Abstract
BackgroundBarriers to assessing depression in advanced dementia include the presence of informant and patient recall biases. Ecological momentary assessment provides an improved approach for mood assessment by collecting observations in intervals throughout the day, decreasing recall bias, and increasing ecological validity.ObjectiveThis study aims to evaluate the feasibility, reliability, and validity of the modified 4-item Cornell Scale for Depression in Dementia for Momentary Assessment (mCSDD4-MA) tool to assess depression in patients with advanced dementia.MethodsA intensive longitudinal pilot study design was used. A total of 12 participants with advanced dementia were enrolled from an inpatient psychogeriatric unit. Participants were assessed using clinical depression assessments at admission and discharge. Research staff recorded observations four times a day for 6 weeks on phones with access to the mCSDD4-MA tool. Descriptive data related to feasibility were reported (ie, completion rates). Statistical models were used to examine the interrater reliability and construct and predictive validity of the data.ResultsOverall, 1923 observations were completed, representing 55.06% (1923/3496) of all rating opportunities with 2 raters and 66.01% (1923/2913) with at least one rater. Moderate interrater reliability was demonstrated for all items, except for lack of interest. Moderate correlations were observed between observers and patient-reported outcomes, where observers reported fewer symptoms relative to participants’ self-reports. Several items were associated with and able to predict depression.ConclusionsThe mCSDD4-MA tool was feasible to use, and most items in the tool showed moderate reliability and validity for assessing depression in dementia. Repeated and real-time depression assessment in advanced dementia holds promise for the identification of clinical depression and depressive symptoms.
Highlights
BackgroundDementia and DepressionDementia and depression are the most common psychiatric conditions in aging, and there is considerable overlap between them, with the prevalence of depression between 5% and 77% in people with dementia and between 7% and 54% in people at the advanced stage of dementia [1,2,3]
This wide range demonstrates the challenge in identifying depression in individuals with dementia, including individuals with advanced dementia, a group frequently excluded from studies [3]
Many clinical interviews and assessments for depression in dementia include both informant reports and self-reports, and informant reports can be affected by confounding depressive symptoms for symptoms of dementia, mood-congruent biases, and recall biases [6,7]
Summary
Dementia and depression are the most common psychiatric conditions in aging, and there is considerable overlap between them, with the prevalence of depression between 5% and 77% in people with dementia and between 7% and 54% in people at the advanced stage of dementia [1,2,3]. People with dementia and comorbid depression are at risk for negative outcomes, such as hastened cognitive decline and higher rates of morbidities and mortality [14,15] Detecting depression where it might otherwise be missed provides an opportunity for greatly enhanced patient care in this vulnerable population. EMA studies in older adults have demonstrated its feasibility, enhanced precision of outcome measurement, and the ability to identify clinically significant depressive symptoms, most studies exclude people with dementia and are typically self-reported [16,17,18]. EMA has been used to monitor daily life behaviors and well-being in people with dementia, and these studies have demonstrated the validity of informant ratings and the ability to capture individual differences over time [20,21,22,23]. No EMA depression screening tools have been developed for people with advanced dementia
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