scholarly journals Mobile technology and cumulative trauma symptomology among millennials

Hand Therapy ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 11-17 ◽  
Author(s):  
Nathan Short ◽  
Madison Blair ◽  
Chloe Crowell ◽  
Abby Loewenstein ◽  
Annie Lynch ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Mobile Technology ◽  
Technology Use ◽  
Elbow Flexion ◽  
Cubital Tunnel Syndrome ◽  
Self Report ◽  
Cumulative Trauma ◽  
Asymptomatic Group ◽  
Convenience Sample ◽  
Cumulative Trauma Disorder

Introduction Technology use among the millennial population is increasing and related postural compromise may lead to cumulative trauma disorder symptomology. The aim of this study was to explore trends of hand-held mobile technology use and upper extremity cumulative trauma disorder symptomology among a sample of millennials. Methods A convenience sample of graduate students ( n = 42) was used for the study. Demographic and technology use information was obtained through self-report using the smartphone screen time tracking feature. Cumulative trauma disorder symptomology was assessed through administration of various orthopedic special tests. Results On average, participants spent 2 h and 23 min per day using hand-held mobile devices. Out of 42 participants, 54.8% tested positive for at least one orthopedic special test. The symptomatic group spent 2 h and 29 min using hand-held mobile devices, while the asymptomatic group spent 2 h and 4 min. The most common positive orthopedic special tests were Finkelstein’s test ( n = 19; 36%), hyperabduction (Wright’s) test ( n = 13; 25%), and the elbow flexion test ( n = 10; 18.9%), indicating symptoms associated with De Quervain’s tenosynovitis, thoracic outlet syndrome, and cubital tunnel syndrome, respectively. Discussion Results were consistent with prior research on time spent using hand-held mobile technology and cumulative trauma disorder among millennials. Additionally, a difference in mean time spent using mobile technology between the asymptomatic and symptomatic groups was found, suggesting a relationship which warrants further research.

The Laptop, the Tablet, and the Smartphone Attend Lectures

2015 ◽  
pp. 183-193 ◽  
Author(s):  
Hagit Meishar Tal ◽  
Gila Kurtz
Keyword(s):  
Mobile Devices ◽  
Mobile Technology ◽  
Technology Use ◽  
Mobile Technologies ◽  
Class B ◽  
Class C ◽  
Mobile Computers

A large number of students bring laptops and other mobile instruments to their lectures. This chapter presents findings of a study that investigated the habits of mobile technology use in class among students. The study probes relations among four elements: (a) mobile technologies available to students in class; (b) students' use of these mobile technologies in class; (c) students' perceptions of these uses (i.e., how they estimate the contribution or damage of the use of these devices during the lecture); and (d) how intensively lecturers engage students via the mobile devices in the students' possession. The findings indicate that the use of mobile computers promotes learning-supportive activities while the use of smartphones encourages distractive activities. The lecturers might not be fully aware of the new phenomenon and, accordingly, do little for their students.

Leveraging Social Media Practices among Adolescent Cannabis Users to Develop a Mobile Health Intervention (Preprint)

2020 ◽  
Author(s):  
Elizabeth Hodgdon ◽  
Eraka Bath ◽  
Janelle Eberhard ◽  
Kara Bagot
Keyword(s):  
Social Media ◽  
Mobile Technology ◽  
Mobile Health ◽  
Technology Use ◽  
Intervention Development ◽  
Self Report ◽  
Retention Rates ◽  
The Internet ◽  
Media Applications ◽  
Media Practices

BACKGROUND Despite the universal adoption of mobile technology, adolescents generally do not use mobile health (mHealth) platforms. Those who do download mHealth applications have low retention rates. OBJECTIVE This study aims to characterize patterns of Internet, smartphone and social media use among adolescent cannabis users to leverage youth behavioral patterns for future mHealth substance use intervention development. METHODS Four self-report questionnaires measuring illicit substance and mobile technology use were administered to cannabis-using adolescents aged 14-18. RESULTS Participants spent, on average, 4-6 hours per day using the Internet, including 1-3 hours spent on social media sites. Nearly every participant used multiple social media applications, most commonly, YouTube, Snapchat, Instagram, and Facebook. The primary reasons given for engaging with social media were boredom and staying connected with friends. CONCLUSIONS Adolescents are frequently engaging with their smartphones, primarily using social media as means to communicate and occupy time. Further examination of cannabis-using adolescents’ technological preferences may be valuable to promote adoption and retention of mHealth interventions.

