Quality of life and health-risk behaviors among adolescents

Quality of life and health-risk behaviors among adolescents

JOURNAL OF ADOLESCENT HEALTH 2001;29:426– 435 ORIGINAL ARTICLE Quality of Life and Health-Risk Behaviors Among Adolescents TARI D. TOPOLSKI, Ph.D., ...

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Quality of Life and Health-Risk Behaviors Among Adolescents TARI D. TOPOLSKI, Ph.D., DONALD L. PATRICK, Ph.D., M.S.P.H., TODD C. EDWARDS, Ph.D., COLLEEN E. HUEBNER, Ph.D., FREDERICK A. CONNELL, M.D., AND K. KIOMI MOUNT, M.S.W.

Purpose: To assess the association between health-risk behaviors and self-perceived quality of life among adolescents Methods: A sample of 2801 students (957 seventh and eighth graders and 1844 ninth through twelfth graders) completed the Teen Assessment Survey (TAP) and the surveillance module of the Youth Quality of Life Instrument (YQOL-S). TAP responses were used to determine health-risks related to tobacco use, alcohol use, illicit drug use, and high risk sexual behavior. Separate multivariate analyses of variance showed mean differences in contextual and perceptual items of the YQOL-S for each health-risk behavior. Differences among engagers (adolescents who often engage), experimenters (occasionally engage), and abstainers (never engage) in the health-risk behavior were evaluated by gender and junior/senior high school groups. Results: In general, adolescent abstainers reported higher quality of life (QoL) than engagers and experimenters on YQOL-S items. Adolescents who engaged in multiple risk behaviors scored even lower than those who engaged in only one health-risk behavior. Experimenters tended to rate their QoL more similar to that of abstainers than to that of engagers. Conclusions: The framework of QoL proved useful in the evaluation of adolescents’ engagement in health-risk behaviors. Additionally, assessing the areas of QoL that From the Department of Health Services, University of Washington, Seattle, Washington Address correspondence to: Tari D. Topolski, University of Washington, Department of Health Services, Box 358852, Seattle, Washington 98195-7660. E-mail: [email protected] Address requests for Youth Quality of Life Instrument to: Donald L. Patrick, University of Washington, Department of Health Services, Box 358852, Seattle, Washington 98195-7660. Email: [email protected] edu. Manuscript accepted June 20, 2001 1054-139X/01/$–see front matter PII S1054-139X(01)00305-6

differ between the groups may provide information for planning interventions aimed at risk reduction among engagers and experimenters. © Society for Adolescent Medicine, 2001 KEY WORDS:

Risk factors Adolescence Risk-taking Smoking Drug use Quality of life Sexual behavior Alcohol drinking

The use and misuse of alcohol, drugs, and sexual behavior are common and contribute to the leading causes of morbidity, mortality, and social problems among youth in the United States [1]. The 1999 Youth Risk Behavior Surveillance System (YRBSS) revealed that nationwide 16.8% of the students surveyed reported frequent use (i.e., ⱖ20 of the preceding 30 days) of cigarettes; 31.5% reported consuming five or more drinks of alcohol on one or more occasions; 26.7% reported using marijuana one or more times; and 36.3% of students had engaged in sexual intercourse in the 3 months preceding the survey [1]. A major goal of United States health policy, reflected in Healthy People 2010, is to increase the percentage of adolescents who reach adulthood without having used tobacco, illicit drugs, or alcohol [2]. Better understanding of risk behaviors among adolescents is important to improving the current and future health of the U.S. population.

© Society for Adolescent Medicine, 2001 Published by Elsevier Science Inc., 655 Avenue of the Americas, New York, NY 10010

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Three major methodological approaches have been used to examine correlates of health-risk behaviors [3]. The first identifies risk factors and risk markers associated with these behaviors, such as environmental factors, demographic characteristics, and psychosocial elements. For example, unsafe sexual behavior frequently has been associated with peer affiliations, personality, and family dysfunction [4 – 6]. Male students are more likely than female students to have used cocaine, smokeless tobacco, alcohol, and marijuana [1]. Adolescents who smoke are more likely to report feelings of depression, suicidal thoughts, dislike of school, and pressure to be sexually active [7,8 –11]. Substance abuse has been correlated with emotional distress [12], low levels of academic achievement [13], and antisocial behavior [14]. The second approach examines the progression of health-risk behaviors, suggesting that engagement in one health-risk behavior can lead to other health compromising behaviors. Thus, early intervention may reduce the likelihood of involvement in future health-risk behaviors [15]. The third approach focuses on the interrelationship of health-risk behaviors, or the co-occurrence of multiple risk behaviors [7]. Adolescents who smoke are more likely to use illicit drugs and alcohol, to be sexually active, to engage in fights, and to carry a weapon [11,16 –19]. Sexually active teenagers report higher rates of alcohol use and misuse than teenagers who are not sexually active [20,21]. Developmental psychological theories have sought to explain who is most likely to initiate health-risk behaviors. These theories have focused on: risk-taking as normal behavior, psychological correlates such as low self-esteem, and contextual factors including peers and neighborhood influences. Quality of life (QoL) may be a useful framework for integrating these internal and external influences from the perspective of the individual. Specifically, as defined by The World Health Organization, QoL is “an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concerns . . . Thus, QoL is a broad ranging concept affected in complex ways by the person’s physical health, psychological state, level of independence, social relationships, and the person’s relationships to salient features of the environment.” [22,23]. Although interest in measuring the QoL of adolescents has increased in recent years [24,25], few investigations of adolescent health-risk behavior



