Bibliographic record
Abstract
BACKGROUND: The limited literature that exists about intellectual disabilities (ID) in Nigeria suggests that perceptions of ID may be shaped by social and cultural beliefs, and that socio-economic factors have prevented the development of policy and services. The present study sought to explore these suggestions in more detail by administering the Family Quality of Life Survey, an instrument used extensively throughout the world to collect comprehensive data on family quality of life. Its specific purposes were: (1) to describe the family quality of life of Nigerian families that have a son or daughter with ID and (2) to provide some initial ideas about the relationship between the families' life experiences and government policy and provision of services. METHOD: Eighty main caregivers from 80 families that received services for their sons and daughters with ID from two community agencies volunteered to participate. Two trained assistants administered the Family Quality of Life Survey in accordance with the administration methods set out by the Survey authors. Quantitative data and explanatory comments were also collected. RESULTS: Regarding the first study purpose, all nine life domains of the Family Quality of Life Survey were rated as important. The two main outcome measures, Attainment and Satisfaction, showed that three domains (Family relationships, Influence of values and Health) were sources of quality for families, but that three domains (Support from services, Support from others and Leisure) detracted from family quality of life. Measures of Opportunities, Initiative and Stability were somewhat related to one another, and with the two main outcome measures. Participants' explanatory comments suggested that the main caregivers perceived some domains to make their lives better and others did not. Regarding the second study purpose, it was only possible with the data available to make suggestions, but it seemed that there is a strong need for the development of government policy and services, and for education and training. CONCLUSIONS: The results of this study suggest that some areas of family life contribute to quality of life for Nigerian families and other areas of life are problematic for families. Although this study is not representative of all Nigerian families that have a son or daughter with ID, it provides important initial information on the family experience with disability in Nigeria.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".