P2‐625: THE DESIGN, EVALUATION AND REPORTING OF NON‐PHARMACOLOGICAL, COGNITION‐ORIENTED TREATMENTS (COTS) FOR OLDER ADULTS: RESULTS OF AN EXPERTS SURVEY
Bibliographic record
Abstract
Non-pharmacological cognition-oriented treatments (COTs), including cognitive stimulation, training and rehabilitation, are a class of interventions in which cognitive strategies are used to directly or indirectly target cognitive processes and functional abilities. Research interest has grown exponentially recently, but consensus regarding the value of these approaches has been difficult to achieve, due to conceptual disagreements, the heterogeneity within and across treatment and trial designs, and inadequate reporting. The aim of the current study was to characterise, by means of a survey, the collective knowledge, attitudes, beliefs and practices of researchers involved in the design and implementation of COT-related trials in older adults. This is an important step towards improving the evidence base for COTs by establishing areas of consensus and disagreement among researchers and clinicians. The survey covered conceptual issues concerning the relevant target populations, intervention design (including critical components, delivery setting, frequency, format, and dosage), and trial methodology (including outcomes, measures and control conditions). The survey was developed using Qualtrics and conducted in mid-2017. Of approximately 120 experts invited by email, 39 (32%) commenced and 32 (26.5%, 16 females) completed the survey from 15 countries. Respondents ranged in age from 25 to 75 years; 81% had over ten years’ experience working in medical (25%), psychological (75%), academic (60%) or combined clinical and research (40%) settings. All respondents reported involvement with implementation of cognitive interventions. There was relative agreement regarding relevance of COTs for various target groups (e.g. healthy older, MCI, dementia), intervention content (e.g., multi-domain interventions), and treatment components (e.g., goal setting). There was poorer consensus for some treatment elements (e.g., explicit instruction, performance feedback), optimal intervention setting (e.g., community, clinic), frequency and duration of sessions, and outcome measures (e.g., assessment batteries, functional outcomes, clinical progression). No consensus was found for COT terminology, the veracity of evidence for COTs in dementia prevention, and several trial design characteristics. In addition to ensuring that areas of relative agreement are supported by evidence, our findings identify important areas of disagreement. Findings may inform critical areas in the development of guidelines for the conduct of COT-related research.
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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 | 0.221 | 0.447 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".