Telepsychogeriatrics: a new horizon in the care of mental health problems in the elderly
Bibliographic record
Abstract
BACKGROUND: The use of telemedicine for the care of mental health problems has developed significantly over the last decade thanks to the emergence of a number of stable telepsychiatry programs in many countries. Parallel to this development, this care modality has also targeted specific populations with higher difficulty in gaining access to mental health services such as the elderly. Telepsychogeriatrics is expected to have an increasing role in providing care to geographically isolated rural communities, with a particular focus on long-term care facilities, in light of the high prevalence of psychiatric disorders in these centers and the lack of available specialized care. METHODS: A thorough search of the literature was conducted using Medline, Web of Science, and PsychINFO databases in order to gather available evidence on the applicability of telepsychiatry, specifically the use of videoconferencing for remote consultation, in the elderly population with mental disorders. A succinct description of the selected studies is given along with a general reflection on the state-of-the-art in the field of psychogeriatric clinical practice and research. RESULTS: Research on the use of telemedicine in this age group has taken into account their special characteristics, and has focused on demonstrating its applicability, the acceptance and satisfaction of elderly users and their healthcare providers, the possibility of carrying out cognitive and diagnostic assessments, and the efficiency of these programs. CONCLUSIONS: Despite limited experience, telepsychogeriatrics appears to be a viable option, well accepted by patients, including those having dementia. More systematized studies are needed in this new field based on larger sample sizes, including comparison with traditional consultations and assessment of the clinical outcomes.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".