[논문]사회 심리 이론에 근거한 학교 흡연 예방 프로그램의 메타분석: 미국 사례와 Explanatory Variables

Hwang, Myung-Hee-Song

사회 심리 이론에 근거한 학교 흡연 예방 프로그램의 메타분석: 미국 사례와 Explanatory Variables
A meta-analysis of adolescent psychosocial smoking prevention programs in the United States: Identifying factors associated with program effectiveness 원문보기

保健敎育健康增進學會誌 = Korean journal of health education and promotion, v.24 no.5, 2007년, pp.1 - 21

Hwang, Myung-Hee-Song (Dept. of Health Education and Management, Ewha Woman's University)

초록
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청소년을 위한 학교 흡연예방 프로그램은 사회심리 이론에 근거한 프로그램이 대체로 성공적이었다고 알려져 있으나, 각 프로그램의 효과 정도에는 많은 차이가 있다. 이 연구는 다른 메타 분석처럼 전체적인 프로그램 효과도를 측정하여 일반적인 결론을 유도한 것이 아니라, 프로그램의 효과와 관계가 깊은 요인 (Explanatory Variables)을 자세히 파악하여 보건교육 담당자, 연구원, 또는 정책 결정자들에게 구체적인 가이드라인을 제공하는 데에 목적을 두고 있다. 주요한 연구결과는 다음과 같다. 1. 8-12학년 학생들보다는 초등학교에서 중등학교로 바뀌는 5-7학년 학생들에게 흡연예방 프로그램은 더 효과가 있었다. 2. 연구 방법론에 있어서는 experimental design, random assignment, 순수 비교그룹을 사용하였을 경우, implementation fidelity와 instrument reliability가 높은 경우, 또는 10% 미만의 attrition rates일 때 프로그램 효과도 (effect size)가 더 높게 나타났다. 3. 프로그램 실행 시 또래 리더를 사용하였을 경우, 알코올 등 다른 약물을 배제한 담배만을 중점적으로 다루었을 경우, 적어도 10회 이상 연속적으로 이루어지거나 프로그램 종료 후 일년 뒤에 추가 프로그램이 주어진 경우가 더욱 효과적이었다.

Abstract ▼ AI-Helper

Adolescent psychosocial smoking prevention programs have been successful, but limited in the magnitude of program effects. The present study is the secondary analysis after the previous study estimated mean effect sizes in smoking knowledge, attitudes, skills, and behaviors with treatment variables. Regardless of overall program effect estimations that other meta.analysis studies have done, this study is conducted to identify explanatory variables that are likely to increase program effects. A decrease of adolescent smoking behaviors is associated with the following factors: a. Younger students ($5^{th}-7^{th}$) than older students ($8^{th}-12^{th}$). b. Research methodology using true experimental design, quasi experimental design with equivalence between groups, use of random assignment, 10% or less attrition rate, use of a no treatment control group, high implementation fidelity, and/or acceptable instrumentation reliability. c. Programs using trained peer leaders, targeting cigarette smoking only, implementing 10 or more treatment sessions and/ or providing booster sessions.

