https://orcid.org/0000-0002-5342-0709
Figures
Abstract
Research shows that over 70% of individuals globally who require mental health services lack access to adequate care. Mobile health (mHealth) technologies, such as phone apps, can be a potential solution to this issue by enabling broader and more affordable reach, thus addressing the problem of limited access to care. This study evaluates the effectiveness of evidence-based health apps on user mental health outcomes, particularly depression, anxiety, and suicidal behaviors. A comprehensive literature search was conducted using PubMed, Web of Science, and IEEE databases. In total, 6894 studies were identified, and 38 studies were selected for the review—thirty out of 38 studies employed randomized controlled trial designs. We identified 35 unique mobile apps. All the apps leveraged Cognitive Behavioral Therapy-based approaches. The most common approaches were context engagement and cognitive change, highlighting a significant focus on using personalized engagement activities and empowering users to alter their perspectives and reframe negative thoughts to improve their mental health. While mental health apps generally positively impact mental health outcomes, the findings also highlight significant variability in their effectiveness. Future studies should prioritize long-term effectiveness, wider reach to ensure it suits a diverse range of people, and the employment of objective evaluation methodologies.
Citation: Shahsavar Y, Choudhury A (2025) Effectiveness of evidence based mental health apps on user health outcome: A systematic literature review. PLoS ONE 20(3): e0319983. https://doi.org/10.1371/journal.pone.0319983
Editor: Ethan Moitra,, Brown University, UNITED STATES OF AMERICA
Received: July 25, 2024; Accepted: February 11, 2025; Published: March 25, 2025
Copyright: © 2025 Shahsavar, Choudhur. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting information files.
Funding: This work was supported by the West Virginia University Internal Seed Grant (#3086). "The funders had no role in study design, data collection and analysis, decision to publish, or manuscript preparation.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Mental health issues have become a significant global public health concern [1]. The World Health Organization (WHO) has projected that by 2030, mental illness will become the primary global disease burden [2]. A systematic review indicated that approximately 14.3% of deaths worldwide, equivalent to around eight million deaths annually, are linked to mental disorders [3]. In the European Union region, an estimated 165 million individuals are affected by mental illnesses each year, predominantly anxiety, mood, and substance abuse disorders [4]. Additionally, a study conducted in Ethiopia revealed that individuals with severe mental health problems have life expectancies 30 years shorter than those without such conditions [5]. Globally, nearly one million people die by suicide annually, with three-quarters of individuals with mental health problems residing in low- and middle-income countries, where less than one in ten receive evidence-based treatment [5]. In the USA, suicide ranks as the second leading cause of death among university students [6]. Additionally, it is estimated that by 2023, mental health-induced reduction in productivity will cost the global economy approximately $16 trillion [7]. While precise global figures on the prevalence of mental health problems may vary, the available data indicate a significant burden of mental disorders worldwide.
Research shows that over 70% of individuals globally who require mental health services lack access to adequate care, contributing to a widening mental health treatment gap [8]. Various barriers hinder individuals from receiving optimal mental health care [9]. System-level barriers, such as difficulties in detecting mental health concerns, limited availability of services, inconsistent pathways to care, and affordability issues, continue to impede access to mental health services [10–13]. Furthermore, stigma, lack of awareness, sociocultural factors, and geographical inaccessibility act as significant barriers that prevent individuals from utilizing mental health services [14,15]. Efforts to enhance access to care have been explored by implementing collaborative care models and integrated service delivery approaches [16,17]. However, challenges persist, such as limited resources in rural areas, disparities in resource distribution, and inadequate support for vulnerable populations [18,19]. The COVID-19 pandemic has further highlighted the inadequacies in mental health care accessibility, leading to a global mental health crisis [20–22].
Efforts to enhance global mental health include increasing access to mental health services [23]. Mobile health (mHealth) technologies, such as phone apps, can be a potential solution to this issue by enabling broader and more affordable reach, thus addressing the problem of limited access to care [24–26]. The rapid increase in the use of mobile phone applications has created an opportunity to enhance access to evidence-based care [27]. In 2018, approximately 325,000 mobile health apps were available, with about 200 being launched daily [28]. mHealth apps have provided new avenues to reach populations that were previously challenging to access through traditional healthcare channels [29]. The scalability of app-based interventions has been suggested as a strategy to tackle the global burden of mental illnesses and offer services to individuals who may have had limited access to care [30]. Studies have indicated that mobile apps can effectively screen for mental health conditions, such as depression, and encourage users with high depressive symptoms to seek help from healthcare professionals [31].
However, there is a lack of understanding about the types of mHealth apps that are effective beyond screening. Existing research highlights that most publicly available mental health apps are not evidence-based and may even pose risks to users [26,32]. A 2022 study points out methodological issues and a lack of robust evidence regarding the effectiveness of these apps in changing behaviors or improving clinical outcomes [33]. Few existing reviews in this field have focused on the feasibility of various apps designed for agoraphobia, eating disorders, post-traumatic stress disorders, substance use disorders, and sleep disorders [34,35]. However, there is a lack of evidence reviewing the effectiveness of mobile apps in improving mental health outcomes [36,37].
