Project description:BackgroundAs mobile technology continues expanding, researchers have been using mobile phones to conduct health interventions (mobile health-mHealth-interventions). The multiple features of mobile phones offer great opportunities to disseminate large-scale, cost-efficient, and tailored messages to participants. However, the interventions to date have shown mixed results, with a large variance of effect sizes (Cohen d=-0.62 to 1.65).ObjectiveThe study aimed to generate cumulative knowledge that informs mHealth intervention research. The aims were twofold: (1) to calculate an overall effect magnitude for mHealth interventions compared with alternative interventions or conditions, and (2) to analyze potential moderators of mHealth interventions' comparative efficacy.MethodsComprehensive searches of the Communication & Mass Media Complete, PsycINFO, Web of Knowledge, Academic Search Premier, PubMed and MEDLINE databases were conducted to identify potentially eligible studies in peer-reviewed journals, conference proceedings, and dissertations and theses. Search queries were formulated using a combination of search terms: "intervention" (Title or Abstract) AND "health" (Title or Abstract) AND "*phone*" OR "black-berr*" (OR mHealth OR "application*" OR app* OR mobile OR cellular OR "short messag*" OR palm* OR iPhone* OR MP3* OR MP4* OR iPod*) (Title or Abstract). Cohen d was computed as the basic unit of analysis, and the variance-weighted analysis was implemented to compute the overall effect size under a random-effects model. Analysis of variance-like and meta-regression models were conducted to analyze categorical and continuous moderators, respectively.ResultsThe search resulted in 3424 potential studies, the abstracts (and full text, as necessary) of which were reviewed for relevance. Studies were screened in multiple stages using explicit inclusion and exclusion criteria, and citations were evaluated for inclusion of qualified studies. A total of 64 studies were included in the current meta-analysis. Results showed that mHealth interventions are relatively more effective than comparison interventions or conditions, with a small but significant overall weighted effect size (Cohen d=0.31). In addition, the effects of interventions are moderated by theoretical paradigm, 3 engagement types (ie, changing personal environment, reinforcement tracking, social presentation), mobile use type, intervention channel, and length of follow-up.ConclusionsTo the best of our knowledge, this is the most comprehensive meta-analysis to date that examined the overall effectiveness of mHealth interventions across health topics and is the first study that statistically tested moderators. Our findings not only shed light on intervention design using mobile phones, but also provide new directions for research in health communication and promotion using new media. Future research scholarship is needed to examine the effectiveness of mHealth interventions across various health issues, especially those that have not yet been investigated (eg, substance use, sexual health), engaging participants using social features on mobile phones, and designing tailored mHealth interventions for diverse subpopulations to maximize effects.
Project description:Physical activity has been shown to improve outcomes across a range of physical and mental health conditions as an adjunct or standalone intervention for many mental disorders. The outcome and effectiveness of physical activity in acute mental health units are less well understood. Systematic searches were completed in three databases (CINAHL, MEDLINE, and PsycINFO). Eligible studies were published between March 2013 and February 2024, included a physical activity intervention for inpatients on acute mental health units, and reported primary quantitative, qualitative, or mixed methods data for patients between 18 and 65 years of age. Participants must have had a primary diagnosis of a mental health condition with or without physical comorbidities. Data extracted included reported components of the interventions and individual health outcomes. Methodological quality and risk of bias was assessed using the mixed methods appraisal tool and cochrane risk of bias tools for randomised and non-randomised controlled trials. Twelve studies were identified for review (combined sample size of 560). Seven studies reported improvements in mental health outcomes, and two reported improvements in physical health outcomes in favour of the intervention group. There was a large variation between intervention characteristics and clarity in reporting. Assessment and measurement of outcomes contributed to a high risk of bias among included studies due largely to self-assessment. Physical activity interventions on AMHUs have the potential to contribute to improvements in mental and physical wellbeing beyond that experienced from usual treatment practices (e.g., medication). However, further work is needed in the specific context of acute mental health units regarding the development and evaluation of physical activity interventions.
