University of Groningen. Depressie bij verzorgingshuisbewoners Eisses, Anne-Marie Henriëtte

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1 University of Groningen Depressie bij verzorgingshuisbewoners Eisses, Anne-Marie Henriëtte IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2005 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Eisses, A-M. H. (2005). Depressie bij verzorgingshuisbewoners s.n. Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date:

2 4 Risk factors and course of depression in residential homes 53

3 Introduction The increasing age of the general population together with the deinstitutionalisation of care for the elderly have profound influences on the composition of the population of residential homes in the Netherlands. It is official policy to keep the elderly in their own home as long as feasible. Home care provides support if needed. Only the most dependent on care move into residential homes, which implies that their population is characterised by high age (mean 85 years) and increasing physical and mental frailty. Elderly in residential care are among the most vulnerable to become and stay depressed. The reported prevalences of depression are high (6%-11% for major depression and around 30% for depressive symptoms) and the prognosis is poor (Ames 1993; Blazer 1994; Palsson & Skoog 1997). Late-life depression appears to be chronic, relapsing, often undetected and untreated (Cole et al. 1999; Ames 1990). Well-being during the last period of one s life asks for prevention and early detection of risk factors in order to prevent subsequent depression. Hoofdstuk 4 Risk factors and course Studies of depression in residential homes are rare. Only four studies reported about longitudinal data allowing separation of causes and consequences of depression (Ames 1990; Ames et al. 1988; Parmelee et al. 1992a;Weyerer 1995; Parmelee et al. 1992b). Other surveys reported risk indicators in a cross-sectional design (Parmelee et al. 1989; Mann et al. 1984; Godlove Mozley et al. 2000).Taken together, physical-health-related factors appear to be the best predictors of depression in residential care, whereas demographic characteristics, and relationships or contacts of residents are less predictive. However, it remains unclear whether health status or the gradient of functional decline is predictive for depression. Our longitudinal study aimed to identify (1) the 6-month outcome of depressive disorder (DSM IV) (American Psychiatric Association 1994) and (2) the impact of putative risk factors and change therein on the course and onset of depressive symptoms in residential homes. This study replicates and extends to residential homes the studies of Henderson and colleagues in the Australian community, and of Parmelee and colleagues in long-term care facilities in the United States (Henderson et al. 1997; Parmelee et al. 1992b). 55

4 Method The study Subjects & sampling The data used for this study were gathered for a randomised controlled trial, in which a screening intervention was offered at home level in the experimental condition. The sample consisted of elderly (65+) in residential homes. In the Netherlands, residential homes provide daily care and, if needed, uncomplicated medical care to infirm elderly above 65 (5% of all 65+ in the Netherlands). From the 42 residential homes in Drenthe, one of the northern provinces of The Netherlands 23 were eligible. The 19 non-eligible homes were excluded, because they met one or more of the following exclusion criteria: - Ongoing or planned relocations, mergers, changes in care methods, or organisational instability (10 excluded). - Homes for specific populations, for example, blind elderly (3 excluded). - Participation in the pilot of the intervention or working with screening procedures (6 excluded). The staff of five of the eligible homes had no interest in participation, as they received adequate assistance from the attending psychologist of a nearby nursing home. Four homes were not interested in the study, and three homes indicated that the intervention took too much time. Ultimately, eleven representative homes were willing to participate in the intervention study. Their data have been used for the current study. In each home, a random sample of residents (65 years and above) was drawn.the researchers notified residents of the study by a letter explaining the study and requesting their approval.those with severe cognitive impairment (score below 15 on the MMSE) and those with severe hearing or speech problems were excluded (Folstein et al. 1975). Trained psychologists and nurses carried out the interviews. The interviews lasted between one and three hours, spread over one to three interview sessions. The medical ethical committee from the university hospital approved the study and informed consent was obtained from all participating residents. 56