In our review, we focused on the effectiveness of evidence-based apps designed using both randomized and non-randomized controlled trials to influence user mental health outcomes, particularly depression, anxiety, and suicidal behaviors. Our review discusses the methodology leveraged by such apps to improve mental health.
Methods
This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines (see S1 File) [38]. The detailed protocol (osf.io/x6m7u) is registered at the Open Science Framework [39].
Search strategy
The search strategy was developed based on People, Intervention, Comparison, and Outcome (PICO) criteria. The population was participants using a mobile app designed to reduce mental health problems; the outcome was the impact of the app on user mental health; the intervention was a mobile app; the comparison was made by classifying the interventions based on their functions and user health outcome. A comprehensive literature search was conducted in PubMed, Web of Science, and IEEE Xplore for relevant articles. The search query consisted of the following: ((Depression OR anxiety OR suicid*) AND (Mobile OR app OR smartphone)) NOT (sleep OR alcohol OR drugs OR addiction OR tobacco) (see S2 File).
Inclusion and exclusion criteria
Studies published in English and within the last ten years (January 2013 to September 2023) were included. We only included peer-reviewed clinical trial study designs that used mobile mental health apps to improve mental health outcomes. We focused on apps designed to address depression, anxiety, and suicidal behavior. Any article that did not assess the impact of an app on user mental health outcomes and solely focused on screening, app feasibility, or app development was eliminated. We also excluded apps that facilitated telehealth by connecting users with a clinician.
The methodology for selecting studies involved a multi-step process. Two authors independently selected the studies using the inclusion and exclusion criteria. Conflicts were then resolved with discussion, without the involvement of third parties. First, duplicates were identified and removed using Excel sheets created from the database exports. Titles of potentially relevant studies were then screened manually to eliminate irrelevant articles. A review of abstracts followed this to exclude studies that did not use mobile phone technology, did not focus on mental health apps, lacked emphasis on treatment or mental health impact, or addressed unrelated topics like mobile or technology addiction. Finally, full-text studies were evaluated against the inclusion and exclusion criteria.
Data collection
For each article included in the final review, we recorded their objective, study design, participant age, survey instrument used by the study, mobile app name, its function, and the study’s primary outcome. These data were extracted at face value, as reported in the reviewed articles. The app functions were then mapped to the principles of Cognitive Behavioral Therapy (CBT), mainly (a) context engagement, (b) attention change, and (c) cognitive change [40]. Context engagement focuses on helping people develop healthier associative learning patterns. Individuals are taught to recognize and respond to cues for threats and rewards in a more balanced and realistic way, leading to improved functioning. Attention changes technique aims to train individuals to direct their attention toward relevant, non-distressing stimuli. It includes therapeutic practices such as attention training, acceptance or tolerance training, and mindfulness. Cognitive change involves helping individuals shift their perspective on events to alter the emotional significance they attach to those events [41]. Methods like cognitive reframing and decentering are commonly used.
Quality assessment and risk of bias
We conducted a quality assessment of the papers following the Mixed Methods Appraisal Tool (MMAT) (see S3 File) [42]. The MMAT assesses the quality of qualitative, quantitative, and mixed methods studies. It focuses on methodological criteria and includes the nature of the study (randomized or nonrandomized clinical trial) across the performance, detection, attrition, and selection biases. No articles were excluded.
Results
Study selection and characteristics
Of the 9,547 abstracts initially identified, 2642 duplicates were removed. Of the remaining 6894 articles, 508 review articles were eliminated. We also eliminated 5982 of the remaining articles based on title screening. These articles were not at all related to our topic of interest. From the remaining 404 articles, 351 were eliminated after abstract screening (studies with no mobile app = 114; studies not about suicide, depression, or anxiety = 47; studies focused only on mental health assessment = 82; studies about phone addiction = 23; telehealth apps = 36; studies focusing only on usability = 49). The remaining 53 full texts were screened, of which 15 were eliminated (telehealth app = 6; no mobile app used = 2; no treatment outcome reported = 7). Fig 1 shows the final 38 full-text articles that met the inclusion criteria for the current systematic review (see S4 File).
Table 1 summarizes the objectives, study design, participants, and survey instruments. We identified 35 unique mobile apps across 38 studies. Thirty-five studies (32 apps) report significant improvements in depressive symptoms [43–66], anxiety [43–45,50–52,54,55,58,60–62,67–75], and suicidal behavior [52,76,77]. Thirty studies employed randomized controlled trial (RCT) designs [43–49,54–60,62–73,75–78], while the other eight clinical trial studies used a non-randomized controlled design [50–53,61,74,79,80].
Mobile health apps characteristics
Table 2 introduces all the apps identified in the review and summarizes the CBT functions they use. We identified 3 CBT approaches: Context engagement, attention change, and cognitive change being used by the studies. Cognitive change was the most commonly used approach, implemented in 30 apps, followed by context engagement in 24 apps and attention change in 23 apps.