have considered both positive and negative aspects in the context of adolescents’ overall perception of life. Most research takes a predominately deficitoriented view of adolescent behavior [3,4,7,26]. The YQOL instruments provide the means by which to measure both positive and negative aspects of adolescents lives providing an overall evaluation that includes both environmental and individual aspects of life. They can, therefore, expand the perimeters of current health-risk behavior research. By including adolescents’ overall perceptions of their lives, as well as a range of verifiable individual and contextual characteristics, a more comprehensive understanding of health-risk behaviors may emerge. Health-risk behaviors may in part reflect a normative stage of adolescent development, where health choices are another example of growing independence characterized by trying on adult roles and behaviors [27,28]. Absence of health-risk behaviors, however, is not equivalent to health and overall well-being [29]. Recent studies of adolescent abstinence, experimentation, and frequent use of alcohol, tobacco, and other drugs, have shown that experimentation does not necessarily lead to maladjustment [30]. Moreover, abstainers and “experimenters” have been found to be more similar to each other than frequent substance users [3]. Self-evaluated QoL could potentially identify which adolescents are most likely to develop longterm patterns of poor health behavior and which escape these habits. The present study investigated the association between self-reported engagement in health-risk behaviors and self-reported QoL among junior high and high school students. We hypothesized, a priori, that adolescents who abstained or adolescents who reported only occasional experimentation with the behavior would have a higher QoL than adolescents who engaged (i.e., misused or abused) in health-risk behaviors. Additionally, we hypothesized that adolescents who engaged in two or more health-risk behaviors would report lower QoL scores than adolescents who engaged in one health-risk behavior.

Methods Sample Data were collected from March through May, 1998, as a part of the Teen Assessment Project (TAP). They have been collected biannually since 1994. TAP [31] was developed to help communities identify, prevent, and begin to solve youth problems. It involves



administering a questionnaire to local teens about their concerns, behaviors, and perceptions [32]. The community involved in the present study was a rural county in Oregon along with two schools in northern California. The TAP survey was sponsored by a coalition of community groups and administered by RMC Research Corporation of Portland, Oregon. In this predominantly lower middle-class community the median household income for the county was $23,054 in 1989 dollars, and 18.5% of persons 18 years and older held an associate’s, bachelor’s, graduate, or professional degree. Thirty-seven percent of the county’s population resided in rural areas, and the majority resided in or around the urban core [33]. Seven out of 10 potential schools in the county provided usable data. The northern California area was also a lower middle-class rural community. One middle school and one high school in this community participated. Principals in all participating schools obtained passive consent from parents, and community volunteers administered the self-completed survey to students during a regular class period. It is estimated that over 70% of eligible students enrolled in the schools participated in the survey (RMC Research Corporation, personal communication, 1999). The percentage of participation was calculated by dividing the total number of participants by the total school district enrollment for that year. Total school district enrollment was obtained by adding each school’s official enrollment for that school year. Survey data were collected from 957 seventh and eighth grade students (across 8 schools), and 1809 ninth to twelfth grade students (across 9 schools).

Instruments The 1998 TAP survey questions assessed the use of tobacco, alcohol, and drugs by asking how often the student used the substance. The rating choices were: (a) “never,” (b) “once or twice,” (c) “sometimes”, and (d) “often.” Sexual activity and engagement in unsafe sex were assessed by a series of questions regarding frequency of sexual intercourse, number of partners, condom use, and whether they had been or had gotten someone pregnant. Answers to these items were used to construct three groups: “Abstainers,” “Experimenters,” and “Engagers.” “Abstainers” were students who never endorsed any high risk behavior. “Experimenters” were those who reported “once or twice” or “sometimes,” whereas “Engagers” were those who reported “often” on one


