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The adolescent health review: a brief, multidimensional screening instrument
JOURNAL OF ADOLESCENT HEALTH 2001;29:131–139
ORIGINAL ARTICLE
The Adolescent Health Review: A Brief, Multidimensional Screening Instrument PATRICIA A. HARRISON, Ph.D., TIMOTHY J. BEEBE, Ph.D., AND EUNKYUNG PARK, Ph.D.
Purpose: To develop a brief, multidimensional screening instrument for adolescents that addresses psychosocial domains critical to adolescent preventive health care services. Methods: Secondary analyses were conducted on survey data obtained in 1995 from a school sample of 76,159 students in grades 9 and 12, as well as 893 adolescents from juvenile correctional facilities, 500 adolescents from chemical dependency treatment programs, and 575 adolescents from residential behavioral treatment programs. A comprehensive set of 300 survey items was used in a series of discriminant analyses to determine which items best distinguished males and females in each clinical sample from their counterparts in the school sample. Results: The item selection for the Adolescent Health Review was guided both by empirical analyses and clinical judgment. The final screen is comprised of 33 demographic and clinical items that address a variety of psychosocial domains. The computerized, self-administered screen can be completed in about 3 minutes. The screen is scored automatically and produces an easy-toread risk-assessment profile. Because screening items were drawn from a large epidemiologic survey, normative profiles are available for each age and gender subgroup. Conclusions: A brief, empirically derived screening instrument, designed to address a range of adolescent risks, offers an opportunity for information gathering that otherwise might not be incorporated into routine clinic visits. © Society for Adolescent Medicine, 2001
From the Minnesota Department of Human Services, St. Paul, Minnesota. Address correspondence to: Dr. Patricia A Harrison, Minnesota Department of Human Services, 444 Lafayette Road, St. Paul, MN 55155-3865; E-mail: [email protected]. Manuscript accepted March 2, 2001.
KEY WORDS: Screening Adolescents Substance abuse Mental health Health risks Adolescent Health Review GAPS
Reducing morbidity and mortality among adolescents depends on early recognition and identification of health risks, most of which derive from social factors [1]. In fact, the 15- to 24-years age group is the only group in the United States for which the top three causes of death (accidents, homicide, and suicide) are all behavior-related; combined, they account for 75% of deaths, as well as 51% of deaths in the 5- to 14-years age group [2]. Substance abuse is believed to be a contributing factor in many adolescent deaths from unintentional or intentional injury [3,4]. In 1992, the American Medical Association issued Guidelines for Adolescent Preventive Services (GAPS) [1,5], a comprehensive set of recommendations that provides a framework for preventive health services to be delivered during annual health care visits. Similar guidelines have been developed by other national organizations, including the Maternal and Child Health Bureau’s “Bright Futures” [6], and all share significant emphasis on systematic screening for behavioral and psychosocial problems. Despite the widespread recognition that screening is critically important, physician surveys have found that most providers do not routinely screen adolescents for suicidal behavior and other risks [7,8]. One major barrier to screening during primary care encounters is the competing demands on physicians’
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time [9 –13]. Because unsafe sexual behavior, substance abuse, aggressive and delinquent behavior, mental health problems, and problems with family relationships frequently co-exist among adolescents [14 –18], the ideal screening procedure should entail a single instrument that is holistic [11,19]. Screening is distinct from assessment. The purpose of screening is to identify individuals who may be at risk for a particular problem and to rule out those who are not [20,21]. A comprehensive assessment needs to be conducted to determine whether and what type of intervention is appropriate. This two-stage process of screening and assessment can conserve limited medical resources while increasing the likelihood of detecting serious problems [22]. A review of existing adolescent screening instruments finds that they vary considerably in scope and length. Several multidimensional instruments have been developed, including the Drug Use Screening Inventory-Revised (DUSI-R) [23], the Juvenile Wellness and Health Survey (JWHS-76) [18], the ProblemOriented Screening Instrument for Teenagers (POSIT) [24], and the Youth Self Report (YSR) [25]. However, the drawback of all is their length (76 to 159 items); 20 to 40 minutes to administer is too long for most primary care encounters [26]. To facilitate the implementation of GAPS, a similarly comprehensive, although not empirically tested, patient questionnaire has been developed by the AMA for the adolescent’s initial preventive services visit [27]. Its length, however, makes it impractical for administration at other visits. Opportunities for screening could be increased if a practical, brief screening procedure were available for use during acute, as well as preventive, health care visits. Although shorter screening instruments for adolescents exist, their focus is typically narrow; they address only one or two domains, such as substance abuse [26,28 –32] or psychiatric symptoms [33]. In summary, existing multidimensional instruments are too long for routine use, and instruments that meet the test of brevity fail to address the requisite range of health-risk domains. Screening efforts could also be enhanced by the use of computer technology to facilitate administration, automate scoring, and produce an easy-to-read risk profile. To date, computer-administered questionnaires have been little explored as effective alternatives to paper-and-pencil screening instruments, despite their clear advantage with respect to the use of complex scoring algorithms [22]. Adolescents, in particular, appear to be attracted to computerized instruments [34,35], and hurried health care providers would
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likely welcome the immediate output of a concise summary highlighting critical concerns. This article describes the development of such a screening instrument, the Adolescent Health Review (AHR). The AHR addresses the objectives of multidimensionality, brevity, and automated reporting. In addition, it capitalizes on the availability of normative data from a statewide sample to assist health care providers in evaluating the deviation of behaviors from the norm for males and females in different stages of adolescence.
