Literature DB >> 27036878

Developing a measure of engagement with telehealth systems: The mHealth Technology Engagement Index.

Alexis R Dewar1, Tyler P Bull1, Donna M Malvey2, James L Szalma1.   

Abstract

Introduction Telehealth systems and mobile health (mHealth) devices allow for the exchange of both physical and mental healthcare data, as well as information from a patient to a practitioner, or care recipient to caregiver; but there has been little research on why users are motivated to engage with telehealth systems. Given this, we sought to create a measure that satisfactorily assesses human motivation to use telehealth devices. Methods 532 survey responses were used in an exploratory factor analysis and confirmatory factor analysis, which tested and retested the feasibility of this new measure. Convergent and divergent validity analyses indicated that the mHealth Technology Engagement Index (mTEI) is a unique measure of motivation. Results The results indicated that autonomy, competence, relatedness, goal attainment, and goal setting underpin motivation to use telehealth systems. Discussion The mTEI shows promise in indexing human motivation to use telehealth technologies. We also discuss the importance of developing measurement tools based on theory and how practitioners can best utilize the mTEI.

Entities:  

Keywords:  eHealth; mHealth; self-determination theory; telehealth systems

Mesh:

Year:  2016        PMID: 27036878     DOI: 10.1177/1357633X16640958

Source DB:  PubMed          Journal:  J Telemed Telecare        ISSN: 1357-633X            Impact factor:   6.184


  4 in total

1.  Designing for engagement with self-monitoring: A user-centered approach with low-income, Latino adults with Type 2 Diabetes.

Authors:  Meghan Reading Turchioe; Elizabeth M Heitkemper; Maichou Lor; Marissa Burgermaster; Lena Mamykina
Journal:  Int J Med Inform       Date:  2019-08-02       Impact factor: 4.046

2.  Design of Mobile Health Tools to Promote Goal Achievement in Self-Management Tasks.

Authors:  Brad Edward Dicianno; Geoffrey Henderson; Bambang Parmanto
Journal:  JMIR Mhealth Uhealth       Date:  2017-07-24       Impact factor: 4.773

3.  Predicting asthma attacks using connected mobile devices and machine learning: the AAMOS-00 observational study protocol.

Authors:  Kevin Cheuk Him Tsang; Hilary Pinnock; Andrew M Wilson; Dario Salvi; Syed Ahmar Shah
Journal:  BMJ Open       Date:  2022-10-03       Impact factor: 3.006

4.  Optimizing Engagement in Behavioral Parent Training: Progress Toward a Technology-Enhanced Treatment Model.

Authors:  Deborah J Jones; Raelyn Loiselle; Chloe Zachary; Alexis R Georgeson; April Highlander; Patrick Turner; Jennifer K Youngstrom; Olga Khavjou; Margaret T Anton; Michelle Gonzalez; Nicole Lafko Bresland; Rex Forehand
Journal:  Behav Ther       Date:  2020-07-15
  4 in total

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