5 The eligible group of respondents and the baseline non-response has been extensively described in Eisses et al. (2004). Examination of residents took place at baseline (Wave 1) and after 6 months (Wave 2).The content of the interviews was identical at both waves. The present study sample consists of residents who were included at Wave 1 and were to follow-up at Wave 2. Included were only those subjects with full SCAN-data (if the GDS score was above 10). Measurements Socio-demographic variables The following variables were recorded: age, sex, marital status (never married or married vs widowed or divorced), and level of education. Psychological health variables A two-stage procedure identified depressed residents.the first screening was conducted with the Dutch version of the 30-item Geriatric Depression Scale, validated for elderly with physical illness (Yesavage et al. 1982; Brink et al. 1982; McGivney et al. 1994; Kok 1994).The GDS does not contain any items assessing physical symptoms, and hence it is an appropriate instrument for elderly suffering from somatic diseases. The recommended cut-off score of higher than 10 on the GDS-30 was used (Yesavage et al. 1982). Residents with a score above this threshold were further assessed with the Schedules for Clinical Assessment in Neuropsychiatry (SCAN)(Wing et al. 1998).The following diagnostic categories were determined: a) major depressive episode as defined by DSM-IV(American Psychiatric Association 1994), b) minor depressive episode as defined by DSM-IV (research) criteria (American Psychiatric Association 1994) and referred to the presence of two through four symptoms during the last month, including one of the two core symptoms: depressed mood or loss of interest/pleasure. Hoofdstuk 4 Risk factors and course Familial vulnerability for depression was assessed with two questions referring to depression in the personal and family history. The Mini-Mental State Examination (MMSE) assessed cognitive impairment. Only scores above 14 were taken into account, because the validity of the GDS below that cut-off score is questionable (Folstein et al. 1975; McGivney et al. 1994). 57

6 Physical health variables - Functional impairment in activities of daily living, as measured with the Groningen Activity Restriction Scale (GARS) (Kempen & Suurmeijer 1990; Suurmeijer & Kempen 1990) The GARS assesses physical restrictions in nine basic and nine instrumental activities of daily living (for example, self-care, mobility, and housekeeping). - Presence of chronic physical diseases as reported by the resident. (Kriegsman et al. 1996).The residents reported eight most prevalent diseases (cardiac, vascular and urinary disorders, presence of diabetes, stroke, malignancy, rheumatism, and COPD) and one category others. In a validation study in elderly in the community, respondents self-reports were compared to information obtained from their GPs, and proved to be sufficiently reliable (Kriegsman et al. 1996). - Recent hospital admission. At baseline, the time span was one year, and at follow-up, it was six months ( period between two waves ). - Visit to a specialist doctor within the last year. Only assessed at Wave 1. - Incontinence: incontinent or use of a catheter, vs not so. - Visual problems, divided into two main categories: blind or very poor eyesight vs not so. - Deafness, dichotomised in hearing with (little, much, or very much) difficulty vs hearing without any difficulty. - Distress from experienced pain as measured by the subscale Pain (eight items) of the Nottingham Health Profile (NHP)(Erdman et al. 1993). Personality Neuroticism was measured by the subscale of the Eysenck Personality Questionnaire Revised Short Scale (EPQ-RSS) (Eysenck & Eysenck 1991; Sanderman et al. 1995). Social support, loneliness, religious affiliation, life events Social support was measured using the shortened (12 items) Social Support Interactive version, and was designed to be applied to the elderly (Van Eijk et al. 1994;Van Sonderen 1993).The 11-item Loneliness Scale assessed loneliness; the scale defines the degree of loneliness as the discrepancy between what one wants and what one gets in term of interpersonal affection and intimacy (De Jong Gierveld & Van Tilburg 1999).Absence of religious affiliation was indexed by no religious affiliation (1), and being religious / belonging to a church (0). Single questions addressed recent ( 1 year) negative life events, such as loss of spouse. Only assessed at Wave 1. 58

7 Statistical analyses For all analyses carried out in this study applies that a p-value smaller than 0.05 was considered statistically significant. The effect of attrition was examined with analyses of variance (ANOVA) for continuous variables, and chi-square tests for categorical variables. All ANOVAs were followed by modified t-tests (using the Bonferroni method to adjust the p values) to compare the attrition groups with the study sample. To identify the 6-months outcome of depressive symptoms and depressive disorders, the changes of subjects with depressive symptoms (GDS>10) or depressive disorders (MDD and MinD) were examined between Wave 1 and Wave 2. The impact of putative risk factors (Wave 1) on depressive symptoms (Wave 2) were tested in multiple linear regression analyses. The GDS score at Wave 2 was the dependent variable in all analyses. For normalisation these GDS scores needed log transformation (LogGDS). The predictors were the scores at the variables measured at Wave 1. Hoofdstuk 4 Risk factors and course To examine whether deterioration or amelioration in cognitive, social and physical functioning between waves had an effect on depressive symptoms, the changes between waves were entered as predictors in the linear regression model. The dependent variable was again the GDS score at Wave 2.At step 1,Wave 1 variables were included in the model to correct for differences in scores at Wave 1. At step 2, GDS at Wave 1 was included.at step 3, change between waves was entered for the variables: cognitive impairment, functional impairment, the number of chronic diseases, social support, hard of hearing, visual problems, pain, loneliness and incontinence. Note that at step 1, only variables were included that correspond to the change variables of step 3. 59

