and Sample
The sample consisted of 111 residents of a 200-bed Medicare-certified, Joint-Commission-accredited nursing home in a suburban area of New England. Sample size was determined by the method described by Tabachnick and Fidell (1996), based on the number of independent variables. With an alpha of .05 and a beta of .20, the sample for five independent variables would be 90 for multivariate prediction and 109 for individual prediction. Inclusion criteria for the study were:
* Being a nursing home resident.
* Being at least 60-years-old.
* Speaking English (to control for the effect of a language barrier on the nurse's ability to assess the nursing home resident).
* Living at the nursing home during the calendar year 1998.
Ages ranged from 60 to 95. The distribution of ages was normal, with a mean age of 77.9 years and a standard deviation of 6.9 years. The population was White and 78% female. No potential participant was included or excluded because of gender or minority status.
Data Collection Procedure
Institutional Review Board approval for the rights of participants was obtained through the University of Massachusetts at Amherst. The project was approved by nursing home administration and by the residents' council at the facility. Written, informed consent was obtained from the participant or proxy. After the participant's consent was recorded, a registered nurse retrieved the participant's medical record. In this faculty, Minimum Data Set (MDS) (Berlowitz, Bezerra, Brandeis, Kader, & Anderson, 2000) forms were completed by nurses who cared for the particular resident on a regular basis. On a sample of 20 MDS forms, interrater reliability between the residents' forms and the corresponding forms completed by the researcher was 96%. For the purpose of this research, the participant's most recent annual MDS was taken from the medical record, photocopied, and returned to the medical record. Each MDS was assigned a random fourdigit code number to assure anonymity of the data, and privacy and confidentiality for the nursing home residents. Using the coded identification number, the data was entered into a spreadsheet. Data were taken from selected subscales of the MDS for Nursing Home Resident Assessment and Care Planning (MDS 2.0) as found in the resident's medical record (Table 1). If multiple MDS documents were available for an individual participant, the most recent annual MDS was selected for the study.
Instrumentation and Measures
The MDS, a comprehensive resident assessment instrument, contains detailed information describing the clinical, behavior, and social status of residents. The MDS has been found suitable for research related to activities of daily living, behavior, cognition, communication, depression, functional status, health conditions, and mood (Burrows et al., 2000; Flacker & Kiely, 1998; Morris, Fries, & Morris, 1999; Snowden et al., 1999). In the United States, the full MDS is completed annually for residents of all Medicare- and Medicaidcertified nursing homes. Personnel who provide direct care to the nursing home residents collect the data. The data come from continuous observations of the daily lives of nursing home residents. This is a strength of using the MDS (Burrows et al., 2000). It is attractive as a data collection instrument because of its availability (Cohen-Mansfield, Taylor, McConnell, & Horton, 1999) and because there is no need for additional data collector training or for development of new instruments (Flacker & Kiely, 1998).
CHARACTERISTICS OF TOTAL SAMPLE AND GROUPS
Reliability of the MDS. Casten, Lawton, Parmelee, and Kleban (1998) found inter-rater reliability scores in clinical settings to range from .80 to .99, with corresponding kappa's ranging from .56 to .84. Inter-rater reliability for MDS pain intensity and frequency scores is reported as .73 (Fries, Simon, Morris, Flodstrom, & Bookstein, 2001). Phillips, Chu, Morris, and Hawes (1993) studied MDS inter-rater reliability in the context of nursing home resident's cognitive impairment. They found that inter-rater reliability of measures of activities of daily living status, communication skills, and vision and hearing for cognitively impaired nursing home residents were adversely affected when compared to these measures in non-cognitively impaired nursing home residents. Reliability was not uniformly affected across all domains. This suggests difficulties in assessment when the nursing home resident is cognitively impaired.
