| Literature DB >> 35815033 |
Reham Shalaby1, Medard K Adu1, Hany M El Gindi2, Vincent I O Agyapong1,3.
Abstract
Background: While mental health problems constitute a worldwide concern contributing to the global rates of morbidity and mortality, conventional mental healthcare services do not meet the current needs. Text messages (TM) represent a live model that incorporates technology into health services, spanning a large number of health conditions and playing different roles that may support the current healthcare system. Objective: To examine the TM services in the field of mental health, regarding their effectiveness, feasibility, acceptability, and economic evaluation in different contexts of mental health diagnoses and during critical times, when provided to individuals with mental health symptoms/disorders.Entities:
Keywords: e-mental health; mental health gap; mobile health; rapid review; text messages
Year: 2022 PMID: 35815033 PMCID: PMC9263363 DOI: 10.3389/fpsyt.2022.921982
Source DB: PubMed Journal: Front Psychiatry ISSN: 1664-0640 Impact factor: 5.435
Figure 1PRISMA flowchart of study inclusion process.
Summary of studies using Web-based interventions for the mental health disorders.
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| Mason et al. ( | 2000–2013 | Meta analysis | Text message-based intervention programs /SUD | To examine the effectiveness of text message interventions for tobacco and alcohol cessation within adolescent and young adult populations | 14 articles / adolescents and/or young adults ages 12 to 29 | - | -Text interventions have a positive effect on reducing substance use behaviors (Effect size = 0.25). |
| Hutton et al. ( | 2005- January 2017 | Systematic review of the literature | mHealth interventions delivered via website or mobile technology (including text messages, apps on smartphone devices, iPad and internet delivered treatment)/alcohol consumption. | To examine current evidence on the effectiveness of mHealth technology use in reducing harmful alcohol-related behaviors among young people without known alcohol addiction. | 18 articles/young people (12–26 y) without known alcohol addiction, alcohol dependency, or a pre-existing condition related to alcohol | - | -The length of interventions, time carried out and follow-up was variable, with the shortest intervention being 2 to 3 h and the longest being 1year. |
| Alvarez-Jimenez et al. ( | From inception to August 2013. | Systematic review | User-led, internet or mobile-based interventions/psychosis | To systematically compile and analyze the current evidence on the acceptability, feasibility, safety and benefits of internet and mobile-based interventions for people suffering from psychosis | 12 articles/No specific demographic characteristics. Participants should be diagnosed with schizophrenia-spectrum disorders using either DSM or ICD criteria. | Cochrane Collaboration ’risk of bias' tool. | |
| Bastola et al. ( | From 2010 to 2018 | Meta-analysis of RCTs and pre-post studies | Mobile phone-based text messaging/SMS/Alcohol abuse and alcoholism | To analyze the effectiveness of mobile phone-based text messages as a preventive intervention for youth and younger adult populations' problem drinking. | 44 articles/College students and younger adults (<39 years). | - Cochrane “Risk of Bias” tool was used. | Forest plot analysis showed reduction in binge drinking episodes in the control group without the intervention (OR = 2.45 [1.32–.53], |
| Berrouiguet et al. ( | In May 2015 | Systematic review of RCTs, non-RCTs and protocols | mobile phone and web-based text messaging. (Text messages could be delivered to a patient by the caregiver or vice versa). / Mental health conditions, including SUD, depression, anxiety, bipolar disorder, and schizophrenia. | To review the literature regarding the use of mobile phone text messaging in mental health care; SMS was used to promote mental health, including any type of preventive or monitoring strategy | 36 articles/No special characteristics were reported. | - Text messaging was used in a wide range of mental health situations, notably substance abuse (31%), schizophrenia (22%), and affective disorders (17%). Four ways were identified in which text messages were used: reminders (14%), information (17%), supportive messages (42%), and self-monitoring procedures (42%). Applications were sometimes combined. | |
| - RCTs reported improved treatment adherence and symptom surveillance. care services -Other positive points included an increase in appointment attendance and in satisfaction with management and health | |||||||
| Boland et al. ( | From January 1980 to May 2016 | Systematic review and Meta-analysis | Technology-based smoking cessation interventions (eg, mobile phone (text or apps), internet, etc.), excluding telephone counseling or VHS video), or conventional mass media campaigns / Smoking | To assess the methodological quality and effectiveness of technology-based smoking cessation interventions in disadvantaged groups. | 13 studies/Disadvantaged groups (vulnerable populations or socioeconomic status or homeless persons or mental health patients or prisoners or juvenile delinquency or Indigenous/Maori/Inuit/north American Indian) | Cochrane Collaboration risk of bias tool was used. | - Regarding mobile text-messaging intervention alone (only one study), a significant effect was reported after 1 month of the intervention, with higher odds of smoking cessation among intervention groups (OR 2.81, 95% CI 1.58, 4.99). |