or more behavior (drug use, alcohol use, or tobacco use). The Youth Quality of Life Instrument — Surveillance Version [34] (YQOL-S) was added to the end of the 65-item TAP survey. The YQOL-S is a 10-item instrument that assesses important areas of young people’s lives as previously defined by adolescents (age 12 to 18 years), their parents, and their teachers and health care providers [35]. Item content reflects family interactions, support from adults, activities missed because of physical and emotional problems, feelings of self-esteem, concerns about the future, and a rating of their life compared to others. The 10 items are divided into five contextual, or extrinsic, questions about the adolescent’s social and personal environment, and five perceptual, or intrinsic questions. Adolescents respond to the contextual items using a five-category Likert frequency scale and to the perceptual items on an 11-point rating scale anchored from “not at all” to “completely.” Items of YQOL-S were chosen from the longer Youth Quality of Life Instrument — Research Version (YQOL-R) as single-item indicators of self-reported adolescent QoL. Table 1 contains the 10 items organized by contextual and perceptual categories. All contextual items, with the exception of item 2 “having a conversation with an adult,” are reverse scored so that a higher score indicates a higher QoL for all items. Surveillance (10 items) and research (78 items) versions of the instrument are available from the authors (contact information listed on first page of this article). Psychometric analyses were conducted to assess floor and ceiling effects, and inter-item correlations [37]. Items that are highly correlated to each other (e.g. r ⬎ .70) are generally considered to be overlapping or redundant [36]. None of the item-pairs yielded a Pearson r above .70, therefore individual items were used in the analyses. One descriptive item “missed activity” showed floor effects with 75.6% of responses in the “never” category. This was not an unexpected finding within a heterogeneous sample such as this because the question was designed to permit comparisons between adolescents with and without chronic illness or disability. The preliminary validation of the YQOL-R perceptual module yielded scores with acceptable internal consistency (␣ ⫽ .77 to .96), reproducibility (ICCs ⫽ .74 to .85), expected associations with other measured concepts, and the ability to distinguish among known groups [34]. Moreover, the Pearson correlation between the total perceptual score on the YQOL-R and the total perceptual score on the

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Table 1. YQOL-S Contextual and Perceptual Items YQOL-S Contextual Items [Response options: Never, Almost Never, Sometimes, Fairly Often, Very Often] 1) During the past month, how often did you miss out on an activity that you wanted to do because of any physical or emotional problem you have? 2) During the past month how often did you have a conversation with an adult about something that is important to you? 3) During the past month, how often have people your age made you feel unwelcome because of how you look? 4) During the past month, how often have any of your family members had serious arguments with one another? 5) During the past month, how often did you feel that you could not shake off the blues, even with help from your family and friends? YQOL-S Perceptual Items [Response Options 10 point scale anchors: Not at all (0) to Completely (10)] 6) I feel I am getting along with my parents or guardians 7) I look forward to the future 8) I feel alone in my life 9) I feel good about myself 10) Compared to others my age, I feel my life is. . .[anchors: Much Worse than Others (0) to Much Better than Others (10)]

YQOL-S is r ⫽ .86, suggesting that both instruments are measuring the same concept.

Data Management and Analyses Because of technical problems in administration, perceptual items were available from only 31% of the junior high school students and 42% of the senior high school student (n ⫽ 1073). Chi-square tests compared those with and without missing data on the relevant proportions for gender, race, and ethnicity. The results showed no significant differences between the two groups on these demographic variables. Before subsequent analyses, the data were screened for inconsistencies in reporting and outliers. The criterion used to define students as “unreliable” was an affirmative answer to all questions regarding a list of chronic health conditions because it was highly unlikely that any individual would have all the conditions. Twenty-seven individuals gave responses that fit this criterion and were, therefore, excluded from the analyses. No outliers were found in the data. The data were screened for departures from normality. Two variables “made to feel unwelcome because of how you look” and “missed out on an activity due to physical or emotional health” were slightly skewed in this general population. Transformation of the variables did not significantly improve the skewness. Therefore, the original variables were retained for analysis. Because of questionnaire formatting constraints in the TAP survey, the YQOL-S perceptual items were re-formatted from 11-point to 10-point scales. All

items were transformed to T-scores so that the scores reflect the percentage based on a 100 point scale.

Obtained Score—Lowest possible score ⴱ 100 Range

A multivariate approach was used to evaluate mean differences in the five YQOL-S contextual and the five YQOL-S perceptual items separately. A 3 ⫻ 2 ⫻ 2 MANOVA design was employed in each of the analyses assessing differences in QoL by health-risk behavior group (classified as engagers, experimenters, and abstainers in the health-risk behavior), gender and age group (junior vs. senior high). Finally, contrast analyses were conducted to evaluate the hypothesis that QoL among the engagers would be significantly lower than that of the abstainers. Because the subgroups differed in size and observed variances, Dunnett’s T3 Studentized range test for unequal variances was employed. Additionally, to account for the relatively large number of factors as well as the number of hypothesized comparisons the alpha level was set at .008.