Validity of the MDS. The MDS measures of functional status, cognitive impairment, and communication correlated well with scores from the Brief Psychiatric Rating Scale, Dementia Mood Assessment Scale, Psychogeriatric Dependency Rating Scale, and the Physical Signs and Symptoms Scale (Frederiksen, Tariot, & De Jonghe, 1996). Pearson correlation coefficients ranged between .89 and .62 for functional status, cognition, and communication. To determine the relationship between the Functional Independence Measure commonly used in acute rehabilitation settings, and the MDS used in nursing homes, Williams, Lie, Fries, and Warren (1997) calculated equal correlations for the motor and cognitive subscales of .81. Data from the MDS-based Cognitive Performance Scale (CPS) correlated well with scores from the MMSE, the Test for Severe Impairment, and nursing judgments of disorientation (Morris et al., 1994). Analysis of correlations between CPS and MMSE revealed sensitivity of .94, specificity of .94, and diagnostic accuracy of .96 (Hartmaier, Sloane, Guess, & Koch, 1994; Hartmaier et al., 1995). The MDS measures of pain intensity and frequency accounted for 56% of the variance in scores on a visual analog pain scale (Fries et al., 2001).
Calculation of Individual Measures
Age was calculated by subtracting the date of birth from the date of MDS completion. The cognitive impairment score was the sum of scores for:
* Short-term memory.
* Long-term memory.
BIVARIATE CORRELATIONS IN GROUPS BASED ON PAIN
ONE-WAY ANALYSIS OF VARIANCE IN DEPRESSION BETWEEN GROUPS BASED ON EXTENT OF COGNITIVE IMPAIRMENT*
* Indicators of delirium (e.g., distractibility, altered perception or awareness, disorganized speech, restlessness, lethargy, variable mental function).
The communication impairment score was the sum of scores for:
* Modes of expression.
* Ability to make self understood.
* Speech clarity.
* Ability to understand others.
* Visual limitations.
The depression score was the sum of scores for:
* Verbal expressions of distress.
* Sleep-cycle issues.
* Sad, apathetic, or anxious appearance.
* Loss of interest.
The pain score was the sum of scores for pain frequency, intensity, and site. The greater the score, the greater the age, cognitive impairment, communication impairment, depression, or pain.
Definition of Groups
For purposes of analysis, the sample was divided into groups (Table 2). Groups were defined based on modality of the distributions and shapes of the scatter plots of each of the major variables and age. Groups were hierarchical and mutually exclusive. They allowed clustering of the participants for the purpose of analysis of variance (ANOVA). For example, one might wish to consider communication status for individuals who had the best, the worst, and the median cognitive function. Differences in mean scores between groups were large and significant (ANOVA, p < .001) An expert gerontological nurse confirmed that the groupings were meaningful (Table 2).
Correlation coefficients were calculated between depression and age, cognitive impairment, communication impairment, and pain. One-way ANOVA was used to detect differences in mean depression scores among groups as defined previously. In cases when the overall F ratio was significant, the Tukey post-hoc test was used to identify the location of significant differences. Stepwise multiple regression analysis was used to identify models which could predict depression in groups defined by age, cognitive impairment, communication impairment, and pain.
Results of Correlation Analysis
Statistically significant correlations between depression and cognitive impairment occurred frequently throughout the sample. The strongest correlations occurred in the oldest residents (r = .50, p < .05), those with severe communication impairment (r = .52, p < .01), and those with moderate (r = .86, ? < .01) or severe pain (r = .67, ? < .01). A modest correlation existed between depression and pain in the total sample (r = 2\,p < .05). Depression correlated strongly with pain in residents with severe cognitive impairment (r = .73, ? < .01) and severe communication impairment (r = .63,/» < .01).
Selected correlations were stronger in the context of pain (Table 3) The correlation between cognitive impairment and depression was .32 in the total sample, .86 among those individuals with moderate pain, and .67 among those with severe pain. The correlation between communication impairment and depression was not significant in the total sample, but was .68 among those individuals with moderate pain, and .47 among those with severe pain.
Results of ANOVA
The differences in the extent of depression were significant between groups defined by cognitive impairment (Table 4). As cognitive impairment increased, depression increased as well. Residents with severe cognitive impairment were significandy (p < .01) more depressed than moderately cognitively impaired residents. These residents, in turn, were signiflcandy (p < .01) more depressed than mildly cognitively impaired residents.