주제어

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제안 방법

Based on previous research on smoking prevention and meta-analysis studies, the variables thought to be potentially related to study results were extracted and coded in considerable numbers. Explanatory variables measured in this study with four categories - demographic, research quality, implementation, and ecological factors.
8%) - a Type III error (Scanlon et al, 1977). Finally, effect sizes were estimated by these seven methodological problems to determine if the magnitude of effect sizes were affected by those factors (Table 2).
They included non-random assignment, baseline non-equivalence, unit of analysis problem, failure to consider the impact of attrition on program outcome, absent or low instrument reliability, self-reported data only problem, and low or unknown implementation fidelity. Second, the problems that typically occurred in the research were examined to discover their prevalence among the studies in this meta-analysis. As shown in Table 2, the self-reported data only problem (20.
The main purpose of this study was not to summarize the results of adolescent psychosocial smoking prevention programs (treatment variable) evaluated between 1978 and 1997, but to identify the program characteristics (explanatory variable) that influence smoking behavior outcomes and estimate how much they modify program effects.
The objectives and methods of this meta-analysis are distinctive from other meta-analysis studies that summarized quantitative findings of a body of empirical research by averaging program effect sizes. This study attempted to determine the source of differences in adolescent psychosocial smoking prevention study findings that represent modest levels of program effects or mixed results in reducing adolescent smoking behaviors in the US. The variation in effect sizes across studies was examined by specific study characteristics, including demographic, research quality, implementation, and ecological factors.
This meta-analysis study is the secondary analysis after the previous study estimated mean effect sizes in smoking knowledge, attitudes, skills, and behaviors with treatment variables. To identify explanatory variables that are likely to increase program effects the author inputs demographic characteristics of program participants, research methodologies used in individual studies, and program variation factors related to ecology and implementation. The findings of the analysis recommend practical guidelines for smoking prevention efforts.
12 for less than 10 sessions (<10 sessions). Treatment period was separately calculated by counting only weekdays (i.e. 5 days per week, 20 days per month), thus converting both the number of treatment sessions and the intensity level to one figure. Treatment periods of 40 days or shorter (<=40 days) had a low effect size of .

대상 데이터

The program leaders investigated in this meta-analysis included peer leaders, peer assistants, teachers, and program staff. Even though the effect sizes were not noticeably different among program leaders, the use of peer leaders was the most effective for overall smoking behavior.

이론/모형

The present meta-analysis found that focused (including only tobacco topics) and intense smoking prevention programs produced higher effects in deterring smoking behaviors. The study results are consistent with Tobler’s (1997) finding of higher effects with cigarette-only programs, and Glynn (1989) and Dusenbury’s (1997) guidelines of at least 10 or more treatment sessions for school-based smoking (drug abuse) prevention strategies.

성능/효과

The smoking behavior effect sizes were re-estimated by categorizing same-aged peer leaders, older-aged peer leaders using high school students in middle school settings, and older-aged peer leaders using college students in high school settings. A conclusion was made that the successful use of peers in the delivery of smoking prevention programs should be primarily led by peers who are same-aged peers or older-aged high school students.
Tobler (1997), on the other hand, analyzed using the number of students that were defined small sample as 20 to 400 youths and large sample as 401 to 4000 youths. Her study results were consistent with current study findings in the direction of effect variations (the smaller number of units; the larger effect sizes), but her effect sizes were more inflated than the present study. The magnitude of effect size was .
In overall program/ or project names, the Life Skills Training (LST) program revealed the highest effect size (.44) and the programs representing medium effects (effect size is .20 to 49) included LST, TAPP, MPP, RASP, MHHP, CLASP, NTE, SHOUT, and PMH for short-term smoking behavior.
The systematic coding of study characteristics permits an analytically precise examination of the relationships between study findings and such study features as respondent characteristics, nature of treatment, research design, and measurement procedures (Lipsy and Wilson 2001). One hundred forty-six variables per program were sorted by six categories regarding demographic characteristics, research methodology, modality, program variation, outcome assessment, and effect sizes (A code book and its descriptions can be requested from the author). Since not every study provided sufficient information to calculate effect sizes, primary researchers were contacted for the missing data on their published articles.
The differences in effect sizes between problem and no-problem subgroups indicated the degree to which the methodological problem affected the magnitude of effect sizes. Possible methodological problems affecting the magnitude of effect sizes for short-term smoking behavior were implementation fidelity, instrument reliability, pretest equivalence, attrition, and random assignment, in order from the largest difference between the subgroups. This order was also compatible with the prevalence of methodological problems except for the unit of analysis problem.
Weighted mean effect sizes were estimated to determine whether adolescent smoking behavior was influenced by the characteristics of program participants that included geographic location, social economic status, gender, predominant ethnicity, grade, and school type. Only one demographic characteristic, grade level, demonstrated an important difference in the magnitude of effect size.

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