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01-08-2010

Factors associated with probability of personal digital assistant-based dietary self-monitoring in those with type 2 diabetes

Auteurs: Mary Ann Sevick, Roslyn A. Stone, Susan Zickmund, Yuanyuan Wang, Mary Korytkowski, Lora E. Burke

Gepubliceerd in: Journal of Behavioral Medicine | Uitgave 4/2010

Abstract

Knowledge of factors associated with the use of technology could inform the design of technology-based behavioral interventions. This study examined modifiable and nonmodifiable factors associated with technology-based self-monitoring. 123 participants with type 2 diabetes self-monitored diet using a personal digital assistant in a 6-month behavioral intervention. Multinomial logistic regression was used to examine probability of nonadherent and suboptimally adherent behavior relative to adherent behavior. Sociodemographic characteristics were not associated with probability of self-monitoring. Probability of adherence generally was greater in the weeks preceding no group session, and lower in the weeks following no group session or following skipped sessions. Non-modifiable factors suggested by the literature to be associated with poorer access to technology (lower income, older age, minority race, and lower education) were not associated with probability of self-monitoring in this population.

vorige artikel Early behavioral adherence predicts short and long-term weight loss in the POUNDS LOST study

volgende artikel The impact of family asthma management on biology: a longitudinal investigation of youth with asthma

During week 1, participants were instructed to record a minimum of 1 meal per day, but were given permission to enter more. While participants entering between 1 and 7 meals during week 1 were technically compliant with the protocol, for the purpose of this paper their level of self-monitoring is defined as “suboptimally adherent”.

Acharya, S. D., Elci, O. U., Sereika, S. M., Music, E., Styn, M. A., Turk, M. T., et al. (2009). Adherence to a behavioral weight loss treatment program enhances weight loss and improvements in biomarkers. Patient Prefer Adherence., 3, 151–160.PubMed

Anonymous. (2003). E-diaries help migraine sufferers predict attacks. Healthcare Benchmarks & Qual Improv. 10:71–72.

Baker, R. C., & Kirschenbaum, D. S. (1993). Self-monitoring may be necessary for successful weight control. Behaviour Therapy, 24, 377–394.CrossRef

Bandura, A. (1997). Self efficacy: The exercise of control. New York, NY: Freeman and Co.

Boissy, P., Jacobs, K., & Roy, S. H. (2006). Usability of a barcode scanning system as a means of data entry on a PDA for self-report health outcome questionnaires: A pilot study in individuals over 60 years of age. BMC Medical Informatics and Decision Making, 6, 42.CrossRefPubMed

Burke, L. E., Dunbar-Jacob, J., & Hill, M. N. (1997). Compliance with cardiovascular disease prevention strategies: A review of the research. Annals of Behaviour Medicine, 9, 239–263.CrossRef

Burke, L. E., Sereika, S., Choo, J., Warziki, M., Music, E., Styn, M., et al. (2005a). Ancillary study to the PREFER trial: A descriptive study of participants’ patterns of self-monitoring—Rational design and preliminary experiences. Contemporary Clinical Trials, 27, 23–33.CrossRefPubMed

Burke, L. E., Starrett, T., Warziski, M., Sereika, S., Stark, S., & Sevick, M. A. (2005b). Self-monitoring dietary intake: Current and future practices—Report of a pilot study using an electronic diary. Journal of Renal Nutrition, 13, 281–290.CrossRef

Burke, L. E., Sereika, S. M., Music, E., Warziski, M., Styn, M. A., & Stone, A. (2008). Using instrumented paper diaries to document self-monitoring patterns in weight loss. Contemporary Clinical Trials, 29, 182–193.CrossRefPubMed

Burke, L. E., Styn, M. A., Glanz, K., Ewing, L. J., Elci, O. U., & Conroy, M. B. (2009). SMART trial: A randomized clinical trial of self-monitoring in behavioral weight management—Design and baseline findings. Contemporary Clinical Trials, 30, 540–551.CrossRefPubMed

