Evidence map›Paper›PMID 36149730›Full record

ArticleJMIR mental health2022

Assessing the Impact of Conversational Artificial Intelligence in the Treatment of Stress and Anxiety in Aging Adults: Randomized Controlled Trial.

Morena Danieli, Tommaso Ciulli, Seyed Mahed Mousavi, Giorgia Silvestri, Simone Barbato, Lorenzo Di Natale, Giuseppe Riccardi

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04809090 (CO-ADAPT), which is not on this map. Cited by 35 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 7 pooled it
9.8field-weighted citation impact, top 1% 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.

NCT04809090 nacompletednot on this map

CO-ADAPT: Adaptive Environments and Conversational Agent Based Approaches for Healthy Ageing and Work Ability

TypeinterventionalSponsorTommaso CiulliRan2021 to 2022Enrolled60ConditionsWork Related Stress, Psychologic AdaptationArmsSMT, App CA
3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 7 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

7 authors at 1 institution in 1 country.

Morena DanieliSignal & Interactive Systems Lab, Dipartimento di Ingegneria e Scienze dell'Informazione, Università degli Studi di Trento, Povo di Trento - Trento, Italy.ORCID https://orcid.org/0000-0001-7888-5935
Tommaso CiulliIDEGO - Digital Psychology srl, Rome, Italy.ORCID https://orcid.org/0000-0002-0828-164X
Seyed Mahed MousaviSignal & Interactive Systems Lab, Dipartimento di Ingegneria e Scienze dell'Informazione, Università degli Studi di Trento, Povo di Trento - Trento, Italy.ORCID https://orcid.org/0000-0002-7790-7730
Giorgia SilvestriIDEGO - Digital Psychology srl, Rome, Italy.ORCID https://orcid.org/0000-0003-3336-1745
Simone BarbatoIDEGO - Digital Psychology srl, Rome, Italy.ORCID https://orcid.org/0000-0002-4430-7632
Lorenzo Di NataleIDEGO - Digital Psychology srl, Rome, Italy.ORCID https://orcid.org/0000-0001-6413-7637
Giuseppe RiccardiSignal & Interactive Systems Lab, Dipartimento di Ingegneria e Scienze dell'Informazione, Università degli Studi di Trento, Povo di Trento - Trento, Italy.ORCID https://orcid.org/0000-0002-0739-8184
University of Trento · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhile mental health applications are increasingly becoming available for large populations of users, there is a lack of controlled trials on the impacts of such applications. Artificial intelligence (AI)-empowered agents have been evaluated when assisting adults with cognitive impairments; however, few applications are available for aging adults who are still actively working. These adults often have high stress levels related to changes in their work places, and related symptoms eventually affect their quality of life.

objectiveWe aimed to evaluate the contribution of TEO (Therapy Empowerment Opportunity), a mobile personal health care agent with conversational AI. TEO promotes mental health and well-being by engaging patients in conversations to recollect the details of events that increased their anxiety and by providing therapeutic exercises and suggestions.

methodsThe study was based on a protocolized intervention for stress and anxiety management. Participants with stress symptoms and mild-to-moderate anxiety received an 8-week cognitive behavioral therapy (CBT) intervention delivered remotely. A group of participants also interacted with the agent TEO. The participants were active workers aged over 55 years. The experimental groups were as follows: group 1, traditional therapy; group 2, traditional therapy and mobile health (mHealth) agent; group 3, mHealth agent; and group 4, no treatment (assigned to a waiting list). Symptoms related to stress (anxiety, physical disease, and depression) were assessed prior to treatment (T1), at the end (T2), and 3 months after treatment (T3), using standardized psychological questionnaires. Moreover, the Patient Health Questionnaire-8 and General Anxiety Disorders-7 scales were administered before the intervention (T1), at mid-term (T2), at the end of the intervention (T3), and after 3 months (T4). At the end of the intervention, participants in groups 1, 2, and 3 filled in a satisfaction questionnaire.

resultsDespite randomization, statistically significant differences between groups were present at T1. Group 4 showed lower levels of anxiety and depression compared with group 1, and lower levels of stress compared with group 2. Comparisons between groups at T2 and T3 did not show significant differences in outcomes. Analyses conducted within groups showed significant differences between times in group 2, with greater improvements in the levels of stress and scores related to overall well-being. A general worsening trend between T2 and T3 was detected in all groups, with a significant increase in stress levels in group 2. Group 2 reported higher levels of perceived usefulness and satisfaction.

conclusionsNo statistically significant differences could be observed between participants who used the mHealth app alone or within the traditional CBT setting. However, the results indicated significant differences within the groups that received treatment and a stable tendency toward improvement, which was limited to individual perceptions of stress-related symptoms.

trial registrationClinicalTrials.gov NCT04809090; https://clinicaltrials.gov/ct2/show/NCT04809090.

Indexed as

conversational artificial intelligencemental health caremHealthmobile healthpersonal health care agent

Identifiers

PMID36149730
PMCPMC9547337
OpenAlexW4286776471

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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 Socratic graph.