Methods Procedure To obtain a comprehensive portrait of at-risk youth, the State of Minnesota periodically administers a survey about risk behaviors to public school students as well as to adolescents in special settings who typically are not represented in school surveys. The analyses described in this report are based on secondary analyses of these survey data. The 1995 Minnesota Student Survey was administered in the spring of that year to 76,159 public school students in grades 9 and 12, representing 97% of the state’s school districts. Included in the sample were 75% of the 9th graders and 57% of the 12th graders enrolled at the start of the school year. (The lower participation rate for high school seniors results from a combination of factors, including shorter school days for students who have completed most of their credits, transfers to alternative education centers, attendance at post-secondary educational institutions, and dropout.) The survey was also administered to adolescents in three clinical settings: 893 adolescents in 20 juvenile correctional facilities (detention centers and longer-term residential facilities), 500 adolescents in 55 outpatient and inpatient chemical-dependency treatment programs, and 575 adolescents in 51 residential behavioral treatment programs (institutions and group homes). The survey respondents represented 85% to 96% of the adolescents in these facilities when the survey was administered. A passive parental consent procedure was used for students; the parental consent requirement was waived for the clinical samples with the approval of the Institutional Review Board of the Minnesota Department of Human Services. Respondent participation was voluntary and surveys were anonymous, coded only by site. The survey instrument included more than 117 questions (300 variables) addressing attitudinal, behavioral, and environmental issues. The substance
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use frequency items were in the Monitoring the Future survey format [36], and 15 items operationalized the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) substance use disorder diagnostic criteria [37]. Other content areas are described in greater detail elsewhere [38].
Sample The adolescents in the special settings constituted the three criterion groups against which the public school students were compared. Placement in a clinical setting was selected as the criterion used to assess “risk,” because admission to one of these settings represented a “real-world” determination that further assessment and/or intervention and treatment was appropriate. The problem severity among the criterion groups ranged considerably. For example, placement in a detention center frequently resulted from a status offense or other relatively minor offense, and stays typically averaged less than 2 weeks. In contrast, placement in residential correctional facilities was typically associated with serious offenses, such as auto theft, burglary, and weapons possession, and stays averaged 5 months. The extent of disorders among adolescents in substance abuse treatment centers ranged from a few, relatively mild symptoms of abuse to multiple, serious signs of dependence. Some adolescents in residential behavioral treatment facilities were in group homes that required no specialized diagnosis, and some were in facilities for individuals with severe emotional disturbance. Because the purpose of a brief screening instrument is to identify individuals who would benefit from a comprehensive assessment, using such varied samples as criterion groups would appear to have great utility.
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ences in group membership, net of the variables already in the model [39]. Differences in Wilks’ lambda determined which variables to include. The minimum probability of F for a variable to enter the model was set at .001, and the maximum probability that a variable could have and not be removed was set at .05. The maximum number of steps was 30. For questions that involved multiple response choices, each response choice was treated as a discrete variable and coded “yes/no.” Because gender distributions in the clinical populations varied considerably, and because different items might emerge for boys and girls, analyses were conducted separately for each gender. Thus, six separate analyses of the 300 survey items were conducted, each involving either boys or girls, one of the three clinical populations, and the combined 9th and 12th grade student sample. The GAPS domains provided the general structure, with some modifications. For example, the concept of family functioning was expanded to include the quality of interpersonal interactions, and the concept of emotional health was expanded to include anxiety as anxiety disorders are the most prevalent types of disorders among adolescents, more than twice as common as mood disorders [40]. For the sake of brevity, the decision was made at the outset to limit item selection to measures of the respondent’s behavior, feelings, and experiences. Other considerations for item reduction included a general preference for behavioral measures over attitudinal measures, preference for items that discriminated more than one clinical group, and preference for behaviors that were not exceedingly rare. Although the guiding principle for item selection was that the process be empirically driven, final decisions were also informed by these criteria and clinical judgment.
Results Statistical Analyses The primary objective of the AHR development was to make the screening tool multidimensional yet brief. Stepwise discriminant analysis was the statistical method chosen to identify potential screening items. Discriminant analysis is a statistical technique in which linear combinations of variables are used to distinguish between two or more categories of cases, and is a useful method to identify items which significantly discriminate a criterion group from a comparison group [39]. The stepwise method added variables individually in the order of their ability to maximize differ-
Most of the survey respondents were between the ages of 14 and 18 years (98% of the school sample and between 87% and 100% of the three clinical samples). The school sample was evenly distributed between males and females, but males predominated in the clinical settings (from 83% in correctional institutions to 62% to 63% in substance abuse and behavioral treatment settings). Screen Domains and Item Selection More than 60 items discriminated at least one clinical population from the school sample for at least one of
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the gender groups. However, 14 of these items were eliminated from further consideration because they did not fit one of the screen development selection criteria, leaving 46 individual items or item composites in the domains of interest. Of the 46 items/ composites, 25 significantly discriminated at least one sample of boys and one sample of girls, 13 significantly discriminated only boys, and 8 significantly discriminated only girls. These items, along with the clinical sample(s) discriminated by each item, are shown in Table 1. Some similar items are presented in composite form to preserve space. (Detailed statistical information, too lengthy to present here, is available from the authors.) The items are presented in the order in which the domains are sequenced in the AHR. The largest number (20) of discriminant items were related to tobacco, alcohol, or other drugs; eight items related to school; five related to abuse victimization; four related to emotional health or suicidal risk; four related to sexual behavior; two related to family functioning; two related to violent behavior; and one related to eating disorders. The paragraphs that follow describe the rationale for item retention/ omission and modification. Unhealthy weight control. The single discriminating item was related to taking diet pills to lose weight. However, to make the item more inclusive for the AHR, it was combined with another survey question on vomiting and use of laxatives. Family interaction problems. The two discriminating family-related items measured the extent to which adolescents believe that their family has fun together and that their parents care about them. Both were retained in the AHR. Problems at school. The school-related domain produced 8 discriminating variables. Among these items, only one (the perception of teachers’ interest in the adolescent) discriminated more than two of the six groups examined and was therefore selected for inclusion. The other seven items (truancy, feelings about school, academic aspirations, grades, reading difficulties, and placement in special classes) all discriminated two groups, but the truancy item was retained because it was the only behavioral measure. Emotional distress and suicidal behavior. Of the two discriminating emotional health variables, the one that discriminated three groups was retained (degree