Carroll, A. E., Zimmerman, F. J., Rivara, F. P., & Ebel, B. E. (2005). Perceptions about computers and the internet in a pediatric clinic population. Ambulatory Pediatrics, 5, 122–126.CrossRefPubMed

Chang, B. L., Bakken, S., Brown, S. S., Houston, T. K., Kreps, G. L., Kukafka, R., et al. (2004). Bridging the digital divide: Reaching vulnerable populations. Journal of the American Medical Informatics Association, 11, 448–457.CrossRefPubMed

Chang, B. L., Omery, A., & Mayo, A. (2003). Use of personal digital assistants by adolescents with severe asthma: Can they enhance patient outcomes? AACN Clinical Issues, 14, 379–391.CrossRefPubMed

Cohen, D. A., & Farley, T. A. (2008). Eating as an automatic behavior. Prev Chronic Dis; 5. Retrieved from http://www.cdc.gov/pcd/issues/2008/jan/07_0046.htm.

Forjuoh, S. N., Reis, M. D., Couchman, G. R., & Ory, M. G. (2007). Incorporating PDA use in diabetes self-care: A central Texas Primary Care Research Network (CenTexNet) study. Journal of the American Board of Family Medicine: JABFM, 20, 375–384.CrossRefPubMed

Fowles, E. R., & Gentry, B. (2008). The feasibility of personal digital assistants (PDAs) to collect dietary intake data in low-income pregnant women. Journal of Nutrition Education and Behaviour, 40, 374–377.CrossRef

Glanz, K., Murphy, S., Moylan, J., Evensen, D., & Curb, J. D. (2006). Improving dietary self-monitoring and adherence with hand-held computers: A pilot study. American Journal of Health Promotion, 20, 165–170.PubMed

Guare, J. C., Wing, R. R., Marcus, M. D., Epstein, L. H., Burton, L. R., & Gooding, W. E. (1989). Analysis of changes in eating behavior and weight loss in type II diabetic patients. Diabetes Care, 12, 500–503.CrossRefPubMed

Helsel, D. L., Jakicic, J. M., & Otto, A. D. (2007). Comparison of techniques for self-monitoring eating and exercise behaviors on weight loss in a correspondence-based intervention. Journal of the American Dietetic Association, 107, 1807–1810.CrossRefPubMed

Jackson, L. A., Zhao, Y., Kolenic, A., & Fitzgerald, H. E. (2008). Race, gender, and information technology use: The new digital divide. Cyberpsychology & Behaviour, 11, 437–442.CrossRef

Kalichman, S. C., Weinhardt, L., Benotsch, E., & Cherry, C. (2002). Closing the digital divide in HIV/AIDS care: Development of a theory-based intervention to increase Internet access. AIDS Care., 14, 523–537.PubMed

Katz, S. J., Nissan, N., & Moyer, C. A. (2004). Crossing the digital divide: Evaluating online communication between patients and their providers. American Journal of Managed Care, 10, 593–598.PubMed

Khan, S., Sylvester, R., Scott, D., & Pitts, B. (2008). Physicians’ opinions about responsibility for patient out-of-pocket costs and formulary prescribing in two Midwestern states. Journal of Managed Care Pharmacy, 14, 780–789.PubMed

Koivusilta, L. K., Lintonen, T. P., & Rimpela, A. H. (2007). Orientations in adolescent use of information and communication technology: A digital divide by sociodemographic background, educational career, and health. Scandinavian Journal of Public Health, 35, 95–103.CrossRefPubMed

Lobach, D. F., Willis, J. M., Macri, J. M., & Simo, J. (2006). Perceptions of Medicaid beneficiaries regarding the usefulness of accessing personal health information and services through a patient Internet portal. AMIA Annual Symposium Proceedings, 2006, 509–513.

