This paper is in the following e-collection/theme issue:

Digital Health Reviews (1289) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1514) Mindfulness and Meditation (204) Reviews in Digital Mental Health (243) mHealth for Wellness, Behavior Change and Prevention (2871)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39128, first published .
Effects of Mobile Mindfulness Meditation on the Mental Health of University Students: Systematic Review and Meta-analysis

Effects of Mobile Mindfulness Meditation on the Mental Health of University Students: Systematic Review and Meta-analysis

Effects of Mobile Mindfulness Meditation on the Mental Health of University Students: Systematic Review and Meta-analysis

Authors of this article:

Bin Chen1 Author Orcid Image ;   Ting Yang1 Author Orcid Image ;   Lei Xiao1 Author Orcid Image ;   Changxia Xu1 Author Orcid Image ;   Chunqin Zhu1 Author Orcid Image
Article Authors Cited by (13) Tweetations (4) Metrics

    Original Paper

    Department of Nursing, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China

    *these authors contributed equally

    Corresponding Author:

    Chunqin Zhu, BSc

    Department of Nursing

    Affiliated Hospital of Nanjing University of Chinese Medicine

    Number 155, Hanzhong Road

    Nanjing, 210001

    China

    Phone: 86 13951086486

    Email: zhu504123@163.com


    Background: Mobile mindfulness meditation (MMM) is a mindfulness meditation intervention implemented using mobile devices such as smartphones and apps. MMM has been used to help manage the mental health of university students.

    Objective: This study aims to evaluate the effectiveness of MMM on the mental health of university students in the areas of stress, anxiety, depression, mindfulness, well-being, and resilience.

    Methods: We conducted a systematic review and meta-analysis of the effectiveness of MMM on the mental health of university students. This study followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. An electronic literature search was performed on PubMed, Web of Science, EBSCO, Cochrane Library, and Embase databases, from inception to July 16, 2021. This study was conducted to identify studies that reported the effects of MMM on the primary outcomes including stress, anxiety, and depression, and on the secondary outcomes including mindfulness, well-being, and resilience. Two reviewers retrieved articles, evaluated quality, and extracted data independently. The methodological quality of the selected studies was determined using the Cochrane criteria for risk-of-bias assessment. Standardized mean differences (SMDs) for continuous outcomes and risk ratios for dichotomous outcomes were calculated. Sensitivity analyses and subgroup analyses were performed for results with high heterogeneity. The RevMan version 5.3 was used to perform meta-analysis.

    Results: A total of 10 studies, including 958 university students, were selected for this meta-analysis. Results of the primary outcome showed that the MMM groups were more effective than the control groups in decreasing stress (SMD –0.41, 95% CI –0.59 to –0.23; P<.001) and alleviating anxiety (SMD –0.29, 95% CI –0.50 to –0.09; P=.004). However, there was no difference between the MMM groups and the control groups in depression (SMD –0.14, 95% CI –0.30 to 0.03; P=.11). The use of either waitlist control or traditional face-to-face intervention in the control group was identified as the source of heterogeneity. Specifically, the waitlist control subgroup (SMD –0.33, 95% CI –0.53 to –0.13; P=.002) was superior when compared with the face-to-face subgroup (SMD 0.29, 95% CI –0.01 to 0.59; P=.06). Results of the secondary outcome showed that the MMM groups were more effective than the control groups in enhancing well-being (SMD 0.30, 95% CI 0.11-0.50; P=.003) and improving mindfulness (SMD 2.66, 95% CI 0.77-4.55; P=.006). Whether commercial sponsorship was obtained was considered as the source of heterogeneity. The “without company support” group (SMD 17.60, 95% CI 11.32-23.87; P<.001) was superior to the “with company support” group (SMD 1.17, 95% CI –0.82 to 3.15; P=.25) in raising the level of mindfulness. However, there was no difference between the MMM and control groups in resilience (SMD –0.06, 95% CI –0.26 to 0.15; P=.59). The evidence level of the results from the 10 studies was determined to be moderate to low.

    Conclusions: MMM was an effective method to reduce stress and anxiety, and to increase the well-being and mindfulness of university students. However, further studies are needed to confirm our findings.

    Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022303585; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=303585

    J Med Internet Res 2023;25:e39128

    doi:10.2196/39128

    Keywords

    digital health; mobile mindfulness meditation; mental health; university students; meta-analysis 


    According to the World Health Organization (WHO), mental health is “a state of well-being in which the individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community” [1]. More than 50% of university students have mental health problems [2], such as stress, anxiety, or depression [3]. Common factors associated with mental health problems are age, specifically around 18 years [4]; distance from parents and friends [5]; class learning-extracurricular activity balance [6]; and economic situation [7]. Persistent mental health problems can lead to a series of physical and psychological issues, such as sleep disorders, changes in eating habits, alcohol addiction, academic disruption [8], and suicide attempts [9]. Poor mental health among college students has become an urgent social problem that the public must focus on and solve [10].

    Mindfulness meditation is a general term for various types of psychotherapy, with mindfulness at the core [11]. Mindfulness meditation is widely used to alleviate or treat emotional and psychological problems, such as anxiety, depression, compulsion, and impulsiveness [12]. Several studies have proved that mindfulness meditation is effective in reducing mental health problems such as stress and burnout [13-15]. However, as mindfulness meditation may be both time-consuming and costly, while university students may perceive the practice as a sense of stigma, most university students with mental health issues have a negative attitude toward mindfulness meditation and may be reluctant about receiving treatment [16].

    In recent years, with the popularity of smartphones and development of apps [17], mindfulness meditation intervention based on smartphone apps emerged [18]. Mobile mindfulness meditation (MMM) is defined as a mindfulness meditation intervention implemented via mobile devices such as smartphones and apps, instead of face-to-face interaction. With advantages such as accessibility, absence of time and space constraints, low or no cost, and privacy [19], MMM was reported to demonstrate similar or better effects than the traditional face-to-face intervention [20,21]. Thus, MMM has attracted considerable attention for improving the mental health of university students.

    Nevertheless, the effects of MMM on the mental health of university students are controversial. Some studies showed that MMM can reduce stress among university students [22,23], whereas others presented contrasting results [24,25]. Several researchers concluded that MMM may raise individuals’ level of mindfulness [23,26], whereas others suggested no such improvement [24,27]. Although MMM demonstrates potential in solving mental health problems, adequate evidence confirming the effects of MMM on the mental health of university students is lacking.

    To the best of our knowledge, a meta-analysis of the effects of MMM on the mental health of university students has yet to be conducted. Few meta-analyses on the effects of MMM on the mental health of university students were conducted in previous studies. Rathbone and Prescott [28] found that MMM can significantly improve mental health; however, their study population included various population groups and was not just limited to university students with mental health problems. Regehr et al [29] reported that various types of cognitive, behavioral, and mindfulness interventions, rather than only the MMM intervention, are effective in reducing mental health problems among university students. Therefore, determining the effectiveness of MMM in reducing mental health problems among university students is essential. In this study, we aim to systematically evaluate the effects of MMM on stress, anxiety, depression, mindfulness, well-being, and resilience among university students.


