IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/71453.html
   My bibliography  Save this paper

Digital Technology and Health: Evaluating the Impact of Mobile Health-Tracking Applications on Patients Well-Being

Author

Listed:
  • Keita, Moussa

Abstract

The number of mobile health applications has witnessed a soaring during the recent years. According the IMS Institute for Healthcare Informatics, more than 165,000 digital health applications have been available in the Apple iTunes Store and the Android App Store in 2015. Despite the enthusiasm aroused by such a growth, the main concern is the lack of evidence regarding the safety and the efficacy of these devices in terms of health benefits. This study attempts to bring in new insight on this problematic by trying to identify the causal effect of the use of technology on health status. For this purpose, we focus on the specific case of health-tracking applications which are among the most used health applications. Our analysis is based on 1020 subjects suffering from Diabetes and High Blood Pressure to compare the results of those using health-tracking applications to monitor their health and those who are not using these applications. We have estimated the model by Ordinary Least Squares (OLS) and multinomial logit regressions methods. We have also corrected potential selection bias in technology adoption by using the Heckman approach. In terms of results, our estimations show significant positive association between technology use and reported health status and quality of life. In particular, we have found that patients who use digital health-tracking feel better and report better health status than those who do not use them. For example, we have found that HealthApps users are 38 % more likely to achieve "good" health status and are 27% more likely to achieve "excellent" health status as compared to non-HealthApps users. These results appear robust to various sensitivity and robustness checks. However, although its promising nature, the effect of technology identified in this study should be regarded as short-term effect since the configuration of the data does not allow to capture potential contextual-effect in health status declaration and possible novelty-effect in technology use.

Suggested Citation

  • Keita, Moussa, 2016. "Digital Technology and Health: Evaluating the Impact of Mobile Health-Tracking Applications on Patients Well-Being," MPRA Paper 71453, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:71453
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/71453/8/MPRA_paper_71453.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jayanta Kumar Bora & Nandita Saikia, 2015. "Gender Differentials in Self-Rated Health and Self-Reported Disability among Adults in India," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    2. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    2. Song, Wei-Ling & Uzmanoglu, Cihan, 2016. "TARP announcement, bank health, and borrowers’ credit risk," Journal of Financial Stability, Elsevier, vol. 22(C), pages 22-32.
    3. Raymundo M. Campos-Vázquez, 2013. "Efectos de los ingresos no reportados en el nivel y tendencia de la pobreza laboral en México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 23-54, November.
    4. Jonathan Gruber & Aaron Yelowitz, 1999. "Public Health Insurance and Private Savings," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1249-1274, December.
    5. Campbell, Randall C. & Nagel, Gregory L., 2016. "Private information and limitations of Heckman's estimator in banking and corporate finance research," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 186-195.
    6. Leye Li & Louise Yi Lu & Dongyue Wang, 2022. "External labour market competitions and stock price crash risk: evidence from exposures to competitor CEOs’ award‐winning events," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1421-1460, April.
    7. Calcagno, R. & Renneboog, L.D.R., 2004. "Capital Structure and Managerial Compensation : The Effects of Renumeration Seniority," Discussion Paper 2004-120, Tilburg University, Center for Economic Research.
    8. Son K. Lam & Thomas E. DeCarlo & Ashish Sharma, 2019. "Salesperson ambidexterity in customer engagement: do customer base characteristics matter?," Journal of the Academy of Marketing Science, Springer, vol. 47(4), pages 659-680, July.
    9. McCausland, David & Pouliakas, Konstantinos & Theodossiou, Ioannis, 2005. "Some are Punished and Some are Rewarded: A Study of the Impact of Performance Pay on Job Satisfaction," MPRA Paper 14243, University Library of Munich, Germany.
    10. Gary F. Peters & Andrea M. Romi & Juan Manuel Sanchez, 2019. "The Influence of Corporate Sustainability Officers on Performance," Journal of Business Ethics, Springer, vol. 159(4), pages 1065-1087, November.
    11. Fossen, Frank M. & König, Johannes, 2015. "Public health insurance and entry into self-employment," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112934, Verein für Socialpolitik / German Economic Association.
    12. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    13. Fernando Rios-Avila & Gustavo Canavire-Bacarreza, 2018. "Standard-error correction in two-stage optimization models: A quasi–maximum likelihood estimation approach," Stata Journal, StataCorp LP, vol. 18(1), pages 206-222, March.
    14. Brian H. Boyer & Taylor D. Nadauld & Keith P. Vorkink & Michael S. Weisbach, 2023. "Discount‐Rate Risk in Private Equity: Evidence from Secondary Market Transactions," Journal of Finance, American Finance Association, vol. 78(2), pages 835-885, April.
    15. Kadreva, Olga, 2016. "The influence of quantity and age of children on working women’ salaries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 41, pages 62-77.
    16. Stolowy, Hervé & Jeanjean, Thomas & Erkens, Michael, 2011. "The economic consequences of increasing the international visibility of financial reports," HEC Research Papers Series 957, HEC Paris.
    17. Bruneel, Johan & Clarysse, Bart & Bobelyn, Annelies & Wright, Mike, 2020. "Liquidity events and VC-backed academic spin-offs: The role of search alliances," Research Policy, Elsevier, vol. 49(10).
    18. Leon Zolotoy & Don O’Sullivan & Keke Song, 2021. "The Role of Ethical Standards in the Relationship Between Religious Social Norms and M&A Announcement Returns," Journal of Business Ethics, Springer, vol. 170(4), pages 721-742, May.
    19. Hans A. Holter & Dirk Krueger & Serhiy Stepanchuk, 2019. "How do tax progressivity and household heterogeneity affect Laffer curves?," Quantitative Economics, Econometric Society, vol. 10(4), pages 1317-1356, November.
    20. Boncinelli, Fabio & Bartolini, Fabio & Casini, Leonardo, 2018. "Structural factors of labour allocation for farm diversification activities," Land Use Policy, Elsevier, vol. 71(C), pages 204-212.

    More about this item

    Keywords

    Digital Technology; Health Applications; Health; Quality of life.;
    All these keywords.

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:71453. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.