Identity development and adaptation in adolescents with genetic conditions: a qualitatively oriented mixed-methods study to develop strategies for optimizing clinical genetics services
Bibliographic record
Abstract
Abstract Background Genetic counselling for adolescents necessitates an approach distinct from that used with adults. Developing best practices is crucial, considering the growing number of disabled adolescents worldwide and increasing use of genomic testing early in life. We investigated perceptions of adolescents (10–19 years) who had been diagnosed with a genetic disorder in terms of how they describe receiving, understanding, and living with a genetic condition. We undertook a cross-sectional, qualitatively oriented mixed methods study underpinned by the pragmatic paradigm. Adolescents completed two self-report measures – the psychological adaptation scale (PAS) and the illness identity questionnaire (IIQ)—and participated in semi-structured interviews. Demographic, PAS, and IIQ data were analyzed using descriptive statistics. We used phronetic iterative analysis to interrogate interview data. Qualitative and quantitative components were integrated through abduction. Results Eighteen participants (median age: 15.5 years; 11/18 women/girls; 13/18 typical cognition; 8/18 de novo presentation) with a variety of genetic conditions participated. Participants had a mean PAS of 3.07 ± 0.84 indicating adequate adaptation. Their IIQ profiles indicated slightly better mean adaptive scores (3.10 ± 1.06) than mean maladaptive scores (2.85 ± 0.99). We developed a conceptual model that describes disability and genetic identity development and psychological adaptation among participants composed of three interacting components: internalizing processes; variability arising from contextual factors; and external factors associated with the processes. Adolescents generally moved among four internalizing processes (initiating, minimizing, exploring, and accepting). Movement across these processes took place frequently because of contextual factors like setting and disability type. Communication and engagement with caregivers, peers, and healthcare professionals, social interactions with others who have the same or a similar condition, and the impact of ableism constituted the main external factors with which adolescents engaged in the development of these identities. Conclusions Our findings present a foundation upon which to develop a care model optimized for the needs of adolescents with genetic conditions. Enhancing access to genetic counselling as a means of facilitating identity development is an important component of these care models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".