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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMH</journal-id>
      <journal-id journal-id-type="nlm-ta">JMIR Ment Health</journal-id>
      <journal-title>JMIR Mental Health</journal-title>
      <issn pub-type="epub">2368-7959</issn>
      <publisher>
        <publisher-name>JMIR Publications</publisher-name>
        <publisher-loc>Toronto, Canada</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">v12i1e77098</article-id>
      <article-id pub-id-type="pmid">41202292</article-id>
      <article-id pub-id-type="doi">10.2196/77098</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Review</subject>
        </subj-group>
        <subj-group subj-group-type="article-type">
          <subject>Review</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Digital Conversational Agents for the Mental Health of Treatment-Seeking Youth: Scoping Review</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="editor">
          <name>
            <surname>Torous</surname>
            <given-names>John</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Jiang</surname>
            <given-names>Xu</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Hawke</surname>
            <given-names>Lisa D</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <address>
            <institution/>
            <institution>Centre for Addiction and Mental Health</institution>
            <addr-line>60 White Squirrel Way</addr-line>
            <addr-line>Toronto, M6J 1H4</addr-line>
            <country>Canada</country>
            <phone>1 416 535 8501</phone>
            <email>lisa.hawke@camh.ca</email>
          </address>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-1108-9453</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author">
          <name name-style="western">
            <surname>Hou</surname>
            <given-names>Jingyi</given-names>
          </name>
          <degrees>MEd</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-9028-6898</ext-link>
        </contrib>
        <contrib id="contrib3" contrib-type="author">
          <name name-style="western">
            <surname>Nguyen</surname>
            <given-names>Anh T P</given-names>
          </name>
          <degrees>BA</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-8053-4875</ext-link>
        </contrib>
        <contrib id="contrib4" contrib-type="author">
          <name name-style="western">
            <surname>Phi</surname>
            <given-names>Thalia</given-names>
          </name>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0009-0006-3791-406X</ext-link>
        </contrib>
        <contrib id="contrib5" contrib-type="author">
          <name name-style="western">
            <surname>Gibson</surname>
            <given-names>Jamie</given-names>
          </name>
          <degrees>BA</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0009-0004-5165-3869</ext-link>
        </contrib>
        <contrib id="contrib6" contrib-type="author">
          <name name-style="western">
            <surname>Ritchie</surname>
            <given-names>Brian</given-names>
          </name>
          <degrees>MBA</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0009-0000-7147-9934</ext-link>
        </contrib>
        <contrib id="contrib7" contrib-type="author">
          <name name-style="western">
            <surname>Strudwick</surname>
            <given-names>Gillian</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-1080-7372</ext-link>
        </contrib>
        <contrib id="contrib8" contrib-type="author">
          <name name-style="western">
            <surname>Rodak</surname>
            <given-names>Terri</given-names>
          </name>
          <degrees>MA, MISt</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-0584-1429</ext-link>
        </contrib>
        <contrib id="contrib9" contrib-type="author">
          <name name-style="western">
            <surname>Gallagher</surname>
            <given-names>Louise</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-9462-2836</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>Centre for Addiction and Mental Health</institution>
        <addr-line>Toronto</addr-line>
        <country>Canada</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>Kama.AI</institution>
        <addr-line>Toronto, ON</addr-line>
        <country>Canada</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Lisa D Hawke <email>lisa.hawke@camh.ca</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>7</day>
        <month>11</month>
        <year>2025</year>
      </pub-date>
      <volume>12</volume>
      <elocation-id>e77098</elocation-id>
      <history>
        <date date-type="received">
          <day>7</day>
          <month>5</month>
          <year>2025</year>
        </date>
        <date date-type="rev-request">
          <day>26</day>
          <month>8</month>
          <year>2025</year>
        </date>
        <date date-type="rev-recd">
          <day>28</day>
          <month>8</month>
          <year>2025</year>
        </date>
        <date date-type="accepted">
          <day>29</day>
          <month>8</month>
          <year>2025</year>
        </date>
      </history>
      <copyright-statement>©Lisa D Hawke, Jingyi Hou, Anh T P Nguyen, Thalia Phi, Jamie Gibson, Brian Ritchie, Gillian Strudwick, Terri Rodak, Louise Gallagher. Originally published in JMIR Mental Health (https://mental.jmir.org), 07.11.2025.</copyright-statement>
      <copyright-year>2025</copyright-year>
      <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
        <p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="https://mental.jmir.org/2025/1/e77098" xlink:type="simple"/>
      <abstract>
        <sec sec-type="background">
          <title>Background</title>
          <p>Digital conversational agents (or “chatbots”) that can generate human-like conversations have recently been adapted as a means of administering mental health interventions. However, their development for youth seeking mental health services requires further investigation.</p>
        </sec>
        <sec sec-type="objective">
          <title>Objective</title>
          <p>This youth-engaged scoping review synthesizes the recent research on digital conversational agents for youth seeking mental health or substance use services.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>Studies were included if they were published between 2016 and 2025 and examined digital conversational agents for youth aged 11 to 24 years with mental health or substance use challenges in clinical settings. Systematic literature searches were conducted in February 2024 in multiple databases and updated in March 2025. Data were extracted using codeveloped forms and synthesized narratively.</p>
        </sec>
        <sec sec-type="results">
          <title>Results</title>
          <p>Ten studies were included, all focusing on mental health. Seven examined the acceptability and feasibility of digital conversational agents; others explored youth perceptions of use, design, and content, with some exploration of impact on mental health symptoms. Eight of ten studies reported high acceptability or positive user experiences. Three were randomized controlled trials that found potential reductions in depressive symptoms. Reporting on the ethical standards was limited. No studies focused on substance use alone.</p>
        </sec>
        <sec sec-type="conclusions">
          <title>Conclusions</title>
          <p>Literature on digital conversational agents for treatment-seeking youth is emerging but limited. Future rigorous research is needed that prioritizes data security, safety measures, and youth co-design in the development of safe, engaging, digital conversational agents for youth with mental health conditions.</p>
        </sec>
      </abstract>
      <kwd-group>
        <kwd>chatbot</kwd>
        <kwd>artificial intelligence</kwd>
        <kwd>youth</kwd>
        <kwd>mental health</kwd>
        <kwd>substance use</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="introduction">
      <title>Introduction</title>
      <sec>
        <title>Background</title>
        <p>Digital conversational agents, or “chatbots,” are tools that can simulate a human interaction in text format, using artificial intelligence to respond intelligently to user inputs. They may use human-generated algorithms to produce conversations, or natural language processing to recognize and respond to inputs with a programmed personality. Digital conversational agents have been used in mental health for tasks such as providing psychoeducation, building coping skills, delivering cognitive-behavioral therapy, and providing diagnostic support [<xref ref-type="bibr" rid="ref1">1</xref>-<xref ref-type="bibr" rid="ref4">4</xref>].</p>