    Study Design

    This study was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses; Multimedia Appendix 1) guidelines [30,31] and AMSTAR 2 (A Measure Tool to Assess Systematic Reviews 2) [32].

    Search Strategy

    A total of 5 digital databases were searched systematically, namely, PubMed, Web of Science, EBSCO, the Cochrane Library, and Embase, from inception to July 16, 2021. Language was restricted to English. After reading a number of documents, a search strategy combining MeSH (Medical Subject Headings) terms and free words was developed. The search strategy for the 5 electronic databases is listed in Multimedia Appendix 2. Irrelevant literature was removed by reading the article titles and abstracts, and the retained literature was further screened by reading the full text. In addition, the references of each included study were retrieved manually. Two researchers (BC and TY) conducted the literature search independently, and disagreements were resolved through discussions. EndNote X9 (Clarivate) was used to import and manage the selected literature.

    Inclusion Criteria

    The inclusion criteria were based on the PICOS method, as follows:

    • P (population): University students with mental health problems.
    • I (intervention): Various types of MMM such as the “Calm” and “Headspace” apps.
    • C (comparison): Traditional mindfulness meditation, such as face-to-face therapy, waitlist control, and sham meditation.
    • O (outcome): A total of 6 outcome indices were analyzed in the meta-analysis (ie, stress, anxiety, depression, well-being, mindfulness, and resilience). Stress was defined as a cognitive and behavioral experience process composed of psychological stressors and psychological stress response. Anxiety was defined as an emotional reflection of someone’s serious deterioration of the value characteristics of reality or future things. Depression was defined as a psychological disease characterized by continuous and long-term low spirits. Well-being was defined as a subjective feeling that people are satisfied with their ideal life. Mindfulness was defined as perceiving in a specific way, that is, on purpose, in the present moment, and nonjudgmentally. Resilience was defined as the ability of individuals to recover from negative experiences and flexibly adapt to the changing external environment.
    • S (study design): Randomized controlled trials (RCTs) and a quasi-experimental design were used.

    Exclusion Criteria

    The exclusion criteria were as follows: (1) studies not about mobile-based mindfulness meditation intervention, (2) conference articles, (3) repeated articles, and (4) studies with no original data.

    Data Extraction

    Data were extracted from the selected studies and entered separately into a prefabricated form by 2 reviewers (BC and TY). Disagreements were resolved by consulting the third author (CZ). The information displayed in the form included the following: the name(s) of author(s), publication year, country, study design, sample size, experimental group intervention regimen(s), control group method(s), time interval, outcome measurement(s), and outcomes.

    Quality Assessment

    The quality of each included study was assessed according to the Cochrane Handbook for Systematic Reviews of Interventions 5.1.0 [33], which includes 7 criteria, namely, random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete data outcomes, selective outcome reporting, and other biases. Each criterion was graded as having a high risk of bias, an unclear risk of bias, or a low risk of bias. A funnel plot was used to quantify the extent of the publication bias.

    The research quality was assessed by applying the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach [34] and calculating the between-rater agreement coefficient. The κ coefficients were classified according to the study of Landis and Koch [35] as follows: 0.0-0.20=slight agreement, 0.21-0.40=fair agreement, 0.41-0.60=moderate agreement, 0.61-0.80=substantial agreement, and 0.81-1.00=nearly perfect agreement [36].

    Two reviewers (BC and TY) independently conducted the quality assessment. Any dissenting opinion was resolved through discussion, and issues that could not be resolved were addressed by the third author (CZ).

    Statistical Analysis

    The meta-analysis was conducted using RevMan 5.3 software (The Cochrane Collaboration). The weighted mean difference model was used to analyze the continuous data if all the outcomes were measured using identical methods; otherwise standardized mean difference (SMD) was used. An I2 test was conducted to assess the degree of heterogeneity of included studies, and I2>50% indicated significant heterogeneity according to the Cochrane Handbook. The P and I2 values were used to determine the model to choose. A fixed-effect model was chosen if P>.1 and I2<50%, whereas a random-effect model was selected if P<.1 and I2>50%. In addition, a sensitivity analysis through the leave-one-out method and a subgroup analysis were performed on studies with significant heterogeneity. All effective quantities were expressed by a 95% CI, and P<.05 defined the statistical significance.


    Search Findings

    A total of 2695 records were identified for retrieval, specifically PubMed (n=2223), Web of Science (n=178), EBSCO (n=4), the Cochrane Library (n=222), Embase (n=66), and additional records from the references provided in the included studies (n=2). After the duplicates were removed, 2030 articles remained. A total of 1982 records were excluded after a thorough review of the titles and abstracts. Of the remaining 48 records, 38 were removed after a full-text screening. Finally, 10 articles [22-27,37-40] were selected for the systematic review and meta-analysis. The study flow diagram of the selection process is shown in Figure 1.

    ‎
    Figure 1. Studyflow diagram.

    Study Characteristics

    The 10 included studies were published between 2018 and 2021 (all within the past 5 years). A total of 3 studies were conducted in the United States [23,24,37], with 1 each in Iran [25], Canada [38], Ireland [39], Spain [26], United Kingdom [40], Finland [27], and Germany [22]. The RCT design was employed for 9 articles [22-24,26,27,37-40], whereas the quasi-experimental study design was used for 1 article [25]. A total of 958 university students were included in this review who were allocated to an experimental group (n=461) and a control group (n=497). MMM involves mindfulness intervention delivered via apps installed on smartphones, and mainly focuses on college students. This intervention method was the only strategy used for the mindfulness meditation intervention in the experimental group. Although the MMM intervention for the control group was conducted using various types of smartphones or apps, all of these were the MMM method. Traditional face-to-face mindfulness meditation or waitlist control was used for the students in the control group. The time interval of the study ranged from 30 days to 8 weeks. All outcomes were completely patient reported. The main characteristics of the selected studies are shown in Table 1.

