medigraphic.com

2015, Número 3

<< Anterior Siguiente >>

Rev Mex Ing Biomed 2015; 36 (3)


Cómputo Ambiental para Facilitar la Asociación de Pistas Contextuales con la Toma de Medicamentos

Rodríguez MD, Zárate E, Stawarz K, García-Vázquez JP, Ibarra EJE

Idioma: Ingles.
Referencias bibliográficas: 25
Paginas: 191-207
Archivo PDF: 1331.18 Kb.


RESUMEN

Las razones más comunes para que adultos mayores no se apeguen a la medicación es el olvido. Las rutinas de vida diaria sirven como pistas contextuales que mejoran el proceso cognitivo relacionado con recordar realizar una acción planeada. Nuestro propósito es presentar el proceso de desarrollo, así como detalles técnicos, de Sistemas de Cómputo Ambiental que proveen pistas contextuales al adulto mayor para ayudarle a recordar acciones de su medicación (e.g., recordar medicarse o recordar que se medicaron). Mediante un estudio cualitativo, obtuvimos evidencia del potencial de nuestra tecnología para que el adulto mayor sea más responsable e independiente para medicarse.


REFERENCIAS (EN ESTE ARTÍCULO)

  1. Murray, M. D., Morrow, D. G., Weiner, M., Tu, W., Deer, M. M., Brater, D. C., & Weinberger, M. “A conceptual framework to study medication adherence in older adults”. The American Journal of Geriatric Pharmacotherapy, vol. 2, no 1, pp. 36- 43, 2004.

  2. Insel, K. C., Einstein, G. O., Morrow, D. G., & Hepworth, J. T. “A multifaceted prospective memory intervention to improve medication adherence: Design of a randomized control trial”. Contemporary Clinical Trials, vol. 34, no. 1, pp. 45-52, 2013.

  3. Smith, G., Della Sala, S., Logie, R.H., & Maylor, E.A. “Prospective and retrospective memory in normal ageing and dementia: A questionnaire study”. Memory, vol. 8, pp. 311-321, 2000.

  4. Palen, L. and S. Aaløkke. “Of pill boxes and piano benches: ‘home-made’ methods for managing medication”. In ACM Proc. of the SIGCHI Conf. on Computer Supported Collaborative Work, Banff, Canada, pp. 79-88, Nov. 2006.

  5. Mankoff, J., Dey, A.K., Hsieh, G., Kientz, J., Lederer, S., and Ames, M. Heuristic evaluation of ambient displays. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’03). ACM, New York, USA, pp. 169-176, 2003

  6. Hix, D., & Hartson, H. R. “Developing user interfaces: ensuring usability through product & process”. John Wiley & Sons, Inc., 1993.

  7. García-Vazquez, J.P., Rodriguez, M. D., Andrade, A.G., Bravo, J. “Supporting the Strategies to Improve Elders’ Medication Compliance by Providing Ambient Aids”. Pers Ubiquit Comput, vol. 15, no. 4, pp. 389-397, 2011.

  8. Stawarz, K., Cox, A.L., and Blandford, A. “Don’t forget your pill!: designing effective medication reminder apps that support users’ daily routines”. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’14). ACM, New York, NY, USA, pp. 2269-2278, 2014

  9. McDaniel MA, et al. “Repetition errors in habitual prospective memory: elimination of age differences via complex actions or appropriate resource allocation”. Aging Neuropsychol Cogn, vol. 16, no. 5, pp. 563-88, 2009.

  10. ADT Plugin Release Notes (n.d.) Retrieved from:http://developer.android. com/tools/sdk/eclipse-adt.html

  11. http://www.microchip.com/

  12. IOIO Microcontroller (n.d.). Retrieved from: https://github.com/ytai/ioio/wiki

  13. Android (n.d.) Retrieved from: http://www.arduino.cc/

  14. https://www.sparkfun.com/products/

  15. Thompson, C., Henry, J.D., Rendell, P.G., Withall, A., Brodaty, H.: Prospective memory function in mild cognitive impairment and early dementia. J Int Neuropsychol Soc., vol. 16, pp. 318-325, 2010.

  16. Vitality. (n.d.). GlowCaps., Retrieved from: http://www.glowcaps.com/

  17. PivoTell. (n.d.). PivoTell Automatic Pill Dispenser Mk 3-11. Retrieved from: http://www.pivotell.co.uk/

  18. Philips. (n.d.). Philips Medication Dispensing Service. Retrieved from: http:// www.managemypills.com/ content/home

  19. Oliveira, R., Cherubini, M., & Oliver, N. “MoviPill: improving medication compliance for elders using a mobile persuasive social game”. In Proc. of the 12th ACM international conference on Ubiquitous Computing - Ubicomp ’10, New York, New York, USA: ACM Press, pp. 251-260, 2010.

  20. Lee, M., & Dey, A. “Real-time feedback for improving medication taking”. In CHI ’14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2259-2268, 2014.

  21. Steinman, M. A.; Hanlon, J. T. Managing medications in clinically complex elders: “There’s got to be a happy medium”. JAMA, vol. 304, no 14, pp. 1592-1601, 2010.

  22. O’Quin, K. E., Semalulu, T., & Orom, H. Elder and caregiver solutions to improve medication adherence. Health Education Research, cyv009, 2015.

  23. Gollwitzer, P. Implementation Intentions: “Strong Effects of Simple Plans”. American Psychologist, vol. 54, no. 7, pp. 493-503, 1999.

  24. MacLaughlin, E. J., Raehl, C. L., Treadway, A. K., Sterling, T. L., Zoller, D. P., & Bond, C. A. Assessing medication adherence in the elderly. Drugs & Aging, vol. 22, no. 3, pp. 231- 255, 2005.

  25. Navarro, R.F., Rodriguez, M.D., and Favela, J. “Intervention tailoring in augmented cognition systems for elders with dementia.” Biomedical and Health Informatics, IEEE Journal, vol. 18, no. 1, pp. 361-367, 2014.




2020     |     www.medigraphic.com