scholarly journals Does technology use moderate the relationship between parental alcoholism and adolescent alcohol and cigarette use?

2009 ◽  
Vol 34 (6-7) ◽  
pp. 606-609 ◽  
Author(s):  
Christine McCauley Ohannessian
Keyword(s):  
Technology Use ◽  
Cigarette Use ◽  
Parental Alcoholism ◽  
Adolescent Alcohol ◽  
The Relationship

A Decade of Disparities in Diabetes Technology Use and HbA1c in Pediatric Type 1 Diabetes: A Trans-Atlantic Comparison

2020 ◽  
Author(s):  
Ananta Addala ◽  
Marie Auzanneau ◽  
Kellee Miller ◽  
Werner Maier ◽  
Nicole Foster ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Technology Use ◽  
Hemoglobin A1c ◽  
Diabetes Technology ◽  
Design And Methods ◽  
Relationship Of ◽  
The Relationship ◽  
Pediatric Type 1 Diabetes

<b>Objective:</b> As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities. <p> </p> <p><b>Research Design and Methods: </b>Participants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, US, n=16,457) and Diabetes Prospective Follow-up (DPV, Germany, n=39,836) registries were categorized into lowest (Q1) to highest (Q5) SES quintiles. Multiple regression analyses compared the relationship of SES quintiles with diabetes technology use and HbA1c from 2010-2012 and 2016-2018. </p> <p> </p> <p><b>Results: </b>HbA1c was higher in participants with lower SES (in 2010-2012 & 2016-2018, respectively: 8.0% & 7.8% in Q1 and 7.6% & 7.5% in Q5 for DPV; and 9.0% & 9.3% in Q1 and 7.8% & 8.0% in Q5 for T1DX). For DPV, the association between SES and HbA1c did not change between the two time periods, whereas for T1DX, disparities in HbA1c by SES increased significantly (p<0.001). After adjusting for technology use, results for DPV did not change whereas the increase in T1DX was no longer significant.</p> <p> </p> <p><b>Conclusions: </b>Although causal conclusions cannot be drawn, diabetes technology use is lowest and HbA1c is highest in those of the lowest SES quintile in the T1DX and this difference for HbA1c broadened in the last decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry. </p>

Combined Model of Technology Use and Medical Adherence in eHealth Technology Implementation

2021 ◽  
Vol 65 (1) ◽  
pp. 776-780
Author(s):  
Bijita Devkota ◽  
Fernando Montalvo ◽  
Daniel S. McConnell ◽  
Janan A. Smither
Keyword(s):  
Human Factors ◽  
Technology Acceptance ◽  
Treatment Adherence ◽  
Technology Use ◽  
Technology Implementation ◽  
Medical Information ◽  
Treatment Protocols ◽  
Lower Treatment ◽  
Relationship Of ◽  
The Relationship

eHealth applications are expected to improve the effectiveness and efficiency of healthcare systems by providing improved medical information flow between medical providers and patients. Although the technology is expected to empower patients, lower treatment costs, and provide real-time collection of health data, individuals may be apprehensive about the use and efficacy of eHealth technologies. Medical professionals are often unaware of human factors technology acceptance or usability models which impact the use of medically focused technology, such as eHealth applications. Similarly, human factors professionals are often unaware of treatment adherence models which map the relationship of illness factors and individual differences to treatment protocols. The present paper presents a theoretical approach through which technology acceptance and usability models should be combined with medical treatment adherence models to ensure that eHealth applications are used properly and effectively.

The relationship between cigarette use, nicotine dependence, and craving in laboratory volunteers

2008 ◽  
Vol 10 (3) ◽  
pp. 447-455 ◽  
Author(s):  
Eric Donny ◽  
Kasey Griffin ◽  
Saul Shiffman ◽  
Michael Sayette
Keyword(s):  
Nicotine Dependence ◽  
Cigarette Use ◽  
The Relationship

Communication technology use and study skills

2017 ◽  
Vol 18 (3) ◽  
pp. 257-270 ◽  
Author(s):  
Penny Thompson
Keyword(s):  
Online Social Networks ◽  
Technology Use ◽  
Study Skills ◽  
Text Messaging ◽  
Instant Messaging ◽  
Negative Relationship ◽  
Communication Technologies ◽  
Study Strategies ◽  
Learning And Study Strategies ◽  
The Relationship

Research suggests a negative relationship between frequent use of communication technologies, such as text messaging and social network sites, and academic performance, but the nature of the relationship needs to be explored in greater detail. This study explored the relationship between use of communication technologies and self-reported study skills. A total of 74 first-year university students completed the online Learning and Study Strategies Inventory and reported on how frequently they used text messaging, instant messaging, and online social networks such as Facebook. Correlation analysis indicated a negative relationship between frequency of communications technology use and the Learning and Study Strategies Inventory measure of Concentration. While the study does not prove a causal relationship, it provides more detail on the specific study skills challenges students may be facing when they interrupt their studying with frequent online social communication. This increased understanding can help educators tailor study skills interventions and support more directly to students’ needs.

scholarly journals Examining Rural and Racial Disparities in the Relationship Between Loneliness and Social Technology Use Among Older Adults