Results Demographics Forty-eight percent of respondents were female; 71% white (not Hispanic); 10% Hispanic; and 19% other ethnic groups (not Hispanic) including 5% Native American (see Table 2). The ethnicity of the sample differs somewhat from the 1999 county census for this age group, which indicated that 94% of the population were white, 8.2% were Hispanic (any race), 4.2% were native Americans, and .9% were




Table 2. Demographic Characteristics of the Sample Characteristic Female Living with both natural parents Ethnicity White Hispanic Native American Mixed/Other Missing

Junior High (n ⫽ 957) %

Senior High (n ⫽ 1809) %

Total (n ⫽ 2801) %

47.6 56.6

49.1 56.6

48.2 56.2

69.8 11.5 5.7 10.0 3.0

72.9 8.7 5.1 11.6 1.7

71.2 9.6 5.4 11.0 2.8

black. In the census data, white includes Hispanic, which in part may account for the difference observed in these data. Within the sample, a Chi-square test showed that there were no significant differences in the proportion of males and females or the proportion in each ethnicity group in the junior and senior high age groups.

perimenter,” or “engager.” Looking separately at each behavior, 18% of the students reported using tobacco products “often,” 17% reported drinking “often,” 13% reported using drugs “often,” and 9% reported engaging in sexually risky behavior. Of the engagers, 62% met criteria as an engager in two or more behaviors, and approximately 10% of the sample endorsed “often” for all risk behaviors. A 30% decline in abstinence across all behaviors from 7th to 12th grades was observed, and with the exception of alcohol use, 12th grade students were twice as likely as 7th grade students to report experimenting with the behavior in question. The proportion of males and females among “engagers,” “experimenters,” and “abstainers” was approximately equal (51% male 49% female) for each of the health-risk behavior groups. For drug use and in sexually risky behavior, however, there was a slightly higher proportion (59%) of males in the engager group. The sample composition by riskbehavior group, gender, and age category is shown in Table 3.

Health-Risk Behaviors Overall, 68% of the students reported that they either experimented (37% reported at least one occasion) or engaged (31% reported often) in at least one of the four included health-risk behaviors. Only 21% of all the students reported they had never tried any of the behaviors in question; these students constituted the abstainer group. Data were missing for 11% of the sample on one or more of the risk behavior variables, precluding their classification as an “abstainer,” “ex-

Mean Group Differences Multivariate analysis of variance was performed on the contextual and perceptual sections of the YQOL-S separately using SPSS MANOVA. Because sample sizes and variances differed for each health behavior group, Pillai trace statistic was used to assess multivariate significance [37]. Significant main effects were found between the vector of means on

Table 3. Sample Composition by Health-Risk Behavior, Grade, and Gender Junior High Male Behavior Tobacco Abstainer Experimenter Engager Alcohol Abstainer Experimenter Engager Illicit drugs Abstainer Experimenter Engager Sexual risk Abstainer Experimenter Engager

