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Mental health is a complex condition, highly related to emotion. The COVID-19 pandemic caused a significant spike in depression (from isolation) and anxiety (event related). Mobile Health (mHealth) and telemedicine offer solutions to augment patient care, provide education, improve symptoms of depression, and assuage fears and anxiety.
This review aims to assess the effectiveness of mHealth to provide mental health care by analyzing articles published in the last year in peer-reviewed, academic journals using strong methodology (randomized controlled trial).
We queried 4 databases (PubMed, CINAHL [Cumulative Index to Nursing and Allied Health Literature], Web of Science, and ScienceDirect) using a standard Boolean search string. We conducted this systematic literature review in accordance with the Kruse protocol and reported it in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 checklist (n=33).
A total of 4 interventions (mostly mHealth) from 14 countries identified improvements in primary outcomes of depression and anxiety as well as in several secondary outcomes, namely, quality of life, mental well-being, cognitive flexibility, distress, sleep, self-efficacy, anger, decision conflict, decision regret, digestive disturbance, pain, and medication adherence.
mHealth interventions can provide education, treatment augmentation, and serve as the primary modality in mental health care. The mHealth modality should be carefully considered when evaluating modes of care.
PROSPERO International Prospective Register of Systematic Reviews CRD42022343489; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=343489
Mental health is a complex topic that is highly related to emotion, because emotional regulation is necessary for daily functioning [
Telemedicine and telehealth are defined as healing at a distance using information communication technologies to improve health outcomes [
Studies have shown that some college students are comfortable with mental health screening through mHealth modalities in the areas of performance expectancy and social influence [
mHealth for an older population has not been entirely successful as well mostly due to the digital divide inherent to older populations and overall digital literacy [
One systematic review from 2022 analyzed 26 articles over 10 years [
Another systematic review from 2022 analyzed 21 articles about telepsychiatry over 15 years [
The purpose of this review is to analyze studies published over the last year that examine mHealth as an intervention to both screen for and treat symptoms of mental health among adults aged over 18 years with strong methodological design (randomized controlled trial [RCT]). The intention of this review is to focus on mental health interventions during 1 year of the COVID-19 pandemic.
This review is conducted in accordance with the Kruse protocol for writing a systematic review. It is reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist. This review is registered with PROSPERO (registration number CRD42022343489).
This review focused on studies with strong methodology including participants who were adults (>18 years of age) that were published in peer-reviewed, academic journals over the last year. Other systematic reviews were excluded to avoid confounding the results. All reporting is in accordance with the PRISMA 2020 standard [
A total of 4 research databases were queried: PubMed (MEDLINE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and ScienceDirect from Embase. They were queried on August 14, 2022. These databases were chosen due to their availability and comprehensive indexing of research. Their availability make it easier for others to duplicate our study. Their comprehensive indexing ensures we capture a majority of the literature in our search.
Our initial process included a search on Google Scholar to better understand the topic and recent work published. We gathered information from Google Scholar into an MS Excel spreadsheet to enable the review team to read the articles so that we could see the key terms these studies used for indexing. Using the Medical Subject Headings (MeSH) from the US National Library of Medicine, we created a Boolean search string to exhaustively query the databases without redundant terms. We used the same search strategy in all databases and similar filter strategies.
In accordance with the Kruse protocol [
The Kruse protocol standardized an MS Excel spreadsheet as a data extraction tool and as an analysis tool [
In accordance with the Kruse protocol [
Risk of bias was determined through multiple means. Reviewers used the John’s Hopkins Nursing Evidence-Based Practice (JHNEBP) tool assessment of the strength and quality of evidence [
The preferred methodologies for this review were the RCT and true experiments because these are the strongest group of methodologies in the JHNEBP tool. The preferred measures of effect were the Cohen
We performed a thematic analysis of the data extracted [
Sensitivity, specificity, and effect size were tabulated and included in the data extraction. Combined with the narrative analysis, this provided us with certainty assessments. The frequency of themes does not imply importance, but it does provide confidence in the data analyzed.
No human subjects were used in this research. It is therefore IRB exempt.
Article selection process. CINAHL: Cumulative Index to Nursing and Allied Health Literature; WoS: Web of Science.
Following the PRISMA checklist [
Summary of study characteristics (PICOSa).
