Use Of mHealth Interventions Research Articles

MHealth interventions to improve public knowledge of HPV-associated oropharyngeal cancer in the UK

In the United Kingdom (UK), the current prevalence rates of oropharyngeal cancer linked to human papillomavirus (HPV) are 6.29% and 2.04% in men and women, respectively. Over the years, the burden of this disease has increased in the UK, and this is mainly due to the rising prevalence of HPV infection in the UK. Research evidence has shown that over 70% of oropharyngeal cancers in the UK are linked to HPV. Oral sex is the major route of transmission of HPV, and over 63% of UK young adults are found to have a positive history of oral sex practice. However, only a minority of the UK population are aware of HPV-associated oropharyngeal cancer; this therefore calls for more public health efforts to increase awareness and knowledge on HPV-associated oropharyngeal cancer in the UK. While the use of technology-based, clinic-based, and community-based interventions have been employed to improve public awareness and knowledge on the role of HPV-associated oropharyngeal cancer, mobile health (mhealth) interventions have not been seriously explored despite existing robust evidence on the effective roles of mhealth in improving awareness and knowledge in diverse diseases. This article therefore calls for the adoption and use of mhealth interventions in educating the UK’s population on HPV-associated oropharyngeal cancer. The use of mhealth interventions in this regard is highly viable as its implementation closely aligns with the country’s National Health Service (NHS) commitment towards the digital transformation of the UK’s healthcare system.

Determining the Effect of Voluntary Participation in Communicating with PLHIV in Siaya County, Kenya

Purpose: This research aimed to determine 1the effect 1of voluntary participation 1in communicating with PLHIV 1in 1Siaya, 1Kenya.
 Methodology: This study utilized a 1descriptive research approach and 1inferential 1design through a 1field survey, employing two distinct 1sets of questionnaires. One was administered 1to the key informant and the other to Persons Living with HIV (PLHIV).1Spearman’s 1rho 1correlations 1and simple linear1regression1models were also applied to assess the association between voluntary engagement as 1the independent variable and communication as the 1dependent 1variable. ANOVA 1test 1was also performed 1to test the hypothesis 1and results were 1presented 1in 1tables.
 Findings: The study comprised a sample size of 376 individuals, constituting 96.18% of willing respondents who agreed to participate in 1interviews. Seventeen unresponsive records were excluded from the analysis. A Normality 1Test was conducted to assess whether the study sample was drawn from a population with a normal distribution. Under the 1null 1hypothesis, no significant difference was found between the sample and the population it represented. Consequently, there was substantial evidence to reject the 1null 1hypothesis and accept the 1alternative 1hypothesis (p-value=0.000 CI=95%). Moreover, the findings revealed that 82.30% voluntarily enrolled in the 1Text 1for 1Adherence (T4A) 1mobile 1app, 70.71% signed the consent form, and 6.07% indicated that 1consent was implied.
 Unique Contribution to Theory, Practice and Policy: This study extends 1Technology readiness theory studies to mhealth field where it is beginning to gain traction. It also indicates the significance of individuals willingly participating in mHealth interventions upon enrollment. Voluntary participation is an imperative condition of any research undertaking. This study's results additionally confirmed that mHealth interventions enhance the well-being of individuals managing chronic illnesses. This study is likely to inform policy changes and or amendments in the mhealth space in many jurisdictions. An 1intervention 1such 1as 1Text for1Adherence (1T4A) may encourage 1the 1government 1to support system developers. It can also take over the project as a public health investment instead of leaving it to private sector or non-governmental organizations. Study further extends the body of knowledge in use of mhealth interventions.

Efficacy of mHealth Interventions for Improving Maternal and Neonatal Outcomes Among Pregnant Women With Hypertensive Disorders: Protocol for a Systematic Review.