    Table 1. Characteristics of included studies.
    StudyCountryDesignSample size, nTa/Cb, nInterventionControlTime intervalOutcome measures and their values (T/C), mean (SD)
    Borjalilu et al [25]IranQuasi-experimental study4828/20Applied the “Aramgar” stress management appFace-to-face therapy only6 weeks
    • Depression: 12.22 (5.34)/9.45 (5.67)
      • ‎
    • Stress: 11.23 (4.34)/10.61 (4.73)
      • ‎
    • Anxiety: 11.43 (4.57)/10.34 (4.34)
      • ‎
    Champion et al [37]United StatesRCTc7438/36The self-guided mindfulness meditation app “Headspace”Waitlist control30 days
    • Resilience: 76.97 (10.53)/76.39 (11.92)
      • ‎
    Huberty et al [23]United StatesRCT8841/47The “Calm” smartphone appWaitlist control8 weeks
    • Stress: 16.15 (6.16)/20.02 (6.16)
      • ‎
    • Mindfulness: 129.20 (18.32)/111.07 (18.31)
      • ‎
    Lee and Jung [38]CanadaRCT16377/86The “DeStressify” appWaitlist control8 weeks
    • Stress: 17.8 (6.2)/19.8 (6.7)
      • ‎
    • Anxiety: 40.1 (12.1)/43.4 (13.2)
      • ‎
    • Depression: 6.4 (3.9)/7.4 (4.7)
      • ‎
    Noone and Hogan [39]IrelandRCT9143/48The “Headspace” appSham meditation group6 weeks
    • Well-being: 50.28 (6.91)/49.98 (6.58)
      • ‎
    Orosa-Duarte et al [26]SpainRCT6131/30The “REM Volver a casa” (Mindfulness-Based Emotion Regulation. Going Home”) appDid not receive any intervention8 weeks
    • Anxiety: 20.48 (12.51)/26.77 (12.57)
      • ‎
    • Mindfulness: 140.35 (20.44)/123.70 (21.25)
      • ‎
    Ponzo et al [40]United KingdomRCT11655/61The “BioBase” appWaitlist control4 weeks
    • Anxiety: 46.31 (11.32)/51.33 (10.35)
      • ‎
    • Well-being: 42.15 (9.02)/40.51 (8.64)
      • ‎
    • Depression: 8.71 (4.45)/9.85 (5.38)
      • ‎
    Raevuori et al [27]FinlandRCT12463/61The Meru Health Program via smartphoneTreatment as usual8 weeks
    • Depression: 9.89 (6.30)/8.57 (6.04)
      • ‎
    • Mindfulness: 73.19 (11.87)/72.59 (11.40)
      • ‎
    • Resilience: 81.82 (11.24)/82.32 (10.78)
      • ‎
    Harrer et al [22]GermanyRCT10540/65An app-based intervention with feedback on demand (StudiCare Stress)Waitlist control7 weeks
    • Stress: 7.43 (2.93)/9.49 (3.06)
      • ‎
    • Depression: 15.88 (8.85)/21.47 (8.96)
      • ‎
    • Well-being: 11.93 (5.03)/9.36 (4.35)
      • ‎
    • Resilience: 5.38 (1.85)/5.05 (1.97)
      • ‎
    Yang et al [24]United StatesRCT8845/43The “Headspace” appWaitlist control30 days
    • Stress: 17.08 (6.02)/19.30 (s5.63)
      • ‎
    • Mindfulness: 25.69 (4.96)/24.35 (5.27)
      • ‎
    • Well-being: 77.10 (11.97)/71.38 (12.37)
      • ‎

    aT: test group.

    bC: control group.

    cRCT: randomized controlled trial.

    Quality of Studies

    Based on the Cochrane Handbook for Systematic Reviews of Interventions criteria, the bias assessment of the selected articles is shown in Figures 2 and 3. Six studies [22,27,37-40] reported randomized methods in detail, 3 studies [23,24,26] used randomization without stating a specific random scheme, and the remaining study [25] did not use random grouping. All studies except 1 [25] described allocation concealment. Moreover, 6 studies [22,23,27,37-39] used blinding methods for the participants and personnel, and 6 studies [22,25-27,38,39] used outcome assessment blinding. All the studies except 1 [27] identified incomplete outcome data and selective reporting as low risks. Furthermore, 5 studies [23,25,26,38,40] reported other bias as low risks. This review did not draw funnel plots owing to the insufficient number of studies for each outcome.

    ‎
    Figure 2. Risk of bias of each included study. See also [22,23-27,36-40].
    ‎
    Figure 3. Overall risk of bias analysis of included studies.

    Meta-analysis Findings

    Stress

    A total of 5 studies [22-25,38] involving 690 university students assessed stress as the outcome. Among the 5 studies, 4 [22-24,38] used the Perceived Stress Scale (PSS) [41], and 1 [25] used the 21-item Depression, Anxiety, and Stress Scale (DASS-21) [42]. Owing to the different measurement tools used in the studies, SMD was chosen for the meta-analysis. A fixed-effect model was selected for the statistical analysis, as low heterogeneity was observed between the studies (I2=39%, P=.16). It was found that stress decreased significantly in the experimental group (SMD –0.41, 95% CI –0.59 to –0.23; P<.001) compared with that in the control group (Figure 4).

    ‎
    Figure 4. Forest plot of mobile mindfulness meditation on stress. See also [22-25,37].
    Anxiety

    A total of 4 studies [25,26,38,40] involving 617 university students assessed anxiety as the outcome. Among the 4 studies, 3 [26,38,40] used the State-Trait Anxiety Inventory (STAI) [43], and 1 [25] used the DASS-21 [42]. SMD was chosen owing to the different types of measurement tools used in the studies. A fixed-effect model was selected for the statistical analysis, as low heterogeneity was observed between the studies (I2=37%, P=.19). It was found that anxiety decreased significantly in the experimental group (SMD –0.29, 95% CI –0.50 to –0.09; P=.004) compared with that in the control group (Figure 5).

    ‎
    Figure 5. Forest plot of mobile mindfulness meditation on anxiety. See also [25,26,37,39].
    Depression

    A total of 5 studies [22,25,27,38,40] involving 556 university students assessed depression. Among the 5 studies, 2 [27,40] used the 9-item Patient Health Questionnaire (PHQ-9) [44] and the other 3 [22,25,38] used the Center for Epidemiological Studies’ Depression Scale (CES-D) [45], the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) [46], and the DASS-21 [42] separately. Owing to the different measurement tools used in the studies, SMD was chosen for the meta-analysis. No statistical significance was found between the experimental and control groups (SMD –0.14, 95% CI –0.30 to 0.03; P=.11). Moreover, significant heterogeneity (I2=72%, P=.006) was observed between the 5 studies. Sensitivity analysis was performed on the outcome, but no individual study was found to qualitatively affect the results. Subgroup analysis was conducted to determine the differences between the studies. The use of either waitlist control or traditional face-to-face intervention in the control group was identified as the source of heterogeneity: specifically, the waitlist control subgroup (SMD –0.33, 95% CI –0.53 to –0.13; P=.002) versus the face-to-face subgroup (SMD 0.29, 95% CI –0.01 to 0.59; P=.06). The results showed that the effects of MMM and traditional face-to-face mindfulness meditation on depression were similar (Figure 6).

    ‎
    Figure 6. Forest plot of mobile mindfulness meditation on depression. See also [22,25,27,37,39].
    Well-being

    Four studies [22,24,39,40] involving 400 university students assessed anxiety as the outcome. Among the 4 studies, 2 [39,40] used the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS) [47], and the remaining 2 [22,24] used the WHO-Five Well-Being Index (WHO-5) [48] and the General Well-being Schedule (GWBS) [49]. SMD was chosen owing to different types of measurement tools used in the studies. A fixed-effect model was selected for the statistical analysis, as small heterogeneity among studies was observed between the studies (I2=25%, P=.26). It was found that well-being increased significantly in the experimental group (SMD 0.30, 95% CI 0.11-0.50; P=.003) compared with the control group (Figure 7).

