Social Mediators of the Association Between Depression and Falls Among Older Adults

Lohman, Matthew C.; Fallahi, Afsaneh; Bawa, Eric Mishio; Wei, Jingkai; Merchant, Anwar T.

doi:10.1177/08982643231152276

Cited by 7 publications

(2 citation statements)

References 70 publications

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“…The interaction between depression and falls may also be self-perpetuating. Depressive symptoms are particularly high among recurrent fallers, which may be related to the demoralizing effect of repeated falling [42]. Prospective cohort studies have reported that increased depressive symptoms were associated with increased falls [43].…”

Section: Overviewmentioning

confidence: 99%

Relationship Between Depression and Falls Among Nursing Home Residents: Protocol for an Integrative Review

Matos Queirós,

von Gunten,

Rosselet Amoussou

et al. 2023

JMIR Res Protoc

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Background Aging exposes individuals to new health disorders and debilitating chronic diseases, yet most older adults, even in functional decline, do not want to leave their homes. Nevertheless, for many, institutionalization in a nursing home (NH) may become essential to ensure their continued safety and health. Depression is one of the most common psychiatric disorders among older adults, especially among those who are institutionalized. Depressed NH residents face a high risk of future functional decline and falls, decreasing their quality of life. The relationship between depression and falls is complex and bidirectional. Previous reviews have focused on home-dwelling older adults or explored the relationship between antidepressant drugs and falls. To the best of our knowledge, no integrative literature reviews have explored the relationship between depression and falls among NH residents. Objective Analyze studies on the relationship between depression and falls among NH residents. Methods We will conduct an integrative literature review of published articles in relevant scientific journals on the relationship between depression and depressive symptomatology and falls among NH residents. As usually defined, we will consider NH residents to be people aged 65 years and older who can no longer live safely and independently in their homes. We will also consider older adults on short-term stays in an NH for rehabilitation after hospital discharge. Retrieved articles will be screened for eligibility and analyzed following previously reported steps. The most pertinent bibliographical databases will be examined for qualitative, quantitative, and mixed methods studies, from inception until August 31, 2023, thus ensuring that all relevant literature is included. We will also hand-search the bibliographies of all the relevant articles found and search for unpublished studies in any language. If appropriate, we will consider conducting a meta-analysis of the studies retrieved. Results A first round of data collection was completed in March 2023. We retrieved a total of 2276 references. A supplementary literature search to ensure the most up-to-date evidence is ongoing. We anticipate that the review will be completed in late September 2023, and we expect to publish results at the end of December 2023. Conclusions This integrative review will increase knowledge and understanding of the complex relationship between depression and falls in NH environments. Its findings will be important for developing integrated, multidisciplinary models and care recommendations, adaptable to each NH resident’s situation and health status, and for creating preventive interventions to help them maintain or recover optimal health stability. International Registered Report Identifier (IRRID) DERR1-10.2196/46995

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Section: Overviewmentioning

confidence: 99%

Relationship Between Depression and Falls Among Nursing Home Residents: Protocol for an Integrative Review

Matos Queirós,

von Gunten,

Rosselet Amoussou

et al. 2023

JMIR Res Protoc

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“…Psychologically, falls among the older adult population tend to result in self-imposed limitations due to the fear of falling again [ 10 , 12 ]. These limitations lead to social isolation as individuals avoid participating in activities or even individual mobility [ 13 ]. Consequently, falls can lead to psychological conditions such as anxiety and depression [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review

González-Castro,

Leirós-Rodríguez,

Prada-García

et al. 2024

J Med Internet Res

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Background Falls and their consequences are a serious public health problem worldwide. Each year, 37.3 million falls requiring medical attention occur. Therefore, the analysis of fall risk is of great importance for prevention. Artificial intelligence (AI) represents an innovative tool for creating predictive statistical models of fall risk through data analysis. Objective The aim of this review was to analyze the available evidence on the applications of AI in the analysis of data related to postural control and fall risk. Methods A literature search was conducted in 6 databases with the following inclusion criteria: the articles had to be published within the last 5 years (from 2018 to 2024), they had to apply some method of AI, AI analyses had to be applied to data from samples consisting of humans, and the analyzed sample had to consist of individuals with independent walking with or without the assistance of external orthopedic devices. Results We obtained a total of 3858 articles, of which 22 were finally selected. Data extraction for subsequent analysis varied in the different studies: 82% (18/22) of them extracted data through tests or functional assessments, and the remaining 18% (4/22) of them extracted through existing medical records. Different AI techniques were used throughout the articles. All the research included in the review obtained accuracy values of >70% in the predictive models obtained through AI. Conclusions The use of AI proves to be a valuable tool for creating predictive models of fall risk. The use of this tool could have a significant socioeconomic impact as it enables the development of low-cost predictive models with a high level of accuracy. Trial Registration PROSPERO CRD42023443277; https://tinyurl.com/4sb72ssv

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The moderating role of psychological resilience in the relationship between falls, anxiety and depressive symptoms

Wang

et al. 2023

Journal of Affective Disorders

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Social Mediators of the Association Between Depression and Falls Among Older Adults

Cited by 7 publications

References 70 publications

Relationship Between Depression and Falls Among Nursing Home Residents: Protocol for an Integrative Review

Relationship Between Depression and Falls Among Nursing Home Residents: Protocol for an Integrative Review

The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review

The moderating role of psychological resilience in the relationship between falls, anxiety and depressive symptoms

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