        <p>There is emerging research available on digital conversational agents for mental health or substance use in treatment-seeking populations such as youth who are seeking or accessing services to support their mental health or substance use. A recent set of 2 reviews found minimal research on digital conversational agents for mental illness, with a specific gap around youth, and the studies were not necessarily in treatment-seeking populations [<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref4">4</xref>]. They did find some acceptability and positive effects for the tool’s ability to establish diagnosis, but less so among youth. Some positive mental health impacts were found, but study limitations made these difficult to determine. Digital conversational agents in the psychiatric sphere have targeted various outcomes. For example, one was designed to promote activity engagement among individuals with severe mental illness [<xref ref-type="bibr" rid="ref5">5</xref>]. Others have been designed to promote service utilization [<xref ref-type="bibr" rid="ref6">6</xref>], develop mindfulness and emotion regulation [<xref ref-type="bibr" rid="ref7">7</xref>], determine diagnoses [<xref ref-type="bibr" rid="ref8">8</xref>], or promote medication adherence [<xref ref-type="bibr" rid="ref9">9</xref>]. Evidence of the development of something akin to a therapeutic alliance has been demonstrated [<xref ref-type="bibr" rid="ref10">10</xref>], while the responses of digital conversational agents have been rated as higher quality and more empathetic than physician responses [<xref ref-type="bibr" rid="ref11">11</xref>]. However, the research evidence for treatment-seeking youth in clinical contexts (ie, receiving treatment) remains limited and has yet to be synthesized.</p>
        <p>There is more research on the use of digital conversational agents as a prevention, promotion, or low-threshold mental health support tool, particularly for youth in school settings [<xref ref-type="bibr" rid="ref12">12</xref>-<xref ref-type="bibr" rid="ref15">15</xref>]. An acceptability study found that youth preferred to receive information through a digital conversational agent versus searching for it online, while the “personality” of the digital conversational agent was appreciated for its friendly, relational aspects [<xref ref-type="bibr" rid="ref12">12</xref>]; the practical advice and referrals offered were also appreciated. Advantages include flexibility, accessibility, the capacity to reach more youth faster than in-person services, cost-effectiveness, and the ability to get help without stigma [<xref ref-type="bibr" rid="ref12">12</xref>,<xref ref-type="bibr" rid="ref13">13</xref>,<xref ref-type="bibr" rid="ref15">15</xref>]. However, evidence on efficacy remains limited [<xref ref-type="bibr" rid="ref16">16</xref>], and the need to empirically test these interventions has been highlighted [<xref ref-type="bibr" rid="ref12">12</xref>,<xref ref-type="bibr" rid="ref15">15</xref>,<xref ref-type="bibr" rid="ref17">17</xref>].</p>
        <p>As digital conversational agents expand around the world, a number of ethical issues have been raised. One team set out recommendations for minimal ethical standards in the use of digital conversational agents for youth mental health [<xref ref-type="bibr" rid="ref17">17</xref>]. Some factors include ensuring confidentiality, being transparent about uses and limits, generating appropriate crisis responses, and protecting against addictive use. The article further highlighted the importance of testing efficacy, being transparent with users about the evidence base, encouraging in-person services, and explaining that these tools are not designed to treat severe mental illness. For vulnerable youth in treatment-seeking contexts, privacy and confidentiality is important, and addictive use might be a particular concern. These concerns have been reflected in discussions of the promise and necessary cautions regarding the implementation of digital conversational agents [<xref ref-type="bibr" rid="ref18">18</xref>,<xref ref-type="bibr" rid="ref19">19</xref>]. These issues must be attended to in the development, testing, and scale of digital conversational agents for mental health.</p>
        <p>Youth are high users of digital technology [<xref ref-type="bibr" rid="ref20">20</xref>] and often use digital means of seeking information about health [<xref ref-type="bibr" rid="ref21">21</xref>]. They may be interested in receiving support through digital conversational agent technology. However, treatment-seeking youth with potentially complex mental health challenges have different needs and may have different preferences than school-based samples. Given ethical concerns about digital conversational agents for severe mental illness [<xref ref-type="bibr" rid="ref17">17</xref>], further exploratory work is an essential prerequisite to digital conversational agent development. It is important to gain the perspectives of treatment-seeking youth around the possible utility, functionality, acceptability, and safety of digital conversational agents to address mental health challenges among them. It is also important to continue to do up-to-date work in this area, given the fast pace of technology development that leaves older research quickly out of date.</p>
      </sec>
      <sec>
        <title>Objective</title>
        <p>This scoping review aims to synthesize the recent literature on digital conversational agents for youth in clinical contexts seeking treatment for mental health or substance use challenges.</p>
      </sec>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Overview</title>
        <p>We used the scoping review methodology given the breadth and nature of the research and the exploratory nature of the research question in an emerging field, using established scoping review processes [<xref ref-type="bibr" rid="ref22">22</xref>,<xref ref-type="bibr" rid="ref23">23</xref>]. The scoping review incorporated the following major steps: (1) defining the research question, (2) identifying relevant studies, (3) screening and selecting studies, (4) extracting the data, and (5) summarizing the data and reporting. PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines have been followed in the reporting of this review (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>) [<xref ref-type="bibr" rid="ref24">24</xref>].</p>
      </sec>
      <sec>
        <title>Youth Engagement</title>
        <p>In accordance with the strategy for patient-oriented research [<xref ref-type="bibr" rid="ref25">25</xref>], we engaged 2 youth engagement specialists with lived experience in the conduct of this review. We endorsed pragmatism as a fundamental worldview and valued youth contributions, as per lived experience engagement paradigms [<xref ref-type="bibr" rid="ref26">26</xref>]. Youth engagement specialists helped identify keywords for the systematic search, coselected information to extract from the resulting studies, and assisted with interpreting and reporting on the findings. Collaboration with the youth engagement specialists helped guard against bias and ensured that the study was relevant to the real-world experiences of young people, enhancing rigor.</p>
      </sec>
      <sec>
        <title>Defining the Research Question</title>
        <p>This scoping review aims to understand the published academic literature on digital conversational agents for treatment-seeking youth with mental health or substance use challenges, in clinical contexts. Based on the PICO (population, intervention, comparison and outcomes) framework [<xref ref-type="bibr" rid="ref27">27</xref>], this review focuses on youth with mental health or substance use challenges (population) and applications of digital conversational agents in treatment-seeking in clinical settings (intervention). Note that the treatment-seeking and clinical settings context was a key inclusion criterion that makes this review very specific to clinical contexts, which is a gap in the literature. It includes studies with or without comparison groups and reports on the full range of findings, regarding applications, acceptability, and outcomes related to digital conversational agents for the target population, as well as other findings highlighted in the selected literature. Literature on preventive interventions and nonclinical settings was excluded.</p>