Project description:This systematic review and meta-analysis assessed the effectiveness of physical activity interventions on undergraduate students' mental health. Seven databases were searched and a total of 59 studies were included. Studies with a comparable control group were meta-analysed, and remaining studies were narratively synthesized. The included studies scored very low GRADE and had a high risk of bias. Meta-analyses indicated physical activity interventions are effective in reducing symptoms of anxiety (n = 20, standardized mean difference (SMD) = -0.88, 95% CI [-1.23, -0.52]), depression (n = 14, SMD = -0.73, 95% CI [-1.00, -0.47]) and stress (n = 10, SMD = -0.61, 95% CI [-0.94, -0.28]); however, there was considerable heterogeneity (anxiety, I2 = 90.29%; depression I2 = 49.66%; stress I2 = 86.97%). The narrative synthesis had mixed findings. Only five studies reported being informed by a behavioural change theory and only 30 reported intervention fidelity. Our review provides evidence supporting the potential of physical activity interventions in enhancing the mental health of undergraduate students. More robust intervention design and implementation are required to better understand the effectiveness of PA interventions on mental health outcomes.
Project description:ImportanceMobile health interventions are increasingly popular in pediatrics; however, it is unclear how effective these interventions are in changing health outcomes.ObjectiveTo determine the effectiveness of mobile health interventions for improving health outcomes in youth 18 years or younger.Data sourcesStudies published through November 30, 2016, were collected through PubMed, Cumulative Index to Nursing and Allied Health Literature, Educational Resources Information Center, and PsychINFO. Backward and forward literature searches were conducted on articles meeting study inclusion criteria. Search terms included telemedicine, eHealth, mobile health, mHealth, app, and mobile application.Study selectionSearch results were limited to infants, children, adolescents, or young adults when possible. Studies were included if quantitative methods were used to evaluate an application of mobile intervention technology in a primary or secondary capacity to promote or modify health behavior in youth 18 years or younger. Studies were excluded if the article was an unpublished dissertation or thesis, the mean age of participants was older than 18 years, the study did not assess a health behavior and disease outcome, or the article did not include sufficient statistics. Inclusion and exclusion criteria were applied by 2 independent coders with 20% overlap. Of 9773 unique articles, 36 articles (containing 37 unique studies with a total of 29 822 participants) met the inclusion criteria.Data extraction and synthesisOf 9773 unique articles, 36 articles (containing 37 unique studies) with a total of 29 822 participants met the inclusion criteria. Effect sizes were calculated from statistical tests that could be converted to standardized mean differences. All aggregate effect sizes and moderator variables were tested using random-effects models.Main outcomes and measuresChange in health behavior or disease control.ResultsA total of 29 822 participants were included in the studies. In studies that reported sex, the total number of females was 11 226 (53.2%). Of those reporting age, the average was 11.35 years. The random effects aggregate effect size of mobile health interventions was significant (n = 37; Cohen d = 0.22; 95% CI, 0.14-0.29). The random effects model indicated that providing mobile health intervention to a caregiver increased the strength of the intervention effect. Studies that involved caregivers in the intervention produced effect sizes (n = 16; Cohen d = 0.28; 95% CI, 0.18-0.39) larger than those that did not include caregivers (n = 21; Cohen d = 0.13; 95% CI, 0.02-0.25). Other coded variables did not moderate study effect size.Conclusions and relevanceMobile health interventions appear to be a viable health behavior change intervention modality for youth. Given the ubiquity of mobile phones, mobile health interventions offer promise in improving public health.