Ulnar Neuropathy at the Elbow Due to Repetition: Myth or Reality?

2006 ◽  
Vol 11 (5) ◽  
pp. 1-3, 7-11
Author(s):  
Richard T. Katz
Keyword(s):  
Causal Relationship ◽  
Task Force ◽  
Case Reports ◽  
Scientific Evidence ◽  
Elbow Flexion ◽  
Cubital Tunnel Syndrome ◽  
Ulnar Neuropathy ◽  
Cumulative Trauma Disorder ◽  
Tunnel Syndrome ◽  
Repetitive Strain

Abstract Repetitive strain injury (RSI), also known as cumulative trauma disorder, implies that an injury exists and was caused by repetitive strain, but both implications are debatable. Ulnar neuropathy at the elbow (UNE), also known as cubital tunnel syndrome, is the second most common upper extremity compression neuropathy (after carpal tunnel syndrome). This article examines one particular aspect of the RSI debate: Is there scientific evidence to support a causal relationship between UNE and repetitive elbow flexion and extension in the workplace? The authors extensively searched published articles, books, and federal task force publications to look for evidence supporting a causal relationship between UNE and RSI. This included a literature review followed by a study of pertinent review articles, bibliographies, national task force reports related to musculoskeletal problems in the workplace, and relevant case reports. In brief, after extensive searches the authors found no credible medical literature to support a causal relationship between RSI and UNE. Case reports and cadaver studies provide tenuous support for causation of UNE by high-force activities such as pitching in baseball. The only prospective study that systematically assessed any causal relationship between RSI and UNE showed there is none. This article includes a three-page Feature Companion, “Rating Guidance: Ulnar Neuropathy,” that identifies common errors and provides an example rating report.

Technology in the Classroom: Teachers’ Technology Choices in Relation to Content Creation and Distribution

10.28945/4201 ◽  
2019 ◽  
Keyword(s):  
Mobile Technology ◽  
Private School ◽  
Technology Use ◽  
Case Study Research ◽  
Educational Experience ◽  
Mobile Technologies ◽  
Future Research ◽  
Content Creation ◽  
Use Of Technology ◽  
Prime Concern

[This Proceedings paper was revised and published in the 2019 issue of the journal Issues in Informing Science and Information Technology, Volume 16] Aim/Purpose: Teachers are being asked to integrate mobile technologies into their content creation and distribution tasks. This research aims to provide an understanding of teachers taking on this process and whether the use of technology has influenced their content creation and distribution in the classroom. Background: Many claim that the use of technology for content creation and distribution can only enhance and improve the educational experience. However, for teachers it is not simply the integration of technology that is of prime concern. As teachers are ultimately responsible for the success of technology integration, it is essential to understand teachers’ viewpoints and lived technology experiences. Methodology: The Task-Technology Fit (TTF) model was used to guide interpretive case study research. Six teachers were purposively sampled and interviewed from a private school where a digital strategy is already in place. Data was then analysed using directed content analysis in relation to TTF. Contribution: This paper provides an understanding of teachers’ mobile technology choices in relation to content creation and distribution tasks. Findings: Findings indicate that teachers fit technology into their tasks if they perceive the technology has a high level of benefit to the teaching task. In addition, the age of learners and the subject being taught are major influencers. Recommendations for Practitioners: Provides a more nuanced and in-depth understanding of teachers’ technology choices, which is necessary for the technology augmented educational experience of the future. Recommendations for Researchers: Provides an unbiased and theoretically guided view of mobile technology use with content creation and distribution tasks. Impact on Society: Teachers do not appear to use technology as a de facto standard, but specifically select technology which will save them time, reduce costs, and improve the educational experiences of their learners. Future Research: A mixed-method approach, including several diverse schools as well as learners would enrich the findings. Furthermore, consideration of hardware limitations and lack of software features are needed.