      </sec>
      <sec>
        <title>Identifying Relevant Studies</title>
        <p>A comprehensive search strategy was developed with a health sciences librarian (TR). Considering the subject areas of the research question, the search was developed, tested, and finalized in Medline, then translated and run on February 22, 2024 in the following bibliographic databases: APA PsycInfo, Medline, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, Applied Social Sciences Index and Abstracts (ASSIA), and Cochrane Central Register of Controlled Trials (CENTRAL). The search was repeated and updated on March 18, 2025. The search strategies used database-specific subject headings and keywords in natural language, as well as advanced search operators such as truncation and adjacency operators, to capture 3 main concepts: youth, digital conversational agent, and mental health or substance use. The review was limited to articles published in the past 8 years (2016-2025) due to the rapid advancement of AI technology. There were no limitations placed on language or study type. Conference abstracts were removed through the search strategy when allowed by a database, but were otherwise included. A supplementary hand search of reference lists and Google Scholar was conducted. Given the nature of the research question, the gray literature search was limited to dissertations in APA PsycInfo, registered clinical trials in the CENTRAL search, and nontraditional publications indexed in CINAHL.</p>
      </sec>
      <sec>
        <title>Study Screening and Selection</title>
        <p>To be included, articles had to present descriptive information or research results on digital conversational agents for youth mental health or substance use, focusing on treatment-seeking populations in clinical contexts. Articles could report on any study design and sample size and could include descriptive process papers. The digital agent and study had to be focused on youth approximately aged 11-24 years, or separate analyses had to be available for a subgroup within this age range. Articles had to be published in English or French consistent with the language skills available on the team, although no non-English language texts were found. We included any outcomes identified by the article in question, including acceptability and feasibility outcomes as well as mental health or substance use outcomes of any kind or intensity. Excluded were any studies not reporting on digital conversational agents for youth mental health or substance use, research conducted on children (majority aged younger than 11 years) or adults (majority aged older than 24 years), and commentaries that did not describe either research results or a specific digital conversational agent. <xref ref-type="boxed-text" rid="box1">Textbox 1</xref> presents inclusion and exclusion criteria, which were developed to optimize the ability to address the research question. Selected articles were screened first at the title and abstract level by 2 of 3 research staff (include or exclude responses), with any conflicts resolved through discussion with the project lead. The resulting set of articles were screened in full using the same process. Article screening was conducted using Covidence software [<xref ref-type="bibr" rid="ref28">28</xref>].</p>
        <boxed-text id="box1" position="float">
          <title>Inclusion and exclusion criteria for literature search.</title>
          <p>Inclusion criteria</p>
          <list list-type="bullet">
            <list-item>
              <p>Addresses digital conversational agents</p>
            </list-item>
            <list-item>
              <p>Agent designed for youth aged 11-24 years</p>
            </list-item>
            <list-item>
              <p>Participants with mental health or substance use challenges (disorders or symptoms)</p>
            </list-item>
            <list-item>
              <p>Participants seeking mental health or substance use treatment (ie, connected with clinical contexts)</p>
            </list-item>
            <list-item>
              <p>Published between 2016 and 2025</p>
            </list-item>
            <list-item>
              <p>Reports on efficacy, effectiveness, feasibility, or acceptability</p>
            </list-item>
            <list-item>
              <p>Reports on youth perspectives using youth-reported data (any method)</p>
            </list-item>
          </list>
          <p>Exclusion criteria</p>
          <list list-type="bullet">
            <list-item>
              <p>Not a youth-focused agent and study</p>
            </list-item>
            <list-item>
              <p>Prevention or promotion that does not support known mental health or substance use challenges</p>
            </list-item>
            <list-item>
              <p>Youth were not treatment-seeking or were not exposed to the digital conversational agent in a clinical context</p>
            </list-item>
            <list-item>
              <p>Published before 2016</p>
            </list-item>
            <list-item>
              <p>Papers without original data</p>
            </list-item>
          </list>
        </boxed-text>
      </sec>
      <sec>
        <title>Data Extraction</title>
        <p>A data extraction form was developed collaboratively among team members, including youth. From the final selected articles, data were extracted by 1 staff member and verified by a second staff member using a spreadsheet. The data extraction form included (1) study general information (eg, reference, location, and data collection years), (2) digital conversational agent description (eg, goal or objective, application and content, context of use, development and testing, youth engagement, software and data strategy, feedback learning integration, delivery method, financial investment, privacy, content monitoring, and sustainability plan), (3) study methods (eg, study objective, design, sampling method, sample size, sample description, exclusion criteria, measures, and other treatments), (4) outcomes (eg, finding overview, youth perspectives, digital conversational agent benefits and limitations, adverse events, and study limitations), (eg, 5) ethical issues (privacy and confidentiality, efficacy, safety, and mitigating strategies), and (eg, 6) other information (author conclusions and recommendations).</p>
      </sec>
      <sec>
        <title>Data Summarization and Reporting</title>
        <p>The data were summarized narratively and in table format. Quality assessment was not conducted, as this is not a priority in scoping reviews in which a wide range of diverse research is mapped.</p>
      </sec>
      <sec>
        <title>Ethical Considerations</title>
        <p>Since this is a scoping review of the literature, ethics board approval was not required. There are no human participants in this article and informed consent is not required.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <sec>
        <title>Study Selection</title>
        <p>Our search identified 8659 records, including 5875 records from the initial search in 2024 and 2784 from the updated search in 2025. After removing 3734 duplicates, we screened 4925 titles and abstracts, excluding 4900. We further assessed 25 full-text articles. Fifteen were excluded due to not meeting our inclusion criteria, which resulted in 10 studies included in the review. The study selection process is illustrated in the PRISMA flow diagram (<xref rid="figure1" ref-type="fig">Figure 1</xref>).</p>
        <fig id="figure1" position="float">
          <label>Figure 1</label>
          <caption>
            <p>PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart.</p>
          </caption>
          <graphic xlink:href="mental_v12i1e77098_fig1.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
        </fig>
        <p><xref ref-type="table" rid="table1">Table 1</xref> summarizes the included articles and digital conversational agents studied. The 10 studies examined 9 digital conversational agents for youth mental health in clinical care contexts. Studies emerged from the United States [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref30">30</xref>], Germany [<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref32">32</xref>], Australia [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref33">33</xref>], Thailand [<xref ref-type="bibr" rid="ref34">34</xref>], Japan [<xref ref-type="bibr" rid="ref35">35</xref>], and Hong Kong [<xref ref-type="bibr" rid="ref36">36</xref>], with publication years ranging from 2017 to 2025. Only 3 articles stipulated that the digital conversational agents were co-designed with youth [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref33">33</xref>].</p>