Hypertension is one of the most prevalent medical conditions that arise during pregnancy, resulting in maternal and neonatal complications. Mobile health (mHealth) has emerged as an innovative intervention for delivering maternal and child health care services. The evidence on the effectiveness of mHealth interventions in improving the health outcomes of pregnant women with hypertensive disorders is lacking. Therefore, there is a need for evidence synthesis using systematic review methods to address this evidence gap. This review aims to determine the efficacy of mHealth interventions in improving maternal and neonatal outcomes among pregnant women with hypertensive disorders. The review will answer the following research questions: (1) What are the types of mHealth interventions used in pregnant women with hypertensive disorders? (2) Are the various mHealth interventions effective in improving maternal and neonatal health outcomes, health behaviors, and their knowledge of the disease? and (3) Are mHealth interventions effective in supporting health care providers to make health care decisions for pregnant women with hypertensive disorders? This review will include randomized controlled trials, nonrandomized controlled trials, and cohort studies focusing on mHealth interventions for pregnant women with hypertensive disorders. Studies reporting health care providers use of mHealth interventions in caring for pregnant women with hypertensive disorders will be included. The search strategy will be tailored to each database using database-specific search terms. The search will be conducted in PubMed-MEDLINE, ProQuest, CINAHL, Scopus, Web of Science, and CENTRAL. Other literature sources, such as trial registries and bibliographies of relevant studies, will be additionally searched. Studies published in English from January 2000 to January 2023 will be included. A total of 2 review authors will independently perform the data extraction and the quality appraisal. For quality appraisal of randomized controlled trials, the Cochrane Risk of Bias 2 tool will be used. The Risk of Bias in Nonrandomized Studies of Interventions (ROBINS-1) tool will be used for nonrandomized controlled trials, and the Critical Appraisal Skills Programme checklist for cohort studies will be used. Any disagreements between the 2 reviewers will be resolved through discussion and a third reviewer if required. A meta-analysis will be performed based on the availability of the data. As per the protocol, the study methodology was followed, and 2 independent reviewers conducted the search in 6 databases and clinical registries. Currently, the review is in the full-text screening stage. The review will publish the results in the first quarter of 2024. The evidence synthesized from this systematic review will help guide future research, support health care decisions, and inform policy makers on the effectiveness of mHealth interventions in improving the maternal and neonatal outcomes of pregnant women with hypertensive disorders. PRR1-10.2196/51792.

Efficacy, Safety, and Evaluation Criteria of mHealth Interventions for Depression: Systematic Review.

Depression is a significant public health issue that can lead to considerable disability and reduced quality of life. With the rise of technology, mobile health (mHealth) interventions, particularly smartphone apps, are emerging as a promising approach for addressing depression. However, the lack of standardized evaluation tools and evidence-based principles for these interventions remains a concern. In this systematic review and meta-analysis, we aimed to evaluate the efficacy and safety of mHealth interventions for depression and identify the criteria and evaluation tools used for their assessment. A systematic review and meta-analysis of the literature was carried out following the recommendations of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Studies that recruited adult patients exhibiting elevated depressive symptoms or those diagnosed with depressive disorders and aimed to assess the effectiveness or safety of mHealth interventions were eligible for consideration. The primary outcome of interest was the reduction of depressive symptoms, and only randomized controlled trials (RCTs) were included in the analysis. The risk of bias in the original RCTs was assessed using version 2 of the Cochrane risk-of-bias tool for randomized trials. A total of 29 RCTs were included in the analysis after a comprehensive search of electronic databases and manual searches. The efficacy of mHealth interventions in reducing depressive symptoms was assessed using a random effects meta-analysis. In total, 20 RCTs had an unclear risk of bias and 9 were assessed as having a high risk of bias. The most common element in mHealth interventions was psychoeducation, followed by goal setting and gamification strategies. The meta-analysis revealed a significant effect for mHealth interventions in reducing depressive symptoms compared with nonactive control (Hedges g=-0.62, 95% CI -0.87 to -0.37, I2=87%). Hybrid interventions that combined mHealth with face-to-face sessions were found to be the most effective. Three studies compared mHealth interventions with active controls and reported overall positive results. Safety analyses showed that most studies did not report any study-related adverse events. This review suggests that mHealth interventions can be effective in reducing depressive symptoms, with hybrid interventions achieving the best results. However, the high level of heterogeneity in the characteristics and components of mHealth interventions indicates the need for personalized approaches that consider individual differences, preferences, and needs. It is also important to prioritize evidence-based principles and standardized evaluation tools for mHealth interventions to ensure their efficacy and safety in the treatment of depression. Overall, the findings of this study support the use of mHealth interventions as a viable method for delivering mental health care. PROSPERO CRD42022304684; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=304684.