Authors | Participants | Experimental intervention | Results (compared with the control group) | Medical outcomes reported | Study design |
Acierno et al [ |
Adult females with PTSDb from sexual trauma, average age 43.4 years, 64% African American | Telemedicine | Reduced depression, but there were no differences in dose received or PTSD symptom reduction | Decrease in depression, but not statistically significant | RCTc |
Baek et al [ |
Adults, average age 41.9 years, 67% female | mHealthd app (MibyeongBogam [MBBG]) | The intervention group showed a decrease in depression (P=.003), anxiety (P=.01), sleep disturbance (P=.02), anger (P=.003), and pain (P=.02) greater than the control group; also fatigue (P=.6) and digestive disturbance (P=.76) were not statistically significant | Decreased depression, anxiety, sleep disturbance, anger, pain, fatigue, digestive disturbance | RCT |
Colomina et al [ |
Adults, average age 73 years, 66% female | mHealth self-management app (CONNECARE) | Decreased anxiety more than the control group, but there were no differences in depression symptom reduction | Decreased anxiety, but not statistically significant over traditional care | RCT |
Dobkin et al [ |
Adult veterans, average age 67.8 years, 100% male, 92% White | Video-to-home cognitive behavioral therapy | Intervention outperformed treatment as usual across all 3 measures of depression (P=.001), decreased anxiety, but not statistically significant | Decreased depression and anxiety | RCT |
Domogalla et al [ |
Adults with psoriasis, average age 49 years, 60% male | mHealth study and disease management app | Significant reduction in HADSe, HADS-Df (P=.04), and HADS-Ag (P=.05) more than those in the control group | Decreased anxiety and depression | RCT |
Fang et al [ |
Adults 100% female | mHealth app (Pink Journey) | Decreased anxiety, depression, decision conflict, and decision regret more than the control group, but not statistically significant from control; decreased body image distress (P=.027) | Decreased anxiety, depression, decision conflict, decision regret, and body image distress | RCT |
Fortney et al [ |
Adults average age 39 years, 70% female, 66% White | Telepsychiatry | Decreased depression and anxiety, but with small effect | Decreased depression and anxiety | RCT |
Huberty et al [ |
Adults average age 44.2 years, 78% female, 56% White | mHealth app | Decreased anxiety (P<.001) and depression (P<.001) more than the control group | Decreased anxiety and depression | RCT |
Jones et al [ |
Adults average age 53.4 years | mHealth app (WRAP) | Decreased HADS more than the control group | Decreased anxiety and depression | RCT |
Krzyzanowska et al [ |
Adults <40<75 years, median age 55 years | Telephone | No effect on anxiety, depression, or self-efficacy | No effect on anxiety, depression, or self-efficacy | RCT |
Moskowitz et al [ |
Adults average age 37.95 years, 74% female | eHealth | Decreased depression (P<.06) more than the control group | Decreased depression | RCT |
Pakrad et al [ |
Adults average age 62.7 years, 82% male | mHealth app | Decreased anxiety (P<.028), stress (P<.022), and quality of life (P<.001) more than the control. Decreased depression more than the control group, but not statistically significant (P<.063) | Decreased depression, anxiety, and stress, and increased quality of life | RCT |
Rollman et al [ |
Adults average age 63.9 years, 56% male, 74% White | Telephone | Decreased depression more than the control group | Decreased depression | RCT |
Romijn et al [ |
Adults, average age 36.25 years, 75% White | eHealth cognitive behavioral therapy (inference-based cognitive behavioral therapy) | Decreased anxiety more than the control group | Decreased anxiety | RCT |
Su and Yu [ |
Adults, average age 55.75 years, 85% male, 100% Chinese | eHealth | Decreased anxiety more than the control group, no effect on depression | Decreased anxiety | RCT |
Taguchi et al [ |
Adults, average age 50 years, 67% female | Video-based cognitive behavioral therapy | Decreased depression and anxiety (not statistically significant from the control) | Decreased depression and anxiety | RCT |
Wong et al [ |
Adults >60 years, average age 72 years, 82% female | mHealth app | Decreased depression (not statistically significant over the control group), increased medication adherence (P<.001), self-efficacy (P<.16), and quality of life (P<.04) | Decreased depression, improved medication adherence, self-efficacy, and quality of life | RCT |