8 Results Characteristics of the sample At Wave 1 the sample consisted of 464 respondents.their mean age was 85.4 years (SD: 6.5). Of these 464 respondents, 304 participated again at Wave 2 (43 died before Wave 2, 4 had insufficient SCAN-data, 69 refused participation, and 44 were too ill, deaf or cognitively impaired to partake, or could not be recontacted). Table 1 Effect of attrition. Comparison of characteristics of three groups of subjects: the study sample (assessed at both Wave 1 and 2), the deceased between waves and the group of those who refused or were too ill at Wave 2 Variables Mean (sd) or percentage Study sample Deceased (n=304) before Wave 2 (n = 43) Age-mean 85.3 (6.3) 87.2 (6.5) Female sex * Bereaved/divorced Education > 6 years Depression score (GDS) b 5.05 (3.7) 7.0 (4.3)* History of depression Cognitive functioning (MMSE) c 23.8 (3.8) 21.9 (3.5)* Functional impairment (GARS) d 42.6 (12.0) 48.0 (12.1)* Number of chronic diseases 2.4 (1.6) 2.1 (1.2) Recent hospital admission (last year) Incontinence Blind Deaf Pain 28.5 (29.4) 27.2 (31.4) Neuroticism score 2.9 (2.7) 2.8 (2.3) Social support (SSL-12-I) 26.4 (5.7) 27.2 (4.9) Loneliness 3.3 (2.6) 3.6 (2.8) Absence of religious affiliation * Differed significantly from the study sample (p<0.05) according to modified t-tests (method Bonferroni) or chi-square tests a Based on analyses of variance (means) or chi-square tests (proportions) 60

9 Sample attrition led to systematic differences between active sample participants and sample dropouts. As Table 1 shows, attrition was related to male sex, depressive symptoms, cognitive impairment, functional impairment, and absence of religious affiliation. Table 2 presents the depression status of the study sample at Wave 1 and Wave 2. The general picture reveals that the sample as a whole was relatively stable regarding depression. The average GDS score increased slightly, but statistically signifi- Hoofdstuk 4 Risk factors and course Difference a Refused or were F (df1, df2) / P too ill at Wave 2 x2 (df) (n=117) 84.9 (7.1) (2, 449) Age-mean (2) Female sex- 64.3* (2) Bereaved/divorced (2) Education > 6 years 6.7 (4.9)* (2, 461) Depression score (GDS) b (2) History of depression 21.2 (4.3)* (2, 446) Cognitive functioning (MMSE)c 44.9 (12.1) (2, 437) Functional impairment (GARS)d 2.1 (1.5) (2, 397) Number of chronic diseases (2) Recent hospital admission (last year) (2) Incontinence (2) Blind (2) Deaf 31.4 (29.1) (2, 438) Pain 3.3 (3.0) (2, 398) Neuroticism score 25.7 (5.7) (2, 398) Social support (SSL-12-I) 4.0 (3.0) (2, 440) Loneliness 46.7* (2) Absence of religious affiliation b GDS = Geriatric Depression Scale c MMSE =Mini Mental State Examination d GARS = Groningen Activity Restriction Scale 61

