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Record W4412461043 · doi:10.21037/mhealth-24-72

Transforming daily support with multidisciplinary teleassistance: impact on health parameters in older adults—a randomized controlled trial

2025· article· en· W4412461043 on OpenAlexaboutno aff
Andressa Crystine da Silva Sobrinho, Guilherme da Silva Rodrigues, Karine Pereira Rodrigues, Larissa Chacon Finzeto, Laura Thais Del Vecchio Sampaio, João Paulo Freitas, João Gabriel Ribeiro de Lima, Grace Angélica de Oliveira Gomes, Carlos Roberto Bueno Júnior

Bibliographic record

VenuemHealth · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialMultidisciplinary approachPhysical therapyMedicineGerontologyPhysical medicine and rehabilitationPsychologySociologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Home care and teleassistance emerge as effective, patient-centered approaches to meet the healthcare needs of older adults, enabling them to remain in familiar environments while receiving personalized care. Despite technological advancements driving teleassistance, the success of these interventions hinges on the acceptance and adherence of older person and their caregivers. This study explores the impact of teleassistance on older adults' health, focusing on daily and simple care, through a randomized clinical trial. Methods: Individuals aged 60 years or older were recruited and divided into two groups: the application group (APPG, n=21) and the control group (CG, n=19). Various anthropometric, motor, clinical, and biochemical measures were utilized for participant assessments. Throughout the 14-week experimental period, participants utilized the "Viva" application, receiving teleassistance and educational resources. Personalized support was provided to address any difficulties. Results: The study demonstrated that the "Viva" application had significant positive impacts on the health and well-being of older adult participants. Specifically, the APPG showed no-table improvements in flexibility [sit and reach (S&R): +5.1 cm, P<0.001], lower limb strength [sit and stand test (S&ST): +5.2 reps, P<0.001], and walking performance [6-minute walk test (6MWT): +41.3 m, P<0.001], compared to the CG. Additionally, the APPG exhibited enhanced overall health (P<0.001), cognitive function [Montreal Cognitive Assessment (MoCA): +4.7 points, P<0.001], and significant reductions in total cholesterol levels (-25 mg/dL, P<0.05). These findings were complemented by improvements in healthy food consumption patterns, reduced daytime sleepiness, and greater health literacy, further emphasizing the application's role in promoting healthy aging and improved quality of life. With technological advances and expanding internet access, telecare has the potential. Conclusions: With technological advances and expanding internet access, telecare has the potential to revolutionize care for older adults by enabling them to safely and autonomously remain at home while receiving personalized support. This study demonstrated significant improvements in health outcomes, including reduced sedentary time, enhanced physical activity, better sleep quality, lower cholesterol levels, improved cognitive function, and healthier dietary habits in the teleassisted group. These results highlight teleassistance as an essential strategy for promoting healthy and active aging, reducing the risk of chronic diseases, and improving the overall quality of life for older adults. Trial Registration: This study is registered in the Brazilian Clinical Trials Registry (RBR-6wgkzs8).

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.011
GPT teacher head0.342
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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