scholarly journals Enhanced Self-Efficacy and Behavioral Changes Among Patients With Diabetes: Cloud-Based Mobile Health Platform and Mobile App Service (Preprint)

2018 ◽  
Author(s):  
Dyna YP Chao ◽  
Tom MY Lin ◽  
Wen-Ya Ma

BACKGROUND The prevalence of chronic disease is increasing rapidly. Health promotion models have shifted toward patient-centered care and self-efficacy. Devices and mobile app in the Internet of Things (IoT) have become critical self-management tools for collecting and analyzing personal data to improve individual health outcomes. However, the precise effects of Web-based interventions on self-efficacy and the related motivation factors behind individuals’ behavioral changes have not been determined. OBJECTIVE The objective of this study was to gain insight into patients' self-efficacy with newly diagnosed diabetes (type 2 diabetes mellitus) and analyze the association of patient-centered health promotion behavior and to examine the implications of the results for IoT and mobile health mobile app features. METHODS The study used data from the electronic health database (n=3128). An experimental design (n=121) and randomized controlled trials were employed to determine patient preferences in the health promotion program (n=62) and mobile self-management education (n=28). The transtheoretical model was used as a framework for observing self-management behavior for the improvement of individual health, and the theory of planned behavior was used to evaluate personal goals, execution, outcome, and personal preferences. A mobile app was used to determine individualized health promotion interventions and to apply these interventions to improve patients’ self-management and self-efficacy. RESULTS Mobile questionnaires were administered for pre- and postintervention assessment through mobile app. A dynamic questionnaire allocation method was used to follow up and monitor patient behavioral changes in the subsequent 6 to 18 months. Participants at a high risk of problems related to blood pressure (systolic blood pressure ≥120 mm Hg) and body mass index (≥23 kg/m2) indicated high motivation to change and to achieve high scores in the self-care knowledge assessment (n=49, 95% CI −0.26% to −0.24%, P=.052). The associated clinical outcomes in the case group with the mobile-based intervention were slightly better than in the control group (glycated hemoglobin mean −1.25%, 95% CI 6.36 to 7.47, P=.002). In addition, 86% (42/49) of the participants improved their health knowledge through the mobile-based app and information and communications technology. The behavior-change compliance rate was higher among the women than among the men. In addition, the personal characteristics of steadiness and dominance corresponded with a higher compliance rate in the dietary and wellness intervention (83%, 81/98). Most participants (71%, 70/98) also increased their attention to healthy eating, being active, and monitoring their condition (30% 21/70, 21% 15/70, and 20% 14/70, respectively). CONCLUSIONS The overall compliance rate was discovered to be higher after the mobile app–based health intervention. Various intervention strategies based on patient characteristics, health care–related word-of-mouth communication, and social media may be used to increase self-efficacy and improve clinical outcomes. Additional research should be conducted to determine the most influential factors and the most effective adherence management techniques.

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 57-58
Author(s):  
Anna M Hood ◽  
Cara Nwankwo ◽  
Emily McTate ◽  
Naomi E Joffe ◽  
Charles T. Quinn ◽  
...  

