<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="letter"><front><journal-meta><journal-id journal-id-type="nlm-ta">JMIR Form Res</journal-id><journal-id journal-id-type="publisher-id">formative</journal-id><journal-id journal-id-type="index">27</journal-id><journal-title>JMIR Formative Research</journal-title><abbrev-journal-title>JMIR Form Res</abbrev-journal-title><issn pub-type="epub">2561-326X</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">v10i1e94673</article-id><article-id pub-id-type="doi">10.2196/94673</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Letter</subject></subj-group></article-categories><title-group><article-title>Physical Activity Monitoring Using Wearable Devices in Young Adults: Secondary Analysis of a 6-Month Motivational Interviewing Pilot Randomized Controlled Trial</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Christodoulakis</surname><given-names>Nicolette</given-names></name><degrees>BHSc</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Incze</surname><given-names>Taylor</given-names></name><degrees>BPH, MSc</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Khademioore</surname><given-names>Sahar</given-names></name><degrees>MSc</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Kwan</surname><given-names>Matthew</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="aff" rid="aff4">4</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Alvarez</surname><given-names>Elizabeth</given-names></name><degrees>MPH, MD, PhD</degrees><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Tarride</surname><given-names>Jean-&#x00C9;ric</given-names></name><degrees>MA, PhD</degrees><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff5">5</xref><xref ref-type="aff" rid="aff6">6</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Mbuagbaw</surname><given-names>Lawrence</given-names></name><degrees>MPH, MD, PhD</degrees><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff7">7</xref><xref ref-type="aff" rid="aff8">8</xref><xref ref-type="aff" rid="aff9">9</xref><xref ref-type="aff" rid="aff10">10</xref><xref ref-type="aff" rid="aff11">11</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Anderson</surname><given-names>Laura N</given-names></name><degrees>PhD</degrees><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff5">5</xref></contrib></contrib-group><aff id="aff1"><institution>Department of Health Research Methods, Evidence, and Impact, McMaster University</institution><addr-line>1280 Main Street West</addr-line><addr-line>Hamilton</addr-line><addr-line>ON</addr-line><country>Canada</country></aff><aff id="aff2"><institution>Department of Child and Youth Studies, Brock University</institution><addr-line>St. Catharines</addr-line><addr-line>ON</addr-line><country>Canada</country></aff><aff id="aff3"><institution>Department of Community Health Sciences, University of Calgary</institution><addr-line>Calgary</addr-line><addr-line>AB</addr-line><country>Canada</country></aff><aff id="aff4"><institution>School of Human Movement and Nutrition Science, The University of Queensland</institution><addr-line>Brisbane</addr-line><addr-line>Queensland</addr-line><country>Australia</country></aff><aff id="aff5"><institution>Centre for Health Economics and Policy Analysis (CHEPA), McMaster University</institution><addr-line>Hamilton</addr-line><addr-line>ON</addr-line><country>Canada</country></aff><aff id="aff6"><institution>Programs for Assessment of Technology in Health (PATH), The Research Institute of St. Joe&#x2019;s Hamilton, St. Joseph&#x2019;s Healthcare Hamilton</institution><addr-line>Hamilton</addr-line><addr-line>ON</addr-line><country>Canada</country></aff><aff id="aff7"><institution>Biostatistics Unit, Father Sean O&#x2019;Sullivan Research Centre, St. Joseph&#x2019;s Healthcare Hamilton</institution><addr-line>Hamilton</addr-line><addr-line>ON</addr-line><country>Canada</country></aff><aff id="aff8"><institution>Department of Anesthesia, McMaster University</institution><addr-line>Hamilton</addr-line><addr-line>ON</addr-line><country>Canada</country></aff><aff id="aff9"><institution>Department of Pediatrics, McMaster University</institution><addr-line>Hamilton</addr-line><addr-line>ON</addr-line><country>Canada</country></aff><aff id="aff10"><institution>Centre for Development of Best Practices in Health, Yaound&#x00E9; Central Hospital</institution><addr-line>Yaound&#x00E9;</addr-line><country>Cameroon</country></aff><aff id="aff11"><institution>Division of Epidemiology and Biostatistics, Department of Global Health, Stellenbosch University</institution><addr-line>Cape Town</addr-line><addr-line>Western Cape</addr-line><country>South Africa</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Mavragani</surname><given-names>Amaryllis</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Tilga</surname><given-names>Henri</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Fraser</surname><given-names>Matthew</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Nicolette