Context engagement
We identified 24 apps that used context engagement methods like video playback, motivational words, guided self-assessments, physical activity tracking, daily health tips, and gamified challenges. Using context engagement approach, 17 apps were effective in reducing depression symptom: Smartphone Positive Stimuli Response System (SPSRS) [44,53], indoor exercise (IE) app [43], the ibobbly app [46], the Problem-Solving Therapy (iPST) app [47], Mood Mission app [51,67], Blue Ice app [52], Headspace [48,49], Smiling Mind [48], Mello App [54], Coping Camp app [55], Down Dog app [56], eQuoo app [60], MindLAMP app [61], FertiStrong app [62], Welzen app [63], We’ll App [65], MoodHacker app [66].
The following 15 apps also reduced anxiety: Smartphone Positive Stimuli Response System (SPSRS) [44], indoor exercise (IE) app [43], Mood Mission app [51], Blue Ice app [52], Insight Timer app [68], Mello App [54], Coping Camp app [55], COVID Coach [70], ImExposure (IE) app [71], Headspace [72,73], eQuoo app [60], MindLAMP app [61], FertiStrong app [62], Aware App [74], Flowy [75].
Furthermore, the Therapeutic Evaluative Conditioning (TEC) app [76] was found to reduce suicidal plans and behaviors, the Loving-Kindness Meditation (LKM) app [77] was found to reduce suicidal ideation, and Blue Ice app [52] users reported a reduction in self-harm symptoms.
Attention change
Twenty-three apps used attention change techniques such as mindfulness, acceptance, self-soothing techniques, and attention bias modification training to improve mental health. The ibobbly app [46], Feel Stress Free app [45], MoodMission app [51,57], BlueIce app [52], Headspace [48,49] and Smiling Mind [48], Mello App [54], Coping Camp app [55], Down Dog app [56], Anchored app [58], Subliminal Priming with Supraliminal Reward Stimulation (SPSRS) [59], eQuoo app [60], MindLAMP app [61], Welzen app [63], We’ll App [65], and MoodHacker app [66] showed a positive effect in reducing depression.
MoodMission app [51], BlueIce app [52], Feel Stress Free app [45], Insight Timer app [68] Mello App [54], Coping Camp app [55], GAMA-AIMS [69], COVID Coach [70], Anchored app [58], ImExposure (IE) app [71], Headspace [72,73], eQuoo app [60], MindLAMP app [61], Aware App [74], Flowy [75] also showed a positive effect in reducing anxiety. Moreover, participants using the Loving-Kindness Meditation (LKM) app [77] reported a reduction in suicidal ideation. However, ABMT was not effective in improving depression and anxiety [78].
Cognitive change
Thirty apps used cognitive change techniques like goal setting, adaptive challenges, structured problem-solving, motivational video playback, mood tracking, and interpretation bias training. Nineteen of these apps showed a positive effect in reducing depression, including the ibobbly app [46], the Cognitive Control (Project: EVO) [47], the Problem-Solving Therapy (iPST) app [47], Smartphone Positive Stimuli Response System (SPSRS) application [44,53], Feel Stress Free app [45], MoodPrism app [50], MoodMission app [51,57], BlueIce app [52], Headspace [48,49] and Smiling Mind [48], Mello App [54], Coping Camp app [55], Anchored app [58], Subliminal Priming with Supraliminal Reward Stimulation (SPSRS) [59], eQuoo app [60], MindLAMP app [61], FertiStrong app [62], CareMom app [64], MoodHacker app [66].
Out of 30, 19 apps had a positive impact on anxiety levels, including the Smartphone Positive Stimuli Response System (SPSRS) application [44], Feel Stress Free app [45], MoodPrism app [50], Interpretation Bias Evaluation app [67], MoodMission app [51], Insight Timer app [68], BlueIce app [52], Mello App [54], Coping Camp app [55], GAMA-AIMS [69], COVID Coach [70], Anchored app [58], ImExposure (IE) app [71], Headspace [72,73], eQuoo app [60], MindLAMP app [61], FertiStrong app [62], Aware App [74], and Flowy [75]. The BlueIce app [52] and the Loving-Kindness Meditation (LKM) app [77] reduced self-harm symptoms and suicide ideation, respectively. Similarly, the TEC app [76] demonstrated a significant decrease in self-cutting episodes, suicide plans, and suicidal behaviors. In contrast, the Mental App [79]and MindSurf app [80] did not significantly improve mental health.
As detailed in Table 3, we identified 71 unique survey instruments used by different studies in the review. Among these, the Patient Health Questionnaire-9 (PHQ-9; n = 10), Generalized Anxiety Disorder-7 (GAD-7; n = 16), and Depression Anxiety Stress Scales-21 (DASS-21; n = 5) were the most frequently used.
Discussion
Our review investigates the impact of mHealth apps in mitigating mental health issues, focusing on depression, anxiety, and suicidal behaviors. Our findings show that context engagement and cognitive change techniques are the most effective CBT methods for mental health apps.