Background: Sickle cell disease (SCD) is associated with medical challenges that often worsen for adolescents and young adults (AYA) when caregivers begin to transfer responsibility for care. Living with SCD requires self-management and self-efficacy and is a critical concern for AYA as they navigate complex medical systems. However, previous research indicates that AYA with SCD often lack the ability, confidence, and skills to manage their disease effectively. As most AYA with SCD are now "technology natives," mobile health (mHealth) holds considerable promise for assessing and changing behaviors to improve health outcomes. In a previous feasibility and acceptability study, AYA with SCD provided qualitative feedback that they would use mHealth (a co-designed mobile app) and that it was beneficial for tracking health behaviors. Thus, we integrated the mHealth app into a group intervention (SCThrive) and hypothesized that more engagement with the mHealth app would result in increased self-management and self-efficacy for AYA with SCD. Methods: Our analysis from a single-site, randomized control trial (NCT02851615) assessed data from only AYA in the treatment arm (N = 26) who received the SCThrive intervention and used the mHealth app. The sample included AYA with SCD aged 13 to 21 years (Mage = 16.7 years; 54% female; 46% HbSS genotype; all African American/Black) who received six-weekly group sessions (3 in-person, 3 online). All SCThrive participants were provided with the mobile app (iManage) on an iPad. The Transition Readiness Assessment Questionnaire (TRAQ-5) assessed self-management skills and the Patient Activation Measure (PAM-13) assessed self-efficacy at baseline and posttreatment. We also assessed engagement (logins), confidence and completion of self-management goals (e.g., exercising, take medications), pain diary entries, and mood symptoms recorded on the iManage app (see Figure 1). Results: Preliminary analyses indicated that most AYA with SCD logged on to the iManage app (Mlogins = 7.8, SD = 9.1, range = 1 - 45) and viewed their pain diary (Mviews = 5.7, SD = 9.1, range = 1 - 45) at least once a week. Eighty-eight percent of AYA saved a pain diary entry and the most commonly used strategies for managing pain episodes were resting (22%), drinking water (19%), and using distraction (8%). AYA viewed their self-management goals about once every 11 days (Mdays = 11.24, SD = 13, range = 0 - 57). All AYA created (Mgoals = 5.7, SD = .72, range = 4 - 7), but only 54% of AYA completed at least one self-management goal. Of the 149 self-management goals created by the entire sample, only 37 (25%) were recorded as completed. AYA with a confidence level of 7 or lower were least likely to complete their self-management goals (14%) (see Figure 2). Correlation analyses demonstrated that logging on to the iManage app more frequently was associated with completing more self-management goals (r = .38), documenting pain symptoms more frequently (r = .54), and lower mood ratings (r = .54). Primary analyses demonstrated that after controlling for scores at baseline, the number of logins to the iManage app (p = .08, η2 = .13) predicted self-efficacy (PAM-13) and (p = .05, η2 = .17) self-management skills (TRAQ-5). Completing more self-management goals on the iManage app did not predict scores on the PAM-13, but, surprisingly, predicted lower scores (less self-management) on the TRAQ-5 (p = .08, η2 = .14). Conclusion: Lessons learned from our study indicate that it can be challenging to maintain engagement in mHealth for AYA with SCD, but for those who do engage there are significant benefits related to self-management goals, documenting pain symptoms, and mood. Supporting hypotheses, engaging more with the iManage app was related to higher-reported self-efficacy and self-management skills. Some AYA engaged with the app infrequently and did not create or complete self-management goals; others were "super users" and logged into the app daily. Increasing the frequency of reminder messages, encouraging more interactions with peers, and tailoring the opportunity to earn incentives are potential modifications for future interventions. However, our findings indicate that a mHealth app can be effectively integrated into a clinical trial and is related to positive outcomes. Although there are challenges to address, mHealth has the potential to bring about changes in behavior and improve health in the SCD population. Disclosures No relevant conflicts of interest to declare.


10.2196/17776 ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. e17776 ◽  
Author(s):  
Ran Li ◽  
Ning Liang ◽  
Fanlong Bu ◽  
Therese Hesketh