Aikens et al [ |
Adults, average age 48.6 years, 81% female, 74% White | Telephone (automated interactive voice response) | Decreased depression more than the control group, with medium effect; increased self-efficacy | Decreased depression, increased self-efficacy | RCT |
Akin-Sari et al [ |
Adults, average age 23 years, 78% female | mHealth app | Decreased depression and COVID-19 distress more than the control group | Decreased depression, decreased COVID-19 distress | RCT |
Bathgate et al [ |
Adults, average age 32.4 years, 81% female, 97% White | Telemedicine | Decreased depression more than the control (P=.78), anxiety but not more than the control (P=.6), increased coping self-efficacy but not more than the control (P=.93), increased quality of life (physical functioning, social functioning, and vitality) | Decreased depression and anxiety, increased coping self-efficacy and quality of life | RCT |
Catuara-Solarz et al [ |
Adults, average age 40 years, 54% female | mHealth app | Decreased anxiety (P=.04), increase in resilience (P=.001), sleep (P=.01), and mental well-being (P=.02) more than the control group | Decreased anxiety, increase in resilience, sleep, and mental well-being | RCT |
Deady et al [ |
Adults, average age 40 years, 74% male | mHealth app (HeadGear) | Improved depression, anxiety, resilience, and well-being more than the control group (P=.0031) | Improved depression, anxiety, resilience, and well-being | RCT |
Drew et al [ |
Adults, average age 48.4 years, 100% male | eHealth app (SHED-IT) | Improved depression, sleep, cognitive flexibility more than the control | Improved depression, sleep, cognitive flexibility | RCT |
Guo et al [ |
Adults, average age 28.3 years, 95% male, 100% Chinese | mHealth, social media (Run4Love) | Improved depression more than the control | Decreased depression | RCT |
Gustafson et al [ |
Adults, >65 years, average age 76.5 years, 74% female, 89% White | eHealth app (ElderTree) | Improved depression (ORh –0.20, P=.034) and overall mental health quality of life (OR 0.32, P=.007) more than the control group | Decreased depression, increased mental health, increased quality of life | RCT |
Kuhn et al [ |
Adults, average age 44.5 years, mostly male | mHealth app | Decreased depression ( |
Decreased depression and sleep-related impairment | RCT |
Lopez et al [ |
Adults, average age 44 years, 100% female | Telemedicine | Reduced depression, but there were no differences in dose received or PTSD symptom reduction | Decrease in depression, but not statistically significant | RCT |
Mitchell et al [ |
Adults, average age 51 years, 60% female | Telemedicine cognitive behavioral therapy (RED-D) | Decreased depression and readmission (P<.012) more than the control | Decreased depression | RCT |
Nardi et al [ |
Adults, average age 42.9 years, 93% female | mHealth app (unwinding anxiety) | Decreased anxiety (P=.005) and worry (P=.01) more than the control | Decreased anxiety and worry | RCT |
Orman et al [ |
Adults, average age 68.4 years, 64% male | Telephone | Decreased depression and anxiety greater than usual care, short-term positive effect on quality of life | Decreased anxiety and depression, and increased quality of life | RCT |
Sun et al [ |
Adults, 100% Chinese | mHealth app (mindfulness) | Decreased depression and anxiety (P=.024) greater than usual care, but depression was not statistically different | Decreased anxiety and depression | RCT |
Volpato et al [ |
Adults, average age 76.2 years, 51% male | mHealth cognitive behavioral therapy | Decreased anxiety and depression, but not statistically significant than the control. Improved adherence to noninvasive ventilation (P<.001) and quality of life (P<.002) | Decreased anxiety and depression, improved quality of life, and noninvasive ventilation | RCT |
Ware et al [ |
Adults, average age 59 years, 56% male | Telemonitoring | No effect on anxiety or depression. Improved self-care maintenance, management, confidence, and physical quality of life | Improved self-care maintenance, management, confidence, and physical quality of life | RCT |
aPICOS: participants, intervention, comparison with the control or other group, medical outcomes, and study design.
bPTSD: posttraumatic stress disorder.
cRCT: randomized controlled trial.
dmHealth: mobile health.
eHADS: Hospital Anxiety and Depression Scale
fHADS-D: Hospital Anxiety and Depression Scale-Depression.
gHADS-A: Hospital Anxiety and Depression Scale-Anxiety.
hOR: odds ratio.
