Increasing condom use among adolescents with coalition-based social marketing.

OBJECTIVES: This study evaluated a multimodal social marketing intervention to reduce the sexual transmission of HIV infection among adolescents in Sacramento, California, USA. DESIGN: Five rounds of a cross-sectional random sample telephone survey were conducted from December 1996 to October 1998. The total number of respondents was 1402. RESULTS: A statistically significant, increasing trend in exposure to the intervention was detected. The number of channels through which an adolescent had been exposed to the intervention was associated with condom use at last sex with main partner [odds ratio (OR) 1.26, P < 0.01] and with psychosocial determinants of this behavior. After statistical adjustments for sex, age, and race/ethnicity to make the survey rounds comparable, the proportion of adolescents who had used a condom at last sex increased 4.3 percentage points over the 1 year intervention period. CONCLUSION: Social marketing can be combined with behavioral science to reduce the risk of HIV infection and other sexually transmitted diseases (STD) among adolescents in a large geographical area. Such a reduction can exceed expectations based on national secular trends.

Assessing community-wide outcomes of prevention marketing campaigns through telephone surveys.

PIP: This random sample survey assesses the outcomes of the community-wide HIV prevention marketing campaigns for adolescents through telephone surveys, as well as the decisions that were made to address these concerns. The study employed repeated cross-sectional analysis to collect data from 1402 adolescents over a 23-month period. Likewise, a dual sampling strategy combined with Random Digit Dialing with Listed Household samples were used. The study was conducted in a manner that protects the anonymity, privacy, and confidentiality; and at the same time, gathers an adequate response rate. Results of the study confirm that the success of the evaluation program depended on the adequacy of the response rate, which includes the use of advanced letters and toll-free phone line, as well as sensitivity to the needs and concerns of the target population. The success that was achieved is still inadequate since the results confirm the challenge of developing feasible, affordable, tailored techniques for measuring risk behavior change in members of these groups.^ieng

Psychopathology and attrition in the Baltimore ECA 15-year follow-up 1981-1996.

Predictors of non-response were investigated in a 15-year follow-up (1981-1996) of 3,481 individuals in a probability sample from the household population of East Baltimore. Demographics (age, sex, race, education, marital status, and unemployment), household factors (living arrangements, household income, household size, and number of children), cultural variables (ancestral ethnicity and foreign language), social variables (social support and networks, committing felony, carrying a weapon, using an alias, and wandering), health factors (physical illness, health insurance, medical assistance, Medicare, receiving disability benefits, social security, and welfare), interviewer's observation, and psychopathologic variables (mental disorders, suicide behavior, comorbidity, and drug use) were collected at baseline in 1981 and in 1982, then linked to follow-up data between 1993 and 1996. A tracing process involving mail, phone, criss-cross directories, motor vehicle administration records, a commercial credit bureau, the state criminal justice system, hospital records, the US National Death Index, and field tracing were used to locate the original sample. A total of 3,066 respondents of the original sample (88.1%) were traced. Non-response was categorized into Sample Mortality (that part of the original sample that died during follow-up), Sample Loss (that part of the original sample that survived but could not be found) and Refusal (that part of the original sample that survived and was found but refused to participate). Stratified analysis and adjusted multiple logistic regression modeling found sample mortality and sample loss were strongly influenced by individual and household variables and by psychopathology. Sample mortality was influenced by specific mental disorders or conditions as mania, drug abuse/dependency, antisocial personality, cognitive impairment, alcohol abuse/dependency, phobia, drug use (except PCP), and comorbidity. Household factors protective against mortality include higher household income, not living as extended members in a married couple family, and living with children in the household. Persons who were unemployed, widowed or single, without high school education, male, and 65 years of age or older were more likely to die. Sample loss was influenced by cognitive impairment, antisocial personality, and cocaine use. Household factors linked to sample loss include living in female-headed families, or non-family households, and living alone. Young nonwhite, divorced/separated, without high school education, and unemployed were also harder to find. Refusal was associated with being white, with incomplete elementary education, living as a spouse in traditional married couple families, or as a child in female-headed families. Psychopathology did not influence refusal.