Our review also highlights a gap in the efficacy of mHealth apps for managing more complex mental health conditions, such as suicidal behaviors, where evidence remains scant and less definitive. Only a few apps specifically target suicidal ideation or behaviors. For example, among the apps reviewed, BlueIce, the Loving-Kindness Meditation (LKM) app, and the Therapeutic Evaluative Conditioning (TEC) app include features designed to help users manage self-harming and suicidal thoughts. These apps employ distress tolerance techniques, mood tracking, and crisis management features to address suicidal behaviors, but the evidence supporting their efficacy remains preliminary. This mirrors concern in the broader literature about the challenges of addressing high-risk mental health conditions through app-based interventions alone.
Our findings underscore the potential of mHealth applications in providing adequate mental health interventions. For populations in remote or underserved regions, where traditional mental health services are scarce or non-existent, mHealth apps can offer a viable avenue for receiving support [81]. Apps that provide self-monitoring and self-help strategies enable users to begin addressing their mental health issues in the early stages, potentially preventing the escalation of symptoms [82]. This early intervention approach can improve individual outcomes while reducing the overall burden on healthcare systems. Integrating mHealth applications into traditional healthcare systems presents a promising avenue as well. By supplementing face-to-face therapy with app-based interventions, healthcare providers can offer continuous support and monitoring, extending the therapeutic engagement beyond the clinical setting. For example, apps facilitating cognitive-behavioral therapy activities or mood tracking can augment therapeutic strategies employed by mental health professionals, creating an integrated care model that capitalizes on the strengths of both digital and traditional methods.
Evaluating mental health apps often hinges on their ability to demonstrate tangible improvements in mental health outcomes. In our study, out of the 35 apps reviewed, three apps, namely ABMT, Mental app, and MindSurf app, did not significantly improve mental health outcomes [78–80]. A common characteristic of these studies was their smaller sample sizes, ranging from 20 to 60 participants. In contrast, studies with larger sample sizes, such as the MoodPrism app (N = 168) [50], MoodMission app (N = 617) [51], Headspace and Smiling Mind apps (N = 208) [48], the iPST and Project: EVO apps (N = 626) [47], and Feel Stress Free app (N = 198) [45], demonstrated improvements in mental health outcomes. This raises important considerations regarding the sample size and its influence on the ability to measure the true impact of app interventions. The importance of sample size in research cannot be overstated. The lack of observed improvement in mental health outcomes in the ABMT, Mental app, and MindSurf app studies could be partially attributed to insufficient sample sizes, which may not provide a robust test of the apps’ efficacy.
Additionally, out of 35 apps, three apps were investigated in multiple studies: the Smartphone Positive Stimuli Response System (SPSRS) [44,53], the MoodMission app [51,57], and the Headspace app [48,49,72,73] with different populations, study duration, and outcomes. For example, a study by Bakker et al.[51] examined the MoodMission app’s impact on a broader population (N = 617), ranging from adolescents to older adults, emphasizing self-guided engagement over 30 days. The findings revealed that the app effectively reduced symptoms of depression and anxiety, particularly for individuals with moderate baseline symptoms, showcasing its utility in promoting coping self-efficacy among a general population. In contrast, another study by Tan et al., [57] with a smaller clinical population of psychiatric outpatients (N = 48), evaluated the MoodMission app as an adjunct to treatment over four weeks. While the app significantly reduced depressive symptoms in this setting, it did not yield significant improvements in anxiety symptoms, suggesting that its effectiveness may depend on the target population and treatment context. Similarly, Headspace was examined in four studies differing in duration, sample size, and outcomes. One study with university students (N = 208) over 30 days reported reductions in depressive symptoms [48]. Another study with college students (N = 72) over 14 days found significant decreases in depressive symptoms [49]. An 8-week intervention with orthopedic surgery residents (N = 24) showed reductions in anxiety with minimal app use (8 minutes per day, 2 days per week) [72]. However, a smaller study with surgical residents and faculty (N = 19) over 14 days reported anxiety reduction but no significant improvements in depressive symptoms [73]. These findings illustrate how differences in intervention duration, population size, and context influence reported outcomes and highlight the importance of tailoring apps used to specific settings and populations.
While our review sheds light on the potential of mHealth apps, a closer examination of the current body of research reveals a critical gap: most of these studies are early-phase trials or pilot studies. While these studies provide valuable insights into their preliminary impact, they lack the rigorous clinical validation found in later-phase trials. This underscores the need to advance mHealth research to phases 2 and 3 trials to ensure clinical validation and facilitate the potential adoption of such apps into mainstream mental health care. For mHealth apps, transitioning into these later phases is imperative to validate their therapeutic value against standardized clinical benchmarks. Such rigorous testing ensures that apps can genuinely benefit users in real-world settings beyond the controlled environments of research studies. Moreover, phase 2 and 3 trials incorporate larger, more diverse participant groups, enhancing the generalizability of findings [83]. Only through such comprehensive evaluation can we identify which apps are genuinely efficacious across different populations, mental health disorders, and severity levels.
One of the limitations of this review study is the exclusion of non-English publications, which may have led to a language bias and the omission of relevant studies from non-English-speaking countries.