Differences in Reward and Persistency characterise Behavior in Chronic Pain for the Iowa Gambling Task in a Web-based Lab-in-the-field study (Preprint)

2020 ◽  
Author(s):  
Lili Zhang ◽  
Himanshu Vashisht ◽  
Alekhya Nethra ◽  
Brian Slattery ◽  
Tomas Ward
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Chronic Pain ◽  
Iowa Gambling Task ◽  
Learning Curves ◽  
Self Report ◽  
Healthy Controls ◽  
Gambling Task ◽  
Convenience Sample ◽  
Pain Experiences

BACKGROUND Chronic pain is a significant world-wide health problem. It has been reported that people with chronic pain experience decision-making impairments, but these findings have been based on conventional lab experiments to date. In such experiments researchers have extensive control of conditions and can more precisely eliminate potential confounds. In contrast, there is much less known regarding how chronic pain impacts decision-making captured via lab-in-the-field experiments. Although such settings can introduce more experimental uncertainty, it is believed that collecting data in more ecologically valid contexts can better characterize the real-world impact of chronic pain. OBJECTIVE We aim to quantify decision-making differences between chronic pain individuals and healthy controls in a lab-in-the-field environment through taking advantage of internet technologies and social media. METHODS A cross-sectional design with independent groups was employed. A convenience sample of 45 participants were recruited through social media - 20 participants who self-reported living with chronic pain, and 25 people with no pain or who were living with pain for less than 6 months acting as controls. All participants completed a self-report questionnaire assessing their pain experiences and a neuropsychological task measuring their decision-making, i.e. the Iowa Gambling Task (IGT) in their web browser at a time and location of their choice without supervision. RESULTS Standard behavioral analysis revealed no differences in learning strategies between the two groups although qualitative differences could be observed in learning curves. However, computational modelling revealed that individuals with chronic pain were quicker to update their behavior relative to healthy controls, which reflected their increased learning rate (95% HDI from 0.66 to 0.99) when fitted with the VPP model. This result was further validated and extended on the ORL model because higher differences (95% HDI from 0.16 to 0.47) between the reward and punishment learning rates were observed when fitted on this model, indicating that chronic pain individuals were more sensitive to rewards. It was also found that they were less persistent in their choices during the IGT compared to controls, a fact reflected by their decreased outcome perseverance (95% HDI from -4.38 to -0.21) when fitted using the ORL model. Moreover, correlation analysis revealed that the estimated parameters had predictive value for the self-reported pain experiences, suggesting that the altered cognitive parameters could be potential candidates for inclusion in chronic pain assessments. CONCLUSIONS We found that individuals with chronic pain were more driven by rewards and less consistent when making decisions in our lab-in-the-field experiment. In this case study, it was demonstrated that compared to standard statistical summaries of behavioral performance, computational approaches offered superior ability to resolve, understand and explain the differences in decision- making behavior in the context of chronic pain outside the lab.

Relationship between medication adherence and psychosocial adjustment in patients with type 2 diabetes: A cross-sectional study

2020 ◽  
Vol 40 (3) ◽  
pp. 116-122
Author(s):  
Duygu Kes ◽  
Feray Gökdoğan
Keyword(s):  
Type 2 Diabetes ◽  
Psychosocial Adjustment ◽  
Large City ◽  
Psychosocial Care ◽  
Self Report ◽  
Cross Sectional ◽  
Convenience Sample ◽  
Adherence To Medication ◽  
The Relationship