Assessing the Effectiveness of mHealth Interventions for Diabetes and Hypertension Management in Africa: Systematic Review and Meta-Analysis.

Mobile health (mHealth) interventions are effective in improving chronic disease management, mainly in high-income countries. However, less is known about the efficacy of mHealth interventions for the reduction of cardiovascular risk factors, including for hypertension and diabetes, which are rapidly increasing in low- and middle-income countries. This study aimed to assess the efficacy of mHealth interventions for diabetes and hypertension management in Africa. We searched PubMed, Cochrane Library, Google Scholar, African Journals Online, and Web of Science for relevant studies published from inception to July 2022. The main outcomes of interest were changes in hemoglobin A1c (HbA1c), systolic blood pressure, and diastolic blood pressure. The random or fixed effect model was used for the meta-analysis, and the I2 statistic was used to gauge study heterogeneity. Z tests and P values were used to evaluate the effect of mHealth interventions on HbA1c and blood pressure levels. This review included 7 studies (randomized controlled trials) with a total of 2249 participants. Two studies assessed the effect of mHealth on glycemic control, and 5 studies assessed the effect of mHealth on blood pressure control. The use of mHealth interventions was not associated with significant reductions in HbA1c levels (weighted mean difference [WMD] 0.20, 95% CI -0.40 to 0.80; P=.51) among patients with diabetes and systolic blood pressure (WMD -1.39, 95% CI -4.46 to 1.68; P=.37) and diastolic blood pressure (WMD 0.36, 95% CI -1.37 to 2.05; P=.69) among patients with hypertension. After conducting sensitivity analyses using the leave-one-out method, the Kingue et al study had an impact on the intervention, resulting in a 2 mm Hg reduction in systolic blood pressure (WMD -2.22, 95% CI -3.94 to -0.60; P=.01) but was nonsignificant for diastolic blood pressure and HbA1c levels after omitting the study. Our review provided no conclusive evidence for the effectiveness of mHealth interventions in reducing blood pressure and glycemic control in Africa among persons with diabetes and hypertension. To confirm these findings, larger randomized controlled trials are required.

“I am not shy anymore”: A qualitative study of the role of an interactive mHealth intervention on sexual health knowledge, attitudes, and behaviors of South African adolescents with perinatal HIV

BackgroundSouth Africa has one of the highest burdens of adolescents with perinatally-acquired HIV (APHIV) in the world. APHIV in South Africa have limited access to sexual and reproductive health (SRH) education and services specific to their HIV status. When lacking comprehensive SRH education, APHIV are prone to sexual risk behaviors that can lead to unintended pregnancy, sexually transmitted infections, and HIV transmission. The use of mHealth interventions has been shown to deliver information, foster social support, and improve decision-making skills. In this study, we evaluate how an mHealth intervention influences sexual health knowledge and behaviors in APHIV.MethodsWe purposively enrolled adolescents from the intervention arm of a randomized clinical trial assessing a multi-module, moderated WhatsApp-based intervention—Interactive Transition Support for Adolescents Living with HIV (InTSHA)—within a government supported clinic in KwaMashu, an urban township of KwaZulu-Natal, South Africa. We conducted in-depth interviews based on World Health Organization guidelines for asking adolescents about SRH. We thematically analyzed data through an iterative, team-based coding approach combining deductive and inductive elements to contextualize SRH attitudes, knowledge, and behaviors before and after receiving the InTSHA intervention.ResultsOf the 21 participants, 13 (61.9%) were female and the mean age was 16.6 years. Most participants reported first learning about SRH as young teenagers in school through non-targeted and negative ways, seeking clarification through peers and the internet rather than clinicians or caregivers. Participants reported that InTSHA provided a holistic perspective on relationships, gender, and sexuality specific to growing up with HIV in South Africa. They praised the ability to give and receive information from peers in a moderated setting through the mHealth intervention, building their confidence, decision-making skills, and communication with partners and caregivers throughout their everyday lives. Despite reporting some technological challenges, adolescents agreed that InTSHA was convenient, confidential, and user-friendly.ConclusionsSouth African APHIV receive incomplete and conflicting sexual education from peers, caregivers, teachers, and technology that can be supplemented by mHealth curricula targeted for the unique needs of APHIV. Future, scaled-up mHealth interventions can lower SRH stigma by expanding access to sexual education and peer support, supplementing adolescents’ existing SRH education.