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of feeling sad), and the one that discriminated only one group was eliminated (degree of satisfaction with personal life). In place of the latter, a nonempirically derived item addressing anxiety was added (“. . . have you felt nervous, worried or upset?”). Both of the suicidal behavior items (ideation and attempt) discriminated clinical samples and were retained. Violent behavior. Both items related to violent behavior (physical assaults and carrying a gun) were retained for the AHR. The gun question was combined with a similar survey question regarding other types of weapons and modified so as not to be restricted solely to school property. Physical/sexual abuse. The 5 items related to abuse victimization included physical abuse at home, extrafamilial sexual abuse, victim of date rape, victim of date violence, and having been stabbed or fired at by a student on school property. All were retained but the last item which was endorsed by fewer than 2% of the adolescents in the school survey. For the AHR, the question about extrafamilial sexual abuse was combined with a similar survey question about intrafamilial sexual abuse. The date rape and other date violence questions were also combined into a single question resulting in a 3-item domain. Sexual activity. The 4 items related to sexual behavior included age of first sexual intercourse, not using protection, having had a sexually transmitted disease, and having been pregnant/gotten someone pregnant. The 2 items included in the AHR were updated survey versions of the sexual intercourse and the protection questions. Substance use. The only tobacco use item (current cigarette smoking frequency) was retained. Alcohol and marijuana use frequency were retained, but similar questions for other drug categories were eliminated, partly for length and partly because use of these substances was relatively rare in the absence of alcohol and/or marijuana use, rendering them redundant for screening purposes. The typical alcohol quantity question was preferred for screening purposes over the 2-week binge question since it was not so severely restricted by recency. Further analyses and reviews were conducted to reduce number of diagnostic criterion and use pattern items. Correlation matrices were generated for males and females in the school sample. Only two of the diagnostic items (giving up activities related to
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Table 1. Survey Items That Significantly Discriminated Clinical Samples From the School Sample Clinical Setting Substance Abuse Treatment Survey Item *. . .take diet pills to lose weight. . .? *. . .family has lots of fun together? *. . .your parents care about you? *. . .teachers are interested in you. . .? . . .teachers show respect for students? *. . .how often have you skipped. . .school? How do you feel about going to school? Which. . .best describes your school plans? . . .reading skills. . .prevented you from keeping up. . .? . . .ever been in any classes for learning problems? . . .the two grades you get most often (Ds or Fs) *. . .have you felt sad? . . .how satisfied have you been with your personal life? *. . .had thoughts about killing/would like to kill myself *. . .ever tried to kill yourself *. . .have you tried or beat up another person? *. . .did you carry a gun on school property? *. . .adult in your household. . .hit you so hard or so often. . .? *. . .adult or older person. . .touched you sexually. . .? *. . .victim of violence on a date? *. . .victim of date rape? . . .a student stabbed or fired a gun at you. . .? *. . .had sexual intercourse (age of onset)? *. . .method. . .to prevent pregnancy and/or STDs? . . .told by a doctor or nurse that you had a STD. . .? . . .have you been pregnant or gotten someone pregnant? *. . .how frequently have you smoked cigarettes? *. . .have you had alcoholic beverages. . .? *. . .how much. . .do you drink at one time/5⫹ drinks in a row?a *. . .have you used marijuana. . .? . . .have you sniffed glue. . .or inhaled. . .? . . .have you used LSD. . .PCP, or other psychedelics. . .? . . .have you used “crack”. . .or cocaine in any other form. . .? . . .have you used steroids. . .? Have you ever used a needle to inject an illegal drug? . . .use. . .before. . .during (at). . .right after. . .school?a *. . .use. . .because I’m sad, lonely, or angry *. . .used so much. . .that you could not remember. . .? *. . .wanted to. . .or. . .tried to cut down. . .? *. . .use. . .hurt your relationships. . .? *. . .missed work or school because of. . .use? . . .given up activities like sports, work, school. . .to use. . .? . . .ever had an injury while using. . .? . . .had any other physical health problems. . .result of using? *. . .use. . .caused you problems with the law? *. . .hit anyone or become violent while using. . .?
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* Items introduced by an asterisk were retained for the Adolescent Health Review. a Represents a composite of several closely related variables. These items were combined merely for ease of presentation; the variables were entered individually in the discriminant function analyses.
use and job/school absenteeism) were moderately correlated (R ⫽ .49) and somewhat redundant in content. Prevalence rates for both items were fairly
comparable among the student population, and both typically occurred in the presence of at least five other diagnostic symptoms [37]. Therefore, only ab-
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senteeism was retained because it was the shorter of the two and easier to understand. Three other items from the substance use subset (injury, physical illness, and injection drug use) were dropped because their prevalence rate in the general population was 1% or less [37]. Items measuring use before, during, and after school were also eliminated owing to length considerations in favor of retaining the diagnostic items. This review/decision process reduced the tobacco/alcohol/drug subset of screening items to 11. They were divided into four domains: “cigarette smoking” (1 item), “alcohol use” (2 items), “marijuana use” (1 item), and “substance abuse/ dependence” (7 items). Additional screening items not derived from empirical analyses. Six additional items were added at the beginning of the AHR, including three demographic descriptors (gender, age, race). Because the instrument was designed for clinical, rather than school, settings an item was needed to determine whether adolescents were attending school, so the schoolrelated items could be scored properly. Two general health questions (exercise and nutrition) were included to serve as a transition to more sensitive items. The addition of these brief items resulted in a 33-item screening instrument. Computerized Scoring and Reporting The computerized scoring output for the AHR was designed to inform the health care provider whether the adolescent’s responses were indicative of “no risk,” “moderate risk,” or “high risk” in a given domain. Designation of “high risk” was limited to domains for which it was believed a referral to specialty behavioral health care might be required and for which there was perceived imminent risk to the adolescent’s health or well-being. Therefore, the maximum risk category for lack of exercise, poor nutrition, unhealthy weight control, family interaction problems, problems at school, and emotional distress was set at “moderate.” Suicidal behavior, violent behavior, sexual activity, cigarette smoking, alcohol use, marijuana use, substance abuse/dependence, and physical/sexual abuse were all potentially “high risk.” Risk thresholds were selected based on clinical judgment, prevalence data, or a combination of these factors. Clinical judgment was the sole determinant for clinically significant problems (such as violent behavior or substance abuse). However, for areas for which risk is less clear-cut, such as family interaction