Christodoulakis, BHSc, Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada, 1 (905) 525-9140; <email>chrisn8@mcmaster.ca</email></corresp></author-notes><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>16</day><month>7</month><year>2026</year></pub-date><volume>10</volume><elocation-id>e94673</elocation-id><history><date date-type="received"><day>04</day><month>03</month><year>2026</year></date><date date-type="rev-recd"><day>16</day><month>05</month><year>2026</year></date><date date-type="accepted"><day>31</day><month>05</month><year>2026</year></date></history><copyright-statement>&#x00A9; Nicolette Christodoulakis, Taylor Incze, Sahar Khademioore, Matthew Kwan, Elizabeth Alvarez, Jean-&#x00C9;ric Tarride, Lawrence Mbuagbaw, Laura N Anderson. Originally published in JMIR Formative Research (<ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>), 16.7.2026. </copyright-statement><copyright-year>2026</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 (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://formative.jmir.org/2026/1/e94673"/><abstract><p>In this secondary analysis of a pilot randomized controlled trial of university students aged 18 to 29 years, we assessed the feasibility of providing wearable devices to measure physical activity over 6 months, finding that daily adherence declined over time in both groups, while moderate and vigorous physical activity levels remained similar between the control and intervention groups.</p><sec><title>Trial Registration</title><p>ClinicalTrials.gov NCT05264740; https://clinicaltrials.gov/study/NCT05264740</p></sec><sec sec-type="registered-report"><title>International Registered Report Identifier (IRRID)</title><p>RR2-10.1186/s40814-023-01385-0</p></sec></abstract><kwd-group><kwd>fitness trackers</kwd><kwd>exercise</kwd><kwd>wearable electronic devices</kwd><kwd>motivational interviewing</kwd><kwd>pilot study</kwd><kwd>young adult</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Health behaviors, including physical activity (PA), are important across the life course for the prevention of chronic disease, with young adulthood representing a key period for establishing lifelong health behaviors [<xref ref-type="bibr" rid="ref1">1</xref>]. PA tends to decline during this transitory period [<xref ref-type="bibr" rid="ref2">2</xref>], yet few studies have reported device-based assessments of PA in young adults over a long-term period.</p><p>We conducted a pilot randomized controlled trial, Motivational Interviewing to Promote Healthy Behaviors for Obesity Prevention in Young Adults (MOTIVATE), to determine the feasibility of a 6-month behavioral and educational motivational interviewing (MI)&#x2013;based intervention. MI is a person-centered counseling method aimed at enhancing intrinsic motivation for behavior change [<xref ref-type="bibr" rid="ref3">3</xref>]. This paper examines a secondary aim of the trial by evaluating the feasibility of using wearable devices for monitoring PA throughout the 6-month study period. Feasibility outcomes included adherence to wearing the device and descriptive summaries of activity types.</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Overview</title><p>In this secondary analysis of a pilot randomized controlled trial, young adults aged 18 to 29 years attending McMaster University were randomized to an intervention or control group [<xref ref-type="bibr" rid="ref4">4</xref>,<xref ref-type="bibr" rid="ref5">5</xref>]. Intervention participants received monthly online individual MI sessions from a trained interviewer, along with educational materials. Control participants received educational materials only. The inclusion criteria were a BMI of 18.5 kg/m<sup>2</sup> or more, access to wireless internet at home, and able to speak English. The exclusion criteria included any physical or mental health conditions that were contraindications to participating in a weight management intervention (eg, eating disorders, pregnancy).</p></sec><sec id="s2-2"><title>Ethical Considerations</title><p>The trial was registered (ClinicalTrials.gov; NCT05264740), and the Hamilton Integrated Research Ethics Board approved the study (HiREB project 14675). All participants provided written informed consent, data were deidentified, and participants were compensated with CA $30 grocery gift cards for each completed questionnaire.