scholarly journals The Potential of Smartphone Apps in Informing Protobacco and Antitobacco Messaging Efforts Among Underserved Communities: Longitudinal Observational Study

10.2196/17451 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e17451
Author(s):  
Edmund WJ Lee ◽  
Mesfin Awoke Bekalu ◽  
Rachel McCloud ◽  
Donna Vallone ◽  
Monisha Arya ◽  
...  
Keyword(s):  
Tobacco Control ◽  
Hot Spot ◽  
Smoking Behavior ◽  
The United States ◽  
Smartphone Apps ◽  
Power Law Distribution ◽  
Underserved Communities ◽  
Tobacco Marketing ◽  
Health Apps ◽  
Smoking Behaviors

Background People from underserved communities such as those from lower socioeconomic positions or racial and ethnic minority groups are often disproportionately targeted by the tobacco industry, through the relatively high levels of tobacco retail outlets (TROs) located in their neighborhood or protobacco marketing and promotional strategies. It is difficult to capture the smoking behaviors of individuals in actual locations as well as the extent of exposure to tobacco promotional efforts. With the high ownership of smartphones in the United States—when used alongside data sources on TRO locations—apps could potentially improve tobacco control efforts. Health apps could be used to assess individual-level exposure to tobacco marketing, particularly in relation to the locations of TROs as well as locations where they were most likely to smoke. To date, it remains unclear how health apps could be used practically by health promotion organizations to better reach underserved communities in their tobacco control efforts. Objective This study aimed to demonstrate how smartphone apps could augment existing data on locations of TROs within underserved communities in Massachusetts and Texas to help inform tobacco control efforts. Methods Data for this study were collected from 2 sources: (1) geolocations of TROs from the North American Industry Classification System 2016 and (2) 95 participants (aged 18 to 34 years) from underserved communities who resided in Massachusetts and Texas and took part in an 8-week study using location tracking on their smartphones. We analyzed the data using spatial autocorrelation, optimized hot spot analysis, and fitted power-law distribution to identify the TROs that attracted the most human traffic using mobility data. Results Participants reported encountering protobacco messages mostly from store signs and displays and antitobacco messages predominantly through television. In Massachusetts, clusters of TROs (Dorchester Center and Jamaica Plain) and reported smoking behaviors (Dorchester Center, Roxbury Crossing, Lawrence) were found in economically disadvantaged neighborhoods. Despite the widespread distribution of TROs throughout the communities, participants overwhelmingly visited a relatively small number of TROs in Roxbury and Methuen. In Texas, clusters of TROs (Spring, Jersey Village, Bunker Hill Village, Sugar Land, and Missouri City) were found primarily in Houston, whereas clusters of reported smoking behaviors were concentrated in West University Place, Aldine, Jersey Village, Spring, and Baytown. Conclusions Smartphone apps could be used to pair geolocation data with self-reported smoking behavior in order to gain a better understanding of how tobacco product marketing and promotion influence smoking behavior within vulnerable communities. Public health officials could take advantage of smartphone data collection capabilities to implement targeted tobacco control efforts in these strategic locations to reach underserved communities in their built environment.

scholarly journals The Potential of Smartphone Apps in Informing Protobacco and Antitobacco Messaging Efforts Among Underserved Communities: Longitudinal Observational Study (Preprint)

2019 ◽  
Author(s):  
Edmund WJ Lee ◽  
Mesfin Awoke Bekalu ◽  
Rachel McCloud ◽  
Donna Vallone ◽  
Monisha Arya ◽  
...  
Keyword(s):  
Tobacco Control ◽  
Hot Spot ◽  
Smoking Behavior ◽  
The United States ◽  
Smartphone Apps ◽  
Power Law Distribution ◽  
Underserved Communities ◽  
Tobacco Marketing ◽  
Health Apps ◽  
Smoking Behaviors

