Development and validation of an instrument to detect depression in nursing homes. Nursing homes short depression inventory (NH-SDI)
Depression is often overlooked in elderly nursing home residents because symptoms may be masked or dismissed as an inevitable consequence of ageing. Current tools for the detection of depression in institutionalised older people are not always specific.
To construct and verify an instrument with which to detect depression in elderly nursing home residents (NH-SDI).
Firstly for the construction, 328 elderly people were selected at random from the residents of 17 nursing homes in France, and examined by a single investigator. The examination included a psychiatric assessment, an evaluation of cognitive function using the MMSE, an evaluation of depressive state using four different instruments (mini-GDS, Goldberg, DMAS, CSDD), and assessment of any changes in behaviour in those suffering from dementia, using the NPI. A second stage was to confirm NH-SDI in 99 institutionalised subjects.
Following the selection of items, we created a scale of 16 dichotomous items (NH-SDI). The internal consistency was satisfactory (α Cronbach = 0.85), as was its reliability with a sensitivity of 85.1% and a specificity of 86.5% for a cut-off score above 5.
The NH-SDI appears to be a useful instrument for the detection of depression in nursing homes and can easily be applied by healthcare staff as part of routine procedures.
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Available from: Yvonne Treusch
- "In contrast to agitation, depressive symptoms in nursing home residents with dementia are often under-diagnosed (Rovner et al., 1991; Baller et al., 2010) by caregivers and physicians because: (1) they overlap with other symptoms like apathy (Marin et al., 1993; Lyketsos et al., 2002); (2) they might present differently compared to depression in persons without dementia (Gallo and Rabins, 1999; Kunik et al., 2010); and (3) patients with more advanced stages of cognitive decline might be unable to express distress adequately (Lee and Lyketsos, 2003). Thus, specific instruments have been developed to detect depression in persons with dementia (Sunderland et al., 1988; Prado-Jean et al., 2010a). Unlike the cognitive symptoms of dementia, where causal therapy is limited, effective nonpharmacological (Deudon et al., 2009) and pharmacological (Sink et al., 2005; Ballard et al., 2009a) strategies are available for the treatment of dementia-related behavioral and psychological symptoms like agitation and depression. "
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ABSTRACT: ABSTRACT Background: The purpose of this study was to investigate the relationship between dementia severity, age, gender, and prescription of psychotropics, and syndromes of agitation and depression in a sample of nursing home residents with dementia. Methods: The Cohen-Mansfield Agitation Inventory (CMAI) was administered to residents with dementia (N = 304) of 18 nursing homes. Agitation symptoms were clustered using factorial analysis. Depression was estimated using the Dementia Mood Assessment Scale (DMAS). Dementia severity was assessed categorically using predefined cut-off scores derived from the Mini-Mental State Examination (MMSE). The relationship between agitation and its sub-syndromes, depression, and dementia severity was calculated using χ 2-statistics. Linear regression analyses were used to calculate the effect of dementia severity and psychotropic prescriptions on agitation and depression, controlling for age and gender. Results: Increasing stages of dementia severity were associated with higher risk for physically aggressive (p < 0.001) and non-aggressive (p < 0.01) behaviors, verbally agitated behavior (p < 0.05), and depression (p < 0.001). Depressive symptoms were associated with physically aggressive (p < 0.001) and verbally agitated (p < 0.05) behaviors, beyond the effects of dementia severity. Prescription of antipsychotics was correlated with depression and all agitation sub-syndromes except hiding and hoarding. Conclusions: Dementia severity is a predictor for agitation and depression. Beyond that, depression increased with dementia severity, and the severity of depression was associated with both physically and verbally aggressive behaviors, indicating that, in advanced stages of dementia, depression in some patients might underlie aggressive behavior.
International Psychogeriatrics 05/2012; 24(11):1779-89. DOI:10.1017/S104161021200066X · 1.93 Impact Factor
Journal of the American Medical Directors Association 11/2011; 12(9):615-626.e6. DOI:10.1016/j.jamda.2011.08.007 · 4.94 Impact Factor
Available from: Eivind Aakhus
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ABSTRACT: The aims of the study were to examine the validity of the MADRS and to compare it with the validity of the Cornell Scale for Depression in Dementia (CSDD).
We included 140 patients without dementia, with mean age 81.5 (sd 7.7) years. Trained psychiatric nurses interviewed all of them using the MADRS. In addition, for 70 patients caregivers were interviewed using the CSDD. A psychiatrist who had no access to the MADRS or the CSDD results made a diagnosis of depression according to the DSM-IV criteria for major depression, and the ICD-10 criteria was also applied for the 70 patients assessed with the CSDD.
Twenty-two out of the 140 had depression according to the DSM IV criteria, whereas 25 out of 70 had depression according to the ICD-10 criteria. The area under the curve (auc) in a receiver operating characteristic analysis was 0.86 (95% CI 0.79-0.93) for the MADRS using the DSM-IV criteria. The best cut-off point was 16/17 with sensitivity of 0.80 and specificity of 0.82. The AUC for the CSDD was 0.83 (95% CI 0.71-0.95). The recommended cut-off score on the CSDD of 7/8 was valid but not the best in this study.
The patients were diagnosed with a diagnosis of depression by only one psychiatrist, and the procedures in the two centres were not exactly the same.
The MADRS has good discriminating power to detect depression in elderly persons and should be preferred to the CSDD for use with persons without dementia.
Journal of Affective Disorders 03/2012; 141(2-3):227-32. DOI:10.1016/j.jad.2012.02.042 · 3.38 Impact Factor
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