    ‎
    Figure 7. Forest plot of mobile mindfulness meditation on well-being. See also [22,24,38,39].
    Mindfulness

    Four studies [23,24,26,27] involving 348 university students assessed mindfulness. All 4 studies used the Five Factor Mindfulness Questionnaire (FFMQ) [50]. Mean difference was chosen for the meta-analysis, and it was found that mindfulness increased significantly in the experimental group (SMD 2.66, 95% CI 0.77-4.55; P=.006) compared with the control group. However, significant heterogeneity (I2=88%, P<.001) was observed between the 4 studies. Sensitivity analysis was performed on the outcome, but no individual study was found to qualitatively affect the results. Subgroup analysis was conducted to determine the differences between the studies. Support from a company may be the source of the heterogeneity, specifically the “without company support” subgroup (SMD 17.60, 95% CI 11.32-23.87; P<.001) versus the “with company support” subgroup (SMD 1.17, 95% CI –0.82 to 3.15; P=.25). The results showed that MMM without company support significantly improved mindfulness (P<.001; Figure 8).

    ‎
    Figure 8. Forest plot of mobile mindfulness meditation on mindfulness. See also [23-25,27].
    Resilience

    A total of 3 studies [22,27,37] involving 302 university students assessed resilience as the outcome. Two studies [27,37] used the Wagnild Resilience Scale (WRS) [51] and 1 [22] used the Connor-Davidson Resilience Scale (CD-RISC) [52]. SMD was selected owing to different types of measurement tools used in the studies. A fixed-effect model was selected for the statistical analysis, as low heterogeneity was observed between the studies (I2=12%, P=.32). No statistical significance was found between the experimental group and the control group (SMD –0.06, 95% CI –0.26 to 0.15; P=.59; Figure 9).

    ‎
    Figure 9. Forest plot of mobile mindfulness meditation on resilience. See also [22,27,36].
    Quality of Evidence

    The results showed that the quality of evidence ranged from moderate to low. The between-rater κ coefficient was 100% (P=.001), indicating perfect between-rater agreement during the evaluation process. The quality of the evidence is summarized in Table 2.

    Table 2. GRADEa summary of findings for all outcomes.
    OutcomesEffect estimate (95% CI)Studies, nParticipants, nI2 (%)Quality of evidence (reasons for downgrading)
    Stress–0.41 (–0.59 to –0.23)569039⊕⊕bLow (inconsistency; publication bias)
    Anxiety–0.29 (–0.50 to –0.09)461737⊕⊕⊕cModerate (inconsistency)
    Depression–0.14 (–0.30 to 0.03)555672⊕⊕Low (inconsistency; publication bias)
    Well-being0.30 (0.11 to 0.50)440025⊕⊕Low (inconsistency; publication bias)
    Mindfulness2.66 (0.77 to 4.55)434888⊕⊕⊕Moderate (publication bias)
    Resilience–0.06 (–0.26 to 0.15)330212⊕⊕Low (inconsistency; publication bias)

    aGRADE: Grading of Recommendations Assessment, Development, and Evaluation.

    b⊕⊕ means there are 2 reasons for downgrading.

    c⊕⊕⊕ means there are 3 reasons for downgrading.


    Principal Findings

    A meta-analysis was conducted on 10 studies to assess the effects of MMM on stress, anxiety, depression, mindfulness, well-being, and resilience among 958 university students. All the studies used MMM in the experimental group and traditional face-to-face mindfulness meditation or waitlist control in the control group. Funnel plots are typically used to assess publication bias when at least ten studies are used for the meta-analysis [53]; however, a funnel plot was not generated in this study, as the number of studies for each outcome was less than 10. The time interval of the study ranged from 30 days to 8 weeks; however, we did not find significant difference between each included studies, which is likely due to the limited study number. We believe that with the increase of the number of studies, this phenomenon will receive more general attention. Overall, a varying quality of evidence was observed for the effects of MMM on the mental health of university students. Specifically, for stress, a low quality of evidence was observed for the finding that MMM significantly reduced stress among university students. For anxiety, a moderate quality of evidence was observed for the result that MMM significantly decreased anxiety in the experimental group compared with the control group. In terms of depression, the low quality of evidence result indicated no statistical significance between the experimental and control groups. With regard to well-being, a low quality of evidence was observed for the outcome that university students in the MMM group had higher well-being than those in the control group. For mindfulness, a moderate quality of evidence was found on the finding that MMM positively enhanced the university students’ mindfulness. Finally, regarding resilience, a low quality of evidence indicated no statistical significance between the experimental and control groups.

    Primary Outcome

    Overview

    The primary outcome of our study was the effectiveness of MMM in reducing stress, anxiety, and depression among university students. These 3 psychological problems were reported as significant factors influencing students’ academic performance and physical health, such as back pains, headaches, and irritable bowel syndrome [54]. Thus, developing effective mental health management strategies to address the aforementioned psychological issues is essential [23].

    Stress

    Stress is an individuals’ natural reflection in the face of tension, which may lead to worry, restlessness, among others [55]. This study showed a significant reduction in stress among university students in the MMM intervention group (SMD –0.41, 95% CI –0.59 to –0.23; P<.001), which is similar to the findings of previous studies [22,23,56]. Possible reasons for this outcome exist. For example, previous studies proved the positive effectiveness of traditional mindfulness therapy in reducing stress among university students [57,58]. Mindfulness meditation through smartphone apps may improve muscle relaxation and diaphragm breathing, focus attention on different parts of the body, raise noncritical awareness of events occurring continuously, and enhance self-reflection [59]. In addition, MMM requires less resources (in terms of cost, personnel, or buildings), as it can be easily accessed through smartphones, regardless of economic and other constraints [60]. In particular, MMM involves minimal time and space constraints, as university students can just turn on their smartphones to receive mindfulness treatment anytime and anywhere at their convenience, instead of setting a fixed time and place for unified concentration, such as in traditional methods. Such advantages can help students obtain increased and convenient treatment, which may be a highly practical way to reduce stress [23].

    Anxiety

    Anxiety refers to an unpleasant complex emotional state, such as tension, uneasiness, and worry, caused by imminent or possible danger or threat [61]. This study revealed that university students in the experimental group were able to lower their anxiety level compared with those in the control group (SMD –0.29, 95% CI –0.50 to –0.09; P=.004), which is consistent with previous findings [40,58]. The possible causes were analyzed as follows: university students often feel stigmatized when they reveal having mental issues, and may be reluctant to seek treatment in the school hospital or psychological counseling center from fear of being seen by classmates or teachers, who may label them as having mental health problems, which can further aggravate their anxiety and other problems [62]. Through mobile devices, students can receive treatment remotely, thus avoiding the embarrassment of face-to-face contact [38]. Intervention through mobile devices may have several advantages, such as usefulness, convenience, and ease of use; additionally, it is more popular among and easily accepted by university students [63]. This improved engagement and accessibility in anxious individuals who may prefer apps to face-to-face group mindfulness programs. Interestingly, a previous study reported that smartphone-aided psychological treatments can decrease anxiety among users [64], which may be another reason for the outcomes.