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problems or problems at school, the thresholds were selected rather conservatively to identify only a relatively small proportion of adolescents (generally less than 20%) with the most problematic responses. The frequency and types of behaviors used as cut points for some risk thresholds were age-specific (e.g., sexual activity, cigarette smoking, alcohol use, marijuana use, substance abuse/dependence) because these behaviors increase in prevalence with age. Recency was a relevant factor for scoring risk only for suicidal behavior, with ideation and/or attempt in the past 12 months scored as “high risk,” and prior to that as “moderate risk.” Any history of physical or sexual abuse was scored as “high risk” to prompt the health care provider to follow up with more specific questions. The scoring output is a one-page summary of the AHR results. (A sample is provided in Figure 1.) Check marks indicate the adolescent’s scores in each domain and are accompanied by comments describing the specific behaviors or events of concern. The Comments column is also used to identify inconsistent or missing responses to alert the health care provider that probing further may be appropriate. A technical manual provides comprehensive detail on all the scoring algorithms and includes normative profiles for boys and girls in early, middle, and late adolescence. Normative profiles showing the risk category distributions in the general school population for each gender-by-age group can be used by health care providers to interpret results and initiate discussions with adolescent patients. The computerized AHR was pilot-tested with a convenience sample of adolescents recruited at the Minnesota State Fair. Participants were selected from Education Building visitors or passersby who appeared to be in the desired age range; survey respondents were given $5 worth of amusement park tickets. For the sample of 54 adolescents ages 12 to 18 years, the mean completion time was 3 minutes and 14 seconds. A post-administration interview found that the adolescents understood the questions, liked the format, thought the content relevant to their age group, and had no difficulty maneuvering through the question layout.
Discussion The AHR was developed in response to the apparent absence of brief, multidimensional screening tools for adolescent psychosocial risks. The AHR is unique in that its discriminant validity was determined
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Figure 1. Sample of Adolescent Health Review report.
using a statewide school population and large multisite samples of adolescents in juvenile correctional facilities, substance abuse treatment programs, and residential programs for youth with a wide range of behavioral and emotional problems. The AHR includes a mix of items that are effective for screening both boys and girls and items that are more effective for one gender than the other. The survey data from which the screening tool was developed provide age- and gender-specific normative profiles of the domains covered by the screening instrument, an important consideration since adolescents typically question how their behavior compares to the norm [42]. Such data can also assist the health care provider in counseling the young patient and/or determining the appropriate intervention. The development procedures used for the AHR can be replicated elsewhere, because several statebased school surveys and privately sponsored surveys exist. An advantage for states with ongoing surveys is that item selection and item scoring can be updated periodically to reflect changing norms, behavior patterns, or areas of concern.
Primary care has been recognized as an ideal setting to screen for adolescents’ health-risk behaviors, since it is the setting in which doctors are most likely to see adolescents [42,43]. The AHR is being tested in experimental and clinical practice studies to assess its utility in primary health care settings. A key research question to be addressed is whether a screening instrument derived from anonymous responses to a school survey will elicit honest answers in a clinical setting where responses will be confidential but not anonymous. Some studies suggest that accurate responses may not be highly dependent on anonymity [44,45]. Some comments about the study limitations are necessary. To accomplish the seemingly incompatible objectives of screen multidimensionality and brevity, item inclusion within specific domains had to be selective. The decision criteria employed and the item selection itself could be challenged as arbitrary. Certainly, many measures other than those included in the AHR have been found to be associated with adolescent risk behaviors. A case in point is familial history of substance abuse, which was
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excluded based on our selection criteria. Family history of alcohol and drug abuse is an undeniably critical component of a thorough assessment [5]; familial mental illness, criminality, and suicide are also important. However, the decision to exclude familial substance abuse as a screening item was based on the preference for measures indicative of risk associated directly with the adolescent’s own behavior, distress, or victimization. On these grounds, familial history in the absence of direct evidence of personal problems was deemed not essential for inclusion in a brief screen. Omitting items from the screening instrument, however, does not minimize their importance for inclusion in a more comprehensive assessment. Generalizability is another critical component for screening tools. In Minnesota, minority populations are rather small, comprising less than 5% of the student sample. However, Minnesota is not atypical of the rest of the country in terms of the prevalence of adolescent substance abuse, and there is no obvious reason to assume differences with respect to other behavioral and emotional disorders. Nonetheless, studies should be replicated with more varied populations. A final concern relevant to the scoring of any screening tool is the categorization of risk thresholds. Screening tools should never be used to supplant clinical inquiry and judgment. Screening instruments, and the summary results derived from them, are at best a guide and starting point for face-to-face conversations. A brief tool such as the AHR offers an opportunity for information-gathering that otherwise might not be incorporated into routine office visits, but the response to this information and the establishment of a trusting relationship between provider and patient require personal contact. This study was supported in part by federal contract no. 277-951035 awarded by the Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Prevention, and federal grant no. 5 R01 AA12179-02 awarded by the National Institute on Alcohol Abuse and Alcoholism and the Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Treatment. The authors thank Michael G. Luxenberg and Matthew Christenson of Professional Data Analysts, Inc., for data analyses; James A. McRae, Jr., for assistance with scoring algorithms; Kathryn B. Quinlan for assistance with the literature review, and Dan Bellandi and Ted Mika of Fanatic Software Corporation for software development. Anonymous reviewers of an earlier draft of this paper also provided valuable suggestions.