Lorence, D., & Park, H. (2006). Web-based consumer health information: Public access, digital division, and remainders. Medscape General Medicine, 8, 4. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1785207/ PubMed

Matthew, A. G., Currie, K. L., Irvine, J., Ritvo, P., Santa Mina, D., Jamnicky, L., et al. (2007). Serial personal digital assistant data capture of health-related quality of life: A randomized controlled trial in a prostate cancer clinic. Health and Quality of Life Outcomes, 5, 38.CrossRefPubMed

Meyers, A. W., Stunkard, A. J., & Coll, M. (1980). Food accessibility and food choice. A test of Schachter’s externality hypothesis. Archives of General Psychiatry, 37, 1133–1135.PubMed

Milas, N. C., Nowalk, M. P., Akpele, L., Castaldo, L., Coyne, T., Doroshenko, L., et al. (1995). Factors Associated with adherence to the dietary protein intervention in the Modification of Diet in Renal Disease study. Journal of the American Dietetic Association, 95, 1295–1300.CrossRefPubMed

Miller, K. S., Bunch-Harrison, S., Brumbaugh, B., & Kutty, R. S. (2005). The meaning of computers to a group of men who are homeless. American Journal of Occupational Therapy, 59, 191–197.PubMed

Mitchell, D. T., Korslund, M. K., Brewer, B. K., & Novascone, M. A. (1996). Development and validation of the Cholesterol-Saturated Fat Index (CSI) Scorecard: A dietary self-monitoring tool. Journal of the American Dietetic Association, 96, 132–136.CrossRefPubMed

Mossavar-Rahamani, Y., Henry, H., Rodabough, R., Bragg, C., Brewer, A., Freed, T., et al. (2004). Additional self-monitoring tools in the dietary modification component of the women’s health initiative. Journal of the American Dietetic Association, 104, 76–85.CrossRef

National Institutes of Health. (2009). NIH science of behavior change meeting summary. Retrieved from http://nihroadmap.nih.gov/documents/SOBC_Meeting_Summary_2009.pdf.

Noar, S. M., Chabot, M., & Zimmerman, R. S. (2008). Applying health behavior theory to multiple behavior change: Considerations and approaches. Preventive Medicine, 46, 275–280.CrossRefPubMed

Nothwehr, F., Dennis, L., & Haotong, Wu. (2007). Measurement of behavioral objectives for weight management. Health Education & Behavior, 34, 793–809.CrossRef

Olsen, S. (2009). Will the digital divide close by itself? New York Times. Retrieved from http://bits.blogs.nytimes.com/2009/10/30/will-the-digital-divide-close-by-itself/?scp=1&sq=Digital%20divide%20Olsen&st=cse.

Prochaska, J. J., Spring, B., & Nigg, C. R. (2008). Multiple health behavior change research: An introduction and overview. Preventive Medicine, 46, 181–188.CrossRefPubMed

Rosenthal, D. A., & Layman, E. J. (2008). Utilization of information technology in eastern North Carolina physician practices: Determining the existence of a digital divide. Perspectives in Health Information Management, 5, 3.PubMed

Sevick, M. A., Piraino, B., Bender, C., Sereika, S., Starrett, T., Bernardini, J., et al. (2005). A pilot study of PDA-based dietary self-monitoring in hemodialysis patients. Journal of Renal Nutrition, 13, 304–311.CrossRef

Sevick, M. A., Stone, R. A., Novak, M., Piraino, B., Snetselaar, L., Marsh, R. M., et al. (2008a). A PDA-based dietary self-monitoring intervention to reduce sodium intake in an in-center hemodialysis patient: A case study. Patient Preference and Adherence., 2, 177–184.PubMed

Sevick, M. A., Zickmund, S., Korytkowski, M., Piraino, B., Sereika, S., Ren, D., et al. (2008b). The ENHANCE Study: A randomized clinical trial testing the efficacy of a behavioral intervention paired with personal digital assistant-based dietary self-monitoring in type 2 diabetes–a unique intervention approach. Contemporary Clinical Trials, 29, 396–409.CrossRefPubMed

Sevick, M. A., Stone, R., Burke, L., Wang, Y., Zickmund, S., & Korytkowski, M. (2009). Factors associated with adherence to dietary self-monitoring. Annals of Behavioral Medicine, 37(Suppl 1), S146.

