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Record W4412107648 · doi:10.1080/02687038.2025.2519333

A strategy-based reading intervention in aphasia: a mixed methods approach to explore individual differences in treatment response

2025· article· en· W4412107648 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAphasiology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsAphasiaPsychologyIntervention (counseling)Reading (process)Cognitive psychologyResponse to interventionPsychotherapistLinguisticsPsychiatry

Abstract

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Background Persons with aphasia (PWA) frequently experience difficulties in text-level reading comprehension. StraTexT is a strategy-based intervention to treat text comprehension in aphasia. Previous studies on StraTexT have analysed quantitative and qualitative data of an intervention study with 22 participants, providing estimates of the magnitude of treatment effects, insights into subjectively perceived improvements, and a comparison with a control condition. Individual-level quantitative analyses and interview data have not been integrated, and it is unclear for which individuals StraTexT may be particularly beneficial when considering both types of data. The rehabilitation treatment specification system (RTSS) provides a helpful framework to integrate the data.Aims (1) to describe different treatment response profiles to the targets improvement in text comprehension and transfer of reading strategies to everyday life based on self-perceived and performance-based measures, and (2) to explore similarities and differences within and across these response profiles in pre-treatment participant characteristics and patterns of change.Methods We integrated the self-perceived and performance-based outcomes on change in text comprehension, reading abilities and the transfer of reading strategies. Then, we identified different response profiles based on similarities in treatment response. We described participant characteristics for individuals at the extreme ends of the response continuum. Finally, based on the interview data, we described similarities and differences in perceived changes in reading functions, cognitive functions, and transfer within and across different response profiles to better understand applicable mechanisms of action.Outcomes and Results Regarding the selected targets, we identified seven response profiles. Subjective and objective improvement did not correlate. The descriptions of pre-treatment characteristics revealed that reading speed, discrepancies between subjective and objective measures, and several other factors differed in PWA with different response profiles. However, self-perceived change in reading functions, cognitive functions and strategy use was heterogeneous within and across response profiles.Conclusions StraTexT contributes to objective and subjective improvements in text comprehension, even in individuals who do not transfer the strategies to everyday reading. The interview data suggests that for each PWA, a different subset of StraTexT’s mechanisms of action may be at work. This likely reflects differences in underlying impairments. We propose potential indicators for candidacy decisions, including the reading speed and the discrepancy between subjective and objective measures, to be explored in future research, and emphasize the need for both performance-based and self-rated outcomes. Furthermore, our results support the use of multiple- rather than single strategy interventions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.166
GPT teacher head0.422
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it