    Depression

    The main clinical characteristics of depression are manifested mainly as depressed moods, slow thinking, reduced language and movement, and retardation [65]. This study showed no statistical difference in depression between university students in the experimental group and those in the control group. Heterogeneity was detected between the studies (I2=72%, P=.006), whereas the sensitivity analysis indicated that no single study qualitatively affected the combined results. Subgroup analysis was performed to identify the potential causes of the heterogeneity. For the experimental design process, in the case of similar interventions in the experimental group, 3 of the 5 studies set the control group as a waitlist control, and the other 2 studies used traditional face-to-face mindfulness meditation. Thus, it can be concluded that the “face-to-face mindfulness meditation” group (SMD 0.29, 95% CI –0.01 to 0.59; P=.06) was superior to the “waitlist control” group (SMD –0.33, 95% CI –0.53 to –0.13; P=.002) in terms of reduced symptoms of depression. This result is in line with previous findings [25,27]. A reason for this outcome maybe that MMM and traditional mindfulness meditation methods can effectively alleviate the depressive symptoms of university students and have the same effect size [25,27]; thus, no significant difference was observed between the MMM and traditional intervention control groups. Meanwhile, no intervention measures were used in the waitlist control group; thus, the depressive symptoms of university students in this group did not change significantly [22]. Therefore, a significant difference existed between the experimental and control groups.

    Secondary Outcome

    Overview

    The secondary outcome of our study was the effectiveness of MMM in increasing well-being, mindfulness, and resilience among university students. The 3 outcomes had a close positive correlation with mental health [66]. Improving well-being, mindfulness, and resilience can help university students to effectively deal with mental distress, such as stress, anxiety, and depression [67].

    Well-being

    Well-being refers to a series of joyful emotions subjectively generated by individuals based on their sense of satisfaction and security [68]. Compared with university students in the control group, MMM may strengthen the well-being of those in the experimental group (SMD 0.30, 95% CI 0.11-0.50; P=.003), which is in line with the findings of previous studies [22,24]. A possible reason is that the advantage of the MMM intervention is the rigorous smartphone intervention, because the standardized guidance scheme and objective compliance measures of the participants in the experimental group were provided by apps; thus, the intervention method was homogeneous [1]. Likewise, a recent meta-analysis showed that 67% of positive psychological interventions are conducted in the form of self-help. This form is similar to the advantage offered by MMM based on smartphone apps, as university students could choose an intervention performed based on their needs [69]. Smartphone-based self-intervention programs allow university students to avoid certain risks and restrictions related to traditional methods, such as time, resource, flexibility, accessibility, and availability constraints [70]. Such programs also meet the requirements of the WHO, especially the use of electronic and mobile health technologies [71].

    Mindfulness

    Mindfulness is perceived in a specific way, that is, conscious awareness, living in the present, and not making judgments [72]. Our study revealed a significant improvement in the mindfulness of university students in the MMM intervention group. Heterogeneity was detected between the studies (I2=88%, P<.001), and the sensitivity analysis suggested that no single study qualitatively affected the combined results. Subgroup analysis was performed to identify the potential causes of the heterogeneity. In the design process, 2 of the 4 studies were funded or technically guided by professional companies, whereas the other 2 did not obtain business funding or guidance. Thus, it can be concluded that the “without company support” group (SMD 17.60, 95% CI 11.32-23.87; P<.001) was superior to the “with company support” group (SMD 1.17, 95% CI –0.82 to 3.15; P=.25) in raising the level of mindfulness. This result is in line with previous findings [23,26]. Besides, the results of the studies funded or technically guided by companies may have risks of bias [33]. Thus, caution should be exercised when interpreting such findings. Research supports this study’s idea that a significant advantage of MMM is the objective recording of the number of meditation sessions completed by university students by an app instead of self-reporting [73].

    Resilience

    Changes in psychological resilience among university students were also observed. Resilience refers to an individuals’ ability to recover from negative experiences and adapt flexibly to the changing external environment [74]. The results indicated no statistical difference between the 2 groups (SMD –0.06, 95% CI –0.26 to 0.15; P=.59), which are in line with those of previous studies [22,27,37]. A possible reason for this outcome may be that resilience-based interventions emphasize individuals’ and community members’ strength and ability to recover from physical, emotional, or environment stress [75]. A positive correlation was observed between psychological resilience and education level [76]. University students have a high education level; therefore, it was assumed in this study that university students had high psychological resilience before seeking the MMM intervention.

    Strengths and Limitations

    This meta-analysis study has several strengths. First, this is the first study to assess the effects of MMM on the mental health of university students. It also represents the future development direction of the mindfulness intervention to university students. Second, all studies were published in the last 5 years, which indicates that this is a whole new research field. Third, to assess the effects of the MMM intervention, we assessed 6 outcomes, including stress, anxiety, depression, well-being, mindfulness, and resilience, which might provide reference for mental health management of university students.

    Limitations to this study were as follows: first, selected articles were limited to the English language, which may lead to the lack of some high-quality articles in non-English languages. Second, different smartphones and apps were used in each study, which may contribute to heterogeneity. Third, regarding the 6 outcomes, different measurements were used for each outcome, which may have had an impact on the bias of the results. Lastly, due to the limited number of included studies, we did not classify different time points of outcome assessment used in studies and consider how this may influence the final results.

    Relevance for Clinical Practice

    This review study presents evidence regarding the effectiveness of MMM in improving the mental health problems of university students. With the serious mental health status of university students [2], this provides a new idea and a method to improve such symptoms. At the same time, it also provides some reference for the MMM research field to improve mental health.

    Conclusions

    This meta-analysis investigated the effectiveness of MMM on stress, anxiety, depression, well-being, mindfulness, and resilience of university students. In general, the effectiveness of MMM on the mental health of university students was superior to that of traditional mindfulness meditation. There were positive effects of MMM in decreasing stress, alleviating anxiety, enhancing well-being, and improving mindfulness of university students. Concerning the outcomes depression and resilience, the MMM method contributed equally to the traditional face-to-face mindfulness meditation method. Therefore, in view of the results of meta-analysis, we cautiously proposed that MMM was an effective method to reduce stress and anxiety, and to increase the well-being and mindfulness of university students. However, due to the limited number of studies that have examined the effectiveness of MMM on mental health, further studies are needed to confirm our findings.

    Acknowledgments

    We thank Professors Peibei Duan and Yan Wang, Department of Nursing; Professors Man Zheng, Weiqian Tian, and Fangbing Ji, Department of Anesthesiology, from Affiliated Hospital of Nanjing University of Chinese Medicine, for their advice on this manuscript. The first author thanks his beautiful wife Tiffany Yang and lovely son Eric Chen for allowing him to dedicate his time to scientific research, and apologizes to Eric Chen for not being able to grow up with him.

    Authors' Contributions

    BC and TY contributed to conceptualization, methodology, formal analysis, investigation, data curation, writing, reviewing, and editing of the original draft. LX and CX contributed to conceptualization, investigation, and editing. CZ contributed to supervision and project administration. All the authors have read and agreed to the published version of the manuscript.

    Conflicts of Interest

    None declared.

    ‎
    Multimedia Appendix 1

    PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 checklist.

    PDF File (Adobe PDF File), 96 KB
    ‎
    Multimedia Appendix 2

    Search strategies.