        <table-wrap position="float" id="table1">
          <label>Table 1</label>
          <caption>
            <p>Summary of the included articles and digital tools.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="90"/>
            <col width="80"/>
            <col width="100"/>
            <col width="140"/>
            <col width="160"/>
            <col width="120"/>
            <col width="200"/>
            <col width="110"/>
            <thead>
              <tr valign="top">
                <td>Author (year)</td>
                <td>Country</td>
                <td>Format</td>
                <td>Technology described</td>
                <td>Digital conversational agent objective</td>
                <td>Intervention modality</td>
                <td>Expressed digital conversational agent limitations</td>
                <td>Codevelopment with youth</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Wrightson-Hester et al [<xref ref-type="bibr" rid="ref33">33</xref>]</td>
                <td>Australia</td>
                <td>Web application</td>
                <td>Artificial intelligence conversational agent</td>
                <td>Help youth manage mental health using curious questioning</td>
                <td>Method of levels therapy</td>
                <td>Repetitive content and input comprehension issues</td>
                <td>Yes</td>
              </tr>
              <tr valign="top">
                <td>Greenwood et al [<xref ref-type="bibr" rid="ref37">37</xref>]</td>
                <td>United States</td>
                <td>Mobile app</td>
                <td>Natural language processing and machine learning</td>
                <td>Help youth develop emotion regulation skills</td>
                <td>CBT, IPT-A<sup>b</sup>, and DBT<sup>c</sup></td>
                <td>Effectiveness not rigorously tested for; not implemented in clinical practice</td>
                <td>Not specified</td>
              </tr>
              <tr valign="top">
                <td>Beilharz et al [<xref ref-type="bibr" rid="ref1">1</xref>]<break/>  <break/>  </td>
                <td>Australia</td>
                <td>Web-based chat accessible on mobile and desktop devices</td>
                <td>Artificial intelligence conversational agent</td>
                <td>Provide support for body image issues and eating disorders</td>
                <td>Psychoeducation, coping skills via CBT,<break/>acceptance and commitment therapy, mindfulness</td>
                <td>Limited to psychoeducation and simultaneous coping skills</td>
                <td>Yes</td>
              </tr>
              <tr valign="top">
                <td>Fitzpatrick et al [<xref ref-type="bibr" rid="ref2">2</xref>]</td>
                <td>United States</td>
                <td>Instant messenger app on mobile or desktop</td>
                <td>Decision tree methodology with predefined responses, including natural language processing at certain points within the tree</td>
                <td>Deliver self-help CBT to young adults with anxiety and depression symptoms.</td>
                <td>CBT</td>
                <td>Potential risk of violating psychotherapeutic processes related to limitations in conversational abilities</td>
                <td>Not specified</td>
              </tr>
              <tr valign="top">
                <td>Robinson et al [<xref ref-type="bibr" rid="ref30">30</xref>]</td>
                <td>United States</td>
                <td>Mobile app</td>
                <td>Not specified</td>
                <td>Deliver CBT to adolescents at adolescent outpatient mental health clinic.</td>
                <td>CBT</td>
                <td>Not specified</td>
                <td>Not specified</td>
              </tr>
              <tr valign="top">
                <td>Mahmud and Porntrakoon [<xref ref-type="bibr" rid="ref34">34</xref>]</td>
                <td>Thailand</td>
                <td>Not specified</td>
                <td>AI<sup>d</sup>-generated or DCA<sup>e</sup> mental health<break/>application</td>
                <td>No specific digital conversational agent introduced</td>
                <td>Not specified</td>
                <td>Lack of customization, depersonalization, algorithm bias, privacy concerns</td>
                <td>N/A<sup>f</sup></td>
              </tr>
              <tr valign="top">
                <td>Kuhlmeier et al [<xref ref-type="bibr" rid="ref31">31</xref>]</td>
                <td>Germany</td>
                <td>Mobile apps and web platforms</td>
                <td>Text-based conversational agent prototype</td>
                <td>Provide youth and young adults personalized therapy for depression</td>
                <td>CBT, IPT<sup>g</sup></td>
                <td>Currently an early-stage prototype</td>
                <td>Yes</td>
              </tr>
              <tr valign="top">
                <td>Kuhlmeier et al [<xref ref-type="bibr" rid="ref32">32</xref>]</td>
                <td>Germany</td>
                <td>Prototype accessed via laptop</td>
                <td>Text-based conversational agent prototype</td>
                <td>Support youth with depression through a behavioral activation exercise</td>
                <td>Behavioral activation</td>
                <td>Currently an early-stage prototype</td>
                <td>No, but participant feedback will influence the future design</td>
              </tr>
              <tr valign="top">
                <td>Hasei et al [<xref ref-type="bibr" rid="ref35">35</xref>]</td>
                <td>Japan</td>
                <td>Accessible via mobile app LINE</td>
                <td>GPT-4 large language model</td>
                <td>Help pediatric, youth, and young adult cancer patient reduce anxiety and stress</td>
                <td>Not specified</td>
                <td>4-turn conversations</td>
                <td>Not specified</td>
              </tr>
              <tr valign="top">
                <td>Li et al [<xref ref-type="bibr" rid="ref36">36</xref>]</td>
                <td>Hong Kong</td>
                <td>Accessible via Microsoft Teams</td>
                <td>An interactive conversational system with natural language understanding</td>
                <td>Support university students with self-reported depression through MBSR<sup>h</sup></td>
                <td>MBSR interventions</td>
                <td>Technical issues with Microsoft Teams, required high self-discipline, limited interactivity</td>
                <td>Not specified</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table1fn1">
              <p><sup>a</sup>CBT: cognitive behavioral therapy.</p>
            </fn>
            <fn id="table1fn2">
              <p><sup>b</sup>IPT-A: interpersonal psychotherapy for adolescents.</p>
            </fn>
            <fn id="table1fn3">
              <p><sup>c</sup>DBT: dialectical behavior therapy.</p>
            </fn>
            <fn id="table1fn4">
              <p><sup>d</sup>AI: artificial intelligence.</p>
            </fn>
            <fn id="table1fn5">
              <p><sup>e</sup>DCA: digital conversational agent.</p>
            </fn>
            <fn id="table1fn6">
              <p><sup>f</sup>N/A: not applicable.</p>
            </fn>
            <fn id="table1fn7">
              <p><sup>g</sup>IPT: interpersonal therapy.</p>
            </fn>
            <fn id="table1fn8">
              <p><sup>h</sup>MBSR: mindfulness-based stress reduction.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec>
        <title>Study Characteristics</title>
