Parental Bereavement in Young Children Living in South Africa and Malawi: Understanding Mental Health
Bibliographic record
Abstract
BACKGROUND: Parental loss is a major stressful event found to increase risk of mental health problems in childhood. Yet, some children show resilient adaptation in the face of adversity across time. SETTING: This study explores predictors of mental health resilience among parentally bereaved children in South Africa and Malawi, and their cumulative effect. The study also explores whether predictors of resilience differed between orphaned and non-orphaned children. METHODS: Consecutive attenders of community based organisations (children;4-13 years, and their caregivers) were interviewed at baseline and 15-18 month follow up (n=833). Interviews comprised of inventories on demographic information, family data, child mental health, bereavement experience and community characteristics. Mental health screens were used to operationalise resilience as the absence of symptoms of depression, suicidality, trauma, emotional and behavioural problems. RESULTS: Almost 60% of children experienced parental loss. One quarter of orphaned children showed no mental health problems at either wave and were classified as resilient. There were equal proportions of children classified as resilient within the orphaned (25%) vs. non-orphaned group (22%). Being a quick learner, aiding ill family members, positive caregiving, household employment, higher community support, and lower exposure to domestic violence, physical punishment, or stigma at baseline predicted sustained resilience. There were cumulative influences of resilience predictors among orphaned children. Predictors of resilience did not vary by child age, gender, country of residence or between orphaned and non-orphaned children. CONCLUSION: This study enhances understanding of resilience in younger children and identifies a number of potential environmental and psychosocial factors for bolstering resilience in orphaned children.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".