Conclusion
In conclusion, mHealth apps are promising for addressing the global mental health crisis, offering scalable, accessible interventions. However, the current evidence base highlights the need for more robust, long-term studies to understand their efficacy better and develop guidelines for their integration into mainstream mental health care. As we move forward, mHealth interventions must be designed and evaluated, emphasizing evidence-based practices, user engagement, and inclusivity to maximize their impact on mental health outcomes worldwide.
Supporting information
S4 File. Article screening prosses and exclusion reasoning.
https://doi.org/10.1371/journal.pone.0319983.s004
(DOCX)
References
- 1. GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789–858. pmid:30496104
- 2.
Organization WH. Comprehensive mental health action plan 2013–2030. 2021.
- 3. Vigo D, Thornicroft G, Atun R. Estimating the true global burden of mental illness. Lancet Psychiatry. 2016;3(2):171–8. pmid:26851330
- 4. Wittchen HU, Jacobi F, Rehm J, Gustavsson A, Svensson M, Jönsson B, et al. The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur Neuropsychopharmacol. 2011;21(9):655–79. pmid:21896369
- 5. De Silva MJ. Making mental health an integral part of sustainable development: the contribution of a social determinants framework. Epidemiol Psychiatr Sci. 2015;24(2):100–6. pmid:25722030
- 6. Turner JC, Leno EV, Keller A. Causes of mortality among american college students: a pilot study. J College Stud Psychother. 2013;27(1):31–42. pmid:26322333
- 7. Center T. Mental Illness Will Cost the World $16 USD Trillion by 2030. Psychiatric Times. 2018;35(11).
- 8. Wainberg ML, Scorza P, Shultz JM, Helpman L, Mootz JJ, Johnson KA, et al. Challenges and Opportunities in Global Mental Health: a Research-to-Practice Perspective. Curr Psychiatry Rep. 2017;19(5):28. pmid:28425023
- 9. Kamody RC, Bloch MH. Editorial: Schools on the frontline of suicide prevention. J Child Psychol Psychiatry. 2022;63(8):833–5. pmid:35861181
- 10. Dixon A, McDaid D, Knapp M, Curran C. Financing mental health services in low- and middle-income countries. Health Policy Plan. 2006;21(3):171–82. pmid:16533860
- 11. Dwidiyanti M, Kurniasari C, Kitu I, Agustriyani F, Utama M, Sari S. The development of information system for mental health nursing interventions: a literature review. KnE Life Sciences. 2019;2019295–303.
- 12. Shah A, Shahil A, Nolan RP, Strudwick G, Sockalingam S, Seto E. Access to mental health services for people with complex chronic conditions: a qualitative study. 2023.
- 13. Abel W, Sewell C, Thompson E, Brown T. Mental health services in Jamaica: from institution to community. Ethnicity and Inequalities HSC. 2011;4(3):103–11.
- 14. Muhorakeye O, Biracyaza E. Exploring barriers to mental health services utilization at kabutare district hospital of rwanda: perspectives from patients. Front Psychol. 2021;12:638377. pmid:33828506
- 15. Victor CK, Gilbert MM, Ondora OM, Abel KO. Barriers to mental health services utilization among outpatient clinic attendees at Mathari National teaching and referral hospital, Nairobi City, Kenya. Int J Community Med Public Health. 2022;9(6):2431.
- 16. Valenstein M, Dalack GW, Simoncic T, Metzger K, Deneke DE, Richardson CR, et al. Implementing the collaborative care model as part of a countywide initiative. Psychiatric Services. 2016.
- 17. Henderson J, Dawson S, Fuller J, O’Kane D, Gerace A, Oster C, et al. Regional responses to the challenge of delivering integrated care to older people with mental health problems in rural Australia. Aging Ment Health. 2018;22(8):1025–31. pmid:28463520
- 18. Hailemariam M, Fekadu A, Selamu M, Medhin G, Prince M, Hanlon C. Equitable access to integrated primary mental healthcare for people with severe mental disorders in Ethiopia: a formative study. Int J Equity Health. 2016;15(1):121. pmid:27460038
- 19. Blodgett N, Coughlan R, Khullar N. Overcoming the barriers in transgender healthcare in rural Ontario: discourses of personal agency, resilience, and empowerment. Int Social Sci J. 2017;67(225–226):83–95.
- 20. Antonova E, Schlosser K, Pandey R, Kumari V. Coping with COVID-19: mindfulness-based approaches for mitigating mental health crisis. Front Psychiatry. 2021;12:563417. pmid:33833695
- 21. Papp T (Therri) A, Cottrell M. Post-Secondary Educational Leadership Working Remotely During a COVID-19 Pandemic in Saskatchewan, Canada: Exploring Best Practices, Experiences, and the New Normal Post-Pandemic. Canadian Journal of Educational Administration and Policy. 2022;(200):63–75.
