Applying the Health Belief Model to Quantify and Investigate Expectations for Computerized Cognitive Training.

Autor: Edwards JD; Department of Psychiatry and Behavioral Neurosciences, University of South Florida, USA.; Department of Communication Sciences and Disorders, University of South Florida, USA., Philllips CB; Atria Senior Living, Louisville, KY USA., O'Connor ML; North Dakota State University, Fargo, ND USA., O'Brien JL; Department of Communication Sciences and Disorders, University of South Florida, USA.; Department of Psychology, University of South Florida, USA., Hudak EM; Department of Psychiatry and Behavioral Neurosciences, University of South Florida, USA., Nicholson JS; University of North Florida, Jacksonville, FL USA.
Jazyk: angličtina
Zdroj: Journal of cognitive enhancement : towards the integration of theory and practice [J Cogn Enhanc] 2021 Mar; Vol. 5 (1), pp. 51-61. Date of Electronic Publication: 2020 Aug 01.
DOI: 10.1007/s41465-020-00183-3
Abstrakt: Despite the demonstrated benefits of computerized cognitive training for older adults, little is known about the determinants of training behavior. We developed and tested scales to quantify expectations about such training, examine whether expectations predicted training adherence, and explore if training expectations changed from pre- to post-training. Participants ( N =219) were healthy older adults aged 55-96 years ( M =75.36, SD =9.39), enrolled in four studies investigating Dakim, Insight, or Posit Science Brain Fitness computerized cognitive training programs. Instruments were adapted from existing health behavior scales: Self Efficacy for Cognitive Training, Outcome Expectations for Cognitive Training, Perceived Susceptibility to Cognitive Decline, Dementia or Alzheimer's Disease, and Perceived Severity of Cognitive Decline, Dementia or Alzheimer's Disease. Participants completed scales at baseline ( N =219) and post-training ( n =173). Eight composites were derived from factor analyses. Adherence rates were high ( M =81%), but none of the composites predicted training adherence. There was an overall significant effect of time, Wilks' λ=.843, F (8, 114)=2.65, p =.010, partial η 2 =.157, a significant overall effect of training group, Wilks' λ=.770, F (16, 228)=1.99, p =.015, partial η 2 =.123, and an overall significant group x time interaction, Wilks' λ=.728, F (16, 226)=2.44, p =.002, partial η 2 =.147. Significant effects of time were found for e xpected psychological outcomes and self-efficacy . Post-training, participants more strongly agreed that training was enjoyable and increased their sense of accomplishment. Changes in s elf-efficacy for cognitive training varied by program, improvingfor Dakim- and declining for the more challenging Brain Fitness- and InSight participants. These newly devised scales may be useful for examining cognitive training behaviors. However, more work is needed to understand factors that influence older adults' enrollment in and adherence to cognitive training.
Competing Interests: Conflicts of Interest: Over an approximate three-month period in 2008, Dr. Edwards worked as a limited consultant to analyze data and prepare a publication for Posit Science, Inc., who marketed the InSight and Brain Fitness programs. Dr. Edwards served on the data safety and monitoring board of NIH grants awarded to employees of Posit Science from 2016–2018.
Databáze: MEDLINE
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