Edwards Jerri D, Philllips Christine B, O'Connor Melissa L, O'Brien Jennifer L, Hudak Elizabeth M, Nicholson Jody S
Department of Psychiatry and Behavioral Neurosciences, University of South Florida, USA.
Department of Communication Sciences and Disorders, University of South Florida, USA.
J Cogn Enhanc. 2021 Mar;5(1):51-61. doi: 10.1007/s41465-020-00183-3. Epub 2020 Aug 1.
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 (=219) were healthy older adults aged 55-96 years (=75.36, =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 (=219) and post-training (=173). Eight composites were derived from factor analyses. Adherence rates were high (=81%), but none of the composites predicted training adherence. There was an overall significant effect of time, Wilks' λ=.843, (8, 114)=2.65, =.010, partial =.157, a significant overall effect of training group, Wilks' λ=.770, (16, 228)=1.99, =.015, partial =.123, and an overall significant group x time interaction, Wilks' λ=.728, (16, 226)=2.44, =.002, partial =.147. Significant effects of time were found for e and . Post-training, participants more strongly agreed that training was enjoyable and increased their sense of accomplishment. Changes in s 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.
尽管计算机化认知训练对老年人的益处已得到证实，但对于训练行为的决定因素却知之甚少。我们开发并测试了一些量表，以量化对这种训练的期望，检验期望是否能预测训练依从性，并探究训练期望在训练前到训练后是否发生变化。参与者（n = 219）为年龄在55 - 96岁（M = 75.36，SD = 9.39）的健康老年人，他们参与了四项研究，这些研究调查了达金（Dakim）、洞察（Insight）或波西特科学大脑健身（Posit Science Brain Fitness）计算机化认知训练项目。相关工具改编自现有的健康行为量表：认知训练自我效能感、认知训练结果期望、认知衰退、痴呆或阿尔茨海默病的感知易感性以及认知衰退、痴呆或阿尔茨海默病的感知严重性。参与者在基线时（n = 219）和训练后（n = 1)）完成了这些量表。通过因子分析得出了八个合成量表。依从率较高（81%），但没有一个合成量表能预测训练依从性。时间存在总体显著效应，威尔克斯' λ = 0.843，F(8, 114) = 2.65，p = 0.010，偏η² = 0.157；训练组存在总体显著效应，威尔克斯' λ = 0.770，F(16, 228) = 1.99，p = 0.015，偏η² = 0.123；并且存在总体显著的组×时间交互作用，威尔克斯' λ = 0.728，F(16, 226) = 2.44，p = 0.00)），偏η² = 0.147。在e和方面发现了时间的显著效应。训练后，参与者更强烈地认同训练是令人愉快的，并增强了他们的成就感。不同项目的方面变化各异，达金项目的参与者有所改善，而更具挑战性的大脑健身项目和洞察项目的参与者则有所下降。这些新设计的量表可能有助于研究认知训练行为。然而，还需要更多工作来了解影响老年人参与和坚持认知训练的因素。
