Using a Mobile App to Promote Smoking Cessation in Hospitalized Patients.

JMIR Mhealth Uhealth

Columbia University, Department of Biomedical Informatics, New York, NY, United States.

Published: May 2016

Background: The potential of interactive health education for preventive health applications has been widely demonstrated. However, use of mobile apps to promote smoking cessation in hospitalized patients has not been systematically assessed.

Objective: This study was conducted to assess the feasibility of using a mobile app for the hazards of smoking education delivered via touch screen tablets to hospitalized smokers.

Methods: Fifty-five consecutive hospitalized smokers were recruited. Patient sociodemographics and smoking history was collected at baseline. The impact of the mobile app was assessed by measuring cognitive and behavioral factors shown to promote smoking cessation before and after the mobile app use including hazards of smoking knowledge score (KS), smoking attitudes, and stages of change.

Results: After the mobile app use, mean KS increased from 27(3) to 31(3) ( P<0.0001). Proportion of patients who felt they "cannot quit smoking" reduced from 36% (20/55) to 18% (10/55) ( P<0.03). Overall, 13% (7/55) of patients moved toward a more advanced stage of change with the proportion of patients in the preparation stage increased from 40% (22/55) to 51% (28/55). Multivariate regression analysis demonstrated that knowledge gains and mobile app acceptance did not depend on age, gender, race, computer skills, income, or education level. The main factors affecting knowledge gain were initial knowledge level ( P<0.02), employment status ( P<0.05), and high app acceptance ( P<0.01). Knowledge gain was the main predictor of more favorable attitudes toward the mobile app (odds ratio (OR)=4.8; 95% confidence interval (CI) (1.1, 20.0)). Attitudinal surveys and qualitative interviews identified high acceptance of the mobile app by hospitalized smokers. Over 92% (51/55) of the study participants recommended the app for use by other hospitalized smokers and 98% (54/55) of the patients were willing to use such an app in the future.

Conclusions: Our results suggest that a mobile app promoting smoking cessation is well accepted by hospitalized smokers. The app can be used for interactive patient education and counseling during hospital stays. Development and evaluation of mobile apps engaging patients in their care during hospital stays is warranted.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4875494PMC
http://dx.doi.org/10.2196/mhealth.5149DOI Listing

Publication Analysis

Top Keywords

mobile app
20
promote smoking
12
smoking cessation
12
cessation hospitalized
8
hospitalized patients
8
hazards smoking
8
smoking
7
mobile
6
app promote
4
hospitalized
4

Similar Publications

In this paper, a sub-1dB Low Noise Amplifier (LNA) with several gain modes, including amplification and attenuation modes required for the fifth and fourth generations (5G/4G) of mobile network applications, is proposed. Its current consumption is adaptive for every gain mode and varies to lower currents for lower amplifications due to the importance of current consumption for mobile network applications. The proposed LNA features an innovative architecture with a three-core input structure supporting multi-gain modes, achieving high gain and ultra-low noise performance.

View Article and Find Full Text PDF

Geohazard Identification in Underground Mines: A Mobile App.

Sensors (Basel)

December 2024

Department of Mining and Geological Engineering, University of Arizona, Tucson, AZ 8572, USA.

Mining is a critical industry that provides essential minerals and resources for modern society. Despite its benefits, the industry is also recognized as one of the most dangerous occupations, with geotechnical hazards being a primary concern. This study introduces the hazard recognition in underground mines application (HUMApp), a mobile application developed to enhance safety within underground mines by efficiently identifying geotechnical hazards, specifically focusing on roof falls.

View Article and Find Full Text PDF

As proximity-aware services among devices such as sensors, IoT devices, and user equipment are expected to facilitate a wide range of new applications in the beyond 5G and 6G era, managing heterogeneous environments with diverse node capabilities becomes essential. This paper analytically models and characterizes the performance of heterogeneous random access-based wireless mutual broadcast (RA-WMB) with distinct transmit (Tx) power levels, leveraging a marked Poisson point process to account for nodes' various Tx power. In particular, this study enables the performance of RA-WMB with heterogeneous Tx power to be represented in terms of the performance of RA-WMB with a common Tx power by deriving an equivalent Tx power based on the probability distribution of heterogeneous Tx power and the path loss exponent.

View Article and Find Full Text PDF

Human Pose Estimation (HPE) is a computer vision application that utilizes deep learning techniques to precisely locate Key Joint Points (KJPs), enabling the accurate description of a person's pose. HPE models can be extended to facilitate Range of Motion (ROM) assessment by leveraging patient photographs. This study aims to evaluate and compare the performance of HPE models for assessing upper limbs ROM.

View Article and Find Full Text PDF

A Mixed Reality (MR) application using an optical see-through headset was developed to assess short-term spatial memory. A study with 29 participants was conducted. Data from this study were compared to two previous studies using mobile Augmented Reality (AR) and Virtual Reality (VR) with headsets.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!