- 22. Goldman ML, Druss BG, Horvitz-Lennon M, Norquist GS, Kroeger Ptakowski K, Brinkley A, et al. Mental Health Policy in the Era of COVID-19. Psychiatr Serv. 2020;71(11):1158–62. pmid:32517639
- 23. Eaton J, Kakuma R, Wright A, Minas H. A position statement on mental health in the post-2015 development agenda. Int J Ment Health Syst. 2014;8:28. pmid:25050137
- 24. Cheung K, Ling W, Karr CJ, Weingardt K, Schueller SM, Mohr DC. Evaluation of a recommender app for apps for the treatment of depression and anxiety: an analysis of longitudinal user engagement. J Am Med Inform Assoc. 2018;25(8):955–62. pmid:29659857
- 25. Bakker D, Kazantzis N, Rickwood D, Rickard N. Mental Health Smartphone Apps: Review and Evidence-Based Recommendations for Future Developments. JMIR Ment Health. 2016;3(1):e7. pmid:26932350
- 26. Torous J, Wisniewski H, Liu G, Keshavan M. Mental Health Mobile Phone App Usage, Concerns, and Benefits Among Psychiatric Outpatients: Comparative Survey Study. JMIR Ment Health. 2018;5(4):e11715. pmid:30446484
- 27. Donker T, Petrie K, Proudfoot J, Clarke J, Birch M-R, Christensen H. Smartphones for smarter delivery of mental health programs: a systematic review. J Med Internet Res. 2013;15(11):e247. pmid:24240579
- 28. Kagen S, Garland A. Asthma and Allergy Mobile Apps in 2018. Curr Allergy Asthma Rep. 2019;19(1):6. pmid:30712150
- 29. Zhao J, Freeman B, Li M. Can Mobile Phone Apps Influence People’s Health Behavior Change? An Evidence Review. J Med Internet Res. 2016;18(11):e287. pmid:27806926
- 30. Ng MM, Firth J, Minen M, Torous J. User Engagement in Mental Health Apps: A Review of Measurement, Reporting, and Validity. Psychiatr Serv. 2019;70(7):538–44. pmid:30914003
- 31. BinDhim NF, Alanazi EM, Aljadhey H, Basyouni MH, Kowalski SR, Pont LG, et al. Does a Mobile Phone Depression-Screening App Motivate Mobile Phone Users With High Depressive Symptoms to Seek a Health Care Professional’s Help? J Med Internet Res. 2016;18(6):e156. pmid:27349441
- 32. Kushlev K, Harris M, Moon K. The Promise and peril of mental health apps. 2023.
- 33. Milne-Ives M, Selby E, Inkster B, Lam C, Meinert E. Artificial intelligence and machine learning in mobile apps for mental health: A scoping review. PLOS Digit Health. 2022;1(8):e0000079. pmid:36812623
- 34. DURDU AKGÜN B, AKTAÇ A, YORULMAZ O. Ruh Sağlığında Mobil Uygulamalar: Etkinliğe Yönelik Sistematik Bir Gözden Geçirme. Psikiyatride Güncel Yaklaşımlar. 2019;11(4):519–30.
- 35. Wang K, Varma DS, Prosperi M. A systematic review of the effectiveness of mobile apps for monitoring and management of mental health symptoms or disorders. J Psychiatr Res. 2018;10773–8. pmid:30347316
- 36. Marshall JM, Dunstan DA, Bartik W. The Digital Psychiatrist: In Search of Evidence-Based Apps for Anxiety and Depression. Front Psychiatry. 2019;10:831. pmid:31803083
- 37. Hwang WJ, Ha JS, Kim MJ. Research trends on mobile mental health application for general population: a scoping review. Int J Environ Res Public Health. 2021;18(5):2459. pmid:33801537
- 38. Moher D, Liberati A, Tetzlaff J, Altman DG, Group* P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Anna Internal Med. 2009;151(4):264–9.
- 39.
Avishek Choudhury. Effectiveness of Evidence Based Mental Health Apps on User Health Outcome: A Protocol for Systematic Literature Review; 2024 [cited 2024 Jul 23]. Available from: osf.io/x6m7u.
- 40. Mennin DS, Ellard KK, Fresco DM, Gross JJ. United we stand: emphasizing commonalities across cognitive-behavioral therapies. Behav Ther. 2013;44(2):234–48. pmid:23611074
- 41. Gross JJ. Emotion regulation: affective, cognitive, and social consequences. Psychophysiology. 2002;39(3):281–91. pmid:12212647
- 42. Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. EFI. 2018;34(4):285–91.
- 43.
Sano Y, Obata A, Yanase K, Yamamoto F, Omata S, Ichikawa M, et al., editors. Verification of Mental Stress Reduction Effects of Exercise Support Apps and Communication Support App for Corporate Health Management. 2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES). IEEE; 2022.