Siek, K. A., Rogers, Y., & Connelly, K. H. (2005). Fat finger worries: How older and younger users physically interact with PDAs. INTERACT, 2005, 267–280. Retrieved from http://www.springerlink.com/content/aphl5wkd04yk3hmq/fulltext.pdf.

Sterns, A. A. (2005). Curriculum design and program to train older adults to use personal digital assistants. Gerontologist., 45, 828–834.PubMed

Stone, A. A., Shiffman, S., Schwartz, J. E., Broderick, J. E., & Hufford, M. R. (2002). Patient non-compliance with paper diaries. BMJ., 324, 1193–1194.CrossRefPubMed

Swartz, R. J., de Moor, C., Cook, K. F., Fouladi, R. T., Basen-Engquist, K., Eng, C., et al. (2007). Mode effects in the center for epidemiologic studies depression (CES-D) scale: Personal digital assistant vs. paper and pencil administration. Quality of Life Research, 16, 803–813.CrossRefPubMed

Tate, D. F., Wing, R. R., & Winett, R. A. (2001). Using internet technology to deliver a behavioral weight loss program. JAMA, 285, 1172–1177.CrossRefPubMed

Tseng, H. M., Tiplady, B., Macleod, H. A., & Wright, P. (1998). Computer anxiety: A comparison of pen-based personal digital assistants, conventional computer and paper assessment of mood and performance. British Journal of Psychology, 89, 599–610.PubMed

Wanke, K. L., Daston, C., Slonim, A., Albert, P. S., Snyder, K., Schatzkin, A., et al. (2007). Adherence to the polyp prevention trial dietary intervention is associated with a behavioral pattern of adherence to nondietary trial requirements and general health recommendation. Journal of Nutrition, 137, 391–398.PubMed

Wansink, B., Painter, J. E., & Lee, Y. K. (2006). The office candy dish: Proximity’s influence on estimated and actual consumption. International Journal of Obesity (London), 30, 871–875.CrossRef

Wansink, B., Painter, J. E., & North, J. (2005). Bottomless bowls: Why visual cues of portion size may influence intake. Obesity Research, 13, 93–100.CrossRefPubMed

Welch, J., Dowell, S., & Johnson, C. S. (2007). Feasibility of using a personal digital assistant to self-monitor diet and fluid intake: A pilot study. Journal of Nephrology Nursing, 34, 43–48.

Willis, J. M., Macri, J. M., Simo, J., & Anstrom, K. J. (2006). Perceptions about use of a patient Internet portal among Medicaid beneficiaries. AMIA Annual Symposium Proceedings, 2006, 1145.

Yon, B. A., Johnson, R. K., Harvey-Berino, J., Gold, B. C., & Howard, A. B. (2007). Personal digital assistants are comparable to traditional diaries for dietary self-monitoring during a weight loss program. Journal of Behavioral Medicine, 30, 165–175.CrossRefPubMed

Titel: Factors associated with probability of personal digital assistant-based dietary self-monitoring in those with type 2 diabetes
Auteurs: Mary Ann Sevick
Roslyn A. Stone
Susan Zickmund
Yuanyuan Wang
Mary Korytkowski
Lora E. Burke
Publicatiedatum: 01-08-2010
Uitgeverij: Springer US
Gepubliceerd in: Journal of Behavioral Medicine / Uitgave 4/2010
Print ISSN: 0160-7715
Elektronisch ISSN: 1573-3521
DOI: https://doi.org/10.1007/s10865-010-9257-9

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