MHealth Interventions to Support Caregivers of Older Adults: Equity-Focused Systematic Review.

BackgroundInformal caregivers, hereafter referred to as caregivers, provide support to older adults so that they can age safely at home. The decision to become a caregiver can be influenced by individual factors, such as personal choice, or societal factors such as social determinants of health, including household income, employment status, and culture-specific gender roles. Over time, caregivers’ health can be negatively affected by their caregiving roles. Although programs exist to support caregivers, the availability and appropriateness of services do not match caregivers’ expressed needs. Research suggests that supportive interventions offered through mobile health (mHealth) technologies have the potential to increase caregivers’ access to supportive services. However, a knowledge gap remains regarding the extent to which social determinants of health are considered in the design, implementation, and evaluation of mHealth interventions intended to support the caregivers of older adults.ObjectiveThis study aimed to conduct a systematic review to determine how health equity is considered in the design, implementation, and evaluation of mHealth interventions for caregivers of older adults using Cochrane Equity’s PROGRESS-Plus (place of residence, race, ethnicity, culture, language, occupation, gender, religion, education, social capital, socioeconomic status–plus age, disability, and sexual orientation) framework and synthesize evidence of the impacts of the identified caregiver-focused mHealth interventions.MethodsA systematic review was conducted using 5 databases. Articles published between January 2010 and June 2021 were included if they evaluated or explored the impact of mHealth interventions on the health and well-being of informal caregivers of older adults. mHealth interventions were defined as supportive services, for example, education, that caregivers of older adults accessed via mobile or wireless devices.ResultsIn total, 28 articles met the inclusion criteria and were included in the review. The interventions evaluated sought to connect caregivers with services, facilitate caregiving, and promote caregivers’ health and well-being. The PROGRESS-Plus framework factors were mainly considered in the results, discussion, and limitations sections of the included studies. Some PROGRESS-Plus factors such as sexual orientation, religion, and occupation, received little to no consideration across any phase of the intervention design, implementation, or evaluation. Overall, the findings of this review suggest that mHealth interventions were positively received by study participants. Such interventions have the potential to reduce caregiver burden and positively affect caregivers’ physical and mental health while supporting them as caregivers. The study findings highlight the importance of making support available to help facilitate caregivers’ use of mHealth interventions, as well as in the use of appropriate language and text.ConclusionsThe successful uptake and spread of mHealth interventions to support caregivers of older adults will depend on creating opportunities for the inclusive involvement of a broad range of stakeholders at all stages of design, implementation, and evaluation.

Effects of m-Health interventions on physical activity level and sedentary behavior in pre-hypertensive and hypertensive individuals: a systematic review

This study aims to identify the effects of m-Health interventions on physical activity (PA) level and sedentary behavior (SB) in pre-hypertensive and hypertensive adults. Therefore, a systematic literature search was conducted according to the guidelines defined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), in the scientific databases Web Of Science, MEDLINE/PubMed, SciELO, Scopus, and ACM Digital Library. Eligibility criteria were: clinical trials; description of the functionalities of m-Health apps (reminders, goals, wearables); description of the intervention characteristics (i.e., duration, expertise of professionals involved in the supervision, and others) and blood pressure assessment. In the end, 1447 studies were identified, of which 147 were duplicates. Through the screening by titles and abstracts, 43 studies were classified as relevant. However, only 12 studies met the eligibility criteria and were included in this systematic review. Most studies presented favorable results with the use of m-Health apps to increase PA and reduce SB. In addition, increasing PA and reducing SB might be an important non-pharmacological therapy to decrease blood pressure in hypertensive patients, when they follow the minimum recommendations proposed by the PA guidelines of the World Health Organization (WHO). However, further studies are still needed to assess the relationship between SB, PA and the use of m-Health interventions.