The JHNEBP quality assessment tool identified the strength and quality of evidence [
Reviewers also noted instances of bias, because bias can limit external and internal validity [
Summary of themes, sorted chronologically by author.
Authors | Intervention themes | Results themes | Medical outcomes themes | Patient satisfaction themes | Effectiveness themes | Barrier themes |
Acierno et al [ |
Telemedicine |
Reduced depression No statistical significance for at least one condition |
Reduced depression |
Satisfied |
Reduced depression Enabled preference for telemedicine |
May not be the preferred treatment method Staff training Low reimbursement |
Baek et al [ |
mHealtha/eHealth app |
Reduced depression Reduced anxiety Increased sleep Decreased anger Decreased pain Decreased digestive disturbance No statistical significance for at least one condition |
Reduced depression Reduced anxiety Increased sleep Decreased anger Decreased pain Decreased digestive disturbance |
Not reported |
Reduced depression Reduced anxiety Increased sleep Decreased anger Decreased pain Decreased digestive disturbance |
May not be the preferred treatment method Staff training Low reimbursement |
Colomina et al [ |
mHealth/eHealth app |
Reduced anxiety No effect on depression No statistical significance for at least one condition |
Reduced anxiety |
Satisfied |
Reduced health costs per patient Reduced anxiety |
May not be the preferred treatment method Staff training Low reimbursement |
Dobkin et al [ |
Telemedicine |
Reduced depression Reduced anxiety No statistical significance for at least one condition |
Reduced anxiety Reduced depression |
Satisfied |
Reduced anxiety Reduced depression Extended care to rural patients |
May not be the preferred treatment method Staff training Low reimbursement |
Domogalla et al [ |
mHealth/eHealth app |
Reduced anxiety Reduced depression |
Reduced anxiety Reduced depression |
Satisfied |
Reduced anxiety Reduced depression |
May not be the preferred treatment method Staff training |
Fang et al [ |
mHealth/eHealth app |
Reduced anxiety Reduced depression Decreased decision conflict Decreased decision regret Decreased distress No statistical significance for at least one condition |
Reduced anxiety Reduced depression Decreased decision conflict Decreased decision regret Decreased distress |
Satisfied |
Reduced anxiety Reduced depression Decreased decision conflict Decreased decision regret Decreased distress |
May not be the preferred treatment method Staff training Low reimbursement |
Fortney et al [ |
Telemedicine |
Reduced anxiety Reduced depression |
Reduced anxiety Reduced depression |
Not reported |
Reduced anxiety Reduced depression |
May not be the preferred treatment method Staff training Low reimbursement |
Huberty et al [ |
mHealth/eHealth app |
Reduced anxiety Reduced depression |
Reduced anxiety Reduced depression |
Satisfied |
Reduced anxiety Reduced depression |
May not be the preferred treatment method Staff training |
Jones et al [ |
mHealth/eHealth app |
Reduced anxiety Reduced depression |
Reduced anxiety Reduced depression |
Satisfied |
Reduced anxiety Reduced depression |
May not be the preferred treatment method Staff training |
Krzyzanowska et al [ |
Telephone |
No effect on anxiety No effect on depression No effect on self-efficacy |
None |
Not reported |
None |
May not be the preferred treatment method Staff training |
Moskowitz et al [ |
mHealth/eHealth app |
Reduced depression |
Reduced depression |
Satisfied |
Reduced depression |
May not be the preferred treatment method Staff training Low reimbursement |
Pakrad et al [ |
mHealth/eHealth app |
Reduced anxiety Decreased distress Increased quality of life Reduced depression No statistical significance for at least one condition |
Reduced anxiety Decreased distress Increased quality of life Reduced depression |
Satisfied |
Reduced anxiety Decreased distress Reduced depression Increased quality of life |
May not be the preferred treatment method Staff training Low reimbursement |
Rollman et al [ |
Telephone |
Reduced depression |
Reduced depression |
Not reported |
Reduced depression |
May not be the preferred treatment method Staff training Low reimbursement |
Romijn et al [ |
mHealth/eHealth app |
Reduced anxiety |
Reduced anxiety |
Satisfied |
Reduced anxiety |
May not be the preferred treatment method Staff training |
Su and Yu [ |
mHealth/eHealth app |
Reduced anxiety No effect on depression |