BACKGROUND People from underserved communities such as those from lower socioeconomic positions or racial and ethnic minority groups are often disproportionately targeted by the tobacco industry, through the relatively high levels of tobacco retail outlets (TROs) located in their neighborhood or protobacco marketing and promotional strategies. It is difficult to capture the smoking behaviors of individuals in actual locations as well as the extent of exposure to tobacco promotional efforts. With the high ownership of smartphones in the United States—when used alongside data sources on TRO locations—apps could potentially improve tobacco control efforts. Health apps could be used to assess individual-level exposure to tobacco marketing, particularly in relation to the locations of TROs as well as locations where they were most likely to smoke. To date, it remains unclear how health apps could be used practically by health promotion organizations to better reach underserved communities in their tobacco control efforts. OBJECTIVE This study aimed to demonstrate how smartphone apps could augment existing data on locations of TROs within underserved communities in Massachusetts and Texas to help inform tobacco control efforts. METHODS Data for this study were collected from 2 sources: (1) geolocations of TROs from the North American Industry Classification System 2016 and (2) 95 participants (aged 18 to 34 years) from underserved communities who resided in Massachusetts and Texas and took part in an 8-week study using location tracking on their smartphones. We analyzed the data using spatial autocorrelation, optimized hot spot analysis, and fitted power-law distribution to identify the TROs that attracted the most human traffic using mobility data. RESULTS Participants reported encountering protobacco messages mostly from store signs and displays and antitobacco messages predominantly through television. In Massachusetts, clusters of TROs (Dorchester Center and Jamaica Plain) and reported smoking behaviors (Dorchester Center, Roxbury Crossing, Lawrence) were found in economically disadvantaged neighborhoods. Despite the widespread distribution of TROs throughout the communities, participants overwhelmingly visited a relatively small number of TROs in Roxbury and Methuen. In Texas, clusters of TROs (Spring, Jersey Village, Bunker Hill Village, Sugar Land, and Missouri City) were found primarily in Houston, whereas clusters of reported smoking behaviors were concentrated in West University Place, Aldine, Jersey Village, Spring, and Baytown. CONCLUSIONS Smartphone apps could be used to pair geolocation data with self-reported smoking behavior in order to gain a better understanding of how tobacco product marketing and promotion influence smoking behavior within vulnerable communities. Public health officials could take advantage of smartphone data collection capabilities to implement targeted tobacco control efforts in these strategic locations to reach underserved communities in their built environment.

scholarly journals SMOKING BEHAVIORS AND ATTITUDES TOWARDS THE SMOKE-FREE CAMPUS POLICY: A SYSTEMATIC REVIEW

2021 ◽  
Vol 21 (3) ◽  
pp. 124-135
Author(s):  
Shazwani Mohmad ◽  
Aniza Ismail
Keyword(s):  
Systematic Review ◽  
Positive Impact ◽  
Smoking Behavior ◽  
The United States ◽  
Second Hand Smoke ◽  
Quit Smoking ◽  
Positive Attitudes ◽  
Campus Policy ◽  
Or Practice ◽  
Smoking Behaviors

We conducted this systematic review to document the published literature related to smoking behaviors and attitudes towards the smoke-free campus policy. Studies on universities that had implemented the smoke-free campus policy were included in this review. The search for published articles from January 2010 to December 2020 involved three main electronic databases: Ovid MEDLINE, ScienceDirect, and Scopus. We searched the databases with the following Boolean string: [(smoke-free OR tobacco-free) AND (campus OR university OR college) AND (knowledge* OR attitude* OR practice*)]. Seventeen studies were included in this review. The majority (n = 8) were from the United States, followed by Saudi Arabia (n = 2) and one each from Israel, Lebanon, Australia, Canada, the United Kingdom, Spain, and China. Eight studies reported a positive impact of the policy on smoking behavior (plan to quit smoking, attempt to quit smoking, reduce smoking). However, 11 studies reported that respondents were still exposed to second-hand smoke and that cigarette butts were still scattered around the university area. Nine studies reported negative attitudes towards smoking, and seven of 12 studies reported positive attitudes towards the policy. Overall, the smoke-free campus policy had mixed impacts. Nevertheless, we found that attitude towards a smoke-free campus and smoking behavior has a good impact.

