Literature DB >> 25785547

Older People with Access to Hand-Held Devices: Who Are They?

Armin Shahrokni1, Sanam Mahmoudzadeh1, Ramyar Saeedi2, Hassan Ghasemzadeh2.   

Abstract

INTRODUCTION: Multiple comorbid conditions among older patients require frequent physician office and emergency room visits, at times leading to hospitalization. In recent years, mobile health (m-health) systems utilizing hand-held devices (e.g., smartphones) have been developed, which could be used for health-related interventions. This study investigates sociodemographic and clinical characteristics of individuals who have or have not accessed Internet via hand-held devices.
MATERIALS AND METHODS: Adults older than 65 years of age who participated in the Health Tracking survey of the Pew Internet and American Life Project in 2012 were included in the analysis. Data were analyzed for prevalence of Internet access via hand-held devices and differences in sociodemographic and clinical characteristics. Different online health information seeking behavior is also reported.
RESULTS: In the weighted sample size of 3,116 responses, 472 (15.1%) had access to Internet via hand-held devices. Those with such an access were younger and had higher income and education and better overall quality of life and quality of life at the time of answering the survey. They were more likely to be female and married or living as married. Those with diabetes or significant change in physical condition in the prior year were less likely to have such an access. In the multivariate analysis, older or diabetic individuals had lower probability of such access. Higher likelihood of access was associated with higher income and education, being married, female gender, better quality of life, higher number of comorbid illnesses, and emergency room visit or hospital admission in the last 12 months.
CONCLUSIONS: Investigators should pay attention to sociodemographic and clinical disparities of older adults to develop feasible m-health interventions.

Entities:  

Keywords:  Pew Internet and American Life Project; comorbid conditions; hand-held devices; mobile health; senior citizens

Mesh:

Year:  2015        PMID: 25785547     DOI: 10.1089/tmj.2014.0103

Source DB:  PubMed          Journal:  Telemed J E Health        ISSN: 1530-5627            Impact factor:   3.536


  5 in total

1.  Electronic Rapid Fitness Assessment: A Novel Tool for Preoperative Evaluation of the Geriatric Oncology Patient.

Authors:  Armin Shahrokni; Amy Tin; Robert J Downey; Vivian Strong; Sanam Mahmoudzadeh; Manpreet K Boparai; Sincere McMillan; Andrew Vickers; Beatriz Korc-Grodzicki
Journal:  J Natl Compr Canc Netw       Date:  2017-02       Impact factor: 11.908

2.  Cross-sectional study about the use of telemedicine for type 2 diabetes mellitus management in Spain: patient's perspective. The EnREDa2 Study.

Authors:  Patricia Rodríguez-Fortúnez; Josep Franch-Nadal; José A Fornos-Pérez; Fernando Martínez-Martínez; Hector David de Paz; María Luisa Orera-Peña
Journal:  BMJ Open       Date:  2019-06-22       Impact factor: 2.692

3.  Collaborative Multi-Expert Active Learning for Mobile Health Monitoring: Architecture, Algorithms, and Evaluation.

Authors:  Ramyar Saeedi; Keyvan Sasani; Assefaw H Gebremedhin
Journal:  Sensors (Basel)       Date:  2020-03-30       Impact factor: 3.576

4.  Barriers, Benefits, and Beliefs of Brain Training Smartphone Apps: An Internet Survey of Younger US Consumers.

Authors:  John Torous; Patrick Staples; Elizabeth Fenstermacher; Jason Dean; Matcheri Keshavan
Journal:  Front Hum Neurosci       Date:  2016-04-20       Impact factor: 3.169

5.  E-health literacy in older adults: an evolutionary concept analysis.

Authors:  Sun Ok Jung; Yoon Hee Son; Eunju Choi
Journal:  BMC Med Inform Decis Mak       Date:  2022-01-31       Impact factor: 2.796

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.