Inhalant abuse: a growing public health concern in india
Bibliographic record
Abstract
Sir—Inhalant abuse has been widely reported in Western countries. Studies on the general population have yielded prevalence rates of 5–15% for young people as having used inhalants in the United States [1], 3–6% in Canada [2] and 6–7% in the United Kingdom [3]. In India, there is a comparative lack of data pertaining to inhalant abuse: so far only a single case series and a few case reports have been reported [4–6]. The reason for the relative paucity of literature from India may be attributed to a lack of awareness among mental health professionals. They fail to elicit information pertaining to solvent abuse/dependence in epidemiologic and clinic-based studies. Inhalants are widely available everywhere, and their abuse is becoming a significant public health problem in India, more so due to the lack of knowledge among the general population and even the medical fraternity regarding their abuse potential. We studied 10 children: three of whom presented to our clinic in a city in northern India; the remaining were contacted by our community team. The mean age was 11.4 years. Most of the children were from a low socioeconomic background and had dropped out of school. Most of them were working, mainly in order to supplement the family income. All the children were abusing correction fluid and its thinner, containing toluene. Petrol and nail polish remover were the other solvents used by these children. Other commonly used substances in this group were tobacco, cannabis and alcohol (in descending order). The parents of six of the children were not aware of the substance use at the time of contact. The children reported using the correction fluid because of its easy accessibility, cheap price, the small size of the container (making it easy to conceal), its fast onset of action and the regular 'high' that it provided. On investigating further, we found that the problem is quite rampant. Therefore, we have instituted a 'Snowball technique' where the children under treatment become prime motivators to bring other children to the treatment centre for weekly group therapy sessions. We have initiated pamphlet distribution among the general population, newspaper articles to spread awareness in the community and puppet shows to educate and sensitize people as to the dangers associated with the practice. Some intervention on the part of the Government is also required and legislation may be enacted so that such substances are not available to minors. Detailed and systematic studies are required to research the extent of the problem, identify the reasons for the high prevalence of inhalant abuse among children and identify effective intervention strategies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".