Terms of Engagement: Understanding the Motivations, Preferences, and Attitudes of Older Adults Toward Mobile Cognitive Assessment and Training.

BACKGROUND AND OBJECTIVES: The future of cognitive assessment is likely to involve mobile applications for smartphones and tablets; cognitive training is also often delivered in these formats. Unfortunately, low adherence to these programs can hinder efforts at the early detection of cognitive decline and interfere with examining cognitive training efficacy in clinical trials. We explored factors that increase adherence to these programs among older adults. RESEARCH DESIGN AND METHODS: Focus groups were conducted with older adults (N = 21) and a younger adult comparison group (N = 21). Data were processed using reflexive thematic analysis with an inductive, bottom-up approach. RESULTS: Three primary themes related to adherence were developed from the focus group data. Switches of engagement reflects factors that must be present; without them, engagement is unlikely. Dials of engagement reflects a cost-benefit analysis that users undergo, the outcome of which determines whether a person will be more or less likely to engage. Bracers of engagement reflects factors that nudge users toward engagement by minimizing barriers associated with the other themes. Older adults in general were more sensitive to opportunity costs, preferred more cooperative interactions, and were more likely to mention technology barriers. DISCUSSION AND IMPLICATIONS: Our results are important for informing the design of mobile cognitive assessment and training apps for older adults. These themes provide guidance about ways apps could be modified to increase engagement and adherence, which in turn can more effectively facilitate the early detection of cognitive impairment and the evaluation of cognitive training efficacy.

Adherence Promotion With Tailored Motivational Messages: Proof of Concept and Message Preferences in Older Adults.

This study examined the feasibility of using tailored text messages to promote adherence to longitudinal protocols and determined what facets of text message tone influence motivation. Forty-three older adults (Mage = 73.21, SD = 5.37) were recruited to engage in video-game-based cognitive training for 10 consecutive days. Participants received encouraging text messages each morning that matched their highest or lowest ranking reasons for participating in the study, after which they rated how effective each message was in motivating them to play the games that day. After 10 days, participants rated all possible messages and participated in semi-structured interviews to elicit their preferences for these messages. Results showed that messages matching participants' reasons for participating were more motivating than mismatched messages. Further, participants preferred messages that were personalized (i.e., use second person voice) and in formal tones. Messages consistent with these preferences were also rated as more motivating. These findings establish the feasibility of using message tailoring to promote adherence to longitudinal protocols and the relevance of tailoring messages to be personal and formal.

Motivation to Engage in Aging Research: Are There Typologies and Predictors?

BACKGROUND AND OBJECTIVES: Study recruitment and retention of older adults in research studies is a major challenge. Enhancing understanding of individual differences in motivations to participate, and predictors of motivators, can serve the dual aims of facilitating the recruitment and retention of older adults, benefiting study validity, economy, and power. RESEARCH DESIGN AND METHODS: Older adults (N = 472) past and potential participants were surveyed about motivations to participate in research, demographic, and individual difference measures (e.g., health status, cognitive difficulties). Latent class and clustering analyses explored motivation typologies, followed by regression models predicting individual motivators and typologies. RESULTS: Older adults endorsed a diversity of research motivations, some of which could be predicted by individual difference measures (e.g., older participants were more motivated by the desire to learn new technology, participants without a college education were more motivated by financial compensation, and participants with greater self-reported cognitive problems were more likely to participate to gain cognitive benefit). Clustering analysis revealed 4 motivation typologies: brain health advocates, research helpers, fun seekers, and multiple motivation enthusiasts. Cognitive difficulties, age, employment status, and previous participation predicted membership in these categories. DISCUSSION AND IMPLICATIONS: Results provide an understanding of different participant motivations beyond differences between younger and older adults and begin to identify different classes of older adults motivated to participate in research studies. Results can provide guidance for targeted recruitment and retention strategies based on individual differences in stated or predicted motivations.

The Cognitive Neuroscience of Stable and Flexible Semantic Typicality.