Insurance disparity in the United States cancer survivors’ smoking rates: A trend study from NHIS 2008-2017.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 1553-1553
Author(s):  
Yannan Zhao ◽  
Binbin Zheng-Lin ◽  
Biyun Wang ◽  
Xi-Chun Hu ◽  
Changchuan Jiang
Keyword(s):  
Cancer Survivors ◽  
Statistical Power ◽  
Private Insurance ◽  
Insurance Coverage ◽  
Smoking Behavior ◽  
The United States ◽  
Current Smoking ◽  
Complex Design ◽  
Adult Cancer Survivors ◽  
Smoking Behaviors

1553 Background: Smoking rates have been decreasing in the U.S over the last decade. Smoking cessation is a critical part of cancer treatment and survivorship care. However, little is known about the trend of smoking rates in U.S. cancer survivors and how it varied by individuals’ insurance coverages. Methods: We conducted a retrospective study to evaluate the temporal trend of smoking rates using the National Health Interview Survey from 2008 through 2017. Adult cancer survivors (n = 20122) were included in the analysis. The outcomes were self-reported current smoking behavior. Insurance coverage was categorized into any private (age ≤65), other coverage (age ≤65), uninsured (age ≤65), Medicare + any private (age > 65), and other coverage (age > 65). We combined every two years data to improve statistical power in the subgroup analysis. Weighted analyses were performed with SAS 9.4 to account for the complex design. Results: The smoking rates in cancer survivors decreased from 18.4% in 2008 to 12.5% in 2017. However, the smoking rates varied remarkably by insurance status (p < 0.001). There was a decreasing trend of smoking rates in participants with any private (age ≤65) (17.3% in 2008/2009 to 12.0% in 2016/2017), Medicare + any private (age > 65) (7.5% in 2008/2009 to 5.9% in 2016/2017), and other coverage (age > 65) (13.2% in 2008/2009 to 9.2% in 2016/2017) whereas the current smoking rates remains high in cancer survivors with other coverage (age ≤65) (40.1% in 2008/2009 to 34.4% in 2016/2017) and uninsured (age ≤65) (43.4% in 2008/2009 to 43,1% in 2016/2017). Conclusions: Cancer survivors report less smoking behaviors over the last decade which is similar to the general population. However, the smoking rate remains dangerously high in non-elderly cancer survivors without any private insurance.

scholarly journals Evaluating the Potential Use of Smartphone Apps for Diabetes Self-Management in an Underserved Population: A Qualitative Approach

2021 ◽  
Vol 18 (18) ◽  
pp. 9886
Author(s):  
Jenny Luo ◽  
Shelley White-Means
Keyword(s):  
Diabetes Management ◽  
Low Cost ◽  
Primary Care Providers ◽  
The United States ◽  
Smartphone Apps ◽  
Care Providers ◽  
Limited Access ◽  
Health Apps ◽  
Underserved Patients ◽  
Patients With Diabetes

Health disparities cause a higher rate of diabetes development in poor and minority groups and also limit the care these people receive. Smartphone applications (apps) may be a low-cost, accessible resource to patients with diabetes who experience barriers to traditional health care. Currently, little is known about using health apps to help underserved patients in the United States. This study aimed to investigate the willingness to use diabetes apps in patients with limited access to primary care providers. Fifteen personal interviews were collected and analyzed according to the interpretative phenomenological analysis framework. The interviews produced three overall themes: (1) Despite having little previous knowledge about health apps, patients were all willing to try at least one diabetes-related app; (2) app functions should be individualized to each patient’s needs for maximum benefit; and (3) barriers to app use were varied but commonly included knowledge and technological challenges and security issues. Underserved patients with diabetes expressed a willingness to try health apps, despite limited experience with the technology. Choosing apps individualized to each patient’s needs, instead of a blanket multifunctional app, would provide the greatest benefit for patient-driven diabetes management. Smartphone apps may be a feasible, low-cost resource for patients with limited access to traditional healthcare.

