Families with Fetal Alcohol Spectrum Disorder: exploring adoptive parents' experiences of family well-being
Bibliographic record
Abstract
Fetal Alcohol Spectrum Disorder (FASD) is the leading non-genetic cause of developmental disability in Canada. Many challenges abound at the individual, family and societal levels. Much of the literature cites high quality home and caregiving environments as an important correlate to optimal outcomes for individuals with FASD, however, research is limited on this experience from a family perspective. Eight adoptive parents’ experiences of family well-being, within the context of having a child with FASD in the family, were explored through in-depth semi-structured interviews. Interpretive Phenomenological Analysis (IPA) drew out four superordinate themes each with their collection of sub-ordinate themes describing participants’ experiences of 1) Managing Individuals with FASD; 2) Navigating Family Cohesion; 3) Psychological Warfare; and 4) Experiences of Supports. The Family Adjustment and Adaptation Response Model (FAAR) is used to illustrate how families attribute meanings and adjust to balance demands against capabilities. Findings highlight how this dynamic disability impacts all aspects of family life and has a constant and cumulative effect on families’ well-being. Subjective overall family well-being is less than what participants feel it should be given their capacity. The duality of this experience was evident as families strive to balance their philosophies of family cohesion with the logistics of managing this complex disability. Hope, community, and parents feeling successful in their efforts seem to have strong connections to well-being. The study contributes to a growing body of FASD research and highlights the importance of a family-centered approach to care. Participant-promoted recommendations for research and practice are outlined.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".