| Cox et al. ( | from 1992 to 18 September 2018 | Systematic review and Meta-analyssi | Text messaging interventions were defined as one or more text messages with health-related content sent to a personal mobile device. The comparator had to be usual care or an attention control One-way and two-way text messaging trials were included. Trials of smartphone applications were excluded./Depression | To quantify the effects of text messaging interventions to reduce depressive symptoms | Seven studies with 1,918 participants/Adults aged ≥18 years and were identified by a healthcare provider, to minimize volunteer bias. No exclusions were made on the basis of any reported medical condition among the participants | Cochrane risk of bias tool for RCTs was used | -Borderline statistically significant reduction in depressive symptom scores between the text messaging intervention and control groups favoring intervention. -Statistically significant reductions were shown in important subgroups, such as in those using the Beck Depression Inventory (BDI) or 9-item- Patient Health Questionnaire (PHQ-9) questionnaires; where text message content was targeted at mental well-being, mood improvement and cognitive behavioral therapy information; and when the message frequency was ≥2 times per week. |
| D'Arcey et al. ( | From January 2000 to March 2019 | Systematic review | Text message/Psychosis | To examine the clinical engagement and feasibility of SMS text messaging services in the treatment of psychosis | 15 studies/Demographic restrictions were not applied | - Most studies demonstrated the positive effects of SMS text messaging on dimensions of engagement such as medication adherence, clinic attendance, and therapeutic alliance. | |
| Senanayake et al. ( | Between 2012 and 2019 | A systematic review and meta-analysis of RCTs | Text messaging/Depression | To evaluate the effectiveness of text messaging interventions for the management of depression | Nine studies (945 patients: 764 adults and 181 adolescents) | Low risk of bias was expected (RCTs used), however publication bias may be expected where negative results may have not been published | - Five studies used text messaging as the only intervention, while the remaining combined text messaging with other treatment modalities such as behavioral activation or CBT. |
| Song, et al. ( | From December 2016 to March 2017 | Systematic review of RCTs | Mobile phone technologies (e.g., SMS, mHealth, interactive voice response (IVR) or app) / Unhealthy alcohol use (UHU) | To synthesize and understand the research evidence about the efficacy of mHealth interventions on various health outcomes for consumer self-control of UAU. | 19 studies/No specific characteristics were reported | - Over half of the SMS interventions were effective in reducing alcohol use or increasing readiness to change UAU in eight out of 12 studies (67%) | |
| Tofighi et al. ( | Not mentioned | Systematic review of the literature | Mobile phone messages (TM)/Drugs and alcohol dependence | To clarify the effects of TM intervention design characteristics (frequency, personalization, user-generated content, interactivity and privacy measures), patient engagement with the interventions, clinical outcomes, and potential adverse events | 11 articles/No specific characteristics were reported | -Most studies demonstrated improved clinical outcomes, medication adherence and engagement with peer support groups. | |
| Fowleret al. ( | From January 2004 to December 2015 | Systematic review of the literature of RCTs | Mobile technology-based interventions (e.g., SMS, texts or apps)/Harmful use of alcohol (alcohol-dependent and non-dependent) | To summarize the current literature and determine the efficacy of mobile technology-based interventions among adult users of alcohol interventions. | Eight studies/At least 18 years of age and reported using alcohol. | -Most of the studies found positive effects of the intervention, even though the interventions themselves varied in design, length, dosage, and target population, and were pilot or preliminary in nature. | |
| Watson et al. ( | From January 1999 to October 2015 | Systematic review | Text messages (TM) / Mental health disorders or SUD | To characterize the impact of TM interventions on medication adherence or mental health related outcomes (such as psychiatric symptoms and social functioning) in people with mental health disorders including substance use. | Seven studies/≥18 years | - Three studies evaluated TM in patients with schizophrenia or schizoaffective disorder, two studies for chronic alcohol dependence, and two for mood disorders. | |
| MacDougall et al. ( | From 2013 to 2020 | Scoping review | SMS text messaging-based interventions/Mental health and addiction care | To map and categorize gaps around the use of SMS text messaging-based interventions. | 31 studies with <100 participants in each trial/Children or Adolescents <18 years | -Intervention engagement was the most common type of outcome measured (18/31), followed by changes in cognitions (16/31); and acceptability (16/31). | |
| Dwyer et al. ( | Up to November 2020 | Scoping review | E-mental health approaches involving text-based, real-time communication with a qualified human therapist and the predictive power of language use patterns./Depression, suicidal ideation or anxiety | To map the research that has explored text-based e-mental health counseling services and studies that have used language use patterns to predict mental health status. | 70 studies/No specific characteristics were reported | -Text-based counseling is effective in treating psychological distress and depression and may be effective for treating substance abuse, reducing high-risk behaviors, and improving the subjective experiences of individuals with attention deficit hyperactivity disorder and/or autism. | |
| Berry et al. ( | From 2005 to 2015 | Systematic review | Online or mobile phone interventions/Severe mental illness (SMI): Psychosis, bipolar disorder, or personality disorder | To explore whether interventions delivered online and via mobile phones are hypothetically or actually acceptable for people with SMI. | 49 studies/No specific characteristics were reported | -The hypothetical acceptability of online and mobile phone-delivered interventions for SMI was relatively low, while actual acceptability tended to be high, however, hypothetical acceptability was higher for interventions delivered via text message than by email |
SAD, social anxiety disorder; DSM-5, Diagnostic and Statistical Manual of Mental Disorders, fifth edition; MI, motivational interviewing; VHS, Video home system.