The Impact of Exposure With No Training: Implications for Future Partner Training Research
Bibliographic record
Abstract
Purpose: This research note reports on an unexpected negative finding related to behavior change in a controlled trial designed to test whether partner training improves the conversational skills of volunteers. Method: The clinical trial involving training in "Supported Conversation for Adults with Aphasia" utilized a single-blind, randomized, controlled, pre-post design. Eighty participants making up 40 dyads of a volunteer conversation partner and an adult with aphasia were randomly allocated to either an experimental or control group of 20 dyads each. Descriptive statistics including exact 95% confidence intervals were calculated for the percentage of control group participants who got worse after exposure to individuals with aphasia. Results: Positive outcomes of training in Supported Conversation for Adults with Aphasia for both the trained volunteers and their partners with aphasia were reported by Kagan, Black, Felson Duchan, Simmons-Mackie, and Square in 2001. However, post hoc data analysis revealed that almost one third of untrained control participants had a negative outcome rather than the anticipated neutral or slightly positive outcome. Conclusions: If the results of this small study are in any way representative of what happens in real life, communication partner training in aphasia becomes even more important than indicated from the positive results of training studies. That is, it is possible that mere exposure to a communication disability such as aphasia could have negative impacts on communication and social interaction. This may be akin to what is known as a "nocebo" effect-something for partner training studies in aphasia to take into account.
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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 | 0.029 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".