Applying the Health Belief Model to Quantify and Investigate Expectations for Computerized Cognitive Training.
Applying the Health Belief Model to Quantify and Investigate Expectations for Computerized Cognitive Training.
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DOI：
10.1007/s41465-020-00183-3
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发表时间：
2021-03
期刊：
影响因子：
--
通讯作者：
Nicholson JS
中科院分区：
文献类型：
--
作者：
Edwards JD;Philllips CB;O'Connor ML;O'Brien JL;Hudak EM;Nicholson JS
尽管计算机化认知训练对老年人有明显的好处，但人们对训练行为的决定因素知之甚少。我们开发并测试了量表来量化对此类培训的期望，检查期望是否预测培训依从性，并探索培训期望是否从培训前到培训后发生变化。参与者（N=219）是年龄在55-96岁（M=75.36，SD=9.39）的健康老年人，参加了四项研究，调查Dakim，Insight或Posit Science Brain Fitness计算机认知训练计划。工具改编自现有的健康行为量表：认知训练的自我效能、认知训练的结果预期、认知衰退、痴呆症或阿尔茨海默病的感知易感性以及认知衰退、痴呆症或阿尔茨海默病的感知严重程度。参与者在基线（N=219）和培训后（n=173）完成量表。八个复合材料来自因子分析。坚持率很高（M=81%），但没有一个复合材料预测培训坚持率。存在时间的总体显著影响，Wilks' λ= 0.843，F（8，114）=2.65，p= 0.010，部分η2= 0.157，训练组的显著总体影响，Wilks' λ= 0.770，F（16，228）=1.99，p= 0.015，部分η2= 0.123，以及总体显著组x时间交互作用，Wilks' λ= 0.728，F（16，226）=2.44，p=.002，部分η2=.147。时间对预期心理结果和自我效能有显著影响。培训后，参与者更加强烈地认为培训是愉快的，增加了他们的成就感。认知训练的自我效能的变化因项目而异，Dakim的自我效能有所提高，而更具挑战性的大脑健康和洞察力参与者则有所下降。这些新设计的量表可能有助于检查认知训练行为。然而，需要更多的工作来了解影响老年人参加和坚持认知训练的因素。
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 η2=.157, a significant overall effect of training group, Wilks’ λ=.770, F(16, 228)=1.99, p=.015, partial η2=.123, and an overall significant group x time interaction, Wilks’ λ=.728, F(16, 226)=2.44, p=.002, partial η2=.147. Significant effects of time were found for expected psychological outcomes and self-efficacy. Post-training, participants more strongly agreed that training was enjoyable and increased their sense of accomplishment. Changes in self-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.
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DOI：
10.1016/j.trci.2017.09.002
发表时间：
2017-11
期刊：
Alzheimer's & dementia (New York, N. Y.)
影响因子：
--
作者：
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