10 Table 2 Depressive symptoms and disorders as defined by DSM-IV criteria, at Wave 1 and Wave 2 (after 6 months) in elderly in residential homes (N=304) Wave 1 n Wave 2 n Average GDS score a (S.D.; range) 5.05 (3.71; 0-25) 5.57 (3.92; 0-26) GDS>10 (no MDD or MinD) b 2.3% 7 4.2% 13 MDD 1.6% 5 1.3% 4 MinD 2.3% 7 2.3% 7 MinD+MajD 3.9% % 11 a GDS = Geriatric Depression Scale b MDD = Major Depressive Disorder, MinD = Minor Depressive Disorder cantly from Wave 1 to Wave 2 (paired t: , df=303, p=0.005).the other characteristics of the study sample have been compared (not shown): the level of functional impairment and the number of chronic diseases were significantly higher at Wave 2 than at Wave 1, in line with what may be expected in this age group. The other characteristics (as listed in Table 1) did not change significantly. Course of depression To examine the course of depression,table 3 shows the change of subjects from different depressive categories at baseline and 6 months later.the results reveal that between waves the very large majority of residents remained free from depression or depressive symptoms (274 out of 304).At the first wave, 19 patients were found to suffer from depressive symptoms (7) or a major or minor depression (12). How did these 19 fare? Unchanged remained 7 residents (6 with minor or major depression; 1 with depressive symptoms).ten residents showed some kind of recovery: full remission from depressive symptoms in 4 cases; full remission from major or minor depression in 2 cases; in 4 cases the major or minor depression partially remitted. Two residents showed deterioration from depressive symptoms into a minor/major depression. From Wave 1 to Wave 2, 11 initially not depressed residents developed either depressive symptoms (8), or a major/minor depression (3). In order to get a more precise idea about changes, Table 4 show the subjects change in GDS scores between Wave 1 and Wave 2. By far the most residents experienced as many (better: as few) depressive symptoms at Wave 1 as at Wave 2. 62

11 Table 3 Course of depressive symptoms and disorders in elderly in residential homes (N=304) Wave 2 (6 months) Wave 1 No depressive Depressive MDD / MinD b Total symptoms symptoms (GDS 10) a (GDS>10) No depressive symptoms (GDS 10) Depressive symptoms (GDS>10) MDD / MinD Total a GDS = Geriatric Depression Scale b MDD = Major Depressive Disorder, MinD = Minor Depressive Disorder Hoofdstuk 4 Risk factors and course Table 4 Change in number of depressive symptoms (GDS scores a ) from Wave 1 to Wave 2 (N=304) Wave 2 GDS scores Wave 1 GDS scores a GDS= Geriatric Depression Scale Comparable numbers of residents increased and decreased in depressive symptoms.the GDS scores at both waves were strongly correlated (Pearson s correlation = 0.655; p<0.001), suggesting a high level of continuity as well. Factors associated with depressive symptoms The cross-sectional associations between risk factors and depressive symptoms (GDS) at Wave 1 have been reported elsewhere (Eisses et al., 2004).They showed that twelve out of 21 putative risk factors were associated with depressive symp- 63

12 Table 5 Multiple regression analysis predicting depressive symptoms (loggds) among elderly home residents at Wave 2 (N=181) Predictor Variable (at Wave 1) Depression at Wave 2 (loggds a ) Beta P Age Sex Marital status Education level GDS at Wave ** Familial vulnerability Cognitive functioning Functional impairment * No of chronic diseases Wave Recent hospital admission Recent visit to specialist doctor Incontinence Blind Deaf Pain Neuroticism * Social support Loneliness No religious affiliation Life event R % Adjusted R % a GDS=Geriatric Depression Scale * P<0.05 ** P<0.001 toms: hearing impairment, no religious affiliation, incontinence, recent hospital admission, blindness, familial vulnerability, younger age, loneliness, pain, functional impairment, neuroticism, and lack of social support. No association was found for sex, marital status, educational level, length of stay, loss of a child, recent life events, recent visit to a medical doctor, number of chronic physical diseases, and cognitive functioning. At Wave 2, the cross-sectional analyses identified largely the same risk factors as found at Wave 1. However, the results revealed a statistically significant association with the GDS at Wave 1 but not at Wave 2 for the risk factors: age, hard hearing, 64

