“Where There Are Stars, There Is Also Darkness”: Young Icelandic Men’s Experience of Prescription Drug Misuse
Bibliographic record
Abstract
Misuse of prescription drugs is a public health problem in many places around the world, including Iceland. It is considered most common among 18- to 25-year-olds, various risk factors and motives explain this trend. The purpose of this study was to examine young Icelandic men’s experience of prescription drug misuse. Participants in this study were seven Icelandic males, 18–26 years old, mean age was 20.9. Data were collected through 14 interviews and then processed using a qualitative methodological approach based on Vancouver’s school of phenomenology. The overriding theme of the study “ Where there are stars, there is also darkness” refers to the common thread in participants’ experiences of misuse of prescription drugs that were initially positive but quickly turned negative. Four main themes were identified: influence factors, reasons, onset, and continued drug misuse. The influencing factors were social influence, social group, lack of knowledge, and curiosity. The main reasons for the drug misuse were to suppress distress, improve capacity and efficiency, or have fun and avoid boredom. The onset of prescription drug misuse was characterized by quick fixes, misuse of one’s own medication or medication from a friend/family member. Continued misuse was characterized by a vicious circle, black market, medical visits on false pretenses, and symptoms of dependence and addiction. It is necessary to highlight this public health problem that prescription drug misuse among young Icelandic males appear to be and it needs to be considered as a multifarious problem as the results indicate that its nature is truly complex.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".