Impact Assessment of Counselling on Family of Children with Intellectual Disability in Cross River State, Nigeria
Bibliographic record
Abstract
This study examined the impact of counseling on the families of children with intellectual disability (ID) in Cross River State, Nigeria. Three research questions were generated to guide the study while the Ex-post-Facto research design was adopted. A purposive sampling technique was used, and 100 parents of children with ID were selected from the Association for Intellectual and Developmental Disabilities of Nigeria (AIDDN), Cross River State Chapter. These parents have been exposed to psychodynamic counseling in the past. The instrument used for data collection was a structured questionnaire titled “Impact of Counseling on Parents of Children with ID (ICPCID)”. The instrument was validated by three experts, two in special education and one in measurement and evaluation. The reliability coefficient of 0.88 was obtained using Cronbach Alpha. The data collected were analyzed using simple percentages, frequencies, and mean scores. The findings revealed, among others, that counseling has a higher impact on the information needs of parents of children with ID. Counseling has a significant positive impact on the emotional stability of parents of children with ID. Counseling has a significant positive impact on stabilizing families of children with ID. Based on the findings, it was recommended, among others, that the Cross River State Government should establish a department of guidance and counseling under the State Ministry of Education that regularly caters for the counseling needs of parents of children with ID in the state.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".