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34. Hallfors D, Khatapoush S, Kadushin C, et al. A comparison of paper vs computer-assisted self interview for school alcohol, tobacco, and other drug surveys. Eval Program Plann 2000;23: 149 –55. 35. Paperny DM, Aono JY, Lehman RM, et al. Computer-assisted detection and intervention in adolescent high-risk health behaviors. J Pediatr 1990;116:456 – 62. 36. Johnston LD, O’Malley PM, Bachman JG. National survey results on drug use from the Monitoring the Future study, 1975–1998. Volume 1: Secondary school students. (NIH Pub. No. 99-4660). Rockville, MD: National Institute on Drug Abuse, 1999. 37. Harrison PA, Fulkerson JA, Beebe TJ. DSM-IV substance use disorder criteria for adolescents: A critical examination based on a statewide school survey. Am J Psychiatry 1998;155:486 – 92. 38. Harrison PA, Luxenberg MG. Comparisons of alcohol and other drug problems among Minnesota adolescents in 1989 and 1992. Arch Pediatr Adolesc Med 1995;149:137– 44. 39. Klecka WR. Discriminant Analysis. Newbury Park, CA, Sage, 1980. 40. Public Health Service. Mental Health: A Report of the Surgeon General. Rockville, MD: U.S. Department of Health and Human Services, 1999. 41. Paperny DM, Hedberg VA. Computer-assisted health counselor visits. Arch Pediatr Adolesc Med 1999;153:63–7. 42. Gilchrist VJ. Preventive health care for the adolescent. Am Fam Pract 1991;43:869 –78. 43. Mason MJ, Adger H Jr. Screening for drug abuse in an adolescent primary health care clinic. J Child Adolesc Substance Abuse 1997;7:33– 43. 44. Malvin JH, Moskovitz JM. Anonymous versus identifiable self-reports of adolescent drug attitudes, intentions, and use. Public Opinion Q 1983;47:557– 66. 45. Vaughan RD, McCarthy JF, Heather J, et al. The development, reliability and validity of a risk factor screening survey for urban minority junior high school students. J Adolesc Health 1996;19:171– 8.
ORIGINAL ARTICLE
The Adolescent Health Review: A Brief, Multidimensional Screening Instrument PATRICIA A. HARRISON, Ph.D., TIMOTHY J. BEEBE, Ph.D., AND EUNKYUNG PARK, Ph.D.
Purpose: To develop a brief, multidimensional screening instrument for adolescents that addresses psychosocial domains critical to adolescent preventive health care services. Methods: Secondary analyses were conducted on survey data obtained in 1995 from a school sample of 76,159 students in grades 9 and 12, as well as 893 adolescents from juvenile correctional facilities, 500 adolescents from chemical dependency treatment programs, and 575 adolescents from residential behavioral treatment programs. A comprehensive set of 300 survey items was used in a series of discriminant analyses to determine which items best distinguished males and females in each clinical sample from their counterparts in the school sample. Results: The item selection for the Adolescent Health Review was guided both by empirical analyses and clinical judgment. The final screen is comprised of 33 demographic and clinical items that address a variety of psychosocial domains. The computerized, self-administered screen can be completed in about 3 minutes. The screen is scored automatically and produces an easy-toread risk-assessment profile. Because screening items were drawn from a large epidemiologic survey, normative profiles are available for each age and gender subgroup. Conclusions: A brief, empirically derived screening instrument, designed to address a range of adolescent risks, offers an opportunity for information gathering that otherwise might not be incorporated into routine clinic visits. © Society for Adolescent Medicine, 2001
From the Minnesota Department of Human Services, St. Paul, Minnesota. Address correspondence to: Dr. Patricia A Harrison, Minnesota Department of Human Services, 444 Lafayette Road, St. Paul, MN 55155-3865; E-mail: [email protected]. Manuscript accepted March 2, 2001.
KEY WORDS: Screening Adolescents Substance abuse Mental health Health risks Adolescent Health Review GAPS
Reducing morbidity and mortality among adolescents depends on early recognition and identification of health risks, most of which derive from social factors [1]. In fact, the 15- to 24-years age group is the only group in the United States for which the top three causes of death (accidents, homicide, and suicide) are all behavior-related; combined, they account for 75% of deaths, as well as 51% of deaths in the 5- to 14-years age group [2]. Substance abuse is believed to be a contributing factor in many adolescent deaths from unintentional or intentional injury [3,4]. In 1992, the American Medical Association issued Guidelines for Adolescent Preventive Services (GAPS) [1,5], a comprehensive set of recommendations that provides a framework for preventive health services to be delivered during annual health care visits. Similar guidelines have been developed by other national organizations, including the Maternal and Child Health Bureau’s “Bright Futures” [6], and all share significant emphasis on systematic screening for behavioral and psychosocial problems. Despite the widespread recognition that screening is critically important, physician surveys have found that most providers do not routinely screen adolescents for suicidal behavior and other risks [7,8]. One major barrier to screening during primary care encounters is the competing demands on physicians’
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time [9 –13]. Because unsafe sexual behavior, substance abuse, aggressive and delinquent behavior, mental health problems, and problems with family relationships frequently co-exist among adolescents [14 –18], the ideal screening procedure should entail a single instrument that is holistic [11,19]. Screening is distinct from assessment. The purpose of screening is to identify individuals who may be at risk for a particular problem and to rule out those who are not [20,21]. A comprehensive assessment needs to be conducted to determine whether and what type of intervention is appropriate. This two-stage process of screening and assessment can conserve limited medical resources while increasing the likelihood of detecting serious problems [22]. A review of existing adolescent screening instruments finds that they vary considerably in scope and length. Several multidimensional instruments have been developed, including the Drug Use Screening Inventory-Revised (DUSI-R) [23], the Juvenile Wellness and Health Survey (JWHS-76) [18], the ProblemOriented Screening Instrument for Teenagers (POSIT) [24], and the Youth Self Report (YSR) [25]. However, the drawback of all is their length (76 to 159 items); 20 to 40 minutes to administer is too long for most primary care encounters [26]. To facilitate the implementation of GAPS, a similarly comprehensive, although not empirically tested, patient questionnaire has been developed by the AMA for the adolescent’s initial preventive services visit [27]. Its length, however, makes it impractical for administration at other visits. Opportunities for screening could be increased if a practical, brief screening procedure were available for use during acute, as well as preventive, health care visits. Although shorter screening instruments for adolescents exist, their focus is typically narrow; they address only one or two domains, such as substance abuse [26,28 –32] or psychiatric symptoms [33]. In summary, existing multidimensional instruments are too long for routine use, and instruments that meet the test of brevity fail to address the requisite range of health-risk domains. Screening efforts could also be enhanced by the use of computer technology to facilitate administration, automate scoring, and produce an easy-to-read risk profile. To date, computer-administered questionnaires have been little explored as effective alternatives to paper-and-pencil screening instruments, despite their clear advantage with respect to the use of complex scoring algorithms [22]. Adolescents, in particular, appear to be attracted to computerized instruments [34,35], and hurried health care providers would
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likely welcome the immediate output of a concise summary highlighting critical concerns. This article describes the development of such a screening instrument, the Adolescent Health Review (AHR). The AHR addresses the objectives of multidimensionality, brevity, and automated reporting. In addition, it capitalizes on the availability of normative data from a statewide sample to assist health care providers in evaluating the deviation of behaviors from the norm for males and females in different stages of adolescence.