</p></sec><sec id="s2-3"><title>Statistical Analysis</title><p>All participants received Fitbit Inspire 2 wearable devices to monitor PA throughout the trial. Data were synced to participants&#x2019; Fitbit accounts and retrieved by the research team via Fitabase [<xref ref-type="bibr" rid="ref6">6</xref>], which provides minute-level data collection. Based on prior literature [<xref ref-type="bibr" rid="ref7">7</xref>], daily adherence was defined as 10 hours or more of wear time per day, determined by heart rate detection. PA intensity was categorized as light (1.5&#x2010;3 metabolic equivalents [METs]), moderate (3&#x2010;6 METs), and vigorous (&#x2265;6 METs) [<xref ref-type="bibr" rid="ref8">8</xref>]. Weekly adherence was calculated for each participant as a 7-day moving average of daily adherence. Daily hours spent in each intensity category were calculated and averaged. Results are presented by month since randomization and by intervention group. Formal comparisons using statistical tests were not conducted due to limited power and an a priori decision to report secondary outcomes descriptively [<xref ref-type="bibr" rid="ref4">4</xref>]. Participants also answered two Fitbit-related questions assessing prior experience at baseline and perceived usefulness at the end of the study (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). Continuous variables were summarized as means (SDs) or medians (IQRs) and categorical variables as counts (percentages).</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><p>Of 120 individuals assessed for eligibility, 101 participants were randomized, and 5 were excluded due to missing Fitabase data (Supplementary Figure 1 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>), resulting in a final analytic sample of 96 participants (46 control and 50 intervention). The flow diagram for the parent trial is shown in Supplementary Figure 2 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>.</p><p>Baseline characteristics were similar in control and intervention groups (<xref ref-type="table" rid="table1">Table 1</xref>). Among 96 participants, the mean age was 22.4 (SD 3.6) years, with 38.5% (n=37) identifying as men, 51.0% (n=49) as women, 2.1% (n=2) as genderqueer/nonbinary, and 8.3% (n=8) preferring not to disclose their gender. At baseline, 60.4% (n=58) of participants reported never having used a fitness tracker or health application. By the end of the study, 57.3% (n=55) indicated that using the Fitbit helped them improve their health behaviors (Supplementary Table 1 in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>).</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Baseline characteristics of study population.</p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Characteristic</td><td align="left" valign="bottom">Total (N=96)</td><td align="left" valign="bottom">Control (n=46)</td><td align="left" valign="bottom">Intervention (n=50)</td></tr></thead><tbody><tr><td align="left" valign="top">Age (years), mean (SD)</td><td align="left" valign="top">22.4 (3.6)</td><td align="left" valign="top">23.0 (3.6)</td><td align="left" valign="top">21.8 (3.5)</td></tr><tr><td align="left" valign="top" colspan="4">Gender, n (%)</td></tr><tr><td align="left" valign="top">&#x2003;Man</td><td align="left" valign="top">37 (38.5)</td><td align="left" valign="top">20 (43.5)</td><td align="left" valign="top">17 (34.0)</td></tr><tr><td align="left" valign="top">&#x2003;Woman</td><td align="left" valign="top">49 (51.0)</td><td align="left" valign="top">24 (52.2)</td><td align="left" valign="top">25 (50.0)</td></tr><tr><td align="left" valign="top">&#x2003;Genderqueer/nonbinary</td><td align="left" valign="top">2 (2.1)</td><td align="left" valign="top">0 (0.0)</td><td align="left" valign="top">2 (4.0)</td></tr><tr><td align="left" valign="top">&#x2003;Prefer not to say or don&#x2019;t know</td><td align="left" valign="top">8 (8.3)</td><td align="left" valign="top">2 (4.3)</td><td align="left" valign="top">6 (12.0)</td></tr><tr><td align="left" valign="top" colspan="4">Race, n (%)</td></tr><tr><td align="left" valign="top">&#x2003;South Asian</td><td align="left" valign="top">27 (28.1)</td><td align="left" valign="top">11 (23.9)</td><td align="left" valign="top">16 (32.0)</td></tr><tr><td align="left" valign="top">&#x2003;Middle Eastern</td><td align="left" valign="top">26 (27.1)</td><td align="left" valign="top">17 (37.0)</td><td align="left" valign="top">9 (18.0)</td></tr><tr><td align="left" valign="top">&#x2003;East and Southeast Asian</td><td align="left" valign="top">20 (20.8)</td><td align="left" valign="top">10 (21.7)</td><td align="left" valign="top">10 (20.0)</td></tr><tr><td align="left" valign="top">&#x2003;Black, Latino, Mixed, or another race</td><td align="left" valign="top">10 (10.4)</td><td align="left" valign="top">4 (8.7)</td><td align="left" valign="top">6 (12.0)</td></tr><tr><td align="left" valign="top">&#x2003;White</td><td align="left" valign="top">10 (10.4)</td><td align="left" valign="top">4 (8.7)</td><td align="left" valign="top">6 (12.0)</td></tr><tr><td align="left" valign="top">&#x2003;Prefer not to say</td><td align="left" valign="top">3 (3.1)</td><td align="left" valign="top">0 (0.0)</td><td align="left" valign="top">3 (6.0)</td></tr><tr><td align="left" valign="top">BMI (kg/m<sup>2</sup>), mean (SD)</td><td align="left" valign="top">25.0 (4.9)</td><td align="left" valign="top">25.6 (5.4)</td><td align="left" valign="top">24.4 (4.3)</td></tr></tbody></table></table-wrap><p>Most