The Use of mHealth in Orthopedic Surgery: A Scoping Review.

(1) Background: It is well known that the success of surgical procedures is related to optimal postoperative management and follow-up. In this regard, mHealth technologies could potentially improve perioperative care. Based on these considerations, the objective of this scoping review is to evaluate the current status and use of mHealth interventions designed to provide perioperative care in orthopedic surgery. (2) Methods: This scoping review was conducted in accordance with the PRISMA statement (Extension for Scoping Review) and follows the framework of Arskey and O’Malley. (3) Results: The use of mHealth in the surgical setting is mainly oriented towards the development of applications for monitoring post-operative pain and optimizing communication between the various health professionals involved in patient care. (4) Conclusions: The mHealth systems can have a positive impact both on patient participation in the therapeutic process and on the communication between health professionals, increasing the quality of care.

Mobile health interventions for improving colorectal cancer screening rates: A systematic review and meta-analysis.

Objective:The aim of this systematic review and meta-analysis was to determine the efficacy of different mHealth interventions in increasing colorectal cancer (CRC) screening rates. Methods:A literature search for eligible studies was done in ClinicalTrials.gov, PubMed, and Scopus in October 2020. Included studies were randomized controlled trials done on adults due for CRC screening, who received either an mHealth intervention to promote screening or usual care. The primary outcome from these studies was completion of CRC screening. Two reviewers independently worked on selecting studies, collecting data, and determining risk of bias. Adjusted odds ratios (AOR) for CRC screening rates were summarized into a Forest plot. Results:A total of ten trials from three continents were included in the qualitative analysis. Risk of bias is low in terms of randomization, but high in terms of participant blinding, due to the nature of the interventions. Meta-analysis of four trials showed low clinical and statistical heterogeneity (I2=0%). Overall, the use of mHealth interventions is associated with higher CRC screening uptake when compared to usual care (AOR 1.33; 95% CI, 1.20-1.46). This effect was seen across different types of mHealth interventions, which included automated and non-automated telephone education and text-message reminders. Conclusion:This study showed that mHealth is associated with increased CRC screening participation regardless of the type of intervention used.

Use of mHealth technology for modification of behavioural risk factors of noncommunicable diseases in primary health care settings

Noncommunicable diseases (NCDs) kill 41 million people each year, of which more than three-quarters occur in low- and middle-income countries. Four groups of diseases, namely cardiovascular diseases, cancers, respiratory diseases, and diabetes, account for over 80% of all premature NCD deaths, and four common modifiable behaviors, namely tobacco use, physical inactivity, unhealthy diet, and the harmful use of alcohol, increase the risk of NCDs. The use of mHealth interventions for Behavior Change Communication has been shown to be effective in modifying the behavioral risk factors, through various studies. The present study proposes to conduct a systematic review and meta-analysis to assess the effectiveness and feasibility of the use of mHealth in improving diet and increasing physical activity, which are two of the major behavioral risk factors of NCDs. Research reported on this, from countries in the South-East Asian Region, during the past 20 years, will be included in this review.

Mothers intention and preference to use mobile phone text message reminders for child vaccination in Northwest Ethiopia

ObjectivesWith the unprecedented penetration of mobile devices in the developing world, mHealth applications are being leveraged for different health domains. Among the different factors that affect the use of mHealth...

A Review on Use of m-Health Interventions in Maternal Health

A Review on Use of m-Health Interventions in Maternal Health

Impact of mobile health (mHealth) interventions during the perinatal period for mothers in low- and middle-income countries: a systematic review.

