Assessing Substance Use and Mental Health in Adolescents With Chronic Conditions
Bibliographic record
Abstract
Abstract BACKGROUND: Mental health disorders and substance use and abuse are significant issues affecting the health of adolescents. While prevalence of these issues have been studied widely in healthy youth, far less is known about these issues in adolescents with chronic disease. This population may experience adverse health effects from potential interactions between prescribed medications and recreational substances, and effects on adherence and response to treatment may be influenced by both mental health issues and substance use. OBJECTIVES: To determine the prevalence of substance use and mental health disorders in adolescentswith chronic conditions who were receiving care at a tertiary care paediatric centre. DESIGN/METHODS: Patients aged 12-18 with a diagnosed chronic illness, requiring ongoing care for greater than 6 months were recruited from outpatient clinics in Rheumatology , Nephrology and Haematology. Data collected included age, gender, diagnosis and duration, current medications, responses to questions drawnfrom the Ontario Student Drug Use Health Survey about alcohol and substanceuse.The GAIN-SS, a validated screening tool that screens for mental health and substance abuse was also administered, minus one questionwhich asks about suicidal thinking as the responses were collected anonymously. Data were analyzed using simple descriptive statistics and chi-square analysis. RESULTS: Data collection is ongoing. For the first 55 patients from who data has been collected, the mean age was15.3 years, with 69% being female, 29% male, and .02% other. Average grade of last completion was 9.2. Patients with SLE comprised 45% of the sample;15% hada diagnosis of Sickle Cell Disease, 13% Thalassemia, 13% chronic kidney disease, and the remaining participants a variety of other rheumatologic and haemato-logic diagnoses. On average, patients were currently taking 2.7 medications. Substance use was infrequent with 70% of participants reported never having drunk alcohol or only trying a sip, and 85% reporting never having tried cannabis. The opposite was true of mental health symptoms, with over 50% endorsing significant low mood overpast year, and a similar proportion endorsing significant problems with anxiety. 13% endorsed missing meals or self inducing vomiting as a way to control their weight. CONCLUSION: There are several possible reasons that this cohort had-lower than expected alcohol and substance use for their age. Their chronic illnessmay limitinteractions with peers,with whom initial teen alcohol and cannabis experimentation tends to occur. They may also have made con-cious decisions not to use because of their illness and treatments. Significantmood and anxiety symptoms that were endorsedwarrant further assessment and may have significant impact on their treatment and overall functioning. The data did not reveal that any of them were receiving phar-macologic treatment for either depression or anxiety. These results suggest that routine screening for mental health symptoms to inform further assessment is warranted in young people with chronic medical conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".