Reduced anxiety |
Not reported |
Reduced anxiety |
May not be the preferred treatment method Staff training |
Taguchi et al [ |
Telemedicine |
Reduced anxiety Reduced depression No statistical significance for at least one condition |
Reduced anxiety Reduced depression |
Not reported |
Reduced anxiety Reduced depression |
May not be the preferred treatment method Staff training |
Wong et al [ |
mHealth/eHealth app |
Reduced depression No statistical significance for at least one condition Increased medication adherence Increased self-efficacy Increased quality of life |
Reduced depression Increased medication adherence Increased self-efficacy Increased quality of life |
Not reported |
Reduced depression Increased medication adherence Increased self-efficacy Increased quality of life |
May not be the preferred treatment method Staff training Low reimbursement |
Aikens et al [ |
Telephone |
Reduced depression Increased self-efficacy |
Reduced depression Increased self-efficacy |
Not reported |
Reduced depression Increased self-efficacy |
May not be the preferred treatment method Staff training Low reimbursement |
Akin-Sari et al [ |
mHealth/eHealth app |
Reduced depression Decreased distress |
Reduced depression Decreased distress |
Not reported |
Reduced depression Decreased distress |
May not be the preferred treatment method Staff training Low reimbursement |
Bathgate et al [ |
Telemedicine |
Reduced depression Reduced anxiety Increased self-efficacy Increased quality of life No statistical significance for at least one condition |
Reduced depression Reduced anxiety Increased self-efficacy Increased quality of life |
Satisfied |
Reduced depression Reduced anxiety Increased self-efficacy Increased quality of life |
May not be the preferred treatment method Staff training Low reimbursement |
Catuara-Solarz et al [ |
mHealth/eHealth app |
Reduced anxiety Decreased fatigue/increased resilience Increased sleep Increased mental well-being/cognitive flexibility |
Reduced anxiety Decreased fatigue/increased resilience Increased sleep Increased mental well-being/cognitive flexibility |
Satisfied |
Reduced anxiety Decreased fatigue/increased resilience Increased sleep Increased mental well-being/cognitive flexibility |
May not be the preferred treatment method Staff training |
Deady et al [ |
mHealth/eHealth app |
Reduced depression Reduced anxiety Decreased fatigue/increased resilience Increased mental well-being/cognitive flexibility |
Reduced depression Reduced anxiety Decreased fatigue/increased resilience Increased mental well-being/cognitive flexibility |
Not reported |
Reduced depression Reduced anxiety Decreased fatigue/increased resilience Increased mental well-being/cognitive flexibility |
May not be the preferred treatment method Staff training |
Drew et al [ |
mHealth/eHealth app |
Reduced depression Increased sleep Increased mental well-being/cognitive flexibility |
Reduced depression Increased sleep Increased mental well-being/cognitive flexibility |
Not reported |
Reduced depression Increased sleep Increased mental well-being/cognitive flexibility |
May not be the preferred treatment method Staff training |
Guo et al [ |
mHealth/eHealth app |
Reduced depression |
Reduced depression |
Not reported |
Reduced depression |
May not be the preferred treatment method Staff training |
Gustafson et al [ |
mHealth/eHealth app |
Reduced depression Increased mental well-being/cognitive flexibility Increased quality of life |
Reduced depression Increased mental well-being/cognitive flexibility Increased quality of life |
Not reported |
Reduced depression Increased mental well-being/cognitive flexibility Increased quality of life |
May not be the preferred treatment method Staff training Low reimbursement |
Kuhn et al [ |
mHealth/eHealth app |
Reduced depression Increased sleep |
Reduced depression Increased sleep |
Not reported |
Reduced depression Increased sleep |
May not be the preferred treatment method Staff training Low reimbursement |
Lopez et al [ |
Telemedicine |
Reduced depression No statistical significance for at least one condition |
Reduced depression |
Not reported |
Reduced depression |
May not be the preferred treatment method Staff training Low reimbursement |
Mitchell et al [ |
Telemedicine |
Reduced depression |
Reduced depression |
Satisfied |
Reduced depression Decreased readmissions |
May not be the preferred treatment method Staff training Low reimbursement |
Nardi et al [ |
