Street Children in Alexandria: Profile and Psychological Disorders
Bibliographic record
Abstract
Background: Today developed and developing countries are facing the problem posed by street children. The continuous and unrestrained exposure to the street and its associated lifestyles makes these children vulnerable to a range of health, social, and other problems. Objective: The aim of the present work was to assess the profile of street children and their living condition from different aspects, in addition to assessment of some psychological disorders among them. Methods: A cross-sectional study was conducted on 50 street boys present at El-Horreya institute for Children Community Development, which is a non-governmental organization in Alexandria. An equal control group of 50 school boys were selected at random from the first and second grades of one governmental boys preparatory school of the Middle District of Alexandria. Every child was subjected to an interviewing questionnaire. The Arabic version of Revised Ontario Child Health study scale, children Depression Inventory and the Cooper-Smith Self-Esteem Inventory,were used to identify children with conduct disorder, depression, and assess self-esteem, respectively. Anthropometric measurements including weight and height were measured for each street child and BMI was calculated. Results: The present study revealed that more than half of street children (58.0%) came from large size families, about three-quarters (72.0%) reported insufficient income, most of them had low educated parents and unskilled fathers, 80.0% reported not living with both parents before coming to the institute, and 91.2% reported bad inter-parental relationship. Family history of drug abuse, alcohol intake, smoking, and imprison were significantly higher among street children compared to school children (p<0.001). The present study showed that 74.0% of street children were smokers, 22.0% reported drug abuse, and 90.0% were dropped out of school. Family violence, beating, and beating without reason significantly increase the risk of being a street child (OR= 31.90, 2.0, and 44.58, respectively). The risk of conduct disorder, depression, and low-self esteem were significantly more among street children compared to school children (OR= 44.59, 14.64, and 9.66, respectively). The main cause of leaving home was beating, 80.0% lived in street after leaving home, 72.0% their main source of living was begging, and most of them faced problems in the street especially with the police. The results revealed that 92.0% were satisfied with the institute and 86.0% prefer to stay in the institute than returning to the street. Recommendations: planning programs to prevent, protect, and rehabilitate street children are essential.
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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 | 0.005 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".