Senior High Female


Total Female











307 132 43

63.7 27.4 8.9

262 136 51

58.4 30.3 11.4

346 340 226

37.9 37.3 24.8

388 318 184

43.6 35.7 20.7

1303 926 504

47.7 33.9 18.4

218 228 48

44.1 46.2 9.7

177 236 43

38.8 51.8 9.4

208 494 220

22.6 53.6 23.9

194 541 159

21.7 60.5 17.8

797 1499 470

28.8 54.2 17.0

298 134 46

62.3 28.0 9.6

264 146 30

60.0 33.2 6.8

297 440 162

33.0 48.9 18.0

309 464 109

35.0 52.6 12.4

1168 1184 347

43.3 43.9 12.9

370 28 31

86.2 6.5 7.2

380 23 13

91.3 5.5 3.1

489 109 112

68.9 15.4 15.8

503 118 93

70.4 16.5 13.0

1742 278 249

76.8 12.3 11.0

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the set of YQOL-S items for gender, age group, and health-risk behavior group on the contextual items. Main effects were also found for health-risk behavior group and gender on the perceptual items (p ⬍ .008). No significant interaction effects were found. Univariate results were examined to aid the interpretation of the multivariate findings. On the contextual items, males reported fewer family arguments (meanmales ⫽ 77.6; meanfemales ⫽ 68.8), and greater ability to shake off the blues (meanmales ⫽ 83.9; meanfemales ⫽ 71.9). In contrast, more females reported having a conversation with an adult (meanfemales ⫽ 52.2; meanmales ⫽ 36.5), than males. On the perceptual items only one item showed a significant mean difference; males reported feeling good about themselves more often than did females (meanmales ⫽ 78.4; meanfemales ⫽ 71.4). The univariate results for grade in school showed that junior high school students reported significantly fewer conversations with adults (meanjunior high ⫽ 38.15; meansenior high ⫽ 47.48). Junior high school students also reported fewer serious family arguments (meanjunior high ⫽ 79.92; meansenior high ⫽ 69.91; p ⫽ .012) and feeling more unwelcome because of how they look (meanjunior high ⫽ 8.74; meansenior high ⫽ 82.47; p ⫽ .017). Although these comparisons were statistically significant at the p ⫽ .05, they did not meet the more stringent criteria of p ⫽ .008. Contrast Analyses Dunnett’s T3 contrast analyses were conducted to examine the hypothesis that abstainers would report higher QoL scores than engagers in healthrisk behaviors. Means for the contextual and perceptual items by health-risk behavior group are presented in Table 4. In general our hypothesis was confirmed, abstainers reported higher QoL scores than engagers across all behaviors. On five items (family argue, blues, get along parents, good about self and life is. . .) abstainers scored significantly higher than either experimenters or engagers in tobacco, alcohol or illicit drugs. The pattern of results was more complex for sexually risky behavior and for items tapping depressive symptoms and social isolation. Within the sexual risk group, experimenters reported significantly higher scores for having a conversation with an adult about something important to them more often than either engagers or abstainers and felt less unwelcome because of how they looked than did engagers. Additionally, experimenters in the sexual risk group reported being less lonely than



either the engagers or the abstainers; however, only the difference between experimenters and engagers was significant. In the illicit drug use group, experimenters reported feeling significantly less alone in life than abstainers. Unlike illicit drugs and sexually risky behavior, tobacco and alcohol use did not differentiate adolescents who reported having a conversation with an adult about important issues. Although the mean score for tobacco use engagers was significantly different from both abstainers and experimenters at the p ⫽ .05 level for feeling unwelcome because of how they looked and lower than abstainers for alcohol use the difference did not meet our more stringent p ⫽ .008 criterion. Comparison of the experimenters with the other groups showed that their scores resembled abstainers more on missing an activity, having a conversation with an adult, and feeling unwelcome because of how they looked. Experimenters scores were intermediate to abstainers and engagers on family arguments.

Multiple Risk Behaviors Analyses Contrast analyses were conducted to evaluate the hypothesis that adolescents who engaged in two or more health-risk behaviors would score significantly lower on the YQOL-S items than those who engaged in only one behavior (Table 5). This was true for two contextual items (family argues and blues) and for four perceptual items (get along parents, forward to future, good about self, and life is. . .). The only perceptual item that did not differentiate the groups was “I feel alone in life.”

Discussion The integrated framework of QoL was used to evaluate aspects of developmental theories of health-risk behavior among adolescents. Specifically, the QoL concept was used to look at differences among adolescent abstainers, experimenters and engagers in health-risk behaviors. Developmental theories of risk-taking behavior suggest that experimentation with health-risk behaviors is typical of adolescence [14]. Behaviors that are considered risky at age 12 years such as tobacco or alcohol use, may be common by age 18 years [32]. Thus, an increase in engagement in health-risk behaviors from 8th to 12th grades should be observed. In the present study, a




Table 4. Mean Contextual and Perceptual Item Scoresd by Health-Risk Behavior Group and Type of Risk

Missed activity Abstainer Experimenter Engager Conversation adult Abstainer Experimenter Engager Feel unwelcome Abstainer Experimenter Engager Family argue Abstainer Experimenter Engager Blues Abstainer Experimenter Engager Get along parents Abstainer Experimenter Engager Forward to future Abstainer Experimenter Engager Alone in life Abstainer Experimenter Engager Feel good about self Abstainer Experimenter Engager Feel life is. . . Abstainer Experimenter Engager

Tobacco Mean (SD)

Alcohol Mean (SD)

Illicit Drugs Mean (SD)

Sexual Risk Mean (SD)

91.42c (19.39) 89.89c (20.60) 84.48a,b (28.10)

91.87b,c (19.26) 89.80a,c (20.89) 85.28a,b (27.58)

92.32b,c (18.59) 89.27a,c (20.93) 80.94a,b (31.67)

90.92c (19.74) 90.25c (19.29) 81.99a,b (32.45)

44.94 44.65 42.27

(33.73) (32.86) (34.72)

45.57 45.23 39.54

(33.59) (32.86) (35.61)

44.64 (33.31) 45.53c (33.09) 38.63b (36.18)

44.26b (32.97) 51.45a,c (33.75) 38.21b (35.47)

82.93 82.51 78.10

(27.27) (27.86) (32.09)

83.09 82.20 78.91

(27.85) (27.31) (32.61)

83.65c (26.72) 82.29c (27.66) 74.67a,b (35.71)

82.56 (27.21) 84.56c (27.28) 75.44b (35.51)

80.84b,c (26.74) 69.27a,c (33.30) 60.38a,b (36.80)