- 44. Kageyama K, Kato Y, Mesaki T, Uchida H, Takahashi K, Marume R, et al. Effects of video viewing smartphone application intervention involving positive word stimulation in people with subthreshold depression: A pilot randomized controlled trial. J Affect Disord. 2021;28274–81. pmid:33401126
- 45. McCloud T, Jones R, Lewis G, Bell V, Tsakanikos E. Effectiveness of a Mobile App Intervention for Anxiety and Depression Symptoms in University Students: Randomized Controlled Trial. JMIR mHealth uHealth. 2020;8(7):e15418. pmid:32735221
- 46. Tighe J, Shand F, Ridani R, Mackinnon A, De La Mata N, Christensen H. Ibobbly mobile health intervention for suicide prevention in Australian Indigenous youth: a pilot randomised controlled trial. BMJ Open. 2017;7(1):e013518. pmid:28132007
- 47. Arean PA, Hallgren KA, Jordan JT, Gazzaley A, Atkins DC, Heagerty PJ, et al. The use and effectiveness of mobile apps for depression: results from a fully remote clinical trial. J Med Internet Res. 2016;18(12):e330. pmid:27998876
- 48. Flett JAM, Hayne H, Riordan BC, Thompson LM, Conner TS. Mobile mindfulness meditation: a randomised controlled trial of the effect of two popular apps on mental health. Mindfulness. 2018;10(5):863–76.
- 49. Fish MT, Saul AD. The gamification of meditation: a randomized-controlled study of a prescribed mobile mindfulness meditation application in reducing college students’ depression. Simulation & Gaming. 2019;50(4):419–35.
- 50. Bakker D, Rickard N. Engagement in mobile phone app for self-monitoring of emotional wellbeing predicts changes in mental health: MoodPrism. J Affect Disord. 2018;227:432–42. pmid:29154165
- 51. Bakker D, Rickard N. Engagement with a cognitive behavioural therapy mobile phone app predicts changes in mental health and wellbeing: MoodMission. Australian Psychologist. 2019;54(4):245–60.
- 52. Cliffe B, Stallard P. Evaluating a smartphone app for university students who self-harm. Education Sciences. 2023;13(4):394.
- 53. Takahashi K, Takada K, Hirao K. Feasibility and preliminary efficacy of a smartphone application intervention for subthreshold depression. Early Interv Psychiatry. 2019;13(1):133–6. pmid:29356332
- 54. Bell I, Arnold C, Gilbertson T, D’Alfonso S, Castagnini E, Chen N, et al. A personalized, transdiagnostic smartphone intervention (mello) targeting repetitive negative thinking in young people with depression and anxiety: pilot randomized controlled trial. J Med Internet Res. 2023;25:e47860. pmid:38090786
- 55. Zhou X, Edirippulige S, Jones A, Bai X, Smith AC, Bambling M. The feasibility, acceptability and efficacy of an app-based intervention (the Coping Camp) in reducing stress among Chinese school adolescents: A cluster randomised controlled trial. PLoS One. 2023;18(11):e0294119. pmid:38011111
- 56. Boucher VG, Haight BL, Hives BA, Zumbo BD, Merali-Dewji A, Hutton S, et al. Effects of 12 weeks of at-home, application-based exercise on health care workers’ depressive symptoms, burnout, and absenteeism: a randomized clinical trial. JAMA Psychiatry. 2023;80(11):1101–9. pmid:37556150
- 57. Tan S, Ismail MAB, Daud TIM, Hod R, Ahmad N. A randomized controlled trial on the effect of smartphone-based mental health application among outpatients with depressive and anxiety symptoms: a pilot study in Malaysia. Indian J Psychiatry. 2023;65(9):934–40. pmid:37841542
- 58. Deady M, Collins DAJ, Lavender I, Mackinnon A, Glozier N, Bryant R, et al. Selective prevention of depression in workers using a smartphone app: randomized controlled trial. J Med Internet Res. 2023;25e45963. pmid:37616040
- 59. Ejiri H, Uchida H, Tsuchiya K, Fujiwara K, Kikuchi S, Hirao K. Immediate effects of mobile phone app for depressed mood in young adults with subthreshold depression: a pilot randomized controlled trial. Neuropsychiatr Dis Treat. 2023;191695–707. pmid:37546515
- 60. Litvin S, Saunders R, Jefferies P, Seely H, Pössel P, Lüttke S. The impact of a gamified mobile mental health app (eQuoo) on resilience and mental health in a student population: large-scale randomized controlled trial. JMIR Ment Health. 2023;10:e47285. pmid:37477955
- 61. Chang S, Alon N, Torous J. An exploratory analysis of the effect size of the mobile mental health Application, mindLAMP. Digit Health. 2023;9:20552076231187244. pmid:37434734
- 62. Domar AD, Jasulaitis L, Matevossian K, Jasulaitis S, Grill EA, Uhler ML. The impact of the fertistrong mobile application on anxiety and depression in men: a randomised control pilot study. J Hum Reprod Sci. 2023;16(3):195–203. pmid:38045496
- 63. Lahtinen O, Aaltonen J, Kaakinen J, Franklin L, Hyönä J. The effects of app-based mindfulness practice on the well-being of university students and staff. Curr Psychol. 2023;42(6):4412–21. pmid:33967565
- 64. Qin X, Liu C, Zhu W, Chen Y, Wang Y. Preventing Postpartum Depression in the Early Postpartum Period Using an App-Based Cognitive Behavioral Therapy Program: A Pilot Randomized Controlled Study. Int J Environ Res Public Health. 2022;19(24):16824. pmid:36554704
- 65. Liu C, Chen H, Zhou F, Long Q, Wu K, Lo L-M, et al. Positive intervention effect of mobile health application based on mindfulness and social support theory on postpartum depression symptoms of puerperae. BMC Womens Health. 2022;22(1):413. pmid:36217135
- 66. Birney AJ, Gunn R, Russell JK, Ary DV. MoodHacker Mobile Web App With Email for Adults to Self-Manage Mild-to-Moderate Depression: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2016;4(1):e8. pmid:26813737
- 67.