The primary objective of this review was to determine the impact of mother-targeted mobile health (mHealth) educational interventions available during the perinatal period in low- and middle-income countries (LMICs) on maternal and neonatal outcomes. There has been significant growth of mHealth projects in LMICs. The use of mHealth interventions across the perinatal period offers the ability to share information with mothers about essential newborn care and to encourage mothers to attend perinatal clinics to obtain additional in-person support as needed. The impact of perinatal mHealth educational interventions on maternal behavior change and early neonatal mortality and morbidity outcomes in LMICs is unknown. This review considered studies that included mHealth educational interventions targeting mothers living in LMICs during the antenatal or postnatal period using mobile devices. The intervention must have been initiated during the antenatal period (conception through birth) through six weeks postnatally. All experimental study designs were included. Outcomes included maternal knowledge, maternal self-efficacy, antenatal/postnatal care attendance and newborn early morbidity and mortality. PubMed, Embase and CINAHL were searched on March 19, 2018 for studies published in English. The search was updated on June 7, 2018. Critical appraisal was undertaken by two independent reviewers using standardized critical appraisal instruments. Quantitative data were extracted from included studies independently by two reviewers using a standardized data extraction tool. All conflicts were resolved through consensus with a third reviewer. Quantitative data were, where possible, pooled in statistical meta-analysis. Where statistical pooling was not possible, the findings were reported narratively. A total of 1514 articles were screened, and 71 full-text papers were assessed for eligibility, with 23 articles critically appraised. Following appraisal, three articles were excluded due to poor quality. Of the 20 articles included, 16 were peer reviewed articles and four were gray literature reports. Eight papers targeted antenatal education, eight covered postnatal education and four covered both antenatal and postnatal education. Studies varied in terms of design, country, approach, frequency and content. Mothers who received an mHealth intervention attended a significantly greater number of antenatal care contacts (mean difference = 0.67, 95% confidence interval, 0.35 to 0.99, P = 0.0001) and were significantly more likely to have at least one postnatal care contact between six and eight weeks (odds ratio = 1.36, 95% confidence interval, 1.00 to 1.85, P = 0.05). Maternal knowledge, self-efficacy and neonatal mortality and morbidity were inconsistently reported across studies. mHealth education interventions are associated with increased maternal contact antenatally and postnatally in LMICs. Due to heterogeneity of studies among country of implementation, approach, frequency and content of the mHealth interventions, the impact on other maternal and neonatal outcomes is inconclusive. Future work using mHealth to target maternal education during the perinatal period should focus on standardization of content and outcome evaluations.

Attitudes, Beliefs, and Willingness Toward the Use of mHealth Tools for Medication Adherence in the Florida mHealth Adherence Project for People Living With HIV (FL-mAPP): Pilot Questionnaire Study.

BackgroundAntiretroviral (ART) adherence among people living with HIV (PLWH) continues to be a challenge despite advances in HIV prevention and treatment. Mobile health (mHealth) interventions are increasingly deployed as tools for ART adherence. However, little is known about the uptake and attitudes toward commercially available, biprogrammatic mobile apps (ie, designed for both smartphone and short message service [SMS] messaging) among demographically diverse PLWH.ObjectivesThe Florida mHealth Adherence Project for PLWH (FL-mAPP) is an innovative pilot study that aimed to determine the acceptability of a commercially available, biprogrammatic mHealth intervention platform to ensure medication adherence and gauge the current attitudes of PLWH toward current and future mHealth apps.MethodsA predeveloped, commercially available, biprogrammatic mHealth platform (Care4Today Mobile Health Manager, Johnson & Johnson, New Brunswick, NJ) was deployed, with self-reported ART adherence recorded in the app and paper survey at both short term (30-day) or long-term (90-day) follow-ups. Consented participants completed baseline surveys on sociodemographics and attitudes, beliefs, and willingness toward the use of mHealth interventions for HIV care using a 5-point Likert scale. Chi-square tests and multivariate logistic regression analyses identified correlations with successful uptake of the mHealth platform.ResultsAmong 132 PLWH, 66% (n=87) initially agreed to use the mHealth platform, of which 54% (n=47) successfully connected to the platform. Of the 87 agreeing to use the mHealth platform, we found an approximate 2:1 ratio of persons agreeing to try the smartphone app (n=59) versus the SMS text messages (n=28). Factors correlating with mHealth uptake were above high school level education (adjusted odds ratio 2.65; P=.05), confidence that a clinical staff member would assist with mHealth app use (adjusted odds ratio 2.92, P=.048), belief that PLWH would use such an mHealth app (adjusted odds ratio 2.89; P=.02), and ownership of a smartphone in contrast to a “flip-phone” model (adjusted odds ratio 2.80; P=.05). Of the sample, 70.2% (n=92) reported daily interest in receiving medication adherence reminders via an app (80.4% users versus 64.7% nonusers), although not significantly different among the user groups (P=.06). In addition, 34.8% (n=16) of mHealth users reported a theoretical “daily” interest and 68.2% (n=58) of non-mHealth users reported no interest in using an mHealth app for potentially tracking alcohol or drug intake (P=.002).ConclusionsThis commercially available, biprogrammatic mHealth platform showed feasibility and efficacy for enhanced ART and medication adherence within public health clinics and successfully included older age groups. Successful use of the platform among demographically diverse PLWH is important for HIV implementation science and promising for uptake on a larger scale.