        <p>Of the 10 included studies, 7 assessed feasibility or usability or the preliminary efficacy or effectiveness [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref35">35</xref>,<xref ref-type="bibr" rid="ref36">36</xref>], while others investigated perceptions of using the agent [<xref ref-type="bibr" rid="ref34">34</xref>], perceptions of their design [<xref ref-type="bibr" rid="ref31">31</xref>], and youth’s interaction experience with them [<xref ref-type="bibr" rid="ref32">32</xref>]. Three studies used qualitative methods [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref32">32</xref>], 1 used quantitative methods [<xref ref-type="bibr" rid="ref30">30</xref>], and 6 used mixed methods [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref33">33</xref>-<xref ref-type="bibr" rid="ref36">36</xref>]. Three studies used randomized controlled trials to evaluate 2 digital conversational agents [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref30">30</xref>]. Participant demographics varied in the studies, covering age groups from adolescents to young adults with depression [<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref32">32</xref>,<xref ref-type="bibr" rid="ref36">36</xref>], anxiety or depression [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref30">30</xref>,<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref34">34</xref>], anxiety and stress [<xref ref-type="bibr" rid="ref35">35</xref>], and eating disorders [<xref ref-type="bibr" rid="ref1">1</xref>]. None focused on substance use disorders. Some studies also included mental health professionals [<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref34">34</xref>] and caregivers [<xref ref-type="bibr" rid="ref1">1</xref>] as participants.</p>
      </sec>
      <sec>
        <title>Intervention Characteristics</title>
        <p>The technology driving the digital conversational agent was not always specified but included artificial intelligence, for example natural language processing, machine learning, and decision trees. While publications were dated 2016 to 2025, the year of the development of the digital conversational agent under examination was not reported. The interventions were delivered via a mobile app [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>-<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref35">35</xref>,<xref ref-type="bibr" rid="ref36">36</xref>] or a computer browser [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref31">31</xref>-<xref ref-type="bibr" rid="ref33">33</xref>]. Treatment modalities included cognitive behavioral therapy or components thereof [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>-<xref ref-type="bibr" rid="ref32">32</xref>]; an integration of cognitive behavioral therapy, interpersonal psychotherapy, and dialectical behavior therapy [<xref ref-type="bibr" rid="ref29">29</xref>]; a method-of-levels approach [<xref ref-type="bibr" rid="ref33">33</xref>]; mindfulness-based stress reduction interventions [<xref ref-type="bibr" rid="ref36">36</xref>]; and unspecified modalities [<xref ref-type="bibr" rid="ref34">34</xref>,<xref ref-type="bibr" rid="ref35">35</xref>]. Some studies included screenshots or sample interactions to illustrate the digital conversational agent’s responses [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref31">31</xref>-<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref35">35</xref>]. For example, one study shows a screenshot of coping skill recommendations made by the chatbot [<xref ref-type="bibr" rid="ref1">1</xref>]. Another shows a screenshot of behavioral activation recommendations [<xref ref-type="bibr" rid="ref32">32</xref>]. However, others did not provide details about the exact nature of the responses of the digital conversational agent. The digital conversational agents were not generally described as being integrated into a system of care to accompany clinical services, except for one that was designed for young cancer patients [<xref ref-type="bibr" rid="ref35">35</xref>].</p>
      </sec>
      <sec>
        <title>Qualitative and Acceptability Findings</title>
        <p>The methodology and outcomes of the included articles are summarized in <xref ref-type="table" rid="table2">Table 2</xref>. Most studies reported that the digital conversational agents were acceptable to youth, with high utilization [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>], high satisfaction [<xref ref-type="bibr" rid="ref2">2</xref>], and overall positive perceptions [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref31">31</xref>-<xref ref-type="bibr" rid="ref33">33</xref>]. Participants appreciated the ease of use [<xref ref-type="bibr" rid="ref33">33</xref>], appealing and accessible design [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref32">32</xref>], and friendly characters [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref32">32</xref>]. They also found that the content was helpful and appropriate [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref35">35</xref>], equipped them with new mental health insight [<xref ref-type="bibr" rid="ref2">2</xref>], and offered them empathy [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref32">32</xref>]. Youth identified advantages, namely the neutrality, anonymity, and availability of these tools compared to traditional psychotherapy [<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref35">35</xref>,<xref ref-type="bibr" rid="ref36">36</xref>]; some youth indicated their willingness to use digital conversational agents for depression and anxiety, with cautions regarding privacy and security [<xref ref-type="bibr" rid="ref34">34</xref>].</p>
        <table-wrap position="float" id="table2">
          <label>Table 2</label>
          <caption>
            <p>Research methodology aspects of the included articles.</p>
          </caption>
          <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
            <col width="80"/>
            <col width="90"/>
            <col width="80"/>
            <col width="70"/>
            <col width="120"/>
            <col width="120"/>
            <col width="120"/>
            <col width="130"/>
            <col width="190"/>
            <thead>
              <tr valign="top">
                <td>Author (year)</td>
                <td>Study <break/>objective</td>
                <td>Sample size</td>
                <td>Sample age (years)</td>
                <td>Mental health or substance use conditions</td>
                <td>Exclusion <break/>criteria</td>
                <td>Measurement</td>
                <td>Amount of use of digital conversational agent within study</td>
                <td>Outcome summary</td>
              </tr>
            </thead>
            <tbody>
              <tr valign="top">
                <td>Wrightson-Hester et al [<xref ref-type="bibr" rid="ref33">33</xref>]</td>
                <td>Assess feasibility and acceptability</td>
                <td>13</td>
                <td>16-24</td>
                <td>Anxiety or depression</td>
                <td>Severe depressive symptoms or frequent suicidal thoughts</td>
                <td>Self-report measures of depression, anxiety, QoL<sup>a</sup>, related psychological constructs, and system usability and engagement  <break/>   Interview/focus group guide</td>
                <td>Week 1: 1-4 days, 1-3 chats/day (average length 2-30 min); Week 2: 1-7 days, 1-5 chats/day (average length 5-15 min)</td>
                <td>Feasible assessments; acceptable system engagement; acceptable interface; acceptable therapeutic conversations; some frustration, but resolved through use; recommendations for improvement; possible improvements in some psychological measures</td>
              </tr>
              <tr valign="top">
                <td>Greenwood et al [<xref ref-type="bibr" rid="ref37">37</xref>]</td>
                <td>Establish the feasibility, preliminary acceptability, effectiveness, and usability</td>
                <td>18 (17 analyzed)</td>
                <td>13-17</td>
                <td>Depression and anxiety</td>
                <td>Parent-reported history of severe depression, substance use, psychotic illness, OCD<sup>b</sup>, PTSD<sup>c</sup>, panic disorder, or specific phobias; psychiatric hospitalization in the previous month; unaccompanied by a guardian at diagnostic visit; no access to a mobile device for regular use; unable to read and write English.</td>
                <td>Self-report measures of depression (primary outcome), anxiety, and self-efficacy; app usage rates; acceptability, feasibility, and usability; safety monitoring.</td>
                <td>Average use of 6 days, 55 mood check-ins, 313.17 sent messages, 13.63 lessons, and 9 tools over 4 weeks</td>
                <td>Acceptability and feasibility confirmed; decreased depression and anxiety; increased self-efficacy; satisfactory usage rates; acceptable safety monitoring.</td>
              </tr>
              <tr valign="top">
                <td>Beilharz et al [<xref ref-type="bibr" rid="ref1">1</xref>]</td>
                <td>Evaluate the acceptability and feasibility</td>