Methods Procedure To obtain a comprehensive portrait of at-risk youth, the State of Minnesota periodically administers a survey about risk behaviors to public school students as well as to adolescents in special settings who typically are not represented in school surveys. The analyses described in this report are based on secondary analyses of these survey data. The 1995 Minnesota Student Survey was administered in the spring of that year to 76,159 public school students in grades 9 and 12, representing 97% of the state’s school districts. Included in the sample were 75% of the 9th graders and 57% of the 12th graders enrolled at the start of the school year. (The lower participation rate for high school seniors results from a combination of factors, including shorter school days for students who have completed most of their credits, transfers to alternative education centers, attendance at post-secondary educational institutions, and dropout.) The survey was also administered to adolescents in three clinical settings: 893 adolescents in 20 juvenile correctional facilities (detention centers and longer-term residential facilities), 500 adolescents in 55 outpatient and inpatient chemical-dependency treatment programs, and 575 adolescents in 51 residential behavioral treatment programs (institutions and group homes). The survey respondents represented 85% to 96% of the adolescents in these facilities when the survey was administered. A passive parental consent procedure was used for students; the parental consent requirement was waived for the clinical samples with the approval of the Institutional Review Board of the Minnesota Department of Human Services. Respondent participation was voluntary and surveys were anonymous, coded only by site. The survey instrument included more than 117 questions (300 variables) addressing attitudinal, behavioral, and environmental issues. The substance
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use frequency items were in the Monitoring the Future survey format [36], and 15 items operationalized the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) substance use disorder diagnostic criteria [37]. Other content areas are described in greater detail elsewhere [38].
Sample The adolescents in the special settings constituted the three criterion groups against which the public school students were compared. Placement in a clinical setting was selected as the criterion used to assess “risk,” because admission to one of these settings represented a “real-world” determination that further assessment and/or intervention and treatment was appropriate. The problem severity among the criterion groups ranged considerably. For example, placement in a detention center frequently resulted from a status offense or other relatively minor offense, and stays typically averaged less than 2 weeks. In contrast, placement in residential correctional facilities was typically associated with serious offenses, such as auto theft, burglary, and weapons possession, and stays averaged 5 months. The extent of disorders among adolescents in substance abuse treatment centers ranged from a few, relatively mild symptoms of abuse to multiple, serious signs of dependence. Some adolescents in residential behavioral treatment facilities were in group homes that required no specialized diagnosis, and some were in facilities for individuals with severe emotional disturbance. Because the purpose of a brief screening instrument is to identify individuals who would benefit from a comprehensive assessment, using such varied samples as criterion groups would appear to have great utility.
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ences in group membership, net of the variables already in the model [39]. Differences in Wilks’ lambda determined which variables to include. The minimum probability of F for a variable to enter the model was set at .001, and the maximum probability that a variable could have and not be removed was set at .05. The maximum number of steps was 30. For questions that involved multiple response choices, each response choice was treated as a discrete variable and coded “yes/no.” Because gender distributions in the clinical populations varied considerably, and because different items might emerge for boys and girls, analyses were conducted separately for each gender. Thus, six separate analyses of the 300 survey items were conducted, each involving either boys or girls, one of the three clinical populations, and the combined 9th and 12th grade student sample. The GAPS domains provided the general structure, with some modifications. For example, the concept of family functioning was expanded to include the quality of interpersonal interactions, and the concept of emotional health was expanded to include anxiety as anxiety disorders are the most prevalent types of disorders among adolescents, more than twice as common as mood disorders [40]. For the sake of brevity, the decision was made at the outset to limit item selection to measures of the respondent’s behavior, feelings, and experiences. Other considerations for item reduction included a general preference for behavioral measures over attitudinal measures, preference for items that discriminated more than one clinical group, and preference for behaviors that were not exceedingly rare. Although the guiding principle for item selection was that the process be empirically driven, final decisions were also informed by these criteria and clinical judgment.