mHealth/eHealth app |
Reduced anxiety Decreased distress |
Reduced anxiety Decreased distress |
Not reported |
Reduced anxiety Decreased distress |
May not be the preferred treatment method Staff training Low reimbursement |
Orman et al [ |
Telephone |
Reduced depression Reduced anxiety Increased quality of life |
Reduced depression Reduced anxiety Increased quality of life |
Not reported |
Reduced depression Reduced anxiety Increased quality of life |
May not be the preferred treatment method Staff training |
Sun et al [ |
mHealth/eHealth app |
Reduced depression Reduced anxiety No statistical significance for at least one condition |
Reduced depression Reduced anxiety |
Not reported |
Reduced depression Reduced anxiety |
May not be the preferred treatment method Staff training |
Volpato et al [ |
mHealth/eHealth app |
Reduced anxiety Reduced depression Increased quality of life |
Reduced anxiety Reduced depression Increased quality of life |
Not reported |
Reduced anxiety Reduced depression Increased quality of life |
May not be the preferred treatment method Staff training Low reimbursement |
Ware et al [ |
Telemonitoring |
No effect on anxiety No effect on depression Increased self-efficacy Increased mental well-being/cognitive flexibility Increased quality of life |
No effect on anxiety No effect on depression Increased self-efficacy Increased mental well-being/cognitive flexibility Increased quality of life |
Not reported |
Increased self-efficacy Increased mental well-being/cognitive flexibility Increased quality of life |
May not be the preferred treatment method Staff training |
amHealth: mobile health.
A thematic analysis helped makes sense of the data collected. Although thematic analyses are typically used for qualitative analysis, other systematic reviews have also used this technique to makes sense of all observations from the data extraction process, whether the studies were qualitative or quantitative [
Patient satisfaction was not reported in all studies (20/33, 61%); however, 13/33 (39%) reported users were satisfied or highly satisfied. At the point where these data were collected, users were very pleased with the user interface and any further progress in the interventions improved their mental health.
Results compared with the control groups.
Results themes and observations | Frequency, n (n=95) |
Reduced depression [ |
26 |
Reduced anxiety [ |
19 |
No statistical significance for at least one condition [ |
11 |
Increased quality of life [ |
7 |
Increased mental well-being/cognitive flexibility [ |
5 |
Decreased distress [ |
4 |
Increased sleep [ |
4 |
Increased self-efficacy [ |
4 |
No effect on depression [ |
4 |
Decreased fatigue/increased resilience [ |
2 |
No effect on anxiety [ |
2 |
Decreased anger [ |
1 |
Decreased decision conflict [ |
1 |
Decreased decision regret [ |
1 |
Decreased digestive disturbance [ |
1 |
Decreased pain [ |
1 |
Increased medication adherence [ |
1 |
No effect on self-efficacy [ |
1 |
Medical outcomes commensurate with the adoption of mobile health.
Medical outcomes themes and observations | Frequency, n (n=78) |
Reduced depression [ |
26 |
Reduced anxiety [ |
19 |
Increased quality of life [ |
7 |
Increased mental well-being/cognitive flexibility [ |
5 |
Decreased distress [ |
4 |
Increased sleep [ |
4 |
Increased self-efficacy [ |
4 |
Decreased fatigue/increased resilience [ |
2 |
Decreased anger [ |
1 |
Decreased decision conflict [ |
1 |
Decreased decision regret [ |
1 |
Decreased digestive disturbance [ |
1 |
Decreased pain [ |
1 |
Increased medication adherence [ |
1 |
None [ |
1 |
Clinical and administrative effectiveness of mobile health to manage mental health.
Effectiveness themes and observations | Frequency, n (n=165) |
Reduced depression [ |
26 |
Reduced anxiety [ |
19 |
Increased quality of life [ |
7 |
Increased mental well-being/cognitive flexibility [ |
5 |
Decreased distress [ |
4 |
Increased self-efficacy [ |
4 |
Increased sleep [ |
4 |
Decreased fatigue/increased resilience [ |
2 |
Decreased anger [ |
1 |
None [ |
2 |
Decreased decision conflict [ |
1 |
Decreased decision regret [ |
1 |
Decreased digestive disturbance [ |
1 |
Decreased pain [ |
1 |
Decreased readmissionsa [ |
1 |
Enabled preference for telemedicine [ |
1 |
Extended care to rural patients [ |
1 |
Increased medication adherence [ |
1 |
Reduced health costs per patienta [ |
1 |
Administrative observationsa | 82 |
aCollected data that show effectiveness.
