scholarly journals Treatment Outcomes of a Multi-Component Mobile Health Smoking Cessation Pilot Intervention for People with Schizophrenia

2020 ◽  
Vol 16 (4) ◽  
pp. 420-428
Author(s):  
Alyssa M. Medenblik ◽  
Adam M. Mann ◽  
Tiffany A. Beaver ◽  
Eric A. Dedert ◽  
Sarah M. Wilson ◽  
...  
Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Shimeng Liu ◽  
Wuwei Feng ◽  
Pratik Y Chhatbar ◽  
Bruce I Ovbiagele

Background: The overwhelming majority of strokes can be prevented via optimal vascular risk factor control. However, there remains an evidence practice gap with regard to treatment of vascular risk factors. With the rapid growth worldwide in cell-phone use, Internet connectivity, and digital health technology, mobile health (mHealth) technology may offer a promising approach to bridge these treatment gaps and reduce the global burden of stroke. Objective: To evaluate the effectiveness of mHealth in vascular risk factor control through a systemic review and meta-analysis. Methods: We searched PubMed from January 1, 2000 to May 17, 2016 using keywords: mobile health, mhealth, short message, cellular phone, mobile phone, stroke prevention and control, diabetes mellitus, hypertension, hyperlipidemia and smoking cessation. We performed a meta-analysis of all eligible randomized control clinical trials that assessed the long-term (at 6 months) effect of mHealth. Results: Of 79 articles identified, 13 of them met eligibility criteria (6 for glycemic control and 7 for smoking cessation) and were included for the final meta-analysis. There were no eligible studies for dyslipidemia or hypertension. mHealth resulted in greater HbA1c reduction at 6 months (6 studies; 663 subjects; SMD: -0.44; 95% CI: [-0.82, -0.06], P =0.02; Mean difference of decrease in HbA1c: -0.39%; 95% CI: [-0.74,-0.04], P =0.03). mHealth also led to relatively higher smoking abstinence rates at 6 months (7 studies; 9,514 subjects; OR: 1.54; 95% CI: [1.24, 1.90], P <0.0001). Conclusion: Use of mHealth improves glycemic control and smoking abstinence rates, two factors that may lead to better stroke outcomes. Future mHealth studies should focus on modifying premier vascular risk factors like hypertension, specifically in people with or at risk of stroke.


2019 ◽  
Vol 4 ◽  
Author(s):  
Nick Noguez And Michael Gonzalez

  Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, thesocial engagement features that exist in current smoking cessation apps and how effective these social features are in engaging users remain unclear. To fill the gap in the literature, a content analysis of free and paid smoking cessation mobile apps isconducted to examine a) the presence of socialengagement features(e.g., social support, social announcement, social referencing) and non-social engagement features (e.g., personal environmental changes, goal setting), and b) their relationship with user ratingsand engagement scores (e.g., Mobile App rating scale [MARS]). The findings will not only extend the mobile health apps engagement typology,but also inform smoking cessation mobile apps design.


2012 ◽  
Vol 92 (5) ◽  
pp. 757-766 ◽  
Author(s):  
Rose M. Pignataro ◽  
Patricia J. Ohtake ◽  
Anne Swisher ◽  
Geri Dino

10.2196/32847 ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. e32847
Author(s):  
Jonathan B Bricker ◽  
Michael Levin ◽  
Raimo Lappalainen ◽  
Kristin Mull ◽  
Brianna Sullivan ◽  
...  

Background Engagement with digital interventions is a well-known predictor of treatment outcomes, but this knowledge has had limited actionable value. Instead, learning why engagement with digital interventions impact treatment outcomes can lead to targeted improvements in their efficacy. Objective This study aimed to test a serial mediation model of an Acceptance and Commitment Therapy (ACT) smartphone intervention for smoking cessation. Methods In this randomized controlled trial, participants (N=2415) from 50 US states were assigned to the ACT-based smartphone intervention (iCanQuit) or comparison smartphone intervention (QuitGuide). Their engagement with the apps (primary measure: number of logins) was measured during the first 3 months, ACT processes were measured at baseline and 3 months (acceptance of internal cues to smoke, valued living), and smoking cessation was measured at 12 months with 87% follow-up retention. Results There was a significant serial mediation effect of iCanQuit on smoking cessation through multiple indicators of intervention engagement (ie, total number of logins, total number of minutes used, and total number of unique days of use) and in turn through increases in mean acceptance of internal cues to smoke from baseline to 3 months. Analyses of the acceptance subscales showed that the mediation was through acceptance of physical sensations and emotions, but not acceptance of thoughts. There was no evidence that the effect of the iCanQuit intervention was mediated through changes in valued living. Conclusions In this first study of serial mediators underlying the efficacy of smartphone apps for smoking cessation, our results suggest the effect of the iCanQuit ACT-based smartphone app on smoking cessation was mediated through multiple indicators of engagement and in turn through increases in the acceptance of physical sensations and emotions that cue smoking. Trial Registration Clinical Trials.gov NCT02724462; https://clinicaltrials.gov/ct2/show/NCT02724462


2017 ◽  
Author(s):  
Kristopher Abbate ◽  
Melanie Hingle ◽  
Julie Armin ◽  
Peter Giacobbi Jr ◽  
Judith S. Gordon

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