Creating a Smoke-Free Hospital: Attitudes and Smoking Behaviors of Nurses and Physicians

1994 ◽  
Vol 9 (2) ◽  
pp. 108-114 ◽  
Author(s):  
Frances A. Stillman ◽  
Donald A. Hantula ◽  
Robert Swank
Keyword(s):  
Smoking Behavior ◽  
The United States ◽  
Smoking Ban ◽  
Full Time ◽  
Quit Smoking ◽  
Smoking Policy ◽  
Smoke Free Policy ◽  
Smoking Behaviors ◽  
Nurses And Physicians ◽  
Free Environment

Purpose. To assess smoking prevalence and attitudes of physicians and nurses before a smoking ban. The relationship between pre-ban attitudes and post-ban smoking behavior was also studied. Design. This is a prospective descriptive study of a cohort of nurses and physicians who were surveyed six months before and six months after a ban on smoking was implemented. Setting. A large, 1,000-bed teaching hospital in the Northeast of the United States. Subjects. All full-time members of the medical (n=1,496) and nursing staff (n=1,500) were surveyed. The overall response rate for the cohort was 41 % for physicians and 39% for nurses. Measures. Surveys included standardized questions on current smoking behavior, and sociodemographic variables. Attitudes toward quitting and the smoking policy and attitudes about implementation and enforcement of the smoking ban were included. Results. Both physicians and nurses were supportive of a smoke-free policy, but the two groups differed significantly on attitudes related to implementation and enforcement, with nurses being more accommodating toward smoking and less likely to enforce a ban on smoking. Physicians were more likely than nurses to quit smoking after implementation of the ban. Pre-ban attitudes were not predictive of post-ban changes in smoking behavior. Conclusions. Physicians and nurses agreed with establishing a smoke-free environment but disagreed over the efforts needed to maintain the smoke-free environment. Quitting behavior was not influenced by pre-ban attitudes.

scholarly journals Patients’ adherence to smartphone apps in the management of bipolar disorder: a systematic review

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Marie-Camille Patoz ◽  
Diego Hidalgo-Mazzei ◽  
Bruno Pereira ◽  
Olivier Blanc ◽  
Ingrid de Chazeron ◽  
...  
Keyword(s):  
Systematic Review ◽  
Bipolar Disorder ◽  
Mobile Health ◽  
Smartphone Apps ◽  
Exclusion Criteria ◽  
Future Studies ◽  
Health Apps ◽  
Definition Of ◽  
Bipolar Patients ◽  
Digital Or

Abstract Background Despite an increasing number of available mental health apps in the bipolar disorder field, these tools remain scarcely implemented in everyday practice and are quickly discontinued by patients after downloading. The aim of this study is to explore adherence characteristics of bipolar disorder patients to dedicated smartphone interventions in research studies. Methods A systematic review following PRISMA guidelines was conducted. Three databases (EMBASE, PsychInfo and MEDLINE) were searched using the following keywords: "bipolar disorder" or "mood disorder" or “bipolar” combined with “digital” or “mobile” or “phone” or “smartphone” or “mHealth” or “ehealth” or "mobile health" or “app” or “mobile-health”. Results Thirteen articles remained in the review after exclusion criteria were applied. Of the 118 eligible studies, 39 did not provide adherence characteristics. Among the selected papers, study length, sample size and definition of measures of adherence were strongly heterogeneous. Activity rates ranged from 58 to 91.6%. Conclusion The adherence of bipolar patients to apps is understudied. Standardised measures of adherence should be defined and systematically evaluated in future studies dedicated to these tools.

scholarly journals Smoking Across the Menopausal Transition in a 10-Year Longitudinal Sample: The Role of Sex Hormones and Depressive Symptoms