Three barriers were identified in the literature for the adoption of mHealth for mental health care. mHealth and telemedicine may not be the preferred modality of treatment for some patients or providers. This, along with the requirement to train staff, was identified in the literature 33 times [
When mHealth was used as the intervention, a reduction in both depression and anxiety was reported [
This systematic literature review analyzed 33 RCTs from 14 countries published over a 1-year period in peer-reviewed, academic journals using adults as participants (half of which were older adults) to analyze the effectiveness of mHealth for mental health care. A total of 4 interventions were studied: mHealth or eHealth apps, telemedicine (delivered over either a computer or a mobile device), telephone, and telemonitoring. Strong study methodologies resulted in low bias within and across studies. Observations of both sample and selection bias were noted, but there was nothing significant to report from these sources of bias. Overall, the interventions resulted in 26 instances of reduced depression; 19 instances of reduced anxiety; 7 instances of increased quality of life; 5 instances of increased mental well-being; 4 instances of decreased stress, increased self-efficacy, and increased sleep; 2 instances of decreased fatigue or increased resilience; and 1 instance each of decreased anger, decision regret, decision conflict, digestive disturbance, pain, readmission, and health care costs per patient. Only 2 studies reported no effect on depression and anxiety.
Future research should focus on standardizing mHealth into clinical practice guidelines for the treatment of some depression and anxiety issues. mHealth interventions can be rapidly deployed to a wide range of patient for very little money [
Results from this systematic review should empower providers to adopt some mHealth interventions to augment or supplant existing practices; however, a few barriers should be addressed. While mHealth interventions can be conveniently adopted by some providers, it may not be the preferred modality for some patients. Providers should be sensitive to patient preferences. As mHealth and telemedicine modalities are introduced to provider clinics, staff training will have to take place, but after initial training has occurred, small refresher training should be all that is necessary. Finally, while many countries introduced reimbursement mechanisms during the pandemic, many have expired or have not been renewed. This is an important policy point that this review documents. It is imperative that the efficacy of this modality be recognized as beneficial to patients, and as such they should be reimbursed appropriately.
This study has several limitations. While confirmation bias can create problems for researchers, multiple reviewers were used to control for this bias. While selection bias can be a problem with internal validity, multiple research databases were used to control for this bias. Publication bias is one this study did not control for. Because we only used studies published in peer-reviewed academic journals, it is possible there are other studies without positive results that we failed to include in the analysis. Our review used a Boolean search string from MeSH to ensure the search was exhaustive, but this technique may have overlooked articles indexed with terms other than those in MeSH. The short time frame of acceptance criteria (1 year) may also have introduced a limitation because there may have been older studies with results worthy of analysis. Including these studies may have biased the results during the pandemic.
mHealth is an effective tool to augment or, in some cases, supplant certain treatments of mental health care. It has been shown to improve depression and anxiety (primary research objectives) and many other conditions such as distress, sleep disturbance, pain, digestive disturbance, anger, fatigue, decision regret, and self-efficacy. Although some studies reported results that were not statistically significant, all but 2 interventions showed improvement in at least one area of care. These results are promising for both patients and providers seeking additional methods of care.
Observation-to-theme conversion (Intervention, Results, Medical Outcomes).
Observation-to-theme conversion (Patient Satisfaction, Effectiveness, Barriers).
Other observations incident to the data extraction process (sample size, country of origin, effect size, statistics used, JHNEBP strength and quality of evidence).
Cumulative Index to Nursing and Allied Health Literature
Hospital Anxiety and Depression Scale
Hospital Anxiety and Depression Scale-Anxiety
Hospital Anxiety and Depression Scale-Depression
John’s Hopkins Nursing Evidence-Based Practice
Medical Subject Headings
mobile health
odds ratio
participants, intervention, comparison with the control or other group, medical outcomes, and study design
posttraumatic stress disorder
randomized controlled trial
Web of Science
Data from this study can be obtained by asking the lead author.
None declared.