Effects of Self-Guided Digital Mindfulness Interventions on the Mental Health of Health Care Workers: Systematic Review and Meta-Analysis of Randomized Controlled Trials.
{"title":"Effects of Self-Guided Digital Mindfulness Interventions on the Mental Health of Health Care Workers: Systematic Review and Meta-Analysis of Randomized Controlled Trials.","authors":"Natsu Sasaki, Akiomi Inoue, Mako Iida, Kazuhiro Watanabe, Yuka Kobayashi, Asuka Sakuraya, Hisashi Eguchi, Kanami Tsuno, Yu Komase, Yasumasa Otsuka, Mai Iwanaga, Reiko Inoue, Kazuto Kuribayashi, Ayako Hino, Hiroki Asaoka, Satoru Kanamori, Yuta Inagawa, Takenori Yamauchi, Hiroki Ikeda, Go Muto, Rika Kato, Takuro Okuyama, Naomichi Tani, Noriko Kojimahara, Takeshi Ebara, Akihito Shimazu, Akizumi Tsutsumi, Norito Kawakami, Kotaro Imamura","doi":"10.2196/74272","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Mindfulness interventions are considered an effective strategy for preventing mental health problems among health care workers (HCWs). While prior reviews have often included facilitator-guided or multicomponent interventions, it is unclear whether self-guided digital mindfulness interventions can also be effective without professional or in-person support.</p><p><strong>Objective: </strong>This systematic review aimed to investigate the effects of self-guided digital mindfulness interventions on the mental health and well-being of HCWs.</p><p><strong>Methods: </strong>This work was conducted as part of the DeLiGHT project. We searched electronic databases, including PubMed (MEDLINE), Embase, Cochrane CENTRAL, PsycINFO, PsycARTICLES, and the Japan Medical Abstract Society database, from inception in 2010 to July 25, 2023. To ensure timeliness, we performed an updated search on December 27, 2025. Database searching yielded 37,851 abstracts and 145 studies that examined the effectiveness of digital health interventions for workers in the initial 2023 screen. In the present study, we limited the included studies to those that met the following criteria: randomized controlled trials (RCTs) using self-guided digital mindfulness interventions (eg, smartphone apps or web-based programs) delivered without face-to-face or professional support compared to waiting list controls or usual care among HCWs. The updated search in 2025 yielded 6328 additional records, of which 11 studies were examined. Study quality was assessed using the Cochrane Risk of Bias tool, with meta-analyses conducted using a random-effects model.</p><p><strong>Results: </strong>A total of 9 RCTs with 3088 participants were included in the final analysis. The study populations were diverse, covering North America, Europe, Oceania, and Asia. Interventions were delivered via various digital platforms, including commercial mindfulness apps (n=3), social networking service tools (n=3), and web-based programs (n=3), with an average duration of 6.17 weeks (range: 1.5-18 wk). Five studies assessed outcomes only postintervention, and 4 included short-term follow-up (4-12 wk); no long-term effects were evaluated. The meta-analysis showed a significant beneficial effect on depression (standardized mean difference [SMD]=-0.44, 95% CI -0.88 to -0.00; <i>P</i>=.049), anxiety (SMD=-0.29, 95% CI -0.51 to -0.06; <i>P</i>=.011), perceived stress (SMD=-0.42, 95% CI -0.77 to -0.06; <i>P</i>=.02), and well-being (SMD=0.20, 95% CI 0.09 to 0.30; <i>P</i><.001) immediately postintervention. The adherence rates reported across studies were highly variable, ranging from 19% to 56%. According to the Cochrane Risk of Bias tool, most studies were rated as having some concerns or a high risk of bias. The certainty of evidence included in the analysis ranged from \"Low\" to \"Very Low.\"</p><p><strong>Conclusions: </strong>Overall, low to very low certainty evidence suggests that self-guided digital mindfulness interventions may have short-term beneficial effects on depression, anxiety, perceived stress, and well-being among HCWs. Future high-quality studies are needed to examine the long-term effects and cross-cultural generalizability of these interventions.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e74272"},"PeriodicalIF":6.3000,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494152/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR mHealth and uHealth","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/74272","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Mindfulness interventions are considered an effective strategy for preventing mental health problems among health care workers (HCWs). While prior reviews have often included facilitator-guided or multicomponent interventions, it is unclear whether self-guided digital mindfulness interventions can also be effective without professional or in-person support.
Objective: This systematic review aimed to investigate the effects of self-guided digital mindfulness interventions on the mental health and well-being of HCWs.
