Non-pharmacological Approaches to Depressed Elderly With No or Mild Cognitive Impairment in Long-Term Care Facilities. A Systematic Review of the Literature
Bibliographic record
Abstract
Introduction: Compared to old people who live at home, depressive symptoms are more prevalent in those who live in long-term care facilities (LTCFs). Different kinds of non-pharmacological treatment approaches in LTCFs have been studied, including behavioral and cognitive-behavioral therapy, cognitive bibliotherapy, problem-solving therapy, brief psychodynamic therapy and life review/reminiscence. The aim of the current review was to systematically review non-pharmacological treatments used to treat depressed older adults with no or mild cognitive impairment (as described by a Mini Mental State Examination score > 20) living in LTCFs. Methods: A research was performed on PubMed and Scopus databases. Following the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) flowchart, studies selection was made. The quality of each Randomized Controlled Trial was scored using the Jadad scale, Quasi-Experimental Design studies and Non-Experimental studies were scored based on the Newcastle-Ottawa Scale (NOS) Results: The review included 56 full text articles; according to the type of intervention, studies were grouped in the following areas: horticulture/gardening ( n = 3), pet therapy ( n = 4), physical exercise ( n = 9), psychoeducation/rehabilitation ( n = 15), psychotherapy ( n = 3), reminiscence and story sharing ( n = 14), miscellaneous ( n = 8). Discussion and Conclusion: Despite mixed or negative findings in some cases, most studies included in this systematic review reported that the non-pharmacological interventions assessed were effective in the management of depressed elderly in the LTCFs context. Regrettably, the limitations and heterogeneity of the studies described above hinder the possibility to generalize and replicate results.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".