How Does a Learning Disability Affect Parent Experience and Advocacy Following Their Child’s Psychoeducational Feedback Meeting?
Bibliographic record
Abstract
Psychoeducational feedback meetings involve the dissemination of assessment results from the psychologist who completed the assessment to relevant stakeholders, including parents, school staff, or other practitioners. These meetings are vital, not only from an ethical perspective, but also in their potential for enhancing a parent’s understanding of their child and enriching parent-school collaboration. Parents with a learning disability (LD) have unique learning needs given their potential difficulties with processing and comprehension, which clinicians must consider when presenting assessment information. Despite the importance of feedback meetings and the important role of parents participating in and implementing relevant information obtained from these meetings, no current literature exists pertaining to parents participating in feedback meetings who have been diagnosed with an LD. It is crucial to study this group to ensure that psychologists can deliver assessment results in a well-informed manner that considers the unique needs of parents with an LD. This qualitative case study examines the lived experiences of four parents who have been diagnosed with an LD and participated in a feedback meeting following their child’s psychoeducational assessment. The aim was to understand what methods, supports, or accommodations may help parents with an LD better understand assessment results, and which factors may impact their ability to advocate for their children following the meeting. Findings indicate that parents with LDs experienced a range of emotions connected to the feedback meeting, with an overall sense that the feedback meeting was highly validating. Though they generally understood the results of their child’s assessment, most parents indicated that they would prefer certain instruments and processes to be utilized during the meeting to help with processing and comprehension. Though some participants had negative historical experiences as students, all parents felt supported by the school team involved in their child’s care and confident in their ability to advocate for their child. This study highlights the importance of practitioners considering parents’ individual learning and emotional needs to ensure that appropriate accommodations are utilized and that there is a connection with the school staff.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".