Project description:BackgroundWith increasing evidence supporting the benefits of physical activity (PA) for older adults, there is a critical need for effective interventions to promote activity in this population. Mobile health (mHealth) technologies offer innovative approaches to enhance engagement in PA, yet evidence of their effectiveness remains varied and insufficiently synthesized. This systematic review and meta-analysis aims to evaluate the effectiveness of mHealth interventions in improving physical health, quality of life, cognitive function, and mental well-being among community-dwelling older adults aged 65 years and over.MethodsThis systematic review and meta-analysis followed the PRISMA guidelines, focusing on studies that utilized mHealth interventions to promote PA among community-dwelling older adults aged 65 years and older. The literature search included electronic databases like PubMed, Web of Science and CENTRAL, with studies published from 2014 onwards. Eligible studies were randomized controlled trials (RCTs), non-RCTs, and single-group studies that provided quantitative and qualitative data on physical health outcomes.ResultsThe search yielded 4,453 studies, with 22 meeting the inclusion criteria. These studies involved a total of 3,055 participants, primarily from high-income countries. The interventions included the use of an application (n=5), websites (n=7), wearable device (n=3), website + wearable device (n=3), and application + wearable device (n=3). Meta-analysis of 11 RCTs, representing 2,204 participants, showed an overall significant effect of the mHealth intervention [standardized mean difference =0.23; 95% confidence interval: 0.08-0.38], subgroup analysis shows varied effects on PA levels, with some studies reporting significant improvements in PA metrics, while others showed minimal impact.ConclusionsmHealth interventions have the potential to promote PA among older adults, but the effectiveness is highly variable. This variability may be influenced by intervention design, technology used, and participant engagement. Future research should focus on personalized, adaptable mHealth solutions that address the specific needs and preferences of older adults to enhance sustained engagement and effectiveness.
Project description:Diet, physical activity, smoking and alcohol behaviour-change interventions delivered in pregnancy aim to prevent adverse pregnancy outcomes. This review reports a synthesis of evidence from meta-analyses on the effectiveness of interventions at reducing risk of adverse health outcomes. Sixty-five systematic reviews (63 diet and physical activity; 2 smoking) reporting 602 meta-analyses, published since 2011, were identified; no data were identified for alcohol interventions. A wide range of outcomes were reported, including gestational weight gain, hypertensive disorders, gestational diabetes (GDM) and fetal growth. There was consistent evidence from diet and physical activity interventions for a significantly reduced mean gestational weight gain (ranging from -0.21 kg (95% confidence interval -0.34, -0.08) to -5.77 kg (95% CI -9.34, -2.21). There was evidence from larger diet and physical activity meta-analyses for a significant reduction in postnatal weight retention, caesarean delivery, preeclampsia, hypertension, GDM and preterm delivery, and for smoking interventions to significantly increase birth weight. There was no statistically significant evidence of interventions having an effect on low or high birthweight, neonatal intensive care unit admission, Apgar score or mortality outcomes. Priority areas for future research to capitalise on pregnancy as an opportunity to improve the lifelong wellbeing of women and their children are highlighted.
Project description:BackgroundThe initial introduction of the World Wide Web in 1990 brought around the biggest change in information acquisition. Due to the abundance of devices and ease of access they subsequently allow, the utility of mobile health (mHealth) has never been more endemic. A substantial amount of interactive and psychoeducational apps are readily available to download concerning a wide range of health issues. mHealth has the potential to reduce waiting times for appointments; eradicate the need to meet in person with a clinician, successively diminishing the workload of mental health professionals; be more cost effective to practices; and encourage self-care tactics. Previous research has given valid evidence with empirical studies proving the effectiveness of physical and mental health interventions using mobile apps. Alongside apps, there is evidence to show that receiving short message service (SMS) messages, which entail psychoeducation, medication reminders, and links to useful informative Web pages can also be advantageous to a patient's mental and physical well-being. Available mHealth apps and SMS services and their ever improving quality necessitates a systematic review in the area in reference to reduction of symptomology, adherence to intervention, and usability.ObjectiveThe aim of this review was to study the efficacy, usability, and feasibility of mobile apps and SMS messages as mHealth interventions for self-guided care.MethodsA systematic literature search was carried out in JMIR, PubMed, PsychINFO, PsychARTICLES, Google Scholar, MEDLINE, and SAGE. The search spanned from January 2008 to January 2017. The primary outcome measures consisted of weight management, (pregnancy) smoking cessation, medication adherence, depression, anxiety and stress. Where possible, adherence, feasibility, and usability outcomes of the apps or SMS services were evaluated. Between-group and within-group effect sizes (Cohen d) for the mHealth intervention method group were determined.ResultsA total of 27 studies, inclusive of 4658 participants were reviewed. The papers included randomized controlled trials (RCTs) (n=19), within-group studies (n=7), and 1 within-group study with qualitative aspect. Studies show improvement in physical health and significant reductions of anxiety, stress, and depression. Within-group and between-group effect sizes ranged from 0.05-3.37 (immediately posttest), 0.05-3.25 (1-month follow-up), 0.08-3.08 (2-month follow-up), 0.00-3.10 (3-month follow-up), and 0.02-0.27 (6-month follow-up). Usability and feasibility of mHealth interventions, where reported, also gave promising, significant results.ConclusionsThe review shows the promising and emerging efficacy of using mobile apps and SMS text messaging as mHealth interventions.
