“I’m trying to figure out who the hell I am”: Examining the psychosocial and mental health experience of individuals learning “Not Parent Expected” news from a direct-to-consumer DNA ancestry test
Bibliographic record
Abstract
BACKGROUND: According to recent estimates, around 30 million people have taken Direct-to-Consumer DNA ancestry tests, typically marketed as a fun, harmless and exciting process of discovery. These tests estimate a user's ethnic ancestry, also matching users with biological relations on their database. This matching can produce a surprising 'not parent expected' discovery, where a user learns that an assumed parent (typically the father) is not a biological parent. Such news may negatively affect mental health, self-identity and familial relationships, while prompting the utilization of putatively helpful resources by affected individuals. However, there is a lack of research on this topic. Thus, this study aimed to document the psychosocial experience of adults who have learnt that an assumed parent is not a biological parent via a Direct-to-Consumer DNA ancestry test. Specific objectives include investigating and understanding impact on mental health, familial relationships and subsequent resources mobilized. METHODS: To meet these objectives, we conducted an inductive qualitative study, allowing for the documentation of common experiences and perspectives. This involved 52 semi-structured interviews with affected individuals, analyzed using thematic analysis. RESULTS: This resulted in five overlapping themes, namely (i) participants typically described their experience as an extraordinary shock that had a negative impact on their mental health, with some exceptions; (ii) the experience typically led to a severe and troubling disruption of their self-identity, with some exceptions; (iii) the news often ruptured extant familial relationships, especially with the mother, and any experiences with the new biological family were mixed; (iv) participants sought support from a variety of resources including spouses, siblings, and online peer support groups, which were generally considered helpful, with some exceptions; and (v) many participants consulted mental health professionals, who were sometimes considered supportive, but some participants noted that they were ill-equipped to help. Common across these themes were issues of grief, loss and trauma. CONCLUSIONS: This study reveals an expanding, vulnerable, and under-researched population facing unique stressors, that may be at high risk of developing a psychiatric disorder. There is a need for new services and supports for this population including tailored clinical interventions and specific self-care resources.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".