82.23b,c (26.68) 72.73a,c (30.84) 59.52a,b (38.35)

81.61b,c (26.69) 69.45a,c (32.18) 57.61a,b (39.64)

76.99c (29.48) 71.04c (32.67) 59.61a,b (38.62)

82.66b,c (28.39) 77.81a,c (30.46) 65.58a,b (36.30)

85.75b,c (25.87) 76.06a (31.60) 70.56a (35.57)

85.74b,c (25.43) 73.51a (32.36) 67.31a (38.20)

80.80c (29.20) 75.0c (33.31) 66.59a,b (36.69)

81.0b,c (28.25) 71.50a,c (29.03) 60.74a,b (34.03)

81.89b,c (28.44) 74.92a,c (27.91) 59.64a,b (35.46)

81.77b,c (27.38) 72.63a,c (27.98) 54.56a,b (37.51)

77.03c (29.23) 75.54c (26.34) 59.37a,b (37.58)

87.44c (22.96) 82.33c (27.18) 73.24a,b (34.38)

87.17c (22.90) 84.56c (25.48) 72.71a,b (34.80)

88.03c (21.42) 83.79c (25.08) 65.03a,b (40.33)

85.88c (23.66) 85.25c (25.72) 66.14a,b (38.81)

74.56c (32.32) 67.99c (33.01) 62.98a,b (35.42)

75.54b (32.40) 67.80a (33.11) 68.84 (35.00)

74.37b (32.68) 66.38a (33.18) 69.23 (35.25)

71.58 (32.50) 76.94c (30.69) 60.21b (37.83)

81.02b,c (25.45) 73.46a,c (26.64) 65.06a,b (33.02)

83.49b,c (24.25) 74.62a,c (26.41) 65.99a,b (33.66)

81.72b,c (24.31) 73.69a,c (26.44) 61.61a,b (36.74)

77.88c (26.20) 74.79 (28.04) 64.87a (33.97)

76.94b,c (24.30) 71.39a,c (24.57) 62.55a,b (30.95)

78.38b,c (23.91) 72.41a,c (24.38) 63.51a,b (31.55)

78.43b,c (23.00) 70.39a,c (24.39) 59.69a,b (34.69)

74.44c (24.51) 76.66c (22.15) 64.02a,b (32.96)


Differs from abstainers. Differs from experimenters. c Differs from engagers. d All scores are on a 100 point scale. Some items were reverse scored so that on all variables a higher score represents a positive expression of Quality of Life. b

30% decline in abstinence across all behaviors from 7th to 12th grade was observed. With the exception of alcohol use, 12th grade students were twice as likely as 7th grade students to report experimenting with the behavior in question. Compared to abstainers, both engagers and experimenters were less likely to get along with their parents. These findings are consistent with those of a recent study of the relationship between family factors and adolescent substance use which found a

significantly lower involvement with substances among adolescents who perceived that their families “cared” or would “stop them” if they got drunk, used drugs, or smoked cigarettes [38]. Abstainers and experimenters were similar in that they rarely reported feeling unwelcome because of how they looked, and both reported high levels of looking forward to the future. In contrast, engagers were more likely to feel unwelcome because of how they looked, and less likely to look forward to the

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Table 5. Descriptive Statistics for Engagers in Multiple vs. Single Risk Behaviors Single Behavior (N ⫽ 799)

Multiple Behaviors (N ⫽ 573)






Missed activity Conversation adult Feel unwelcomeb Family argueb Bluesb

89.71 45.90 81.70 71.40 76.63

20.97 33.04 28.49 31.89 31.12

85.73 40.49 79.19 59.64 69.59

26.82 34.59 31.98 37.66 35.34

.01 .01 .35 .00 .00

Get along parents Forward to future Alone in lifeb Feel good about self Feel life is . . .

74.70 84.69 67.68 74.76 71.65

26.58 23.78 33.29 25.80 23.78

60.25 71.90 65.82 65.74 63.90

34.66 35.52 34.81 32.51 30.86

.00 .00 .87 .00 .002


(N ⫽ 339)

a b

(N ⫽ 289)

Alpha level set at .008 to control for multiple comparisons. Items are reverse scored so that a higher score represents a positive expression of Quality of Life.