Project description:A systematic review and meta-analysis were conducted to assess the effectiveness of app-based mobile interventions for improving nutrition behaviours and nutrition-related health outcomes, including obesity indices (eg, body mass index [BMI]) and clinical parameters (eg, blood lipids). Seven databases were searched for studies published between 2006 and 2017. Forty-one of 10 132 identified records were included, comprising 6348 participants and 373 outcomes with sample sizes ranging from 10 to 833, including 27 randomized controlled trials (RCTs). A beneficial effect of app-based mobile interventions was identified for improving nutrition behaviours (g = 0.19; CI, 0.06-0.32, P = .004) and nutrition-related health outcomes (g = 0.23; CI, 0.11-0.36, P < .001), including positive effects on obesity indices (g = 0.30; CI, 0.15-0.45, P < .001), blood pressure (g = 0.21; CI, 0.01-0.42, P = .043), and blood lipids (g = 0.15; CI, 0.03-0.28, P = .018). Most interventions were composed of four behaviour change technique (BCT) clusters, namely, "goals/planning," "feedback/monitoring," "shaping knowledge," and "social support." Moderating effects including study design, type of app (commercial/research app), sample characteristics (clinical/non-clinical sample), and intervention characteristics were not statistically significant. The inclusion of additional treatment components besides the app or the number or type of BCTs implemented did not moderate the observed effectiveness, which underscores the potential of app-based mobile interventions for implementing effective and feasible interventions operating at scale for fighting the obesity epidemic in a broad spectrum of the population.
Project description:IntroductionCardiovascular disease is among the most common of non-communicable diseases, affecting 13.9 million children and young people (CYP) globally. Survival rates for CYP with heart conditions are rising, however, support for adjusting to life with a heart condition is lacking, as such it is unsurprising that one in three suffer from anxiety, depression or adjustment disorder. The proposed review aims to identify and assess the effectiveness of physical and mental health interventions across physical and mental health outcomes in young people with cardiac conditions using narrative synthesis and meta-analysis if appropriate.Methods and analysisEmbase, Medline, PubMed, PsycINFO, Cochrane Databases, Web of Science and reference lists of relevant publications will be searched from 1980 to June 2022 for articles published in English or Italian. Screening, data extraction, intervention coding and risk of bias will be performed by two independent reviewers using an extraction checklist. Intervention content and features will be identified and reported using the Template for Intervention Description and Replication checklist. A narrative review of the included studies will be conducted. If possible and appropriate, a random-effects model meta-analysis will be conducted to calculate the pooled within-group and between-group effect sizes for the primary outcome measures. If sufficient data are available, a subgroup meta-analysis will investigate whether specific intervention types are associated with different levels of intervention effectiveness.Ethics and disseminationThis systematic review does not directly involve the use of human beings, therefore, there is no requirement for ethical approval. Findings will be disseminated through peer-reviewed publication and in various media, such as conferences, congresses or symposia.Prospero registration numberCRD42022330582.
Project description:BackgroundWith a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps-their target patient group, health behavior, and behavioral change strategies-has resulted in a large but incohesive body of literature.ObjectiveThis systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps.MethodsPubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer.ResultsA total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis-37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive-only one app was rated as less helpful and satisfactory than the control-and the studies that measured engagement and usability found relatively high study completion rates (mean 83%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70%). However, there was little evidence of changed behavior or health outcomes.ConclusionsThere was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias.