Access to therapy for child sexual abuse survivors: Preliminary dialogue of barriers and facilitators between caregivers
Bibliographic record
Abstract
BACKGROUND: Difficulties in access to therapy were highlighted by COVID-19 measures restricting in-person gatherings. Additional challenges arise when focusing on caregivers of child sexual abuse (CSA) survivors in particular, which are a population that has been historically difficult to engage with due to issues of stigma and confidentiality. OBJECTIVES: To present preliminary qualitative results from caregivers of CSA survivors. METHODS: This study was conducted with caregivers of CSA survivors. Two hybrid webinar/focus groups were conducted using a video conferencing platform in fall of 2021 with two groups of stakeholders (11 caregivers and 5 moderators/clinical staff at Little Warriors, an intensive episodic treatment facility). Sessions were recorded, transcribed, and thematically-analyzed using standard qualitative methodology. RESULTS: A total of 11 caregivers contributed to the data. Themes include: (1) Challenges of starting and maintaining treatment (i.e., emotional impact of intake day, challenges of enrolling), (2) Therapeutic benefits of specialized treatment (i.e., feeling safe and supported and the importance of trauma-informed care), and (3) Barriers and facilitators of treatment (i.e., avenues to scale-up and self-care). CONCLUSION: The importance of a strong therapeutic alliance was highlighted by both caregivers/clinical staff and further support is needed for families post-treatment. The present hybrid webinar/focus group also achieved engagement goals in a population that is typically difficult to reach. Overall, the response rate (12%) was equivalent to reported registrant attendance rates for general business to consumer webinars and the recommended focus group size. This preliminary approach warrants replication in other populations outside our clinical context.
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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 | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".