    DOC File , 33 KB
    1. Mental health. World Health Organization (WHO).   URL: https://www.who.int/health-topics/mental-health#tab=tab_1 [accessed 2022-10-04]
    2. Yulia A, Fong ACN, Ali A, Subramaniam H, Amiruddin S. Response Actions of Malaysian Universities and Colleges in Managing Student Mental Health: A Systematic Review. Int. Journal of Com. WB 2021 Jun 16;5(1):21-36. [CrossRef]
    3. Liu H, Zhou Z, Fan X, Luo H, Wang D, Wang J, et al. A mixed method study to examine the mental health problems of college students who had left-behind experiences. J Affect Disord 2021 Sep 01;292:149-160. [CrossRef] [Medline]
    4. Safhi M, Alafif R, Alamoudi N, Alamoudi M, Alghamdi W, Albishri S, et al. The association of stress with sleep quality among medical students at King Abdulaziz University. J Family Med Prim Care 2020 Mar;9(3):1662-1667 [FREE Full text] [CrossRef] [Medline]
    5. Kalkbrenner MT, Flinn RE, Sullivan DK, Esquivel Arteaga LE. A Mental Health Literacy Approach to Supporting First-Generation Community College Student Mental Health: The REDFLAGS Model. Community College Review 2021 Mar 26;49(3):243-261. [CrossRef]
    6. Wang Q, Du T. Implementation of the college student mental health education course (CSMHEC) in undergraduate medical curriculum: effects and insights. BMC Med Educ 2020 Dec 11;20(1):505 [FREE Full text] [CrossRef] [Medline]
    7. Akeman E, Kirlic N, Clausen AN, Cosgrove KT, McDermott TJ, Cromer LD, et al. A pragmatic clinical trial examining the impact of a resilience program on college student mental health. Depress Anxiety 2020 Mar 04;37(3):202-213 [FREE Full text] [CrossRef] [Medline]
    8. Wilbur T. Stressed but not Depressed: A Longitudinal Analysis of First-Generation College Students, Stress, and Depressive Symptoms. Soc Forces 2020 Oct;100(3):e1 [FREE Full text] [CrossRef]
    9. Liu CH, Stevens C, Wong SH, Yasui M, Chen JA. The prevalence and predictors of mental health diagnoses and suicide among U.S. college students: Implications for addressing disparities in service use. Depress Anxiety 2019 Jan 06;36(1):8-17 [FREE Full text] [CrossRef] [Medline]
    10. Wang C, Yan S, Gan Y, Jiang H, Lu Z. Association Between Social Support and Mental Health Status Among College Students: A Nationwide Survey. Research Gate.   URL: https:/​/www.​researchgate.net/​publication/​346098727_Association_ Between_Social_Support_and_Mental_Health_Status_Among_College_Students_A_Nationwide_Survey [accessed 2022-04-10]
    11. Paulson S, Davidson R, Jha A, Kabat-Zinn J. Becoming conscious: the science of mindfulness. Ann N Y Acad Sci 2013 Nov;1303:87-104. [CrossRef] [Medline]
    12. Wells RE, O'Connell N, Pierce CR, Estave P, Penzien DB, Loder E, et al. Effectiveness of Mindfulness Meditation vs Headache Education for Adults With Migraine: A Randomized Clinical Trial. JAMA Intern Med 2021 Mar 01;181(3):317-328 [FREE Full text] [CrossRef] [Medline]
    13. Yildirim M. Mediating Role of Resilience in the Relationships Between Fear of Happiness and Affect Balance, Satisfaction With Life, and Flourishing. Eur J Psychol 2019 Jun 07;15(2):183-198 [FREE Full text] [CrossRef] [Medline]
    14. Zhao Y, Wang Q, Wang J. Valuing happiness predicts higher well-being: The moderating role of acceptance. Psych J 2020 Mar 24;9(1):132-143. [CrossRef] [Medline]
    15. Martin-Cuellar A, Lardier DT, Atencio DJ. Therapist mindfulness and subjective vitality: the role of psychological wellbeing and compassion satisfaction. J Ment Health 2021 Mar 31;30(1):113-120. [CrossRef] [Medline]
    16. Magowan S, Burgoine K, Ogara C, Ditai J, Gladstone M. Exploring the barriers and facilitators to the acceptability of donor human milk in eastern Uganda - a qualitative study. Int Breastfeed J 2020 Apr 17;15(1):28-48 [FREE Full text] [CrossRef] [Medline]
    17. Chen B, Wang Y, Xiao L, Xu C, Shen Y, Qin Q, et al. Effects of mobile learning for nursing students in clinical education: A meta-analysis. Nurse Educ Today 2021 Mar;97:104706. [CrossRef] [Medline]
    18. Narayanasamy MJ, Thomson L, Coole C, Nouri F, Drummond A. Investigating the barriers and facilitators to implementing mental health first aid in the workplace: a qualitative study. JMHTEP 2020 Dec 12;16(2):164-178. [CrossRef]
    19. Bruhns A, Lüdtke T, Moritz S, Bücker L. A Mobile-Based Intervention to Increase Self-esteem in Students With Depressive Symptoms: Randomized Controlled Trial. JMIR Mhealth Uhealth 2021 Jul 12;9(7):e26498. [CrossRef] [Medline]
    20. Graham AK, Greene CJ, Kwasny MJ, Kaiser SM, Lieponis P, Powell T, et al. Coached Mobile App Platform for the Treatment of Depression and Anxiety Among Primary Care Patients: A Randomized Clinical Trial. JAMA Psychiatry 2020 Sep 01;77(9):906-914 [FREE Full text] [CrossRef] [Medline]
    21. Kerst A, Zielasek J, Gaebel W. Smartphone applications for depression: a systematic literature review and a survey of health care professionals' attitudes towards their use in clinical practice. Eur Arch Psychiatry Clin Neurosci 2020 Mar;270(2):139-152. [CrossRef] [Medline]
    22. Harrer M, Adam SH, Fleischmann RJ, Baumeister H, Auerbach R, Bruffaerts R, et al. Effectiveness of an Internet- and App-Based Intervention for College Students With Elevated Stress: Randomized Controlled Trial. J Med Internet Res 2018 Apr 23;20(4):e136 [FREE Full text] [CrossRef] [Medline]
    23. Huberty J, Green J, Glissmann C, Larkey L, Puzia M, Lee C. Efficacy of the Mindfulness Meditation Mobile App "Calm" to Reduce Stress Among College Students: Randomized Controlled Trial. JMIR Mhealth Uhealth 2019 Jun 25;7(6):e14273 [FREE Full text] [CrossRef] [Medline]
    24. Yang E, Schamber E, Meyer RML, Gold JI. Happier Healers: Randomized Controlled Trial of Mobile Mindfulness for Stress Management. J Altern Complement Med 2018 May;24(5):505-513. [CrossRef] [Medline]
    25. Borjalilu S, Mazaheri MA, Talebpour A. Effectiveness of Mindfulness-Based Stress Management in The Mental Health of Iranian University Students: A Comparison of Blended Therapy, Face-to-Face Sessions, and mHealth App (Aramgar). Iran J Psychiatry Behav Sci 2019 May 12;13(2):e84726. [CrossRef]
    26. Orosa-Duarte A, Mediavilla R, Muñoz-Sanjose A, Palao A, Garde J, López-Herrero V, et al. Mindfulness-based mobile app reduces anxiety and increases self-compassion in healthcare students: A randomised controlled trial. Medical Teacher 2021 Feb 28;43(6):686-693. [CrossRef]
    27. Raevuori A, Vahlberg T, Korhonen T, Hilgert O, Aittakumpu-Hyden R, Forman-Hoffman V. A therapist-guided smartphone app for major depression in young adults: A randomized clinical trial. J Affect Disord 2021 May 01;286:228-238 [FREE Full text] [CrossRef] [Medline]
    28. Rathbone AL, Prescott J. The Use of Mobile Apps and SMS Messaging as Physical and Mental Health Interventions: Systematic Review. J Med Internet Res 2017 Aug 24;19(8):e295 [FREE Full text] [CrossRef] [Medline]
    29. Regehr C, Glancy D, Pitts A. Interventions to reduce stress in university students: a review and meta-analysis. J Affect Disord 2013 May 15;148(1):1-11. [CrossRef] [Medline]
    30. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev 2021 Mar 29;10(1):89 [FREE Full text] [CrossRef] [Medline]
    31. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021 Mar 29;372:n71 [FREE Full text] [CrossRef] [Medline]
    32. Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ 2017 Sep 21;358:j4008 [FREE Full text] [CrossRef] [Medline]
    33. Green S, Higgins JPT, Alderson P, Clarke M, Mulrow CD, Oxman AD. Introduction. In: Higgins JPT, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions. Hoboken, NJ: Wiley; Sep 22, 2008.
    34. Guyatt GH, Oxman AD, Sultan S, Glasziou P, Akl EA, Alonso-Coello P, GRADE Working Group. GRADE guidelines: 9. Rating up the quality of evidence. J Clin Epidemiol 2011 Dec;64(12):1311-1316. [CrossRef] [Medline]
    35. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977 Mar;33(1):159-174. [Medline]
    36. Du S, Liu W, Cai S, Hu Y, Dong J. The efficacy of e-health in the self-management of chronic low back pain: A meta analysis. Int J Nurs Stud 2020 Jun;106:103507. [CrossRef] [Medline]
    37. Champion L, Economides M, Chandler C. The efficacy of a brief app-based mindfulness intervention on psychosocial outcomes in healthy adults: A pilot randomised controlled trial. PLoS One 2018;13(12):e0209482 [FREE Full text] [CrossRef] [Medline]