Perceptions of Health Care Providers Regarding a Mobile Health Intervention to Manage Chronic Obstructive Pulmonary Disease: Qualitative Study.

BackgroundUsing a mobile health (mHealth) intervention, consisting of a smartphone and compatible medical device, has the potential to enhance chronic obstructive pulmonary disease (COPD) treatment outcomes while mitigating health care costs.ObjectiveThe aim of this study was to explore the potential facilitators and barriers among health care providers (HCPs) regarding the use of mHealth interventions for COPD management.MethodsThis was a qualitative study. Semistructured individual interviews were conducted with HCPs, including nurses, pharmacists, and physicians who work directly with patients with COPD. A flexible prompts guide was used to facilitate discussions. Interview topics included the following: demographics, mHealth usage, perceptions toward challenges of mHealth adoption, factors facilitating mHealth adoption, and preferences regarding features of the mHealth intervention for COPD management. Interviews were conversational in nature, and items were not asked verbatim or in the order presented. The interviews were transcribed verbatim and compared against the digital recordings to ensure the accuracy of the content. After creating a codebook for analysis, 2 researchers independently coded the remaining interview data using pattern coding. They discussed commonalities and differences in coding until a consensus was reached.ResultsA total of 30 nurses, physicians, and pharmacists participated. The main facilitators to mHealth adoption are possible health benefits for patients, ease of use, educating patients and their HCPs, credibility, and reducing cost to the health care system. Alternatively, the barriers to adoption are technical issues, privacy and confidentiality issues, lack of awareness, potential limited uptake from the elderly, potential limited connection between patients and HCPs, and finances.ConclusionsIt is important to understand the perceptions of HCPs regarding the adoption of innovative mHealth interventions for COPD management. This study identifies some potential facilitators and barriers that may inform the successful development and implementation of mHealth interventions for COPD management.

Data Mining in the Development of Mobile Health Apps: Assessing In-App Navigation Through Markov Chain Analysis.

BackgroundMobile apps generate vast amounts of user data. In the mobile health (mHealth) domain, researchers are increasingly discovering the opportunities of log data to assess the usage of their mobile apps. To date, however, the analysis of these data are often limited to descriptive statistics. Using data mining techniques, log data can offer significantly deeper insights.ObjectiveThe purpose of this study was to assess how Markov Chain and sequence clustering analysis can be used to find meaningful usage patterns of mHealth apps.MethodsUsing the data of a 25-day field trial (n=22) of the Start2Cycle app, an app developed to encourage recreational cycling in adults, a transition matrix between the different pages of the app was composed. From this matrix, a Markov Chain was constructed, enabling intuitive user behavior analysis.ResultsThrough visual inspection of the transitions, 3 types of app use could be distinguished (route tracking, gamification, and bug reporting). Markov Chain–based sequence clustering was subsequently used to demonstrate how clusters of session types can otherwise be obtained.ConclusionsUsing Markov Chains to assess in-app navigation presents a sound method to evaluate use of mHealth interventions. The insights can be used to evaluate app use and improve user experience.