2021 ◽  
Vol 9 ◽  
Author(s):  
Kaileigh A. Byrne ◽  
Reza Ghaiumy Anaraky ◽  
Cheryl Dye ◽  
Lesley A. Ross ◽  
Kapil Chalil Madathil ◽  
...  
Keyword(s):  
Older Adults ◽  
Racial Disparities ◽  
Technology Use ◽  
Social Engagement ◽  
Social Contact ◽  
Primary Study ◽  
Social Technology ◽  
Study Results ◽  
The Relationship ◽  
Rural Older Adults

Loneliness, the subjective negative experience derived from a lack of meaningful companionship, is associated with heightened vulnerability to adverse health outcomes among older adults. Social technology affords an opportunity to cultivate social connectedness and mitigate loneliness. However, research examining potential inequalities in loneliness is limited. This study investigates racial and rural-urban differences in the relationship between social technology use and loneliness in adults aged 50 and older using data from the 2016 wave of the Health and Retirement Study (N = 4,315). Social technology use was operationalized as the self-reported frequency of communication through Skype, Facebook, or other social media with family and friends. Loneliness was assessed using the UCLA Loneliness scale, and rural-urban differences were based on Beale rural-urban continuum codes. Examinations of race focused on differences between Black/African-American and White/Caucasian groups. A path model analysis was performed to assess whether race and rurality moderated the relationship between social technology use and loneliness, adjusting for living arrangements, age, general computer usage. Social engagement and frequency of social contact with family and friends were included as mediators. The primary study results demonstrated that the association between social technology use and loneliness differed by rurality, but not race. Rural older adults who use social technology less frequently experience greater loneliness than urban older adults. This relationship between social technology and loneliness was mediated by social engagement and frequency of social contact. Furthermore, racial and rural-urban differences in social technology use demonstrated that social technology use is less prevalent among rural older adults than urban and suburban-dwelling older adults; no such racial differences were observed. However, Black older adults report greater levels of perceived social negativity in their relationships compared to White older adults. Interventions seeking to address loneliness using social technology should consider rural and racial disparities.

scholarly journals The Impact of Information Technology on Motor Carrier Productivity

2010 ◽  
Author(s):  
B. Starr McMullen
Keyword(s):  
Information Technology ◽  
Marketing Strategy ◽  
Technical Efficiency ◽  
Economic Efficiency ◽  
Technology Use ◽  
Malmquist Index ◽  
Satellite Communications ◽  
Efficiency Change ◽  
Motor Carrier ◽  
The Relationship

This study examines the relationship between motor carrier productivity, marketing strategy, and use of information technology for a sample of U.S. general freight commodity carriers. We use a unique data set containing information on firm marketing strategy and information technology use collected in a survey of Class I and II motor carrier firms (U.S. Department of Transportation, 1999). The measure of productivity used here is the non-parametric Malmquist Index as explained in Grosskopf (1993) and previously applied to general freight motor carriers by McMullen and Okuyama (2000). The Malmquist Index is decomposed into two components: economic efficiency change (EC) and technical efficiency change (TC). A tobit model regression model is used to examine the relationship between firm productivity, marketing strategy, and use of information technology. Information technologies included in the tobit analysis are electronic data interchange (EDI) and satellite communications (SATCOM). We also include firm size, use of owner-operators, and percent unionization as explanatory variables in the tobit regression. Results indicate that use of EDI has a positive and significant impact on economic efficiency (EC). Firms that try to market their product by providing service at the "lowest freight rate" are found to exhibit greater technical efficiency (TC), suggesting that productivity and cost measures that ignore marketing strategy may be biased. Finally, economic efficiency (EC) is found to be significantly greater for firms that are more heavily unionized.

scholarly journals E-cigarette use and onset of first cigarette smoking among adolescents: An empirical test of the ‘common liability’ theory

F1000Research ◽  
2020 ◽  
Vol 8 ◽  
pp. 2099
Author(s):  
Hui G. Cheng ◽  
Edward G. Largo ◽  
Maria Gogova
Keyword(s):  
Structural Equation Modeling ◽  
Cigarette Smoking ◽  
Structural Equation ◽  
Equation Modeling ◽  
Cigarette Use ◽  
Tobacco Products ◽  
Latent Construct ◽  
The Us ◽  
The Common ◽  
The Relationship

Background: E-cigarettes have become the most commonly used tobacco products among youth in the United States (US) recently. It is not clear whether there is a causal relationship between e-cigarette use and the onset of cigarette smoking. The “common liability” theory postulates that the association between e-cigarette use and cigarette smoking can be attributed to a common risk construct of using tobacco products. This study aims to investigate the relationship between ever e-cigarette use and cigarette smoking onset in the US using a structural equation modeling approach guided by the “common liability” theory. Methods: The study population is non-institutionalized civilian adolescents living in the US, sampled in the longitudinal Population Assessment of Tobacco and Health study. Information about tobacco product use was obtained via confidential self-report. A structural equation modeling approach was used to estimate the relationship between e-cigarette use at wave 1 and the onset of cigarette smoking at wave 2 after controlling for a latent construct representing a “common liability to use tobacco products.” Results:  After controlling for a latent construct representing a “common liability to use tobacco products”, ever e-cigarette use does not predict the onset of cigarette smoking (β=0.13, 95% CI= -0.07, 0.32, p=0.204). The latent “common liability to use tobacco products” is a robust predictor for the onset of cigarette smoking (β=0.38; 95% CI=0.07, 0.69; p=0.015). Conclusions: Findings from this study provide supportive evidence for the ‘common liability’ underlying observed associations between e-cigarette use and smoking onset.

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