                <td>25 (17 youth, 8 caregivers)</td>
                <td>Youth: 13-18; caregivers: 46-57</td>
                <td>Body image concerns or eating disorders</td>
                <td>Not specified</td>
                <td>Focus group guide</td>
                <td>Not specified</td>
                <td>Appealing character and design; preference for brief content with a conversational tone; acceptable flow via button-based navigation; preference for free-text option; appreciation of accessibility.</td>
              </tr>
              <tr valign="top">
                <td>Fitzpatrick et al [<xref ref-type="bibr" rid="ref2">2</xref>]</td>
                <td>Assess feasibility, acceptability, and preliminary efficacy</td>
                <td>70</td>
                <td>18-28</td>
                <td>Anxiety and depression</td>
                <td>Not specified</td>
                <td>Self-report measures of depression, anxiety, affect, and acceptability and usability; open-ended questions; usage tracking</td>
                <td>Up to 20 sessions, average 12.14 check-ins over 2 weeks</td>
                <td>Feasibility confirmed; reduction in depression symptoms, but not anxiety or positive or negative affect; high engagement and satisfaction; some positive comments on process and content; some challenges with process, technology, and content; limitations existed.</td>
              </tr>
              <tr valign="top">
                <td>Robinson et al [<xref ref-type="bibr" rid="ref30">30</xref>]</td>
                <td>Explore the feasibility and noninferiority</td>
                <td>141</td>
                <td>13-17</td>
                <td>Depression or anxiety</td>
                <td>Not specified</td>
                <td>Self-report measure of depression and anxiety</td>
                <td>Not specified</td>
                <td>Noninferiority to clinician-delivered CBT<sup>d</sup>-skills group in reducing depression symptoms.</td>
              </tr>
              <tr valign="top">
                <td>Mahmud and Porntrakoon [<xref ref-type="bibr" rid="ref34">34</xref>]</td>
                <td>Explore perspectives on DCAs<sup>e</sup> as alternative treatments</td>
                <td>15 (10 youth, 5 psychologists)</td>
                <td>Youth: 20-25</td>
                <td>Depression or anxiety</td>
                <td>Not specified</td>
                <td>Interview guide; self-report measures of depression and anxiety.</td>
                <td>Not specified</td>
                <td>Interest in using DCA when experiencing depression or anxiety; concerns about privacy, confidentiality, and security; preferences varied on the extent and time of expert assistance</td>
              </tr>
              <tr valign="top">
                <td>Kuhlmeier et al [<xref ref-type="bibr" rid="ref31">31</xref>]</td>
                <td>Design a<break/>personalized conversational agent to treat youth depression</td>
                <td>Problem awareness phase: 15 youth; evaluation phase: 5 experts, 5 potential users</td>
                <td>Problem awareness phase: 14-17; evaluation phase: experts: mean 29; potential users: mean 24</td>
                <td>Depression</td>
                <td>Not specified</td>
                <td>Interview guide</td>
                <td>Not specified</td>
                <td>Personalization of the conversational agent and content is essential, combined with structure; areas of improvement identified</td>
              </tr>
              <tr valign="top">
                <td>Kuhlmeier et al [<xref ref-type="bibr" rid="ref32">32</xref>]</td>
                <td>Investigate how youth interact with the conversational agent for depression</td>
                <td>15</td>
                <td>14-17</td>
                <td>Depression</td>
                <td>Suicidal ideation, psychosis, or low cognitive functioning.</td>
                <td>User interaction data and think-aloud sessions documenting thoughts about the DCA</td>
                <td>11:54-20:38 min</td>
                <td>Engaging interaction style; preferences varied on emoji and language use; appreciation of predefined responses, optional reminders, and clear interface; varied perceptions of responding speed and the dialogue content</td>
              </tr>
              <tr valign="top">
                <td>Hasei et al [<xref ref-type="bibr" rid="ref35">35</xref>]</td>
                <td>Assess feasibility and potential impact in pediatric, youth, and young adult cancer patients</td>
                <td>5</td>
                <td>13 to 20s</td>
                <td>Not specified, but cancer patients usually experience anxiety and stress from cancer</td>
                <td>Not specified</td>
                <td>Self-report measure of anxiety and stress; open-ended questions.</td>
                <td>Most used every 2-3 days for about 10-15 min/session over 1-2 weeks</td>
                <td>Reduced anxiety and stress; possible increased cancer treatment engagement; possible increased self-expression and informal help-seeking.</td>
              </tr>
              <tr valign="top">
                <td>Li et al [<xref ref-type="bibr" rid="ref36">36</xref>]</td>
                <td>Evaluate feasibility, acceptability, safety, and preliminary efficacy</td>
                <td>30 (27 completed)</td>
                <td>18-25</td>
                <td>Depression</td>
                <td>Diagnosed with a clinical psychotic condition preintervention or were currently involved in any mindfulness-based or other psychosocial interventions.</td>
                <td>Self-report measure of depression, stress, anxiety, and mindfulness; open-ended questions.</td>
                <td>8 weeks; encouraged at least 1 hour of daily interaction.</td>
                <td>Feasibility, acceptability, safety, and preliminary efficacy confirmed; limitations identified.</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="table2fn1">
              <p><sup>a</sup>QoL: quality of life.</p>
            </fn>
            <fn id="table2fn2">
              <p><sup>b</sup>OCD: obsessive compulsive disorder.</p>
            </fn>
            <fn id="table2fn3">
              <p><sup>c</sup>PTSD: posttraumatic stress disorder.</p>
            </fn>
            <fn id="table2fn4">
              <p><sup>d</sup>CBT: cognitive behavioral therapy.</p>
            </fn>
            <fn id="table2fn5">
              <p><sup>e</sup>DCA: digital conversational agent.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>A number of problems, challenges, or barriers were identified by participants across the studies. These included limited natural conversation [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref35">35</xref>], limited customization [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref34">34</xref>], technical glitches [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref36">36</xref>], and concerns regarding the quality of the therapeutic interventions [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref34">34</xref>]</p>
      </sec>
      <sec>
        <title>Quantitative Findings</title>
        <p>Six studies provided quantitative results on the digital conversational agents’ ability to improve participants’ mental health. A randomized controlled trial (RCT) of a digital conversational agent called Woebot found that, compared to a self-help e-book, the intervention significantly reduced depressive symptoms after 2 weeks, with a moderate effect size (d=0.44) [<xref ref-type="bibr" rid="ref2">2</xref>]. In another RCT, 4 weeks of using Woebot was found to be noninferior to a standard clinician-led CBT group in reducing depression when comparing pre-post average scores and the number of participants with elevated depression; the effect size was not provided [<xref ref-type="bibr" rid="ref30">30</xref>]. In a pilot RCT, the treatment group showed greater mean improvement in depression than the waitlist control group (d=0.98) [<xref ref-type="bibr" rid="ref29">29</xref>]. No significance testing was reported for these trials [<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref30">30</xref>]. A single arm study found a large effect size (d=1.26) for reducing problem-related distress and a medium effect size (d=–0.66) for improving goal conflict reorganization among participants with anxiety or depression [<xref ref-type="bibr" rid="ref33">33</xref>]. Additionally, a single arm pretest-posttest study of a digital conversational agent delivering a mindfulness intervention reported significant and large improvements in depression, anxiety, stress, and mindfulness levels, with large effect sizes across all outcomes, at d=–1.95 for stress, d =–1.53 for depression, and d=–1.09 for anxiety [<xref ref-type="bibr" rid="ref36">36</xref>].</p>