How and why front-line health workers (did not) use a multifaceted mHealth intervention to support maternal and neonatal healthcare decision-making in Ghana

IntroductionDespite increasing use of mHealth interventions, there remains limited documentation of ‘how and why’ they are used and therefore the explanatory mechanisms behind observed effects on beneficiary health outcomes. We...

Adoption of Mobile Apps for Depression and Anxiety: Cross-Sectional Survey Study on Patient Interest and Barriers to Engagement.

BackgroundEmerging research suggests that mobile apps can be used to effectively treat common mental illnesses like depression and anxiety. Despite promising efficacy results and ease of access to these interventions, adoption of mobile health (mHealth; mobile device–delivered) interventions for mental illness has been limited. More insight into patients’ perspectives on mHealth interventions is required to create effective implementation strategies and to adapt existing interventions to facilitate higher rates of adoption.ObjectiveThe aim of this study was to examine, from the patient perspective, current use and factors that may impact the use of mHealth interventions for mental illness.MethodsThis was a cross-sectional survey study of veterans who had attended an appointment at a single Veterans Health Administration facility in early 2016 that was associated with one of the following mental health concerns: unipolar depression, any anxiety disorder, or posttraumatic stress disorder. We used the Veteran Affairs Corporate Data Warehouse to create subsets of eligible participants demographically stratified by gender (male or female) and minority status (white or nonwhite). From each subset, 100 participants were selected at random and mailed a paper survey with items addressing the demographics, overall health, mental health, technology ownership or use, interest in mobile app interventions for mental illness, reasons for use or nonuse, and interest in specific features of mobile apps for mental illness.ResultsOf the 400 potential participants, 149 (37.3%, 149/400) completed and returned a survey. Most participants (79.9%, 119/149) reported that they owned a smart device and that they use apps in general (71.1%, 106/149). Most participants (73.1%, 87/149) reported interest in using an app for mental illness, but only 10.7% (16/149) had done so. Paired samples t tests indicated that ratings of interest in using an app recommended by a clinician were significantly greater than general interest ratings and even greater when the recommending clinician was a specialty mental health provider. The most frequent concerns related to using an app for mental illness were lacking proof of efficacy (71.8%, 107/149), concerns about data privacy (59.1%, 88/149), and not knowing where to find such an app (51.0%, 76/149). Participants expressed interest in a number of app features with particularly high-interest ratings for context-sensitive apps (85.2%, 127/149), and apps focused on the following areas: increasing exercise (75.8%, 113/149), improving sleep (73.2%, 109/149), changing negative thinking (70.5%, 105/149), and increasing involvement in activities (67.1%, 100/149).ConclusionsMost respondents had access to devices to use mobile apps for mental illness, already used apps for other purposes, and were interested in mobile apps for mental illness. Key factors that may improve adoption include provider endorsement, greater publicity of efficacious apps, and clear messaging about efficacy and privacy of information. Finally, multifaceted apps that address a range of concerns, from sleep to negative thought patterns, may be best received.

A Systematic Review of the mHealth Interventions to Prevent Alcohol and Substance Abuse

Substance abuse in young adults is a public health issue with costs to the individual and society. There is mounting evidence that the increased uses of mHealth approaches have promise as a way to facilitate reductions in substance use. This systematic review evaluated the recent body of research on mHealth-based interventions for substance use, with aims of (a) examining the functionality and effectiveness of these interventions, (b) evaluating the available research on the effectiveness of these interventions for substance use, and (c) evaluating the design, methodology, results, theoretical grounding, limitations, and implications of each study. We identified eligible studies by searching electronic databases using Boolean methods. The reviewed studies (N = 12) indicated that that a wide range of Internet-based, text messaging, and smartphone application interventions have been developed to address substance use. Interventions had an assortment of features; participants in each study highlighted the ease and convenience of the interventions; and the majority of studies provided support for the efficacy of mHealth in reducing substance use. Mobile technology is a promising tool for reducing substance use and warrants further development. Future practice including the use of mHealth interventions can be an integral part of reducing substance use.