The Guttman Approach to Modeling Drug Sequences: Bridging Literature Gaps/L'APPROCHE GUTTMAN POUR LA MODÉLISATION DE SÉQUENCES DE DROGUE: COMBLER LES LACUNES DOCUMENTAIRE
Bibliographic record
Abstract
Abstract: In addressing several literature gaps in the drug sequencing literature, this study investigated the sequencing of alcohol, cigarette, and marijuana initiation among a sample of rural American youth, by using age of initiation data to develop a Guttman scale of soft drug involvement. Explicit attention was paid to the role and importance of cigarette initiation in the soft drug sequence and an effort was made to determine whether the scalability of the sequence is impacted by the type of drug measures employed. To attend to these lines of inquiry, two Guttman scales were used to test a modified version of Kandel's (1975, 2002) drug sequencing hypothesis. The first scale utilized age of initiation data, while the second scale was developed with dichotomous initiation measures. Cross-sectional data were derived from a rural sample of American 6th, 9th, and 12th grade students. The type of initiation measures utilized had a direct bearing on scale fit and the degree to which the hypothesis was supported. Indicated are the implications that the findings have for school-based drug prevention programs. Keywords: Guttman scale; cigarette initiation in the soft drug sequence; Modeling Drug Sequences Resume: Afin de combler les lacunes documentaires dans le sequencage de drogue, cette etude a etudie le sequencage de l'alcool, de la cigarette et de l'initiation de marijuana aupres d'un echantillon de jeunes americains en milieu rural, en utilisant des donnees d'âge d'initiation a developper une echelle de Guttman de l'utilisation de drogue douce. Une attention explicite a ete accordee au role et a l'importance de l'initiation de cigarette dans la sequence de drogue douce et un effort a ete fait afin de determiner si l'evolutivite de la sequence est affectee par le type de mesures de drogue employe. Afin d'assister a ces lignes de l'enquete, deux echelles de Guttman ont ete utilisees a tester une version modifiee de l'hypothese de sequencage de drogue de Kandel (1975, 2002). La premiere echelle a utilise les donnees d'âge d'initiation, tandis que la deuxieme echelle a ete developpee avec des mesures d'initiation dichotomiques. Des donnees trans-sectionnelles ont ete calculees a partir d'un echantillon des etudiants americains ruraux en 6eme, 9eme et 12eme annee. Le type de mesures d'initiation utilisees a une incidence directe sur l'ajustement d'echelle et la mesure dans laquelle l'hypothese a ete soutenue. Les resultats utiles pour des programmes de prevention de la toxicomanie dans l'ecole. Mots-cles: echelle de Guttman; initiation de cigarette dans la sequence de drogue douce; modelisation de sequences de drogue The use of psychoactive drugs by people of all ages is an issue that warrants monitoring; however, juvenile drug use should be approached with considerably more concern (Golub & Johnson, 2001). Although a statistically normative behavior, the initiation and use of soft drugs (i.e., alcohol, cigarettes, and marijuana) during adolescence can carry high human costs (DeBellis & Clark, 2000). The human brain, which generally reaches maturity when individuals reach their 20s (Giedd, 2004), still is developing throughout the teen years. Youth who continue drug use not only are exposed to toxic chemicals at a time in which their brains are growing, but they subsequently are exposed for longer periods of time than individuals who initiate use in adulthood, when the brain is fully developed (DeBellis & Clark, 2000). Youth who initiate during childhood or early adolescence, and then develop patterned use, also may contend with homeostasis and drug tolerance at a relatively early age (Brown, Taper, Granholm, & Delis, 2000). These physiological processes taking place in the developing brain subject juveniles to significant risk for drug addiction (see, e.g., Brown et al., 2000; DeBellis & Clark, 2000). Perhaps one of the major reasons why the health consequences of soft drug use continue to pose a major concern is because alcohol, cigarette, and marijuana use remain three of the most prevalent forms of drug use among youth (Johnston, O'Malley, Bachman, & Schulenberg, 2006). …
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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 | 0.017 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".