Table 2.
Measures for the Capable Families and Youth Project: Indirect Effects Model of Young Adult Outcomes
| Measure | Description | Coding |
|---|---|---|
| Drunkenness frequency | This and other substance misuse frequency measures were adapted from item sets in the Monitoring the Future study (see Johnston et al., 2012). Drunkenness frequency was assessed with one question, “How often do you usually get drunk?” | Scaled from 1 = “Not at all” to 7 = “About every day.” |
| Alcohol-related problems | Alcohol-related problem behaviors during the past year were measured with a short, modified form of the Rutgers Alcohol Problems Index (White & Labouvie, 1989); included ten questions with the stem, “How often have the following things happened during the past 12 months?” An example item was “You had trouble remembering what you had done when you were drinking.” | Scaled from 0 = “Never” to 4 = “Four or more times”; averaged (α = .70). |
| Cigarette frequency | Past year cigarette frequency was measured with the item: “During the past 12 months how often did you smoke cigarettes?” | Scaled from 1 = “Not at all” to 7 = “About 2 packs/day.” |
| Illicit substance use frequency | Past year illicit substance use frequency was measured with nine open-ended items (e.g., “How many times in the past 12 months did you use [specific substance]?”). Items assessed past year use of marijuana, cocaine, ecstasy (MDMA), methamphetamine, and LSD (hallucinogens), as well as misuse of narcotics (Vicodin, Oxycontin, Percocet), amphetamines, barbiturates (sedatives), and tranquilizers—not under a doctor’s order. | In order to address item skew and to obtain an appropriate weighting of items in the measure, each item was natural-log transformed and summed. |
| Additional Measures not included in Spoth et al. (2014) | ||
| Marijuana index | Lifetime, past year, and past month marijuana use were combined in this index to assesses more serious use and address the problem associated with a small number of very frequent users that can skew results. | Each item was coded dichotomously, so that 0 = “No” and 1 = “Yes” and the items were summed, for an index where 0 = “Never used,” 1= “Used at least once,” 2 = “Used within the last year,” and 3 = “Used within the past month.” |
| Lifetime illicit drug use | This scale combined five lifetime illicit drug use items: methamphetamine, ecstasy, cocaine, GHB or Rohypnol, and LSD or other hallucinogens. | Each item was dichotomously scored (0 = “No”; 1 = “Yes”) and summed. |
| Lifetime prescription drug misuse | This scale combined four lifetime misuse items addressing commonly-misused prescription drugs – narcotics, barbiturates, tranquilizers, and amphetamines. The questions inquired about the use of these drugs “not under a doctor’s order.” | Each item was scored 0 = “No” or 1 = “Yes” and summed. |
Note: In order to further explore and differentiate the illicit substances analyzed in the past year illicit substance use frequency measure above, the number of users and the frequency of use for each substance were examined. As expected, marijuana had both the largest number of current users and the highest frequency of use, so it was analyzed separately. Of the additional items, prescription drug misuse is separately addressed in the literature; as applied in an earlier report (Spoth et al., 2013), an “overall” measure of such use was employed here. The additional illicit drugs assessed had low frequencies, so they were combined into an index, based on dichotomous lifetime use (to avoid issues of skewing resulting from elevated use of any given substance).
SFP 10–14 = Strengthening Families Program: For Parents and Youth 10–14; LST = Life Skills Training. The latent growth factor loadings on the observed measures of ASI set the growth model intercept to the midpoint of the post-intervention period so that the intercept value corresponded to the average level of initiation across that time period, as estimated by the model. Growth was modeled as linear (polynomial contrasts fixed at −2, −1, 0, 1 and 2). The growth factor indicators were modeled with an autoregressive error structure and the latent intercept and slope factors were allowed to correlate. The model controlled for pre-intervention ASI, dual biological parent families, and gender on the adolescent growth factors.