    38. Lee RA, Jung ME. Evaluation of an mHealth App (DeStressify) on University Students' Mental Health: Pilot Trial. JMIR Ment Health 2018 Jan 23;5(1):e2 [FREE Full text] [CrossRef] [Medline]
    39. Noone C, Hogan MJ. A randomised active-controlled trial to examine the effects of an online mindfulness intervention on executive control, critical thinking and key thinking dispositions in a university student sample. BMC Psychol 2018 Apr 05;6(1):13 [FREE Full text] [CrossRef] [Medline]
    40. Ponzo S, Morelli D, Kawadler JM, Hemmings NR, Bird G, Plans D. Efficacy of the Digital Therapeutic Mobile App BioBase to Reduce Stress and Improve Mental Well-Being Among University Students: Randomized Controlled Trial. JMIR Mhealth Uhealth 2020 Apr 06;8(4):e17767 [FREE Full text] [CrossRef] [Medline]
    41. Hewitt PL, Flett GL, Mosher SW. The Perceived Stress Scale: Factor structure and relation to depression symptoms in a psychiatric sample. J Psychopathol Behav Assess 1992 Sep;14(3):247-257. [CrossRef]
    42. Osman A, Wong JL, Bagge CL, Freedenthal S, Gutierrez PM, Lozano G. The Depression Anxiety Stress Scales-21 (DASS-21): further examination of dimensions, scale reliability, and correlates. J Clin Psychol 2012 Dec 28;68(12):1322-1338. [CrossRef] [Medline]
    43. Spieberger C, Gonzalez-Reigosa F, Martinez-Urrutia A. State-Trait Anxiety Inventory. A Comparative Bibliography. Qeios. 1971.   URL: https://www.qeios.com/read/OWDFR4 [accessed 2022-04-10]
    44. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA 1999 Nov 10;282(18):1737-1744. [CrossRef] [Medline]
    45. Hann D, Winter K, Jacobsen P. Measurement of depressive symptoms in cancer patients. Journal of Psychosomatic Research 1999 May;46(5):437-443. [CrossRef]
    46. Rush A, Trivedi MH, Ibrahim HM, Carmody TJ, Arnow B, Klein DN, et al. The 16-Item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biological Psychiatry 2003 Sep;54(5):573-583. [CrossRef]
    47. Tennant R, Hiller L, Fishwick R, Platt S, Joseph S, Weich S, et al. The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): development and UK validation. Health Qual Life Outcomes 2007 Nov 27;5:63 [FREE Full text] [CrossRef] [Medline]
    48. Saipanish R, Lotrakul M, Sumrithe S. Reliability and validity of the Thai version of the WHO-Five Well-Being Index in primary care patients. Psychiatry Clin Neurosci 2009 Apr;63(2):141-146 [FREE Full text] [CrossRef] [Medline]
    49. Fazio A. A concurrent validational study of the NCHS General Well-Being Schedule. Vital Health Stat 2 1977 Sep(73):1-53 [FREE Full text] [Medline]
    50. Christopher MS, Neuser NJ, Michael PG, Baitmangalkar A. Exploring the Psychometric Properties of the Five Facet Mindfulness Questionnaire. Mindfulness 2012 Jan 6;3(2):124-131. [CrossRef]
    51. Wagnild GM, Young HM. Development and psychometric evaluation of the Resilience Scale. J Nurs Meas 1993;1(2):165-178. [Medline]
    52. Campbell-Sills L, Stein MB. Psychometric analysis and refinement of the connor–davidson resilience scale (CD-RISC): Validation of a 10-item measure of resilience. J. Traum. Stress 2007 Dec;20(6):1019-1028. [CrossRef]
    53. Sterne JAC, Sutton AJ, Ioannidis JPA, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ 2011 Jul 22;343(jul22 1):d4002. [CrossRef] [Medline]
    54. Gorman E, Burke H, Rubino L, Vargas I, Haeffel GJ. Teasing Apart the Effect of Depression Specific and Anxiety Specific Symptoms on Academic Outcomes. Klin Spec Psihol 2020;9(3):91-104 [FREE Full text] [CrossRef] [Medline]
    55. Balmus IM, Robea M, Ciobica A, Timofte D. Perceived stress and gastrointestinal habits in college students. Acta Endocrinol (Buchar) 2019;15(2):274-275 [FREE Full text] [CrossRef] [Medline]
    56. Crandall KJ, Steward K, Warf T. A Mobile App for Reducing Perceived Stress in College Students. AJHS 2020 Nov 12;31(2):e163. [CrossRef]
    57. Ritvo P, Ahmad F, El Morr C, Pirbaglou M, Moineddin R, Team M. Correction: A Mindfulness-Based Intervention for Student Depression, Anxiety, and Stress: Randomized Controlled Trial. JMIR Ment Health 2021 Jan 25;8(1):e27160 [FREE Full text] [CrossRef] [Medline]
    58. González-Valero G, Zurita-Ortega F, Ubago-Jiménez JL, Puertas-Molero P. Use of Meditation and Cognitive Behavioral Therapies for the Treatment of Stress, Depression and Anxiety in Students. A Systematic Review and Meta-Analysis. Int J Environ Res Public Health 2019 Nov 10;16(22):4394 [FREE Full text] [CrossRef] [Medline]
    59. Marshall JM, Dunstan DA, Bartik W. Apps With Maps-Anxiety and Depression Mobile Apps With Evidence-Based Frameworks: Systematic Search of Major App Stores. JMIR Ment Health 2020 Jun 24;7(6):e16525 [FREE Full text] [CrossRef] [Medline]
    60. Kvillemo P, Brandberg Y, Bränström R. Feasibility and Outcomes of an Internet-Based Mindfulness Training Program: A Pilot Randomized Controlled Trial. JMIR Ment Health 2016 Jul 22;3(3):e33 [FREE Full text] [CrossRef] [Medline]
    61. Balsamo M, Cataldi F, Carlucci L, Fairfield B. Assessment of anxiety in older adults: a review of self-report measures. CIA 2018 Apr;Volume 13:573-593. [CrossRef]
    62. Hayes D, Edbrooke-Childs J, Town R, Wolpert M, Midgley N. Barriers and facilitators to shared decision making in child and youth mental health: clinician perspectives using the Theoretical Domains Framework. Eur Child Adolesc Psychiatry 2019 May 18;28(5):655-666 [FREE Full text] [CrossRef] [Medline]
    63. Chen B, Yang T, Wang Y, Xiao L, Xu C, Shen Y, et al. Nursing students' attitudes toward mobile learning: An integrative review. Int J Nurs Sci 2021 Oct 10;8(4):477-485 [FREE Full text] [CrossRef] [Medline]
    64. Wu IHC, Bathje GJ, Kalibatseva Z, Sung D, Leong FTL, Collins-Eaglin J. Stigma, mental health, and counseling service use: A person-centered approach to mental health stigma profiles. Psychol Serv 2017 Nov;14(4):490-501. [CrossRef] [Medline]
    65. Friedman MJ, Resick PA, Bryant RA, Brewin CR. Considering PTSD for DSM-5. Depress Anxiety 2011 Sep 13;28(9):750-769. [CrossRef] [Medline]
    66. Litvin S, Saunders R, Maier MA, Lüttke S. Gamification as an approach to improve resilience and reduce attrition in mobile mental health interventions: A randomized controlled trial. PLoS One 2020 Sep 2;15(9):e0237220 [FREE Full text] [CrossRef] [Medline]
    67. Eaves JL, Payne N. Resilience, stress and burnout in student midwives. Nurse Educ Today 2019 Aug;79:188-193. [CrossRef] [Medline]
    68. Fiorillo L. Oral Health: The First Step to Well-Being. Medicina (Kaunas) 2019 Oct 07;55(10):676 [FREE Full text] [CrossRef] [Medline]
    69. Hendriks T, Schotanus-Dijkstra M, Hassankhan A, de Jong J, Bohlmeijer E. The Efficacy of Multi-component Positive Psychology Interventions: A Systematic Review and Meta-analysis of Randomized Controlled Trials. J Happiness Stud 2019 Feb 11;21(1):357-390. [CrossRef]
    70. Carissoli C, Villani D, Riva G. Does a meditation protocol supported by a mobile application help people reduce stress? Suggestions from a controlled pragmatic trial. Cyberpsychol Behav Soc Netw 2015 Jan;18(1):46-53. [CrossRef] [Medline]
    71. Coelhoso CC, Tobo PR, Lacerda SS, Lima AH, Barrichello CRC, Amaro E, et al. A New Mental Health Mobile App for Well-Being and Stress Reduction in Working Women: Randomized Controlled Trial. J Med Internet Res 2019 Nov 07;21(11):e14269 [FREE Full text] [CrossRef] [Medline]
    72. van der Riet P, Levett-Jones T, Aquino-Russell C. The effectiveness of mindfulness meditation for nurses and nursing students: An integrated literature review. Nurse Educ Today 2018 Jun;65:201-211. [CrossRef] [Medline]
    73. Bostock S, Crosswell AD, Prather AA, Steptoe A. Mindfulness on-the-go: Effects of a mindfulness meditation app on work stress and well-being. J Occup Health Psychol 2019 Feb;24(1):127-138 [FREE Full text] [CrossRef] [Medline]
    74. Foster K, Roche M, Delgado C, Cuzzillo C, Giandinoto J, Furness T. Resilience and mental health nursing: An integrative review of international literature. Int J Ment Health Nurs 2019 Feb 07;28(1):71-85. [CrossRef] [Medline]
    75. Sommovigo V, Setti I, Argentero P. The Role of Service Providers’ Resilience in Buffering the Negative Impact of Customer Incivility on Service Recovery Performance. Sustainability 2019 Jan 08;11(1):285. [CrossRef]
    76. Mealer M, Jones J, Meek P. Factors Affecting Resilience and Development of Posttraumatic Stress Disorder in Critical Care Nurses. Am J Crit Care 2017 May;26(3):184-192 [FREE Full text] [CrossRef] [Medline]

