Spoken Language Dual-Task Effects in Typical Aging: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Many studies have shown that several spoken language production skills are negatively affected by the typical aging process. In contrast, how language is affected when older adults are asked to speak under conditions of distraction using dual- or multitask paradigms has received less empirical attention, even though such conditions align with the demands of everyday communication contexts. Accordingly, the objectives in this original systematic review were to synthesize and appraise literature on spoken language production in neurotypical older adults when they talk under conditions of distraction. To our knowledge, this is the first systematic review that focuses on this topic. METHOD: Five databases (EMBASE, LLBA, Medline, PsycINFO, Web of Science Core Collection) were searched (from databases' inception to January 2024) for eligible studies using comprehensive search terms. All steps from screening of records, selection of studies, data extraction, and critical appraisal were carried out by two reviewers who worked independently. RESULTS: Thirteen studies culminated in the qualitative evidence synthesis. Critical appraisal was carried out and showed that the current evidence base is overall weak. CONCLUSIONS: The findings were mixed as to whether dual-task costs (i.e., worse performance in single-task, talking only) are evident in aging. However, speech fluency in discourse appears to be more vulnerable under conditions of distraction in older than younger adults. Across all included studies, significant methodological shortcomings were present. Whereas this literature points to some age-related changes when speaking in more challenging, dual-task contexts, further research is clearly needed on topics such as the types of dual-task contexts that reveal age-related language changes, the role of instructions on task prioritization, and the role of influential participant variables (e.g., cardiovascular risk factors) on dual-task language performance in older adults. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.29525795.
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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 | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".