Evidence map›Paper›PMID 36923686›Full record

ArticleHealth information science and systems2023

Towards data-driven tele-medicine intelligence: community-based mental healthcare paradigm shift for smart aging amid COVID-19 pandemic.

Lan Cheng, W K Chan, Yi Peng, Harry Qin

Open access · bronzeAbstract read
In one paragraph

Article in Health information science and systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 2 countries.

Lan ChengBig Data Bio-Intelligence Lab, Big Data Institute, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong.ORCID 0000-0001-6931-4508
W K ChanDepartment of Computer Science and Engineering, Chinese University of Hong Kong, Sha Tin, Hong Kong.
Yi PengSchool of Government, Nanjing University, Nanjing, China.
Harry QinFaculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Chinese University of Hong Kong · HKGovernment of Jiangsu Province · CNHong Kong Polytechnic University · HKHong Kong University of Science and Technology · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Telemedicine are experiencing an unprecedented boom globally since the beginning of the COVID-19 pandemic. As the most vulnerable groups amid COVID-19, the digital delivery of healthcare poses great challenges to the elderly population, caregiver, health service providers, and health policy makers. To bridge the service delivery gaps between the telemedicine demand side and supply side, explore evidence-based approach for integrated care, address challenges for aging policy, and build foundation for the development of data-driven and community-based telemedicine, our R&D team applied translational research to design and develop telemedicine "SMART" for enhancing elderly mental health wellbeing amid COVID-19. Our aim is to investigate the preparedness mechanisms of mental health disease including response, intervention, and connection these three healthcare delivery pipelines with the collection, consolidation, and synergy of heath parameters and social determinants, using data analytics approach to achieve Evidence-Based Medicine (EBM). Methods: A mix of quantitative and qualitative research design for scientifically rigorous consultation and analysis was conducted from Jan 2020 to June 2021 in Hong Kong. An exploratory and descriptive qualitative design was used in this study. The data were collected through focus group discussions conducted from elderly and their caregivers living in 10 main districts of Hong Kong. Our research pilot tested "SMART" targeting for elderly with mental health improvement needs. Baseline questionnaire with 110 tele-medicine product users includes questions on demographic information, self-rated mental health digital adoption. The follow-up five focus group discussions with 57 users (elderly and their caregivers) further explore the social determinants of telemedicine transformation and help propose the integrated telemedicine paradigm shift framework establishment, development, and enhancement. Results: Grounded on the baseline needs assessment and feedbacks collected, it is evident that multi-dimensional health information from the four various streams (community, clinic, home, remote) and customized digital health solutions are playing a key role in addressing elderly mental health digital service needs and bridging digital divide. The designed tele-medicine product lines up health service provider (supplier side) and elderly specific needs (demand side) with our three-level design, enables elderly and their families to follow and control their own health management and connect with the service provider, community of practice (CoP), and health policy makers. Conclusion: It's beneficial to involve elderly and gerontechnology stakeholders as part of Community-Based Participatory Research (CBPR) before and throughout the developing and delivery phases an integrated and age-friendly digital intervention. The challenges in applying and disseminating telemedicine reflected by the elderly and caregivers can be used as important input for further development and indicators for the sustainable and integrated elderly primary care framework. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-022-00198-4.

Indexed as

COVID-19 pandemicDigital divideElderly mental healthTelemedicine

Identifiers

PMID36923686
PMCPMC10011761
OpenAlexW4327682141

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.