      </sec>
      <sec>
        <title>Ethical and Safety Considerations</title>
        <p>The minimal ethical standards proposed for digital conversational agents revolve around (1) privacy and confidentiality, (2) efficacy, and (3) safety [<xref ref-type="bibr" rid="ref17">17</xref>]. One study encompassed these requirements by providing user participants with an information package regarding privacy, efficacy, and safety issues as part of the application onboarding process [<xref ref-type="bibr" rid="ref29">29</xref>]. Another study emphasized rigorous approval and safety measures that include anonymized and secure data handling and adherence to the Declaration of Helsinki [<xref ref-type="bibr" rid="ref35">35</xref>]. However, most of the included articles did not discuss ethical issues in depth. While concerns over privacy and confidentiality were mentioned by many youths and stakeholders [<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref31">31</xref>,<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref34">34</xref>], only half of the articles included any information on their privacy policies. A case series assessing feasibility and acceptability for depression or anxiety reported that secure user identification and anonymized data collection was not conducted within the study, but would be implemented in the future [<xref ref-type="bibr" rid="ref33">33</xref>]. One study informed participants that they would not be monitored by a counsellor [<xref ref-type="bibr" rid="ref1">1</xref>], while another disclosed that a psychologist would monitor participants’ activities asynchronously [<xref ref-type="bibr" rid="ref2">2</xref>].</p>
        <p>Despite the ethical importance of ensuring efficacy, most of the articles described pilot trials examining acceptability and feasibility without adequate power to determine efficacy. Prominent limitations were small sample sizes and the lack of diversity. As a result, while many of the interventions were reportedly inspired by evidence-based therapeutic approaches [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref36">36</xref>], the delivery of the interventions via these tools has not been demonstrated efficacious or effective in real-world settings and thus requires further evaluation.</p>
        <p>Safety issues are also worthy of note. Only 6 of the selected studies described safety features [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>,<xref ref-type="bibr" rid="ref33">33</xref>,<xref ref-type="bibr" rid="ref35">35</xref>,<xref ref-type="bibr" rid="ref36">36</xref>]. Among these, 3 reported that participants were informed of about the tool and given explanation of its function and capacities [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref29">29</xref>]. Only 1 study mentioned having a crisis response measure, in which the digital conversational agent could identify concerning language and confirm it with users [<xref ref-type="bibr" rid="ref29">29</xref>]. One study emphasized that their safety measures include automated escalation systems for distress detection and professional involvement during development and testing [<xref ref-type="bibr" rid="ref35">35</xref>]. Another study involved continuous monitoring by mental health professionals, weekly participants check-ins, and mental health support resources and referral pathways [<xref ref-type="bibr" rid="ref36">36</xref>]. The digital conversational agents featured in these 4 trials offered additional mental health resources and provided easily accessible channels to connect users with suicide helplines or emergency services.</p>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <sec>
        <title>Principal Findings</title>
        <p>This review synthesized the recent literature on digital conversational agents for youth with mental health or substance use conditions, specifically in treatment-seeking clinical contexts. It was found that the literature is quite preliminary and is focused entirely on mental health, not substance use conditions. Yet, this is an emerging area of work that is a high priority to some research teams and health care organizations. Several of the digital conversational agents reviewed applied the principles of cognitive behavioral therapy, but this was not universal. Promising findings were identified in terms of feasibility and acceptability, together with reasonable usage rates and positive youth perspectives of acceptability. Preliminary findings suggested that digital conversational agents might be an acceptable means of delivering therapeutic content to treatment-seeking youth, with positive impacts on their mental health.</p>
        <p>The literature was largely made up of feasibility and acceptability studies rather than efficacy trials. The digital conversational agents were not described as being embedded in intervention contexts, such as being integrated with in-person clinical care. Sample sizes were small and diversity was limited. People with different sociodemographic profiles and different clinical needs might be differentially interested in using e-health innovations [<xref ref-type="bibr" rid="ref38">38</xref>,<xref ref-type="bibr" rid="ref39">39</xref>], although differences across population subgroups have not been definitively established. This leaves the evidence base in a very premature state. For example, there is a lack of exploration of the impact the tools might have as an integrated component of youth mental health care among diverse youth.</p>
        <p>All of the articles addressed mental health; none addressed substance use. It is important to consider mental health and substance use together, given the high levels of overlap and increasing trends toward treating concurrent disorders together [<xref ref-type="bibr" rid="ref40">40</xref>]. Examining digital conversational agents for substance use challenges, or for concurrent mental health and substance use challenges, is a pressing area for future work. Investigations into suitability using different treatment modalities for specific diagnostic groups might also be worthy of consideration, given that specific symptoms may interact with whether and how one might use such a tool (eg, low motivation, paranoia, suicidal ideation, and mood instability).</p>
        <p>This review focused on very recent literature on digital conversational agents, given the fast pace of technology. However, any article published in 2016 was likely examining a digital conversational agent developed at the latest in 2015, potentially earlier. These tools were not leveraging today’s latest technology, and the technology used was not thoroughly described. The rapid pace of technology advancement is not a new challenge, but rather one that the health care sector has been grappling with for years [<xref ref-type="bibr" rid="ref41">41</xref>]. This leaves two problems: (1) the technology is already out of date by the time the research is complete, and (2) the evidence base that a new study leverages is out of date and may no longer be relevant by the time it is used. Ongoing rapid research and publication in this area is essential, with thorough descriptions of the technology underpinning the tool, including the year of tool development to help readers understand the state of technological advancement of the digital conversational agent in question.</p>
        <p>In digital intervention development, co-design with the end users is critical [<xref ref-type="bibr" rid="ref42">42</xref>]. This can be done using appropriate patient engagement frameworks [<xref ref-type="bibr" rid="ref43">43</xref>]. Co-design helps ensure that the digital tool is appropriate for the end users and relevant to their needs. However, multiple articles reviewed did not discuss co-design, which may reduce acceptability. Future digital design teams should adhere to patient engagement principles for e-health innovation [<xref ref-type="bibr" rid="ref43">43</xref>] as well as youth engagement principles [<xref ref-type="bibr" rid="ref44">44</xref>]. Co-design has the potential to be a meaningful opportunity for young people to gain experience in technology development and clinical research, supporting their personal and professional growth and development [<xref ref-type="bibr" rid="ref45">45</xref>]. In conducting co-design, teams should incorporate principles of equity, diversity, inclusion and accessibility to ensure that a diverse range of voices are included, to generate a digital conversational agent that is appropriate for a wide range of diverse youth, and to mitigate the harms that can come from biases, discrimination, and inequities. Specifically, a lack of diversity at the co-design stage could perpetuate algorithmic bias, which should be guarded against. Engagement can also be leveraged to increase digital literacy and the use of resulting tools, potentially with the support of digital navigators [<xref ref-type="bibr" rid="ref46">46</xref>].</p>
