Efficacy of a strategy-based intervention on text-level reading comprehension in persons with aphasia: a study protocol for a repeated measures study
Bibliographic record
Abstract
INTRODUCTION: At least 68% of persons with aphasia (PWA) experience reading difficulties. Even though strategy-based interventions are a promising treatment approach for text level reading comprehension deficits in PWA, empirical evidence for their efficacy remains rare. The primary objective of this study is the analysis of the efficacy of a strategy-based intervention on text-level reading comprehension and on reading activities in PWA. METHODS AND ANALYSIS: In a repeated measures trial, 24 PWA will first participate in a waiting period and then in a strategy-based intervention (14 face-to-face-sessions, 60 min each). We will apply two combinations of strategies to treat either the microstructure or the macrostructure, respectively. Participants will be randomly allocated to two parallel groups that will receive these combinations in interchanged sequences. Assessments will be implemented before and after each period as well as 3 and 6 months after the intervention. The primary outcome measure is text-level reading comprehension measured with a German version of the Test de Compréhension de Textes (TCT-D) and represented by the score TCT-D Total . A non-blinded and a blinded rater will evaluate the primary outcome measure. Secondary outcome measures will address specific reading functions, reading activities and cognitive functions. The sample size was determined with an a priori power analysis. For statistical analysis, we will use contrast analyses within repeated measures analysis of variance models. We expect significant improvements in primary and secondary outcome measures during the intervention as compared with changes during the waiting period. ETHICS AND DISSEMINATION: This study was approved by the ethics committee of Deutscher Bundesverband für akademische Sprachtherapie und Logopädie (20-10074-KA-MunmErw+Ko). Results and relevant data will be disseminated in peer-reviewed journals, at conferences and on the Open Science Framework. TRIAL REGISTRATION NUMBER: DRKS00021411 (see Supplementary Table 1).
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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 | 0.043 | 0.033 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".