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DEPRESSIVE SYMPTOMS IN OLDER PEOPLE PREDICT NURSING HOME ADMISSION

2006· letter· en· W1983952152 on OpenAlexaffabout
Philip D. St. John, Patrick R. Montgomery

Bibliographic record

VenueJournal of the American Geriatrics Society · 2006
Typeletter
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineActivities of daily livingGerontologyGeriatric Depression ScaleGeriatricsDepression (economics)Mental healthConfoundingMini–Mental State ExaminationIndependent livingCohortPopulationNursing homesCohort studyAging in placeDepressive symptomsCognitionCognitive impairmentPsychiatryEnvironmental healthNursing

Abstract

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To the Editor: In a recent article in the Journal of the American Geriatrics Society, Harris and Copper1 showed that depressive symptoms predict admission to a nursing home (NH). The study had numerous strengths, but there were some limitations. The measure of depressive symptoms was crude, and potential confounding variables such as cognition, social support, and functional status were incompletely measured. Furthermore, this association may be different in other health and social systems, as well as in different uses of NHs in other countries than in the United States. We would like to add information to this topic by presenting data from a population-based study in the Canadian province of Manitoba. The Manitoba Study of Health and Aging (MSHA) is a cohort study conducted in conjunction with the Canadian Study of Health and Aging.2 In 1991/92, 1,751 community-dwelling persons aged 65 and older were interviewed in their homes. Age, sex, education, living arrangement, and the number of persons providing support were all self-reported. Measures included the Center for Epidemiologic Studies Depression Scale (CES-D),3 the Mini-Mental State Examination (MMSE),4 and the Older Americans Resources and Services;5 activities of daily living (ADLs) and instrumental activities of daily living (IADLs) were considered impaired if a participant required assistance or used an assistive device for any ADL or IADL. The CES-D was dichotomized, with a score greater than 15 indicating depression. To investigate gradient versus threshold effects, the CES-D was also divided into categories of 0 to 5, 6 to 10, 11 to 15, and greater than 15. NH admission was determined at the time of follow-up, in 1996/97. Six persons had missing data for NH admission. The process of entering a NH requires review by a panel for eligibility and is registered in a central database. NHs in Manitoba are not used for convalescence or rehabilitation, and temporary admission is highly unusual. Bivariate analyses were conducted using Student t tests for continuous variables and chi-square tests for categorical variables. Logistic regression models were constructed with NH admission over 5 years as the outcome. SPSS version 13 (SPSS Inc., Chicago, IL) was used. There were 1,745 persons interviewed at time 1 with data available on institutionalization; 211 were admitted to a NH over the 5-year interval. The average age was 76.2, 58.5% were female, the mean educational level was 9.3 years, 42.3% lived alone, the median number of persons providing help was 3, 17.0% had an MMSE score of less than 24, 19.9% had impairments in one or more ADLs, 39.3% had impairments in one or more IADLs, and 13.9% had depressive symptoms. Depressive symptoms predicted NH admission; 19.4% of those with depressive symptoms were institutionalized, versus 10.9% of those without (P<.001, chi-square test). The association between CES-D score and NH admission was present in those with and without cognitive impairment. There was a gradient effect in the association between CES-D score and NH admission (Figure 1). In logistic regression models adjusted for age, sex, education, living arrangement, and social support, depressive symptoms predicted NH admission; the adjusted odds ratio (AOR) for NH admission was 1.57 (95% confidence interval (CI)=1.05–2.35). When the MMSE was added into this model, the AOR was 1.52 (95% CI=1.01–2.28). When ADLs and IADLs were considered as well, depressive symptoms no longer predicted NH admission, with an AOR of 1.19 (95% CI=0.78–1.80). Depressive symptoms predicted admission to a nursing home over a 5-year period. This effect is seen in those with and without cognitive impairment. There is a gradient in this association, extending into the normal range of the Center for Epidemiologic Studies Depression Scale (CES-D) score (range 0–60). MMSE=Mini-Mental State Examination (range 0–30, with >23 considered normal). In this sample, depressive symptoms predicted NH admission, but when functional impairment was considered, this association was no longer apparent. This adds information to Harris and Cooper's article.1 The MSHA used the CES-D, a reliable, valid measure of depressive symptoms, which also allows the exploration of gradient effects. In addition, there were data on potential confounders such as cognitive status, functional status, and social support. Furthermore, it is important to note that the association between depressive symptoms and institutionalization is present in a different healthcare system. There are also some limitations to our analysis; a crude measure of social support was used, and the CES-D is not a measure of major depression, which requires a clinical examination. It is possible that functional status acts as a confounding variable, with functionally impaired persons experiencing depressive symptoms before NH admission, but it is also possible that functional impairment is a mediating factor. Depression has been shown to predict functional decline,6 which may in turn lead to NH admission. Whether the effect is causal or not, the observation that depressive symptoms predict NH admission is important for clinicians and policy-makers, and older adults with depressive symptoms should be assessed and monitored. Financial Disclosure: The MSHA was funded primarily by Manitoba Health, with additional funding provided through the Canadian Study of Health and Aging by the Seniors Independence Research Program of the National Health Research and Development Program of Canada (Project no. 6606–3954-MC(S)).The MSHA-2 was funded primarily by Manitoba Health's Health Communities Development Fund with additional funding provided through the Canadian Study of Health and Aging by the Seniors Independence Research Program of the National Health Research and Development Program of Health Canada (Project no. 6606–3954-MC(S)). The results and conclusions are those of the authors, and no official endorsement by Manitoba Health or other funding agencies is intended or should be inferred. Author Contributions: Philip St. John examined participants; gathered data for and was involved with the original data collection for this study; contributed to the concept, interpretation, and manuscript preparation; and analyzed the data. Patrick Montgomery examined participants; gathered data for and was involved with the original data collection for this study; and contributed to the concept, interpretation, and manuscript preparation. Sponsor's Role: The sponsors had no role in the design, methods, subject recruitment, data collection, or analysis of preparation of this study. The results and conclusions are those of the authors, and no official endorsement by Manitoba Health or other funding agencies is intended or should be inferred.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.261
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations11
Published2006
Admission routes2
Has abstractyes

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