future. It might be that these adolescents who engage in health-risk behaviors are not as concerned about how their current behavior will affect their future because they do not find the future promising. It is evident from these data that most adolescents are not talking with adults about issues that they consider important. Both experimenters and engagers report feeling less good about themselves and more alone in life than did abstainers, although interestingly the experimenters scored significantly higher than the engagers, suggesting that self-esteem may be an important factor in health-risk behavior. Additionally, engagers reported that their life was worse than others their age. The inability to shake off the blues even with the help from their friends suggests an association between depressive mood and health-risk behaviors. Involvement in one type of health-risk behavior has been shown to increase the likelihood of involvement in other health-risk behaviors [7,16,39]. Most adolescent engagers in our study engaged in more than one of the health risk behaviors. Moreover, there appears to be an association between the number of health risk behaviors and perceived QoL. Adolescents who reported engaging in more than one risk behavior were the lowest scoring group on all perceptual items except feeling alone in life. Also, they reported more family arguments than the other groups, and were less likely to be able to shake off the blues even with the help of their friends. These findings suggest that there may be cumulative/ transactional effects among health-risk behavior and QoL. Self-perceived QoL is a valuable, measurable con-

cept that may help to evaluate teens at risk for long-term health problems associated with high-risk behaviors because it provides a framework for integrating multiple internal (e.g. self-esteem and social isolation) and external (e.g., peer and neighborhood influences) factors. For health providers and educators who want to know about high-risk health behaviors, QoL may be a more valuable way of identifying teens than direct questions about drugs, alcohol, and sex because it is less confrontational and less likely to yield socially acceptable responses. Additionally, the QoL framework provides important information about areas for potential intervention. Limitations Several limitations of this study should be considered. The conclusions are based on one rural area of the Pacific Northwest and may not generalize to other populations, and there is no report on the total population versus responders, which was not tracked in the school survey. In interpreting the results presented here it should be noted that some of the variation may been have lost by collapsing two of the response categories into one to create the risk-behavior groups. Likewise, it is unclear how missing data may have influenced the results. The students who did not provide data on the health risk-behaviors may have fallen disproportionately into one of the groups. Although there were no demographic differences between those who did and did not complete the perceptual items, there may have been differences on the YQOL-S items. Lastly,



the data are based on self-reports of adolescents collected at one point in time. The direction of causality between QoL and health-risk behavior remains to be elucidated. It is unclear whether lower QoL leads to engagement in health-risk behaviors, or whether engaging in healthrisk behaviors leads to lower QoL. It may be that poorer QoL leads to increased involvement in healthrisk behaviors. It is also possible that engaging in health-risk behaviors influences adolescent’s perceptions of their QoL which in turn affects behavior. The direction of causality awaits a longitudinal investigation. The YQOL-R version provides additional information on peer and family relationships as well as a more in-depth assessment of self, environment and general QoL. Thus, the integrated framework of QoL may provide the means to evaluate the cumulative/ transactional effects of these factors with health-risk behaviors. This research was supported by a cooperative agreement with the Centers for Disease Control and Prevention (#U48/CCU009654), and a grant awarded to the Klamath Tribes by the Substance Abuse and Mental Health Services Administration (#1 HD4 SP0770D).

References 1. Kann L, Kinchen SA, Williams BI, et al. Youth Risk Behavior Surveillance—United States, 1999. MMWR 2000; 49(SS-5):1– 94. 2. Healthy People 2010. 2000. Available at: http://www.health. gov/healthypeople/document. Accessed February 4, 2000. 3. Brener ND, Collins JL. Co-occurrence of health-risk behaviors among adolescents in the United States. J Adolesc Health 1998;22:209 –13. 4. Metzler CW, Noell J, Biglan A, et al. The social context for risky sexual behavior among adolescents. J Behav Med 1994; 17:419 –38. 5. Brooks-Gunn J, Furstenberg FF Jr. Adolescent sexual behavior. Am Psychol 1989;44:249 –57. 6. Hawkins JD, Catalano RF, Miller JY. Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychol Bull 1992;112:64 –105. 7. Biglan A, Metzler CW, Wirt R, et al. Social and behavioral factors associated with high-risk sexual behavior among adolescents. J Behav Med 1990;13:245– 61. 8. Malkin SA, Allen DL. Differential characteristics of adolescent smokers and non-smokers. J Fam Pract 1980;10:437– 40. 9. Abernathy TJ, Massad L, Romano DL. The relationship between smoking and self-esteem. Adolescence 1995;30:899 –907. 10. Patton GC, Hibbert M, Rosier MJ, et al. Is smoking associated with depression and anxiety in teenagers? Am J Public Health 1996;86:225–30. 11. Executive summary of the Surgeon General’s report: preventing tobacco use among young people. Oncology 1994;8, 16,19,46 passim.