Results Statistical Analyses The primary objective of the AHR development was to make the screening tool multidimensional yet brief. Stepwise discriminant analysis was the statistical method chosen to identify potential screening items. Discriminant analysis is a statistical technique in which linear combinations of variables are used to distinguish between two or more categories of cases, and is a useful method to identify items which significantly discriminate a criterion group from a comparison group [39]. The stepwise method added variables individually in the order of their ability to maximize differ-
Most of the survey respondents were between the ages of 14 and 18 years (98% of the school sample and between 87% and 100% of the three clinical samples). The school sample was evenly distributed between males and females, but males predominated in the clinical settings (from 83% in correctional institutions to 62% to 63% in substance abuse and behavioral treatment settings). Screen Domains and Item Selection More than 60 items discriminated at least one clinical population from the school sample for at least one of
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the gender groups. However, 14 of these items were eliminated from further consideration because they did not fit one of the screen development selection criteria, leaving 46 individual items or item composites in the domains of interest. Of the 46 items/ composites, 25 significantly discriminated at least one sample of boys and one sample of girls, 13 significantly discriminated only boys, and 8 significantly discriminated only girls. These items, along with the clinical sample(s) discriminated by each item, are shown in Table 1. Some similar items are presented in composite form to preserve space. (Detailed statistical information, too lengthy to present here, is available from the authors.) The items are presented in the order in which the domains are sequenced in the AHR. The largest number (20) of discriminant items were related to tobacco, alcohol, or other drugs; eight items related to school; five related to abuse victimization; four related to emotional health or suicidal risk; four related to sexual behavior; two related to family functioning; two related to violent behavior; and one related to eating disorders. The paragraphs that follow describe the rationale for item retention/ omission and modification. Unhealthy weight control. The single discriminating item was related to taking diet pills to lose weight. However, to make the item more inclusive for the AHR, it was combined with another survey question on vomiting and use of laxatives. Family interaction problems. The two discriminating family-related items measured the extent to which adolescents believe that their family has fun together and that their parents care about them. Both were retained in the AHR. Problems at school. The school-related domain produced 8 discriminating variables. Among these items, only one (the perception of teachers’ interest in the adolescent) discriminated more than two of the six groups examined and was therefore selected for inclusion. The other seven items (truancy, feelings about school, academic aspirations, grades, reading difficulties, and placement in special classes) all discriminated two groups, but the truancy item was retained because it was the only behavioral measure. Emotional distress and suicidal behavior. Of the two discriminating emotional health variables, the one that discriminated three groups was retained (degree
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of feeling sad), and the one that discriminated only one group was eliminated (degree of satisfaction with personal life). In place of the latter, a nonempirically derived item addressing anxiety was added (“. . . have you felt nervous, worried or upset?”). Both of the suicidal behavior items (ideation and attempt) discriminated clinical samples and were retained. Violent behavior. Both items related to violent behavior (physical assaults and carrying a gun) were retained for the AHR. The gun question was combined with a similar survey question regarding other types of weapons and modified so as not to be restricted solely to school property. Physical/sexual abuse. The 5 items related to abuse victimization included physical abuse at home, extrafamilial sexual abuse, victim of date rape, victim of date violence, and having been stabbed or fired at by a student on school property. All were retained but the last item which was endorsed by fewer than 2% of the adolescents in the school survey. For the AHR, the question about extrafamilial sexual abuse was combined with a similar survey question about intrafamilial sexual abuse. The date rape and other date violence questions were also combined into a single question resulting in a 3-item domain. Sexual activity. The 4 items related to sexual behavior included age of first sexual intercourse, not using protection, having had a sexually transmitted disease, and having been pregnant/gotten someone pregnant. The 2 items included in the AHR were updated survey versions of the sexual intercourse and the protection questions. Substance use. The only tobacco use item (current cigarette smoking frequency) was retained. Alcohol and marijuana use frequency were retained, but similar questions for other drug categories were eliminated, partly for length and partly because use of these substances was relatively rare in the absence of alcohol and/or marijuana use, rendering them redundant for screening purposes. The typical alcohol quantity question was preferred for screening purposes over the 2-week binge question since it was not so severely restricted by recency. Further analyses and reviews were conducted to reduce number of diagnostic criterion and use pattern items. Correlation matrices were generated for males and females in the school sample. Only two of the diagnostic items (giving up activities related to
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Table 1. Survey Items That Significantly Discriminated Clinical Samples From the School Sample Clinical Setting Substance Abuse Treatment Survey Item *. . .take diet pills to lose weight. . .? *. . .family has lots of fun together? *. . .your parents care about you? *. . .teachers are interested in you. . .? . . .teachers show respect for students? *. . .how often have you skipped. . .school? How do you feel about going to school? Which. . .best describes your school plans? . . .reading skills. . .prevented you from keeping up. . .? . . .ever been in any classes for learning problems? . . .the two grades you get most often (Ds or Fs) *. . .have you felt sad? . . .how satisfied have you been with your personal life? *. . .had thoughts about killing/would like to kill myself *. . .ever tried to kill yourself *. . .have you tried or beat up another person? *. . .did you carry a gun on school property? *. . .adult in your household. . .hit you so hard or so often. . .? *. . .adult or older person. . .touched you sexually. . .? *. . .victim of violence on a date? *. . .victim of date rape? . . .a student stabbed or fired a gun at you. . .? *. . .had sexual intercourse (age of onset)? *. . .method. . .to prevent pregnancy and/or STDs? . . .told by a doctor or nurse that you had a STD. . .? . . .have you been pregnant or gotten someone pregnant? *. . .how frequently have you smoked cigarettes? *. . .have you had alcoholic beverages. . .? *. . .how much. . .do you drink at one time/5⫹ drinks in a row?a *. . .have you used marijuana. . .? . . .have you sniffed glue. . .or inhaled. . .? . . .have you used LSD. . .PCP, or other psychedelics. . .? . . .have you used “crack”. . .or cocaine in any other form. . .? . . .have you used steroids. . .? Have you ever used a needle to inject an illegal drug? . . .use. . .before. . .during (at). . .right after. . .school?a *. . .use. . .because I’m sad, lonely, or angry *. . .used so much. . .that you could not remember. . .? *. . .wanted to. . .or. . .tried to cut down. . .? *. . .use. . .hurt your relationships. . .? *. . .missed work or school because of. . .use? . . .given up activities like sports, work, school. . .to use. . .? . . .ever had an injury while using. . .? . . .had any other physical health problems. . .result of using? *. . .use. . .caused you problems with the law? *. . .hit anyone or become violent while using. . .?
