Effectiveness of Telecare Interventions on Depression Symptoms Among Older Adults: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Depression is the most common psychiatric disorder among older adults. Despite the effectiveness of pharmacological and psychological therapies, many patients with late-life depression (LLD) are unable to access timely treatment. Telecare has been shown to be effective in addressing patients' psychosocial issues, while its effectiveness in serving patients with LLD remains unclear. OBJECTIVE: This study aimed to evaluate the effectiveness of telecare in reducing depression and anxiety symptoms and improving quality of life (QoL) in patients with LLD. METHODS: Databases including the Cochrane Library, Web of Science, PubMed, Embase, and EBSCO were searched for randomized controlled trials (RCTs) evaluating the effectiveness of telecare for LLD from database establishment to December 28, 2022. RESULTS: A total of 12 RCTs involving 1663 participants were identified in this study. The meta-analysis showed that (1) telecare significantly reduced depressive symptoms in patients with LLD compared to those in usual care (UC; standardized mean difference [SMD]=-0.46, 95% CI -0.53 to -0.38; P<.001), with the best improvement observed within 3 months of intervention (SMD=-0.72, 95% CI -1.16 to -0.28; P<.001); (2) other scales appeared more effective than the Patient Health Questionnaire-9 for LLD in telecare interventions (SMD=-0.65, 95% CI -0.96 to -0.35; P<.001); (3) telecare was more effective than telephone-based interventions for remote monitoring of LLD (SMD=-1.13, 95% CI -1.51 to -0.76; P<.001); (4) the reduction of depressive symptoms was more pronounced in patients with LLD with chronic conditions (SMD=-0.67, 95% CI -0.89 to -0.44; P<.001); (5) telecare was more effective for LLD in Europe and the Americas than in other regions (SMD=-0.73, 95% CI -0.99 to -0.47; P<.001); (6) telecare significantly reduced anxiety symptoms in patients with LLD (SMD=-0.53, 95% CI -0.73 to -0.33; P=.02); and (7) there was no significant improvement in the psychological components of QoL in patients with LLD compared to those receiving UC (SMD=0.30, 95% CI 0.18-0.43; P=.80). CONCLUSIONS: Telecare is a promising modality of care for treatment, which can alleviate depression and anxiety symptoms in patients with LLD. Continued in-depth research into the effectiveness of telecare in treating depression could better identify where older patients would benefit from this intervention.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".