Liao C, Li L, Hoid D, Li X, editors. The mental health benefits and feasibility of the smartphone-based interpretation bias modification training in working population. 2022 12th International Conference on Information Technology in Medicine and Education (ITME). IEEE; 2022.
- 68. O’Donnell K, Dunbar M, Speelman D. Effectiveness of Daily Mindfulness Meditation App Usage to Reduce Anxiety and Improve Well-Being During the COVID-19 Pandemic: A Randomized Controlled Trial. Cureus. 2023;15(7):e42432. pmid:37637657
- 69. Kusumadewi A, Marchira C, Widyandana D, Wirasto R. Randomized clinical trial on the comparison of effect of asynchronous mobile application and guided brief cognitive behavioral therapy in managing anxiety among medical students. Trends in Psychiatry and Psychotherapy. 2023.
- 70. Kirykowicz K, Jaworski B, Owen J, Kirschbaum C, Seedat S, van den Heuvel LL. Feasibility, acceptability and preliminary efficacy of a mental health self-management app in clinicians working during the COVID-19 pandemic: a pilot randomised controlled trial. Psychiatry Res. 2023;329:115493. pmid:37778231
- 71. Schwob JT, Newman MG. Brief imaginal exposure exercises for social anxiety disorder: A randomized controlled trial of a self-help momentary intervention app. J Anxiety Disord. 2023;98:102749. pmid:37542755
- 72. Boden LM, Rodriguez C, Kelly JD 4th, Khalsa AS, Casper DS. Mindfulness Applications: Can They Serve as a Stress, Anxiety, and Burnout Reduction Tool in Orthopaedic Surgery Training? A Randomized Control Trial. JB JS Open Access. 2023;8(3):e22.00114. pmid:37497194
- 73. Hicks MD, Braden LA, Walsh EM, Greene BJ, Grayson JW. Mobile meditation for improving quality of life, anxiety and depression among surgical residents and faculty. J Laryngol Otol. 2022;136(11):1034–8. pmid:34674779
- 74. Duraimani SL. A Cross-Sectional and Longitudinal Study of the Effects of a Mindfulness Meditation Mobile Application Platform on Reducing Stress and Anxiety. Int J Yoga. 2019;12(3):226–32. pmid:31543631
- 75. Pham Q, Khatib Y, Stansfeld S, Fox S, Green T. Feasibility and Efficacy of an mHealth Game for Managing Anxiety: “Flowy” Randomized Controlled Pilot Trial and Design Evaluation. Games Health J. 2016;5(1):50–67. pmid:26536488
- 76. Franklin JC, Fox KR, Franklin CR, Kleiman EM, Ribeiro JD, Jaroszewski AC, et al. A brief mobile app reduces nonsuicidal and suicidal self-injury: Evidence from three randomized controlled trials. J Consult Clin Psychol. 2016;84(6):544–57. pmid:27018530
- 77. Liu C, Chen H, Zhang A, Gong X, Wu K, Liu C-Y, et al. The effects of short video app-guided loving-kindness meditation on college students’ mindfulness, self-compassion, positive psychological capital, and suicide ideation. Psicol Reflex Crit. 2023;36(1):32. pmid:37902928
- 78. Dennis-Tiwary TA, Egan LJ, Babkirk S, Denefrio S. For whom the bell tolls: neurocognitive individual differences in the acute stress-reduction effects of an attention bias modification game for anxiety. Behav Res Ther. 2016;77:105–17. pmid:26745621
- 79. Kajitani K, Higashijima I, Kaneko K, Matsushita T, Fukumori H, Kim D. Short-term effect of a smartphone application on the mental health of university students: A pilot study using a user-centered design self-monitoring application for mental health. PLoS One. 2020;15(9):e0239592. pmid:32976515
- 80. Carey TA, Haviland J, Tai SJ, Vanags T, Mansell W. MindSurf: a pilot study to assess the usability and acceptability of a smartphone app designed to promote contentment, wellbeing, and goal achievement. BMC Psychiatry. 2016;16(1):442. pmid:27955643
- 81. Ahamed F, Palepu S, Dubey M, Nongkynrih B. Scope of mobile health in Indian health care system – the way forward. Int J Community Med Public Health. 2017;4(4):875.
- 82. Everitt N, Broadbent J, Richardson B, Smyth JM, Heron K, Teague S, et al. Exploring the features of an app-based just-in-time intervention for depression. J Affect Disord. 2021;291:279–87. pmid:34058610
- 83. Ben-Zeev D, Schueller SM, Begale M, Duffecy J, Kane JM, Mohr DC. Strategies for mHealth research: lessons from 3 mobile intervention studies. Adm Policy Ment Health. 2015;42(2):157–67. pmid:24824311