SIGNIFICANT REGRESSION MODELS PREDICTING DEPRESSION
Results of Multiple Regression
For the entire sample, cognitive impairment alone predicted 14% of the variance in depression, but when pain was entered into the equation, the predicted variance increased by half to 22% (p < .01). Among residents in Age Groups 1 and 2 (Table 2), the only significant predictor of depression was cognitive impairment, but cognitive impairment explained only 10% and 14% of the variance, respectively. Among the most elderly adults, cognitive impairment alone predicted 21% of the variance in depression, but when pain was entered into the equation, the predicted variance in depression doubled to 42% (p < .01).
Among residents with severe communication impairment, cognitive impairment explained 37% (p < .01) of the variance in depression, but pain and cognitive impairment together predicted 57% (p < .01). Among residents with moderate pain, cognitive impairment was a strong (72%, ? < .01) predictor of depression. In residents with severe pain, the role of cognitive impairment in predicting variance in depression was somewhat less (42%, ? < .01 ) than in the moderate pain group, but still substantial. Among residents with severe cognitive impairment, pain alone was responsible for 50% (p < .01) of the variance in depression (Table 5).
A complex link among cognitive impairment, pain, and depression is identified through this study. Cognitive impairment is significantly associated with depression, and pain increases the strength of the relationship between cognitive impairment and depression. This effect is strongest among the most elderly adults and those with severe communication impairment. Among participants with pain, the presence of cognitive impairment was a major predictor of depression. When individuals with severe cognitive impairment or severe communication impairment experience pain, they are very likely to experience depression as well. Neither age nor communication impairment alone are significant predictors of depression. The oldest participants were more likely than others to experience depression if they were also cognitively impaired, but this difference did not reach statistical significance.
This work suggests the following:
* Substantial variance in depression among nursing home residents can be explained by cognitive impairment and pain.
* Nursing home residents are not a homogeneous group. Meaningful information can be obtained by stratifying samples by age, cognitive impairment, communication impairment, and pain.
* Nurses may be able to ameliorate symptoms of depression in nursing home residents by using new approaches. These approaches are based on knowledge of the resident's cognitive, communication, and pain status, and thus deviate from the usual etiology-driven approaches based on drugs, diseases, and loss.
The following recommendations are made for clinical practice:
* Nurses should look carefully for evidence of depression in nursing home residents, especially those with cognitive impairment or pain. Use of both pharmacological and non-pharmacological methods of treatment should be considered.
* In a population of cognitively impaired nursing home residents who are depressed, nurses should look carefully for evidence of pain or risk factors for pain and treat for pain whenever appropriate.
Research is needed to further develop the study findings and their implications. Examples of suitable research questions are listed in the Sidebar.
This research involved a group of White, predominandy female, residents of a single suburban nursing home. Although the population of nursing home residents in the United States is largely White and female, further studies should include members of other racial and ethnic groups, and residents who live in urban and rural settings. Generalizability of findings is decreased when research is conducted at only one site. Studying only one nursing home, however, may have led to increased reliability and validity of findings because of consistency and availability of data and because the data was generated by nurses actually caring for the residents.
The present study found that the prevalence of depression increases with the extent of cognitive impairment. Nursing home residents with severe cognitive impairment are significantly more depressed than are those with moderate cognitive impairment. Those with moderate cognitive impairment are more depressed than those with minimal cognitive impairment. Depression, pain, and cognitive impairment form a triad that helps to describe characteristics of nursing home residents. The presence of pain increases the likelihood that the cognitively impaired nursing home resident will be depressed. The presence of cognitive impairment increases the likelihood that the nursing home resident with pain will be depressed. The effect of pain on the relationship between cognitive impairment and depression is striking among the most elderly individuals in this study and among those with severe communication impairment. The presence of pain was not a significant correlate of depression in residents who did not have severe cognitive or communication impairment. Further research exploring application and utility of these findings is warranted.
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MINIMUM DATA SET (MDS) SUBSCALES USED AS DATA SOURCES
CHARACTERISTICS OF TOTAL SAMPLE AND GROUPS
BIVARIATE CORRELATIONS IN GROUPS BASED ON PAIN
ONE-WAY ANALYSIS OF VARIANCE IN DEPRESSION BETWEEN GROUPS BASED ON EXTENT OF COGNITIVE IMPAIRMENT*
SIGNIFICANT REGRESSION MODELS PREDICTING DEPRESSION