{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T08:21:55Z","timestamp":1772180515863,"version":"3.50.1"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T00:00:00Z","timestamp":1772150400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Physical inactivity is a critical factor exacerbating obstructive sleep apnea (OSA) and its associated comorbidities. Previous evidence has largely relied on subjective questionnaires, leading to a lack of definitive evidence based on objective measurements. This study aimed to systematically evaluate the effects of digital health interventions (DHIs) on objective physical activity, body composition, and sleep parameters in OSA patients, while further exploring the efficacy differences between active intervention and passive monitoring modes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A systematic search was conducted across five major databases (including PubMed and Embase) and registration platforms up to November 19, 2025. Only randomized controlled trials (RCTs) that assessed physical activity using objective tools were included. Bias was evaluated using the Cochrane Risk of Bias Tool 2.0 (RoB 2.0), and the quality of evidence was graded using the GRADE system. Statistical analyses utilized random-effects models to calculate Mean Differences (MD) and 95% Confidence Intervals (CI). Subgroup analyses were performed based on a refined classification of intervention modes, accounting for interaction patterns, theoretical foundations, and the application of behavior change techniques (BCTs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of seven randomized controlled trials involving 693 patients were included. Overall meta-analyses revealed no statistically significant differences between digital interventions and standard care in increasing daily steps (MD = 86.94,\n                      <jats:italic>P<\/jats:italic>\n                      = 0.85), reducing body mass index (\n                      <jats:italic>P<\/jats:italic>\n                      = 0.74), improving the Apnea-Hypopnea Index (\n                      <jats:italic>P<\/jats:italic>\n                      = 0.31), or alleviating somnolence (\n                      <jats:italic>P<\/jats:italic>\n                      = 0.15). However, telerehabilitation-based interventions significantly improved peak oxygen uptake [MD = 342.41 ml\/min, 95% CI (38.05, 646.77)]. Exploratory subgroup analyses and individual study data suggested that active intervention modes characterized by synchronous interaction or theory-driven protocols showed a greater tendency for weight loss compared to passive monitoring and significantly increased absolute step counts during the intervention period (\n                      <jats:italic>P<\/jats:italic>\n                      = 0.02). The overall quality of evidence for the primary outcomes was rated as low to moderate.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Current evidence suggests that the application of digital health technology alone may be insufficient to significantly alter objective step counts or clinical outcomes in OSA patients, which might be largely attributed to the prevalence of passive monitoring modes lacking deep interaction in current studies14. Nevertheless, the physiological benefits observed in VO\n                      <jats:sup>2<\/jats:sup>\n                      max reveal the unique value of these interventions, and active modes integrating closed-loop feedback show potential in driving behavioral changes compared to passive monitoring. Future clinical strategies should shift toward theory-driven active interaction modes that integrate core BCTs, potentially providing a new pathway to further improve long-term cardiovascular prognosis beyond traditional treatments.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Systematic review registration<\/jats:title>\n                    <jats:p>\n                      [\n                      <jats:ext-link>www.crd.york.ac.uk\/prospero<\/jats:ext-link>\n                      ], identifier [CRD420251246601].\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1760571","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:52:36Z","timestamp":1772175156000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["From passive monitoring to active engagement: a systematic review and meta-analysis of digital health technologies for improving objective physical activity and cardiorespiratory fitness in patients with obstructive sleep apnea"],"prefix":"10.3389","volume":"14","author":[{"given":"Jingkang","family":"Xia","sequence":"first","affiliation":[{"name":"School of Competitive Sport, Shandong Sport University","place":["Rizhao, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayi","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Physical Education, China University of Mining and Technology","place":["Xuzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haozhe","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Physical Education, China University of Mining and Technology","place":["Xuzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongliang","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Competitive Sport, Shandong Sport University","place":["Rizhao, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lihong","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Competitive Sport, Shandong Sport University","place":["Rizhao, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueqiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Competitive Sport, Shandong Sport University","place":["Rizhao, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,2,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1016\/S2213-2600(19)30198-5","article-title":"Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis","volume":"7","author":"Benjafield","year":"2019","journal-title":"Lancet Respir 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