Typicality effects are among the most well-studied phenomena in the study of concepts. The classical notion of typicality is that typical concepts share many features with category co-members and few features with members of contrast categories. However, this notion was challenged by evidence that typicality is highly context dependent and not always dependent on central tendency. Dieciuc and Folstein (2019) argued that there is strong evidence for both views and that the two types of typicality effects might depend on different mechanisms. A recent theoretical framework, the controlled semantic cognition framework (Lamdon Ralph et al., 2017) strongly emphasizes the classical view, but includes mechanisms that could potentially account for both kinds of typicality. In contrast, the situated cognition framework (Barsalou, 2009b) articulates the context-dependent view. Here, we review evidence from cognitive neuroscience supporting the two frameworks. We also briefly evaluate the ability of computational models associated with the CSC to account for phenomena supporting SitCog (Rogers and McClelland, 2004). Many predictions of both frameworks are borne out by recent cognitive neuroscience evidence. While the CSC framework can at least potentially account for many of the typicality phenomena reviewed, challenges remain, especially with regard to ad hoc categories.

Typicality: Stable structures and flexible functions.

Some research suggests typicality is stable, other research suggests it is malleable, and some suggests it is unstable. The two ends of this continuum-stability and instability-make somewhat contradictory claims. Stability claims that typicality is determined by our experience of decontextualized feature correlations in the world and is therefore fairly consistent. Instability claims that typicality depends on context and is therefore extremely inconsistent. After reviewing evidence for these two claims, we argue that typicality's stability and instability are not contradictory but rather complementary when they are understood as operating on two different levels. Stability reflects how information gets encoded into semantic memory-what we call structural typicality. Instability reflects the task-dependent recruitment of semantic knowledge-what we call functional typicality. Finally, we speculate on potential factors that may mediate between the recruitment of structural or functional typicality.

The spatial dynamics of mouse-tracking reveal that attention capture is stimulus-driven rather than contingent upon top-down goals.

There has been a longstanding debate over why stimuli capture attention. Some argue that capture is driven by stimulus salience, while others believe that capture only occurs when the features of a stimulus match what we are searching for. This debate has recently focused on attentional disengagement, with the stimulus-driven camp claiming that all salient stimuli capture attention but attention is quickly disengaged from items dissimilar from our target, producing little cost in terms of response time. We used mouse-tracking to examine the spatial effect of cues that either matched or mismatched an observer's target. Experiment 1 demonstrated that a cue mismatching the feature defining the target initially produced a spatial effect that was rapidly resolved, consistent with quick disengagement. Experiment 2 was a preregistered replication with double the sample size that replicated the results of Experiment 1. Overall, computer mouse-tracking provided a direct observation of attentional disengagement, supporting stimulus-driven capture. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Trait self-control does not predict attentional control: Evidence from a novel attention capture paradigm.

To what extent are low-level visual and attentional phenomena related to higher-level personality traits? Trait self-control is thought to modulate behavior via two separate mechanisms: 1) by preventing initial temptation and, 2) by inhibiting temptation when it occurs (disengagement). Similarly, the control of visual attention often entails preventing initial distraction by irrelevant but tempting (goal-similar) objects, and disengaging attention when it has been inappropriately captured. Given these similarities, we examined whether individuals higher versus lower in trait self-control would differ in their susceptibility to attention capture using mouse-tracking as a sensitive, online measure of how attentional dynamics resolve over time and space in response to a distracting visual cue. Using a variety of metrics of attention capture, we found that differences among people in trait self-control did not predict initial selection of visual information nor subsequent disengagement. Overall, these results suggest that trait self-control and attention capture operate via separate mechanisms.

Changing similarity: Stable and flexible modulations of psychological dimensions.

Successfully categorizing objects requires discriminating between relevant and irrelevant dimensions (e.g., shape, color). Categorization can lead to changes in the visual system that stretch psychological space, making relevant dimensions more distinct and irrelevant dimensions more similar. These changes are known as dimensional modulation (DM) and they can be both stable and flexible in nature. The current study examined the interaction between stable DM and flexible DM, as well as the time course of relative changes in similarity. Using a two-dimensional space of cars, participants learned to categorize the space and then completed a target identification task during EEG recording. We found that attention, operationally defined as the selection negativity, was sensitive to category-relevance and appeared to selectively enhance previously irrelevant differences in the service of a target detection task. In contrast, we found that late decisional stages, operationally defined as the P3 b, were less sensitive to relevance and instead more sensitive to the number of morphsteps that separated targets from non-targets. Thus, it appears that relative similarity between targets and non-targets dynamically changed over the time course of individual decisions. Similarity between exemplars was greater along the irrelevant than the relevant dimension early on in the time course but a compensatory allocation of attention led to similarity being optimized among all dimensions for later stages. This finding is important because it 1) provides a new source of converging evidence for stable DM and 2) links a neural measure of attentional modulation with facilitation of an unpracticed, but task-relevant perceptual dimension.