Background Effective treatment of hypertension requires careful self-management. With the ongoing development of mobile technologies and the scarcity of health care resources, mobile health (mHealth)–based self-management has become a useful treatment for hypertension, and its effectiveness has been assessed in many trials. However, there is a paucity of comprehensive summaries of the studies using both qualitative and quantitative methods. Objective This systematic review aimed to measure the effectiveness of mHealth in improving the self-management of hypertension for adults. The outcome measures were blood pressure (BP), BP control, medication adherence, self-management behavior, and costs. Methods A systematic search was conducted using 5 electronic databases. The snowballing method was used to scan the reference lists of relevant studies. Only peer-reviewed randomized controlled trials (RCTs) published between January 2010 and September 2019 were included. Data extraction and quality assessment were performed by 3 researchers independently, adhering to the validation guideline and checklist. Both a meta-analysis and a narrative synthesis were carried out. Results A total of 24 studies with 8933 participants were included. Of these, 23 studies reported the clinical outcome of BP, 12 of these provided systolic blood pressure (SBP) and diastolic blood pressure (DBP) data, and 16 articles focused on change in self-management behavior and medication adherence. All 24 studies were included in the narrative synthesis. According to the meta-analysis, a greater reduction in both SBP and DBP was observed in the mHealth intervention groups compared with control groups, −3.78 mm Hg (P<.001; 95% CI −4.67 to −2.89) and −1.57 mm Hg (P<.001; 95% CI −2.28 to −0.86), respectively. Subgroup analyses showed consistent reductions in SBP and DBP across different frequencies of reminders, interactive patterns, intervention functions, and study duration subgroups. A total of 16 studies reported better medication adherence and behavioral change in the intervention groups, while 8 showed no significant change. Six studies included an economic evaluation, which drew inconsistent conclusions. However, potentially long-term financial benefits were mentioned in all economic evaluations. All studies were assessed to be at high risk of bias. Conclusions This review found that mHealth self-management interventions were effective in BP control. The outcomes of this review showed improvements in self-management behavior and medication adherence. The most successful mHealth intervention combined the feature of tailored messages, interactive communication, and multifaceted functions. Further research with longer duration and cultural adaptation is necessary. With increasing disease burden from hypertension globally, mHealth offers a potentially effective method for self-management and control of BP. mHealth can be easily integrated into existing health care systems. Trial Registration PROSPERO CRD42019152062; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=152062


2018 ◽  
Author(s):  
Amy Danh Nguyen ◽  
Lauren J Frensham ◽  
Michael XC Wong ◽  
Sylvain MM Meslin ◽  
Paige Martin ◽  
...  

BACKGROUND Gout is a form of chronic arthritis caused by elevated serum uric acid (SUA) and culminates in painful gout attacks. Effective uric acid-lowering therapies exist, however adherence is low. This is partly due to the lack of support for patients to self-manage their disease. Mobile health applications (apps) have been used in self-management of chronic conditions. However, not all are developed with patients, limiting their effectiveness. OBJECTIVE This study aimed to design an effective gout self-management app by collecting feedback from gout patients. METHODS Two mixed-methods studies were conducted. In Study 1, researchers developed a short educational video and written materials about gout management, designed to be embedded into an app. Six interviews and one focus group were held with gout patients to gather feedback on these materials. Usability testing in Study 2 involved additional gout patients using a pilot version of Healthy.me Gout, a gout self-management app, for two weeks. Following the trial, patients participated in an interview about their experiences using the app. RESULTS Patients viewed the gout educational material positively, appreciating the combined use of video, text and images. Patients were receptive to using a mobile app to self-manage their gout. Feedback about Healthy.me Gout was generally positive, with patients reporting that the tracking and diary features were most useful. Patients also provided suggestions for improving the app and educational materials. CONCLUSIONS These studies involved patients in the development of a gout self-management app. Patients provided insight to improve the app’s presentation and usability, and general lessons on useful features for chronic disease apps. Gout patients enjoyed tracking their SUA concentrations and gout attack triggers. These capabilities can be translated to self-management apps for chronic diseases that require monitoring of pathological values, medication adherence and/or symptoms. Future health app design should integrate patient input and be developed iteratively to address concerns identified by patients.


2017 ◽  
Vol 25 (3) ◽  
pp. 350-360 ◽  
Author(s):  
Hissei Imai ◽  
Toshiaki A Furukawa ◽  
Shin-u Hayashi ◽  
Atsushi Goto ◽  
Kazuo Izumi ◽  
...  

We evaluated the associations of risk perception, self-efficacy, and trust with two health promotion behaviors (food habits and exercise) and depressive mood. Diabetic patients aged between 40 and 64 ( n = 1195) were included in the analyses. Risk perception worsened behavioral changes in terms of food habits and depression, whereas self-efficacy and trust improved food habits, exercise, and depression; trust improved exercise and depression. In conclusion, self-efficacy and trust appear to be more beneficial than risk perception for positive behavioral changes and for improving depression in diabetic patients. However, their influence on behavioral changes may be different according to the types of behaviors.


2019 ◽  
Author(s):  
Meghan Bradway ◽  
Elia Gabarron ◽  
Monika Johansen ◽  
Paolo Zanaboni ◽  
Patricia Jardim ◽  
...  