Adherence to drug treatment is a multidimensional concept. It is affected by many factors, such as physiological, psychological, family, environmental and social conditions. However, relatively little is known about the relationship between adherence to medication and psychosocial adjustment. The aim was to explore the relationship between adherence to antidiabetic drugs and the psychosocial adjustment of patients with type 2 diabetes mellitus. This cross-sectional descriptive correlational study was conducted between March and June 2018. A convenience sample of participants was recruited from seven internal disease outpatient clinics at a public tertiary hospital, located in a large city that serves as a gateway to nearby rural and urban areas in the north-west region of Turkey. Data were collected using the Adherence to Refills and Medications Scale (ARMS-7), and the Psychosocial Adjustment to Illness Scale–Self Report (PAIS–SR). This study is reported in accordance with STROBE. Pearson’s correlation analysis found a significant weak positive correlation between all domains of the PAIS–SR and the total scores on the ARMS‐7. The participants’ scores on medication refill were found to be significantly and positively correlated with all of the PAIS–SR domain scores except the sexual relationships domain. Psychosocial care could play a crucial role in improving drug regimen adherence among patients with diabetes. Therefore, nurses should integrate psychosocial care into daily practice.

The Use of Mobile Technology in Management and Risk Control in the Supply Chain

2014 ◽  
Vol 22 (1) ◽  
pp. 14-33 ◽  
Author(s):  
Amarolinda Zanela Klein ◽  
Eliane Gomes da Costa ◽  
Luciana Marques Vieira ◽  
Rafael Teixeira
Keyword(s):  
Supply Chain ◽  
Risk Reduction ◽  
Mobile Technology ◽  
Technology Use ◽  
Single Case ◽  
Risk Control ◽  
Mobile Technologies ◽  
Food Markets ◽  
Safety Risks ◽  
Study Results

The use of mobile technologies is important for Supply Chain Management (SCM) because these technologies allow for a ubiquitous flow of information, higher agility and risk reduction in supply chains. In food markets, these issues are particularly relevant due to food safety risks. The main goal of this paper is to analyze the use of mobile technology for management and risk control in the Brazilian beef supply chain, since Brazil is one of the main producers and beef exporters in the world. The research method was a single case study. Results show the actual level of mobile technology use; drivers and barriers to mobile technology adoption and how mobile technology is applied to beef traceability and risk reduction along the chain. The authors propose a framework that links the issues of mobile technology use for SCM and risk control, considering the context of a developing country such as Brazil.

scholarly journals Linking Phubbing Behavior to Self-Reported Attentional Failures and Media Multitasking

2021 ◽  
Vol 13 (4) ◽  
pp. 100
Author(s):  
Kayla S. Sansevere ◽  
Nathan Ward
Keyword(s):  
Technology Use ◽  
Past Research ◽  
Self Report ◽  
Media Multitasking ◽  
Cognitive Errors ◽  
Personality Variables ◽  
Cognitive Framework ◽  
Self Report Data ◽  
Attentional Lapses ◽  
Use Behavior

Phubbing, or using a phone to snub another person, has been investigated through social and personality frameworks. Phubbing involves attending to and performing competing tasks, implying the involvement of attentional abilities. Yet, past research has not yet used a cognitive framework to establish a link between phubbing and attention. Using self-report data from a large online sample, we explored the associations between phubbing and everyday attentional failures. Phubbing was associated with difficulties in attentional shifting and distractibility, frequent attentional lapses, spontaneous and deliberate mind wandering, and attention-related cognitive errors. When examining these attention variables alongside several psychosocial and personality variables, attention-related cognitive errors acted as the biggest predictor of phubbing behavior. Phubbing was also positively correlated with media multitasking, which is a conceptually similar yet distinct technology use behavior. The results suggest that perceived everyday attentional failures are strongly associated with, and to an extent can predict, phubbing behavior, even more so than some social and personality variables. Technology has incorporated itself as a necessity, or at the very least a favored convenience, in most people’s lives. Characterizing technology multitasking behaviors from a variety of frameworks can help us better understand who is engaging in these behaviors and why.

scholarly journals Conversational engagement and mobile technology use

2019 ◽  
Vol 99 ◽  
pp. 66-75
Author(s):  
Jens F. Binder ◽  
Klaudia Cebula ◽  
Sondos Metwally ◽  
Michael Vernon ◽  
Christopher Atkin ◽  
...  
Keyword(s):  
Mobile Technology ◽  
Technology Use
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