Consequences of loneliness/isolation and visitation restrictions on the mood of long-term care residents without severe dementia pre-COVID-19 and during COVID-19: a scoping review
Bibliographic record
Abstract
BACKGROUND: Mental health disorders are common among residents of long-term care (LTC). Despite depression being the most common type of mental illness, it is often undiagnosed in LTC. Due to its prevalence, chronicity and associated morbidity, depression poses a considerable service use burden. The COVID-19 pandemic has brought needed attention to the mental health challenges faced by older adults in LTC. OBJECTIVES: To explore the effects of isolation on the mood of LTC residents and compare between both the pre-COVID-19 and COVID-19 periods. DESIGN: A scoping review. METHODS: PubMed, CINAHL, PsycINFO, SCOPUS, Google Scholar and medRxiv were searched for studies that met the eligibility criteria: (1) articles assessing mood or mental health status of LTC residents; (2) mood disturbance resulting from visitation restrictions/isolation or loneliness; (3) residents were without severe dementia or moderate/severe cognitive impairment and (4) studies were available in English. Studies were excluded if their entire sample was residents with severe cognitive impairment or severe dementia. A total of 31 studies were included in this review. The total number of articles retrieved from the databases searched was 3652 articles, of which 409 duplicates were removed. 3242 article titles and abstracts were screened for eligibility, of which 3063 were excluded. The remaining 180 full-text studies were reviewed for eligibility, where an additional 149 studies were excluded. Data were then extracted from all full-length pieces for analysis, and findings were summarised. RESULTS: The review identified contradictory views with a diversity of findings highlighting the complexity of factors influencing residents' mood during a global health crisis such as that of COVID-19. Studies highlighted the importance of quality interactions with others for the well-being of LTC residents. Significant correlations were found between social isolation, loneliness and depression. During COVID-19, visitation restrictions led to increased loneliness, depression and mood problems, especially among residents without cognitive impairment. However, some studies reported no significant adverse effects or even a decrease in depression symptoms during COVID-19 restrictions, possibly due to implemented strategies to maintain social engagement. CONCLUSION: The COVID-19 pandemic had a substantial impact on LTC homes, influencing the physical and mental well-being of residents. This highlighted pre-existing challenges in the LTC system, emphasising the importance of comprehensive strategies to safeguard resident mental health. It is important to combine measures to ensure both physical safety and mental well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".