        <p>From our review, it was clear that the minimum ethical standards for digital conversational agents were not adequately attended to [<xref ref-type="bibr" rid="ref17">17</xref>]. Few studies reported directly on privacy, confidentiality, and safety, and efficacy has not been definitively established. We call on developers and trialists to directly attend to the proposed ethical standards in their initiatives, proactively integrate these minimum standards into their technology and trials, integrate an ethical review stage into their initiative, and report clearly on the use of these standards. The ethics of delivering evidence-based intervention modalities via digital conversational agents should be considered—and when which modality is appropriate and for whom—since a clinician may naturally adapt their services to the individual youth, while digital tools may function differently using artificial intelligence in attempt to do the same. Matching the tool’s aim to the youth’s need, ensuring youth can withdraw at any time, and offering access to a person to talk to would all further enhance tools’ ethics and should be considered by interventionists. It should be transparent that a digital conversational agent can supplement clinical care but is not a replacement for it; integrating tools into clinical care rather than leaving them as stand-alone tools might address this challenge [<xref ref-type="bibr" rid="ref47">47</xref>].</p>
        <p>The use of digital conversational agents is not without risk. A recent news story highlights a case of youth suicide after the youth’s ongoing interaction with a digital conversational agent [<xref ref-type="bibr" rid="ref48">48</xref>]. It should be noted that youth are using digital conversational agents for mental health support even if these agents are not designed for that purpose. By developing a digital conversational agent with and for youth, with the explicit purpose of supporting mental health in appropriate ways using evidence-based content, it may be possible to provide young people with a safer tool and prevent such tragedies from occurring.</p>
        <p>While some articles discussed soliciting youth feedback as part of a study, none discussed collecting youth feedback within the digital platform. Providing opportunities to submit feedback within the platform is a potential mechanism to enable continuous improvement and incremental alignment with the needs and preferences of the users. The feedback could be directed to programming teams for programming feedback, and potentially separately to clinical teams to support clinical care as part of an integrated treatment plan. It would be important to determine means to balance the importance of privacy and confidentiality [<xref ref-type="bibr" rid="ref17">17</xref>] with the potential for identified clinical support.</p>
        <p>The next steps in this line of work would be to address some of the limitations, such as co-design and ethical concerns, with the ultimate goal of moving forward to full-scale trials to examine efficacy. This would have to be followed by implementation and ongoing refinement. The evaluation of complex interventions is expected to begin with iterative stages of intervention development, feasibility testing, evaluation, and implementation [<xref ref-type="bibr" rid="ref49">49</xref>,<xref ref-type="bibr" rid="ref50">50</xref>], and the research for this type of intervention is in the early stages of this process.</p>
      </sec>
      <sec>
        <title>Limitations</title>
        <p>Strengths and limitations of this review should be kept in mind. Important partners were engaged in the review, including industry partners and youth with lived experience. These partnerships ensured that the search terms, data extraction, and interpretations are relevant to the artificial intelligence industry and youth. However, readers should note the methodological and scope limitations: the search included only an 8-year period to ensure that the findings are as relevant as possible to recent technology, but may have missed early findings. We excluded any articles focusing on prevention or promotion, which may have relevant findings. Any publications indexed after March 2025 were not captured. The search was run only in English-based databases.</p>
      </sec>
      <sec>
        <title>Conclusions</title>
        <p>Emerging but preliminary literature is examining digital conversational agents for treatment-seeking youth with mental health conditions, but not substance use challenges. Digital technology already exists and will inevitably expand, making it essential that we support its expansion with rigorous research. This research must therefore continue, with attention to establishing efficacy, as well as ensuring appropriate protection of privacy and confidentiality and attention to safety and ethical concerns. While digital technology comes with challenges, it also comes with potential benefits. Co-design with youth, for youth, should be a priority. Nevertheless, promising early research justifies continuing this work with the possibility of codeveloping safe, accessible, youth-friendly, and potentially efficacious tools for youth mental health.</p>
      </sec>
    </sec>
  </body>
  <back>
    <app-group>
      <supplementary-material id="app1">
        <label>Multimedia Appendix 1</label>
        <p>PRISMA-SCR checklist.</p>
        <media xlink:href="mental_v12i1e77098_app1.pdf" xlink:title="PDF File  (Adobe PDF File), 166 KB"/>
      </supplementary-material>
    </app-group>
    <glossary>
      <title>Abbreviations</title>
      <def-list>
        <def-item>
          <term id="abb1">ASSIA</term>
          <def>
            <p>Applied Social Sciences Index and Abstracts</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb2">CENTRAL</term>
          <def>
            <p>Cochrane Central Register of Controlled Trials</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb3">CINAHL</term>
          <def>
            <p>Cumulative Index to Nursing and Allied Health Literature</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb4">PICO</term>
          <def>
            <p>population, intervention, comparison and outcomes</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb5">PRISMA-ScR</term>
          <def>
            <p>Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb6">RCT</term>
          <def>
            <p>randomized controlled trial</p>
          </def>
        </def-item>
      </def-list>
    </glossary>
    <ack>
      <p>We would like to thank Shelby McKee for support with the article selection process. The authors disclosed receipt of the following financial support for the research, authorship, or publication of this article: this work was supported by the Ontario Brain Institute.</p>
    </ack>
    <notes>
      <sec>
        <title>Data Availability</title>
        <p>The data underlying this project are included herein. Additional data are available upon request.</p>
      </sec>
    </notes>
    <fn-group>
      <fn fn-type="con">
        <p>LDH conceptualized and led the project and drafted the manuscript. JH contributed to selecting the articles, extracting and verifying the data, and drafting the article. ATPN contributed to selecting the articles and extracting and verifying the data. TR formulated and conducted the search. All authors contributed to the design of the study and edited and approved the final manuscript.</p>
      </fn>
      <fn fn-type="conflict">
        <p>Brian Ritchie is the founder and CEO of Kamazooie Development Corporation (“Kama.AI”), a private company specializing in artificial intelligence, including digital conversational agents. The other authors have no conflicts of interest to disclose.</p>
      </fn>
    </fn-group>
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