    ‎
    AMSTAR 2: A Measure Tool to Assess Systematic Reviews 2
    CD-RISC: Connor-Davidson Resilience Scale
    CES-D: Center for Epidemiological Studies’ Depression Scale
    DASS-21: 21-item Depression, Anxiety, and Stress Scale
    FFMQ: Five Factor Mindfulness Questionnaire
    GRADE: Grading of Recommendations Assessment, Development, and Evaluation
    GWBS: General Well-being Schedule
    MeSH: Medical Subject Headings
    MMM: mobile mindfulness meditation
    PHQ-9: 9-item Patient Health Questionnaire
    PICOS: population, intervention, comparison, outcome, study design
    PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
    PSS: Perceived Stress Scale
    QIDS-SR: Quick Inventory of Depressive Symptomatology Self-Report
    RCT: randomized controlled trial
    STAI: State-Trait Anxiety Inventory
    WEMWBS: Warwick-Edinburgh Mental Well-Being Scale
    WHO: World Health Organization
    WHO-5: WHO-Five Well-Being Index
    WRS: Wagnild Resilience Scale

    Edited by T Leung; submitted 29.04.22; peer-reviewed by R Rahimi, H Veldandi, H Mehdizadeh; comments to author 28.06.22; revised version received 17.08.22; accepted 05.09.22; published 03.01.23

    Copyright

    ©Bin Chen, Ting Yang, Lei Xiao, Changxia Xu, Chunqin Zhu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.01.2023.

    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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.