13 no religious affiliation, and blindness. Furthermore, cognitive impairment and recent life events showed significant associations with the GDS only at Wave 2. And, not associated with depressive symptoms at both waves were educational level, loss of a child, number of chronic diseases, and recent visit to a specialist doctor, marital status, female sex, length of stay. Prediction of Wave 2 depression from Wave 1 variables GDS score at Wave 1 was the best single predictor of GDS score at Wave 2 (Table 5). Furthermore, neuroticism, functional impairments, and the number of chronic diseases were important predictors of depressive symptoms at Wave 2.The total variance explained by all Wave 1 predictors reached 48.7% (Adj. R 2 =42.7%). Prediction of the GDS score at Wave 2 from changes in functioning between waves Hoofdstuk 4 Risk factors and course Table 6 shows the results of the regression model that predicts GDS scores at Wave 2 (Log GDS) not only from Wave 1 characteristics but also from the changes therein between Wave 1 and 2. (Note that a limited number of Wave 1 variables have been entered in the model.) Especially an increase in loneliness and cognitive impairment were independently associated with more depressive symptoms at Wave 2.The full model explained 43.5% (Adj. R 2 = 39.2%) of the variance in Wave 2 GDS scores.the R 2 change of the change variables was 4.7%, after the inclusion of Wave 1 variables. Discussion This longitudinal study showed that the 6-month outcome of depression in residential homes is rather bleak.although the prevalences of depressive symptoms and disorders were not high (2.3% and 3.9% respectively), only 2 out of 12 residents with a depressive disorder had recovered after 6 months. Of the 7 with depressive symptoms, 4 had recovered after 4 months, and 2 had become more severely depressed (MDD or MinD). Since attrition was considerable (34.4%), though very much comparable to other follow-up studies in community settings (Henderson et al. 1997), and related to 65

14 Table 6 Multiple regression analyses predicting depression at Wave 2 (log GDS a ) from change in functioning between waves.wave 1 variables included as covariates in the model (N= 241) Predictor Variable Beta P R 2 Change Wave % Cognitive impairment Functional impairment No of chronic diseases Deafness Visual problems Pain Social support Loneliness * GDS score ** Change variables 4.7% Cognitive impairment- decline * Functional impairment -increase No of chronic diseases - increase Social Support- increase Hard of hearing- increase Visual problems- increase Pain- increase Loneliness- increase * Incontinence a GDS=Geriatric Depression Scale Full model R 2 =43.5%. Adj.R 2 =39.2%. *P<0.05, **P<0.001 depression, the reported outcome is probably an underestimation of the real outcome of depression in residential homes.the fact that many subjects died or were not able anymore to participate in Wave 2 highlights the frailty of the residential population. In line with Henderson s findings, is the high level of persistence of depressive symptoms over time. The impact of putative risk factors and change therein on the course and onset of depressive symptoms in residential homes was determined. Depressive symptoms at Wave 2 were best predicted, after controlling for baseline depressive symptoms, by neuroticism and functional impairments. Increased loneliness and cognitive 66

15 impairment during the 6-month follow-up were associated with an increase in depressive symptoms.these results are in line with the findings of Parmelee (1992) and Weyerer and colleagues (1995) and stress the significance of impairments and interpersonal affection and intimacy in late life depression (Ormel et al. 2001; Beekman et al. 2001). Further research should examine whether the causal relationship between chronic physical diseases and depressive symptoms is mediated by functional impairment and or a reduced sense of control, as was found in an elderly population in the community, in The Netherlands (Ormel et al. 1997). Limitations Since the -selective- attrition of depressed cases was high, our results are probably positively biased and should be interpreted with caution. Furthermore, although the current study was longitudinal in design, it does not allow pertinent conclusions regarding causal effects of the reported risk factors. It is likely that some determinants such as physical disability and loneliness have bi-directional relationships with depression (Ormel et al. 2002). Finally, -negative- response tendencies and recall bias may have coloured the answers of depressed residents on items regarding their physical and psychological wellbeing. In other words, they may have reported inadequately on putative risk factors. This process is a common threat to the internal validity of findings like ours. Hoofdstuk 4 Risk factors and course Clinical implications Given the persistence of depressive symptoms in residential homes, mental health care in this setting might not be provided or ineffective. The most important risk factors of depression in residential homes are not easily modified.the best opportunity might well be in the interpersonal domain. Conclusion Depressive disorders have a poor outcome in residential homes for the elderly in The Netherlands. In order to prevent -chronic- depression, attention is needed for residents who worry a lot, are functional impaired, suffer from several chronic physical diseases, are cognitive impaired, and those who have current depressive symptoms. Preventive activities are best targeted at interpersonal relationships and social contacts since physical and cognitive frailty are hard to avoid. 67

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