Effects of Expectations on Cognitive Enhancement Interventions in Young and Older Adults
Bibliographic record
Abstract
With increasing life expectancy and global population of older adults, preserving cog- nitive function throughout life represents a growing priority. Numerous approaches to cognitive enhancement exist, but few have scientific merit. Among the most preva- lent – and commercialized – approaches are cognitive training (“brain training”) and non-invasive brain stimulation through electric currents applied at the surface of the scalp. The present dissertation describes a collection of work contextualizing the appeal of these cognitive enhancement methods and addressing some of the most pervasive limitations of research in this field thus far. One largely ignored issue in cognitive intervention research pertains to people’s expectations of programs and their relationship with intervention outcomes. In a series of initial studies, we developed and validated the Expectation Assessment Scale (EAS), a tool created to measure as well as prime expectations of outcomes in the context of cognitive enhancement interventions. In our first two studies, we probed expectations of cognitive training or non-invasive brain stimulation in over 1,000 young, middle-aged, and older adults. Ratings on the EAS suggested that older adults may have particularly high expectations of cognitive training, but that expectations can be primed to increase or decrease – at least in hypothetical scenarios. We used these data to assess the psychometric properties of the EAS with item-response theory, and confirmed its internal consistency. Next, we incorporated the EAS into two cognitive enhancement trials, one in- vestigating a computerized cognitive training intervention in nearly 100 older adults and another examining non-invasive brain stimulation in nearly 100 young adults. Both trials had a double-blind balanced-placebo design in which participants were assigned to the intervention or control condition, and then subdivided to receive ei- ther high or low expectation priming (i.e., primed to have high or low expectations of the program’s effectiveness). Although expectation ratings replicated our previous findings, results from these trials suggest little, if any, effect of either expectations or the intervention on performance outcomes. We nevertheless found that participants enjoyed their assigned program and that those who received high expectation prim- ing tended to report a more positive experience. Our findings put into question the effectiveness of such interventions and support the need for more rigorous trials of cognitive enhancement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".