Methods: This work was conducted as part of the DeLiGHT project. We searched electronic databases, including PubMed (MEDLINE), Embase, Cochrane CENTRAL, PsycINFO, PsycARTICLES, and the Japan Medical Abstract Society database, from inception in 2010 to July 25, 2023. To ensure timeliness, we performed an updated search on December 27, 2025. Database searching yielded 37,851 abstracts and 145 studies that examined the effectiveness of digital health interventions for workers in the initial 2023 screen. In the present study, we limited the included studies to those that met the following criteria: randomized controlled trials (RCTs) using self-guided digital mindfulness interventions (eg, smartphone apps or web-based programs) delivered without face-to-face or professional support compared to waiting list controls or usual care among HCWs. The updated search in 2025 yielded 6328 additional records, of which 11 studies were examined. Study quality was assessed using the Cochrane Risk of Bias tool, with meta-analyses conducted using a random-effects model.
Results: A total of 9 RCTs with 3088 participants were included in the final analysis. The study populations were diverse, covering North America, Europe, Oceania, and Asia. Interventions were delivered via various digital platforms, including commercial mindfulness apps (n=3), social networking service tools (n=3), and web-based programs (n=3), with an average duration of 6.17 weeks (range: 1.5-18 wk). Five studies assessed outcomes only postintervention, and 4 included short-term follow-up (4-12 wk); no long-term effects were evaluated. The meta-analysis showed a significant beneficial effect on depression (standardized mean difference [SMD]=-0.44, 95% CI -0.88 to -0.00; P=.049), anxiety (SMD=-0.29, 95% CI -0.51 to -0.06; P=.011), perceived stress (SMD=-0.42, 95% CI -0.77 to -0.06; P=.02), and well-being (SMD=0.20, 95% CI 0.09 to 0.30; P<.001) immediately postintervention. The adherence rates reported across studies were highly variable, ranging from 19% to 56%. According to the Cochrane Risk of Bias tool, most studies were rated as having some concerns or a high risk of bias. The certainty of evidence included in the analysis ranged from "Low" to "Very Low."
Conclusions: Overall, low to very low certainty evidence suggests that self-guided digital mindfulness interventions may have short-term beneficial effects on depression, anxiety, perceived stress, and well-being among HCWs. Future high-quality studies are needed to examine the long-term effects and cross-cultural generalizability of these interventions.
背景:正念干预被认为是预防卫生保健工作者(HCWs)心理健康问题的有效策略。虽然之前的评论通常包括辅导员指导或多成分干预,但尚不清楚自我指导的数字正念干预是否在没有专业或亲自支持的情况下也能有效。目的:本系统综述旨在探讨自我引导的数字正念干预对医护人员心理健康和幸福感的影响。方法:本工作作为DeLiGHT项目的一部分进行。我们检索了电子数据库,包括PubMed (MEDLINE)、Embase、Cochrane CENTRAL、PsycINFO、PsycARTICLES和日本医学文摘协会数据库,检索时间从2010年成立到2023年7月25日。为了确保时效性,我们在2025年12月27日进行了更新搜索。数据库搜索产生了37,851份摘要和145项研究,这些研究检查了2023年初期对工人进行数字健康干预的有效性。在本研究中,我们将纳入的研究限制为符合以下标准的研究:随机对照试验(rct)使用自我引导的数字正念干预(例如,智能手机应用程序或基于网络的程序),与等候名单对照或常规护理相比,在医护人员中没有面对面或专业支持。2025年的更新搜索产生了6328个额外的记录,其中11个研究进行了检查。使用Cochrane偏倚风险工具评估研究质量,并使用随机效应模型进行meta分析。结果:最终分析共纳入9项rct,共3088名受试者。研究人群多种多样,包括北美、欧洲、大洋洲和亚洲。干预措施通过各种数字平台提供,包括商业正念应用程序(n=3),社交网络服务工具(n=3)和基于网络的程序(n=3),平均持续时间为6.17周(范围:1.5-18周)。5项研究仅评估干预后的结果,4项研究包括短期随访(4-12周);没有评估长期影响。meta分析显示,对抑郁(标准化平均差[SMD]=-0.44, 95% CI -0.88至-0.00;P= 0.049)、焦虑(SMD=-0.29, 95% CI -0.51至-0.06;P= 0.011)、感知压力(SMD=-0.42, 95% CI -0.77至-0.06;P= 0.02)和幸福感(SMD=0.20, 95% CI 0.09至0.30;结论:总体而言,低至极低确定性的证据表明,自我引导的数字正念干预可能对医护人员的抑郁、焦虑、感知压力和幸福感有短期有益影响。未来需要高质量的研究来检验这些干预措施的长期效果和跨文化的普遍性。
期刊介绍:
JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636.
The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics.
JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.