Evidence map›Paper›PMID 37974630›Full record

ArticleIEEE sensors journal2021

Potential Applications of Mobile and Wearable Devices for Psychological Support During the COVID-19 Pandemic: A Review.

Kawisara Ueafuea, Chiraphat Boonnag, Thapanun Sudhawiyangkul, Pitshaporn Leelaarporn, Ameen Gulistan, Wei Chen, Subhas Chandra Mukhopadhyay, Theerawit Wilaiprasitporn, Supanida Piyayotai

Open access · greenAbstract read
In one paragraph

Article in IEEE sensors journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
4.8field-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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 71 citations in OpenAlex.

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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

9 authors at 5 institutions in 3 countries.

Kawisara UeafueaBio-Inspired Robotics and Neural Engineering (BRAIN) Lab, School of Information Science and Technology (IST)Vidyasirimedhi Institute of Science & Technology (VISTEC) Rayong 21210 Thailand.
Chiraphat BoonnagFaculty of MedicineChiang Mai University Chiang Mai 50200 Thailand.ORCID https://orcid.org/0000-0001-5429-9659
Thapanun SudhawiyangkulBio-Inspired Robotics and Neural Engineering (BRAIN) Lab, School of Information Science and Technology (IST)Vidyasirimedhi Institute of Science & Technology (VISTEC) Rayong 21210 Thailand.ORCID https://orcid.org/0000-0003-2486-9280
Pitshaporn LeelaarpornBio-Inspired Robotics and Neural Engineering (BRAIN) Lab, School of Information Science and Technology (IST)Vidyasirimedhi Institute of Science & Technology (VISTEC) Rayong 21210 Thailand.ORCID https://orcid.org/0000-0001-8755-875X
Ameen GulistanBio-Inspired Robotics and Neural Engineering (BRAIN) Lab, School of Information Science and Technology (IST)Vidyasirimedhi Institute of Science & Technology (VISTEC) Rayong 21210 Thailand.
Wei ChenCenter for Intelligent Medical Electronics, School of Information Science and TechnologyFudan University Shanghai 200433 China.ORCID https://orcid.org/0000-0003-3720-718X
Subhas Chandra MukhopadhyaySchool of EngineeringMacquarie University Sydney NSW 2109 Australia.ORCID https://orcid.org/0000-0002-8600-5907
Theerawit WilaiprasitpornBio-Inspired Robotics and Neural Engineering (BRAIN) Lab, School of Information Science and Technology (IST)Vidyasirimedhi Institute of Science & Technology (VISTEC) Rayong 21210 Thailand.ORCID https://orcid.org/0000-0003-4941-4354
Supanida PiyayotaiLearning Institute, King Mongkut's University of Technology Thonburi Bangkok 10140 Thailand.ORCID https://orcid.org/0000-0003-0630-7380
Vidyasirimedhi Institute of Science and Technology · THChiang Mai University · THKing Mongkut's University of Technology Thonburi · THMacquarie University · AUUniversity of Shanghai for Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 19 (COVID-19) pandemic that has been raging in 2020 does affect not only the physical state but also the mental health of the general population, particularly, that of the healthcare workers. Given the unprecedented large-scale impacts of the COVID-19 pandemic, digital technology has gained momentum as invaluable social interaction and health tracking tools in this time of great turmoil, in part due to the imposed state-wide mobilization limitations to mitigate the risk of infection that might arise from in-person socialization or hospitalization. Over the last five years, there has been a notable increase in the demand and usage of mobile and wearable devices as well as their adoption in studies of mental fitness. The purposes of this scoping review are to summarize evidence on the sweeping impact of COVID-19 on mental health as well as to evaluate the merits of the devices for remote psychological support. We conclude that the COVID-19 pandemic has inflicted a significant toll on the mental health of the population, leading to an upsurge in reports of pathological stress, depression, anxiety, and insomnia. It is also clear that mobile and wearable devices (e.g., smartwatches and fitness trackers) are well placed for identifying and targeting individuals with these psychological burdens in need of intervention. However, we found that most of the previous studies used research-grade wearable devices that are difficult to afford for the normal consumer due to their high cost. Thus, the possibility of replacing the research-grade wearable devices with the current smartwatch is also discussed.

Indexed as

COVID-19Mental healthsmartphonesSmartwatcheswearable devices

Identifiers

PMID37974630
PMCPMC8768987
OpenAlexW3116998974

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.