2019 ◽  
Vol 22 (6) ◽  
pp. 872-877 ◽  
Author(s):  
MacKenzie R Peltier ◽  
José M Flores ◽  
Philip H Smith ◽  
Walter Roberts ◽  
Terril L Verplaetse ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Sex Hormones ◽  
Smoking Behavior ◽  
Menopausal Transition ◽  
Current Cigarette Smoking ◽  
Logistic Regression Models ◽  
Smoking Behaviors ◽  
Current Cigarette ◽  
Smoking Patterns ◽  
The Impact

Abstract Introduction Current cigarette smoking rates among older women remain problematic, especially given that this population experiences increased smoking-related health consequences. Despite these increased health concerns, little research to date has explored smoking patterns across the menopausal transition (pre-, early-peri-, late-peri-, and postmenopausal) or the effect of unique factors such as sex hormones and depression during this transition. Methods This study used 10 yearly waves of data from the Study of Women’s Health Across the Nation, a longitudinal dataset. Data included 1397 women endorsing ever smoking regularly at baseline. Random-effects logistic regression models were used to examine smoking transitions. Results Although there were no associations between menopausal transition stage and smoking behavior, increased estradiol was associated with an increased likelihood of quitting regular smoking (eg, transitioning from regular smoking to non-regular or no smoking; odds ratio [OR] = 1.28), whereas increased testosterone was associated with an increased likelihood of relapsing to regular smoking (eg, transitioning from former or nonregular smoking to regular smoking OR = 2.56). Depression was associated with increased likelihood of continued smoking (OR = 0.97) and relapse (OR = 1.03). Conclusions The results emphasize the need to develop interventions to target initiated or continued smoking among women across the menopausal transition and specifically highlight the importance of developing treatments that target depressive symptoms in this population. In addition, although singular hormone measures were associated with smoking behavior, there is a need for future study of dynamic changes in hormones, as well as the impact of progesterone on smoking behaviors across the menopausal transition. Implications To date, no studies have examined smoking behaviors across the menopausal transition. In this study, although menopausal transition status was not significantly related to transitions in smoking behavior, important relationships between sex hormones and depression were observed. Increased estradiol was associated with an increased likelihood of quitting regular smoking, whereas increased testosterone was associated with an increased likelihood of relapsing to regular smoking behavior. Higher depression scores were related to continued smoking and relapse to regular smoking behavior. These results highlight the need to develop interventions to target smoking cessation among women across the menopausal transition.

scholarly journals Time to First Cigarette and Self-Reported Health Among US Adult Smokers

2019 ◽  
Vol 12 ◽  
pp. 1179173X1882526 ◽  
Author(s):  
Baksun Sung
Keyword(s):  
United States ◽  
Propensity Score ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Smoking Behavior ◽  
The United States ◽  
Elevated Risk ◽  
Poor Health ◽  
Increased Risk ◽  
Reported Health

Background: Numerous studies have reported that shorter time to first cigarette (TTFC) is linked to elevated risk for smoking-related morbidity. However, little is known about the influence of early TTFC on self-reported health among current smokers. Hence, the objective of this study was to examine the association between TTFC and self-reported health among US adult smokers. Methods: Data came from the 2012-2013 National Adult Tobacco Survey (NATS). Current smokers aged 18 years and older (N = 3323) were categorized into 2 groups based on TTFC: ≤ 5 minutes (n = 1066) and >5 minutes (n = 2257). Propensity score matching (PSM) was used to control selection bias. Results: After adjusting for sociodemographic and smoking behavior factors, current smokers with early TTFC had higher odds for poor health in comparison with current smokers with late TTFC in the prematching (adjusted odds ratio [AOR] = 1.65; 95% confidence interval [CI] = 1.31-2.08) and postmatching (AOR = 1.60; 95% CI = 1.22-2.09) samples. Conclusions: In conclusion, smokers with early TTFC were associated with increased risk of poor health in the United States. To reduce early TTFC, elaborate efforts are needed to educate people about harms of early TTFC and benefits of stopping early TTFC.

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