participants (91.7%) had at least one adherent day during the study, including 40 of 46 in the control group and 48 of 50 in the intervention group. The median adherent days were 73.0 (IQR 122.0) for the control group and 80.5 (IQR 121.5) for the intervention group. Adherence declined steadily over the 6-month study period in both groups. The intervention group showed higher adherence than the control group, except during the fifth month, when adherence was similar in both groups (<xref ref-type="fig" rid="figure1">Figure 1A</xref>). In terms of PA intensity, there was some variation in light activity, whereas time spent in moderate and vigorous activity remained relatively stable in both groups (<xref ref-type="fig" rid="figure1">Figure 1B</xref>). On average, participants spent 2.0 to 2.6 hours per day in light activity, 0.2 to 0.3 hours in moderate activity, and 0.2 to 0.4 hours in vigorous activity.</p><fig position="float" id="figure1"><label>Figure 1.</label><caption><p>(A) Box plots of the distribution of daily group-level 7-day rolling adherence to wearing the Fitbit, and (B) line plots of average daily hours spent on different types of activity by month since randomization and intervention group.</p></caption><graphic alt-version="no" mimetype="image" position="float" xlink:type="simple" xlink:href="formative_v10i1e94673_fig01.png"/></fig></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><p>We observed variability in Fitbit adherence, with the intervention group demonstrating higher adherence than the control group. Adherence declined substantially in both groups over the 6 months, but moderate and vigorous PA levels remained comparable. Additionally, more than half of the participants reported that using the Fitbit helped improve their health behaviors.</p><p>These findings are broadly consistent with a previous review among healthy adults that reported that wearable activity trackers were associated with modest increases in PA [<xref ref-type="bibr" rid="ref9">9</xref>], suggesting that such devices can positively influence behavior, particularly in the short-term. In contrast, a review of children and adolescents found no significant improvements in moderate-to-vigorous activity compared with control groups [<xref ref-type="bibr" rid="ref10">10</xref>]. This highlights that the effectiveness of wearable devices may vary by population and context. Nonadherence, noncompliance, and reduced engagement with the device over time were common limitations across studies [<xref ref-type="bibr" rid="ref10">10</xref>], consistent with our observations.</p><p>While wearable devices allow continuous monitoring of PA, our results raise questions regarding their long-term feasibility in trial settings. Although moderate and vigorous PA levels appeared stable over time, this may reflect selection bias, as participants with longer follow-up periods were more engaged. Despite gift cards for questionnaire completion (twice per month), adherence declined, suggesting that longer interventions may require additional engagement strategies such as personalized feedback, behavioral prompts, or counseling-based approaches. Given the short duration of previous wearable device studies [<xref ref-type="bibr" rid="ref10">10</xref>], future trials with longer intervention periods, such as our 6-month design, are needed to assess sustained behavior change. Our findings provide valuable insight into the feasibility of integrating wearables into behavior change interventions. Overall, wearables show clear potential for scalable application in public health, postsecondary education, and primary care settings, where early prevention is crucial.</p></sec></body><back><notes><sec><title>Funding</title><p>This work was funded by a Proof-of-Concept Intervention Grant in Primary Prevention of Cancer (Action Grant) of the Canadian Cancer Society (grant 707228) and the Canadian Institutes of Health Research&#x2013;Institute for Cancer Research (grant #POC-181032).</p></sec><sec><title>Data Availability</title><p>The datasets analyzed in this study are not publicly available due to the confidential nature of the information provided by participants randomized in this trial.</p></sec></notes><fn-group><fn fn-type="conflict"><p>None declared.</p></fn></fn-group><glossary><title>Abbreviations</title><def-list><def-item><term id="abb1">MET</term><def><p>metabolic equivalent</p></def></def-item><def-item><term id="abb2">MI</term><def><p>motivational 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eligibility/randomization flow and participant Fitbit-related responses.</p><media xlink:href="formative_v10i1e94673_app1.docx" xlink:title="DOCX File, 162 KB"/></supplementary-material><supplementary-material id="app2"><label>Checklist 1</label><p>CONSORT-EHEALTH (V 1.6.1) checklist.</p><media xlink:href="formative_v10i1e94673_app2.pdf" xlink:title="PDF File, 888 KB"/></supplementary-material></app-group></back></article>