Evidence map›Paper›PMID 36514493›Full record

ReviewNeuropsychiatric disease and treatment2022

Recognizing Depression in the Elderly: Practical Guidance and Challenges for Clinical Management.

Maria Devita, Rossella De Salvo, Adele Ravelli, Marina De Rui, Alessandra Coin, Giuseppe Sergi, Daniela Mapelli

Abstract readReview
In one paragraph

Review in Neuropsychiatric disease and treatment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  8. Definition of treatment-resistant late-life depression: Conclusions from a European Task Force Delphi process.European psychiatry : the journal of the Association of European Psychiatrists · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Maria DevitaDepartment of General Psychology (DPG), University of Padua, Padua, Italy.ORCID 0000-0001-5899-8000
Rossella De SalvoDepartment of General Psychology (DPG), University of Padua, Padua, Italy.ORCID 0000-0002-1686-9056
Adele RavelliGeriatrics Division, Department of Medicine (DIMED), University of Padua, Padua, Italy.
Marina De RuiGeriatrics Division, Department of Medicine (DIMED), University of Padua, Padua, Italy.
Alessandra CoinGeriatrics Division, Department of Medicine (DIMED), University of Padua, Padua, Italy.
Giuseppe SergiGeriatrics Division, Department of Medicine (DIMED), University of Padua, Padua, Italy.
Daniela MapelliDepartment of General Psychology (DPG), University of Padua, Padua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Depression is one of the most common mood disorders in the late-life population and is associated with poor quality of life and increased morbidity, disability and mortality. Nevertheless, in older adults, it often remains undetected and untreated. This narrative review aims at giving an overview on the main definitions, clinical manifestations, risk and protective factors for depression in the elderly, and at discussing the main reasons for its under/misdiagnosis, such as cognitive decline and their overlapping symptomatology. A practical approach for the global and multidisciplinary care of the older adult with depression, derived from cross-checking evidence emerging from the literature with everyday clinical experience, is thus provided, as a short and flexible "pocket" guide to orient clinicians in recognizing, diagnosing and treating depression in the elderly.

Indexed as

geriatric depressionlate-life depressionmood disordersolder adults

Identifiers

PMID36514493
PMCPMC9741828

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.