Evidence map›Paper›PMID 38477965›Full record

ArticleJMIR formative research2024

User-Friendly Chatbot to Mitigate the Psychological Stress of Older Adults During the COVID-19 Pandemic: Development and Usability Study.

Ya-Hsin Chou, Chemin Lin, Shwu-Hua Lee, Yen-Fen Lee, Li-Chen Cheng

Abstract read
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Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  5. A Walk With Grief: A Personal Narrative of Coping With the Death of a Same Sex Partner in Late Life.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2026
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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

5 authors.

Ya-Hsin ChouDepartment of Psychiatry, Taoyuan Chang Gung Memorial Hospital, Taoyuan County, Taiwan.ORCID https://orcid.org/0000-0002-7593-1438
Chemin LinDepartment of Psychiatry, Keelung Chang Gung Memorial Hospital, Keelung City, Taiwan.ORCID https://orcid.org/0000-0001-6889-4686
Shwu-Hua LeeCollege of Medicine, Chang Gung University, Taoyuan County, Taiwan.ORCID https://orcid.org/0000-0001-5606-1118
Yen-Fen LeeDepartment of Information and Finance Management, National Taipei University of Technology, Taipei, Taiwan.ORCID https://orcid.org/0000-0001-6128-6725
Li-Chen Cheng *Department of Information and Finance Management, National Taipei University of Technology, Taipei, Taiwan.ORCID https://orcid.org/0000-0001-8640-5049

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo safeguard the most vulnerable individuals during the COVID-19 pandemic, numerous governments enforced measures such as stay-at-home orders, social distancing, and self-isolation. These social restrictions had a particularly negative effect on older adults, as they are more vulnerable and experience increased loneliness, which has various adverse effects, including increasing the risk of mental health problems and mortality. Chatbots can potentially reduce loneliness and provide companionship during a pandemic. However, existing chatbots do not cater to the specific needs of older adult populations.

objectiveWe aimed to develop a user-friendly chatbot tailored to the specific needs of older adults with anxiety or depressive disorders during the COVID-19 pandemic and to examine their perspectives on mental health chatbot use. The primary research objective was to investigate whether chatbots can mitigate the psychological stress of older adults during COVID-19.

methodsParticipants were older adults belonging to two age groups (≥65 years and <65 years) from a psychiatric outpatient department who had been diagnosed with depressive or anxiety disorders by certified psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) criteria. The participants were required to use mobile phones, have internet access, and possess literacy skills. The chatbot's content includes monitoring and tracking health data and providing health information. Participants had access to the chatbot for at least 4 weeks. Self-report questionnaires for loneliness, depression, and anxiety were administered before and after chatbot use. The participants also rated their attitudes toward the chatbot.

resultsA total of 35 participants (mean age 65.21, SD 7.51 years) were enrolled in the trial, comprising 74% (n=26) female and 26% (n=9) male participants. The participants demonstrated a high utilization rate during the intervention, with over 82% engaging with the chatbot daily. Loneliness significantly improved in the older group ≥65 years. This group also responded positively to the chatbot, as evidenced by changes in University of California Los Angeles Loneliness Scale scores, suggesting that this demographic can derive benefits from chatbot interaction. Conversely, the younger group, <65 years, exhibited no significant changes in loneliness after the intervention. Both the older and younger age groups provided good scores in relation to chatbot design with respect to usability (mean scores of 6.33 and 6.05, respectively) and satisfaction (mean scores of 5.33 and 5.15, respectively), rated on a 7-point Likert scale.

conclusionsThe chatbot interface was found to be user-friendly and demonstrated promising results among participants 65 years and older who were receiving care at psychiatric outpatient clinics and experiencing relatively stable symptoms of depression and anxiety. The chatbot not only provided caring companionship but also showed the potential to alleviate loneliness during the challenging circumstances of a pandemic.

Indexed as

chatbotconversational agentdesigndevelopdevelopmentelderlygeriatricgeriatric psychiatrygeriatricsgerontologyhealth promotionlonelinesslonelymental healtholder adultspandemicpsychiatrytechnology-assisted interventionsuser experience

Identifiers

PMID38477965
PMCPMC10973967

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.