12. Overholser JC, Freiheit SR, DiFilippo JM. Emotional distress and substance abuse as risk factors for suicide attempts. Can J Psychiatry 1997;42:402– 8. 13. Newcomb M, Earleywine M. Intrapersonal contributors to drug use: The willing host. Am Behav Sci 1996;39:823–37. 14. Taylor J, Carey G. Antisocial behavior, substance use and somatization in families of adolescent drug abusers and adolescent controls. Am J Drug Alcohol Abuse 1998;24:635– 46. 15. Warren CW, Kann L, Small ML, et al. Age of initiating selected health-risk behaviors among high school students in the United States. J Adolesc Health 1997;21:225–31. 16. Coogan PF, Adams M, Geller AC, et al. Factors associated with smoking among children and adolescents in Connecticut. Am J Prev Med 1998;15:17–24. 17. O’Malley PM, Johnston LD, Bachman JG. Alcohol use among adolescents. Alcohol Health Res World 1998;22:85–93. 18. Torabi MR, Bailey WJ, Majd Jabbari M. Cigarette smoking as a predictor of alcohol and other drug use by children and adolescents: evidence of the “gateway drug effect”. J Sch Health 1993;63:302– 6. 19. Escobedo LG, Reddy M, DuRant RH. Relationship between cigarette smoking and health risk and problem behaviors among US adolescents. Arch Pediatr Adolesc Med 1997;151: 66 –71. 20. Strunin L, Hingson R. Alcohol, drugs, and adolescent sexual behavior. Int J Addict 1992;27:129 – 46. 21. Orr DP, Beiter M, Ingersoll G. Premature sexual activity as an indicator of psychosocial risk. Pediatrics 1991;87:141–7. 22. The WHOQOL Group. The Development of the World Health Organization Quality of Life Assessment Instrument (the WHOQOL). In: Orley J, Kuyken W (eds). Quality of Life Assessment: International Perspectives. Berlin: Springer-Verlag, 1994:41–57. 23. Bonomi AE, Patrick DL, Bushnell DM, et al. Validation of the United States’ Version of the World Health Organization Quality of Life (WHOQOL) Measurement. J Clin Epidemiol 2000;53:1–12. 24. Bullinger M, Ravens-Sieberer U. General principles, methods and areas of application of quality of life research in children. Prax Kinderpsychol Kinderpsychiatr 1995;44:391–9. 25. Drotar D (ed). Measuring Health-related Quality of Life in Children and Adolescents: Implications for Research and Practice. Mahwah, NJ: Lawrence Erlbaum Associates, 1998. 26. Lifrak PD, McKay JR, Rostain A, et al. Relationship of perceived competencies, perceived social support, and gender to substance use in young adolescents. J Am Acad Child Adolesc Psychiatry 1997;36:933– 40. 27. Baumrind D. A developmental perspective on adolescent risk taking in contemporary America. In: Irwin, CE (ed). Adolescent Social Behavior and Health. New Directions for Child Development. Social and Behavioral Sciences Series, No. 37, Fall. San Francisco: Jossey Bass, 1987:93–125. 28. Igra V, Irwin CE. Theories of adolescent risk-taking behavior. In: DiClemente RJ, Hansen WB, Ponton LE (eds). Handbook of Adolescent Risk Behavior. New York: Plenum Press, 1996:35– 51. 29. Pal DK. Quality of life assessment in children: A review of conceptual and methodological issues in multidimensional health status measures. J Epidemiol Community Health 1996; 50:391– 6. 30. Shedler J, Block J. Adolescent drug use and psychological health: A longitudinal inquiry. Am Psychol 1990;45:612–30. 31. Small SA. Enhancing contexts of adolescent development: The role of community-based action research. In: Crockett LJ,

December 2001





Crouter AC (eds). Pathways Through Adolescence: Individual Development in Relation to Social Contexts. Mahwah, NJ: Lawrence Erlbaum Associates, 1995:211–33. Nelson S. Teen Assessment Project — Creating Community Awareness About Youth-at-risk. 1997. Available at: http:// www.cas.nercrd.psu.edu/Publications/followup_TAP.html. Accessed February 2, 2000. US Census Bureau State and County Quick Facts. 2000. Available at: www.census.gov/population/estimates/ county/crh/crhor99.txt. Accessed August 17, 2001. Patrick DL, Edwards TC, Topolski TD. Adolescent Quality of Life, Part II: Initial Validation of a New Instrument. J Adolescence 2001. In press. Edwards TC, Huebner CE, Connell FA, et al. Adolescent



37. 38.



Quality of Life, Part I: Conceptual and Measurement Framework. J Adolescence 2001. In press. Medical Outcomes Trust Scientific Advisory Committee Instrument Review Criteria. MOT Bulletin II: I-IV 1995. Boston: MOT Committee. Tabachnick BG, Fidell, LS. Using Multivariate Statistics, 2nd Edition. New York: Harper & Row, 1989:398 –9. Scheer SD, Borden LM, Donnermeyer JF. The relationship between family factors and adolescent substance use in rural, suburban and urban settings. J Child Family Studies 2000:105– 15. Perry CL, Staufacker MJ. Tobacco Use. In: DiClemente RJ, Hansen WB, Ponton LE (eds). Handbook of Adolescent Risk Behavior. New York: Plenum Press, 1996:53– 81.