Critical Reflections on the Usefulness of <i>eConnect</i> to a Sample of Child and Youth Care Workers in South Africa
Bibliographic record
Abstract
In South Africa, most children in care have been removed from homes characterized by violence, abuse, poverty, and neglect, with many of these children often exposed to multiple traumatic events.Research points to a strong causal association between child trauma and attachment difficulties.Poor attachment increases children's risk for a range of externalizing behaviors, with related negative consequences for the child in both the short and long term.Addressing attachment difficulties of children who have experienced disrupted care is therefore vital.This paper reflects critically on the usefulness of eConnect, a trauma informed and attachment-based programme in such cases.It reports the interview-facilitated insights of 11 child and youth care workers (CYCW) from a care facility in Johannesburg, South Africa, who completed the eConnect programme in 2021.The first interviews were conducted in the last eConnect session (2021); follow-up interviews were done in 2022.The resulting insights allow evaluation of the contextual fit of eConnect for CYCW in SA and understanding of which programme aspects had enduring uptake.They nudge continued sensitivity to situational and cultural dynamics to optimize programme efficacy and best enable care workers. IMPLICATIONS FOR PRACTICE Implications for practice: Scrutinize roleplays and training materials to ensure cultural translatability, inclusivity, and relevance for diverse caregiver backgrounds. Explore ways to integrate trauma-informed programmes into existing family support initiatives within residential care settings. Recognize challenges associated with online programme delivery in under-resourced contexts, such as technical difficulties and power outages. Tailoring a programmes delivery mode to local conditions enhances practicality and ensures the programme's usefulness in real-world contexts.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".