BACKGROUND Despite the prevalence of mobile health (mHealth) technologies and observations of their impacts on patients’ health, there is still no consensus on how best to evaluate these tools for patient self-management of chronic conditions. Researchers currently do not have guidelines on which qualitative or quantitative factors to measure or how to gather these reliable data. OBJECTIVE This study aimed to document the methods and both qualitative and quantitative measures used to assess mHealth apps and systems intended for use by patients for the self-management of chronic noncommunicable diseases. METHODS A scoping review was performed, and PubMed, MEDLINE, Google Scholar, and ProQuest Research Library were searched for literature published in English between January 1, 2015, and January 18, 2019. Search terms included combinations of the description of the intention of the intervention (eg, self-efficacy and self-management) and description of the intervention platform (eg, mobile app and sensor). Article selection was based on whether the intervention described a patient with a chronic noncommunicable disease as the primary user of a tool or system that would always be available for self-management. The extracted data included study design, health conditions, participants, intervention type (app or system), methods used, and measured qualitative and quantitative data. RESULTS A total of 31 studies met the eligibility criteria. Studies were classified as either those that evaluated mHealth apps (ie, single devices; n=15) or mHealth systems (ie, more than one tool; n=17), and one study evaluated both apps and systems. App interventions mainly targeted mental health conditions (including Post-Traumatic Stress Disorder), followed by diabetes and cardiovascular and heart diseases; among the 17 studies that described mHealth systems, most involved patients diagnosed with cardiovascular and heart disease, followed by diabetes, respiratory disease, mental health conditions, cancer, and multiple illnesses. The most common evaluation method was collection of usage logs (n=21), followed by standardized questionnaires (n=18) and ad-hoc questionnaires (n=13). The most common measure was app interaction (n=19), followed by usability/feasibility (n=17) and patient-reported health data via the app (n=15). CONCLUSIONS This review demonstrates that health intervention studies are taking advantage of the additional resources that mHealth technologies provide. As mHealth technologies become more prevalent, the call for evidence includes the impacts on patients’ self-efficacy and engagement, in addition to traditional measures. However, considering the unstructured data forms, diverse use, and various platforms of mHealth, it can be challenging to select the right methods and measures to evaluate mHealth technologies. The inclusion of app usage logs, patient-involved methods, and other approaches to determine the impact of mHealth is an important step forward in health intervention research. We hope that this overview will become a catalogue of the possible ways in which mHealth has been and can be integrated into research practice.


2021 ◽  
pp. 109980042110618
Author(s):  
Mei-Chen Lee ◽  
Shu-Fang Vivienne Wu ◽  
Kuo-Cheng Lu ◽  
Wen-Hug Wang ◽  
Yen-Yen Chen ◽  
...  

This longitudinal study with a randomized controlled trial evaluated the long-term effectiveness of the patient-centered self-management intervention program on the control of blood pressure and renal function, as well as the quality of life of patients with hypertensive nephropathy. The control group ( n = 38) received usual care while the experimental group ( n = 38) participated in a patient-centered self-management program. After the pre-test, the intervention was performed with the experimental group once a week for a total of 4 weeks. Then, the post-test was performed 1, 3, and 6 months later. A questionnaire was used to collect the demographic data and disease characteristics, laboratory data, and quality of life scale. This study tracked three time points (i.e., 1, 3, and 6 months) after the intervention and found that the experimental group achieved significant results in controlling systolic blood pressure ( p < 0.001), diastolic blood pressure ( p = 0.007), and eGFR ( p = 0.013). Significant results were achieved in the overall quality of life ( p < 0.001) and the quality of life in the physical (PHC; p < 0.001) and mental health components (MHC; p < 0.001). Furthermore, the effects in the experimental group lasted for as long as 6 months and were better than those in the control group. Moreover, this program can provide nursing staff with a reference different from traditional health education methods.


