Effects of the Attachment Video-feedback Intervention (AVI) on parents and children at risk of maltreatment during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: The global health crisis caused by the COVID-19 pandemic has led to an increase in situations of risk of child abuse and neglect. OBJECTIVE: The objective of this study was to examine whether the Attachment Video-feedback Intervention (AVI) program can improve protective factors (decrease parental stress and household chaos, increase parent-child emotional availability and parental reflective functioning) that may diminish child maltreatment in a group of families at risk for child abuse and neglect during the COVID-19 pandemic. PARTICIPANTS AND SETTING: = 35.44, SD = 6.04; 75.6 % mothers). METHODS: The study design incorporated two randomized groups (Intervention group: AVI; Control group: treatment as usual) with pre- and post-test evaluations. RESULTS: In comparison to the control group, parents and children exposed to the AVI showed increases in emotional availability. Parents in the AVI group also presented increases in certainty regarding their child's mental states and reported lower levels of household chaos compared to those of the control group. CONCLUSIONS: The AVI program is a valuable intervention for increasing protective factors in families at risk of child abuse and neglect in times of crisis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".