2019 ◽  
Author(s):  
Himali Weerahandi ◽  
Soaptarshi Paul ◽  
Lisa M Quintiliani ◽  
Sara Chokshi ◽  
Devin M Mann

BACKGROUND The seminal Dietary Approaches to Stopping Hypertension (DASH) study demonstrated the effectiveness of diet to control hypertension; however, the effective implementation and dissemination of its principles have been limited. OBJECTIVE This study aimed to determine the feasibility and effectiveness of a DASH mobile health intervention. We hypothesized that combining Bluetooth-enabled data collection, social networks, and a human coach with a smartphone DASH app (DASH Mobile) would be an effective medium for the delivery of the DASH program. METHODS We conducted a single-arm pilot study from August 2015 through August 2016, using a pre-post evaluation design to evaluate the feasibility and preliminary effectiveness of a smartphone version of DASH that incorporated a human health coach. Participants were recruited both online and offline. RESULTS A total of 17 patients participated in this study; they had a mean age of 59 years (SD 6) and 10 (60%) were women. Participants were engaged with the app; in the 120 days of the study, the mean number of logged blood pressure measurements was 63 (SD 46), the mean number of recorded weight measurements was 52 (SD 45), and participants recorded a mean of 55 step counts (SD 36). Coaching phone calls had a high completion rate (74/102, 73%). The mean number of servings documented per patient for the dietary assessment was 709 (SD 541), and patients set a mean number of 5 (SD 2) goals. Mean systolic and diastolic blood pressure, heart rate, weight, body mass index, and step count did not significantly change over time (<i>P</i>&gt;.10 for all parameters). CONCLUSIONS In this pilot study, we found that participants were engaged with an interactive mobile app that promoted healthy behaviors to treat hypertension. We did not find a difference in the physiological outcomes, but were underpowered to identify such changes.


2021 ◽  
Author(s):  
Yin Ting Cheung ◽  
Pok Hong Lam ◽  
Teddy Tai-Ning Lam ◽  
Henry Hon Wai Lam ◽  
Chi Kong Li

BACKGROUND The lifelong management of hemophilia is demanding and complex. In July 2019, we published a review in the <i>Journal of Medical Internet Research</i>, summarizing telehealth interventions that facilitate monitoring of bleeding events and promoting the appropriate use of clotting factors among patients with hemophilia. This work has led to the development of a community program that aims to harness technology to promote self-management among patients with hemophilia in Hong Kong. OBJECTIVE Before the inception of this program, we conducted a cross-sectional survey to evaluate the patients’ level of technology acceptance and identify their expectations of the use of mobile technology for self-management of hemophilia. METHODS In total, 56 participants (75% adult patients and 25% parents of pediatric patients; 87.5% with moderate to severe disease) were recruited from a local nongovernmental organization that serves patients with hemophilia. They rated their perceived confidence and acceptance in using the new mobile technology (score 1 to 5 for each item, with a higher score indicating better acceptance) using a structured questionnaire (adapted from the Technology Acceptance Model). They also identified the top features that they perceived to be the most important components of a mobile app for the self-management of hemophilia. The Mann–Whitney <i>U</i> test was used to compare technology acceptance scores across subgroups of different clinical and socioeconomic characteristics. RESULTS In general, the participants considered themselves skilled in using mobile apps (mean 4.3, 95% CI 4.1-4.5). They were willing to learn to use the new mobile app to organize their bleeding records (mean 4.0, 95% CI 3.7-4.3) and to manage their health (mean 4.2, 95% CI 4.1-4.5). Participants who lived in public housing (a surrogate marker for lower socioeconomic status in Hong Kong) reported lower technology acceptance than those who lived in private housing (<i>P</i>=.04). The most important features identified by the participants concerned documenting of infusion logs (n=49, 87.5%), bleeding events (n=48, 85.7%), and the secure delivery of the bleeding information to health care professionals (n=40, 71.4%). CONCLUSIONS It is encouraging to infer that patients with hemophilia in Hong Kong are receptive to the use of mobile health technology. The findings of this survey are applicable in designing the key features of a patient-centered, multimodal program harnessing mobile technology to promote self-management among patients with hemophilia. Future studies should evaluate participants’ acceptability and perceived usability of the mobile app via user metrics and assess clinical and humanistic outcomes of this program.


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