Boys
Juvenile Corrections Facilities
Girls
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* Items introduced by an asterisk were retained for the Adolescent Health Review. a Represents a composite of several closely related variables. These items were combined merely for ease of presentation; the variables were entered individually in the discriminant function analyses.
use and job/school absenteeism) were moderately correlated (R ⫽ .49) and somewhat redundant in content. Prevalence rates for both items were fairly
comparable among the student population, and both typically occurred in the presence of at least five other diagnostic symptoms [37]. Therefore, only ab-
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senteeism was retained because it was the shorter of the two and easier to understand. Three other items from the substance use subset (injury, physical illness, and injection drug use) were dropped because their prevalence rate in the general population was 1% or less [37]. Items measuring use before, during, and after school were also eliminated owing to length considerations in favor of retaining the diagnostic items. This review/decision process reduced the tobacco/alcohol/drug subset of screening items to 11. They were divided into four domains: “cigarette smoking” (1 item), “alcohol use” (2 items), “marijuana use” (1 item), and “substance abuse/ dependence” (7 items). Additional screening items not derived from empirical analyses. Six additional items were added at the beginning of the AHR, including three demographic descriptors (gender, age, race). Because the instrument was designed for clinical, rather than school, settings an item was needed to determine whether adolescents were attending school, so the schoolrelated items could be scored properly. Two general health questions (exercise and nutrition) were included to serve as a transition to more sensitive items. The addition of these brief items resulted in a 33-item screening instrument. Computerized Scoring and Reporting The computerized scoring output for the AHR was designed to inform the health care provider whether the adolescent’s responses were indicative of “no risk,” “moderate risk,” or “high risk” in a given domain. Designation of “high risk” was limited to domains for which it was believed a referral to specialty behavioral health care might be required and for which there was perceived imminent risk to the adolescent’s health or well-being. Therefore, the maximum risk category for lack of exercise, poor nutrition, unhealthy weight control, family interaction problems, problems at school, and emotional distress was set at “moderate.” Suicidal behavior, violent behavior, sexual activity, cigarette smoking, alcohol use, marijuana use, substance abuse/dependence, and physical/sexual abuse were all potentially “high risk.” Risk thresholds were selected based on clinical judgment, prevalence data, or a combination of these factors. Clinical judgment was the sole determinant for clinically significant problems (such as violent behavior or substance abuse). However, for areas for which risk is less clear-cut, such as family interaction
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problems or problems at school, the thresholds were selected rather conservatively to identify only a relatively small proportion of adolescents (generally less than 20%) with the most problematic responses. The frequency and types of behaviors used as cut points for some risk thresholds were age-specific (e.g., sexual activity, cigarette smoking, alcohol use, marijuana use, substance abuse/dependence) because these behaviors increase in prevalence with age. Recency was a relevant factor for scoring risk only for suicidal behavior, with ideation and/or attempt in the past 12 months scored as “high risk,” and prior to that as “moderate risk.” Any history of physical or sexual abuse was scored as “high risk” to prompt the health care provider to follow up with more specific questions. The scoring output is a one-page summary of the AHR results. (A sample is provided in Figure 1.) Check marks indicate the adolescent’s scores in each domain and are accompanied by comments describing the specific behaviors or events of concern. The Comments column is also used to identify inconsistent or missing responses to alert the health care provider that probing further may be appropriate. A technical manual provides comprehensive detail on all the scoring algorithms and includes normative profiles for boys and girls in early, middle, and late adolescence. Normative profiles showing the risk category distributions in the general school population for each gender-by-age group can be used by health care providers to interpret results and initiate discussions with adolescent patients. The computerized AHR was pilot-tested with a convenience sample of adolescents recruited at the Minnesota State Fair. Participants were selected from Education Building visitors or passersby who appeared to be in the desired age range; survey respondents were given $5 worth of amusement park tickets. For the sample of 54 adolescents ages 12 to 18 years, the mean completion time was 3 minutes and 14 seconds. A post-administration interview found that the adolescents understood the questions, liked the format, thought the content relevant to their age group, and had no difficulty maneuvering through the question layout.
Discussion The AHR was developed in response to the apparent absence of brief, multidimensional screening tools for adolescent psychosocial risks. The AHR is unique in that its discriminant validity was determined
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Figure 1. Sample of Adolescent Health Review report.
using a statewide school population and large multisite samples of adolescents in juvenile correctional facilities, substance abuse treatment programs, and residential programs for youth with a wide range of behavioral and emotional problems. The AHR includes a mix of items that are effective for screening both boys and girls and items that are more effective for one gender than the other. The survey data from which the screening tool was developed provide age- and gender-specific normative profiles of the domains covered by the screening instrument, an important consideration since adolescents typically question how their behavior compares to the norm [42]. Such data can also assist the health care provider in counseling the young patient and/or determining the appropriate intervention. The development procedures used for the AHR can be replicated elsewhere, because several statebased school surveys and privately sponsored surveys exist. An advantage for states with ongoing surveys is that item selection and item scoring can be updated periodically to reflect changing norms, behavior patterns, or areas of concern.
Primary care has been recognized as an ideal setting to screen for adolescents’ health-risk behaviors, since it is the setting in which doctors are most likely to see adolescents [42,43]. The AHR is being tested in experimental and clinical practice studies to assess its utility in primary health care settings. A key research question to be addressed is whether a screening instrument derived from anonymous responses to a school survey will elicit honest answers in a clinical setting where responses will be confidential but not anonymous. Some studies suggest that accurate responses may not be highly dependent on anonymity [44,45]. Some comments about the study limitations are necessary. To accomplish the seemingly incompatible objectives of screen multidimensionality and brevity, item inclusion within specific domains had to be selective. The decision criteria employed and the item selection itself could be challenged as arbitrary. Certainly, many measures other than those included in the AHR have been found to be associated with adolescent risk behaviors. A case in point is familial history of substance abuse, which was
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excluded based on our selection criteria. Family history of alcohol and drug abuse is an undeniably critical component of a thorough assessment [5]; familial mental illness, criminality, and suicide are also important. However, the decision to exclude familial substance abuse as a screening item was based on the preference for measures indicative of risk associated directly with the adolescent’s own behavior, distress, or victimization. On these grounds, familial history in the absence of direct evidence of personal problems was deemed not essential for inclusion in a brief screen. Omitting items from the screening instrument, however, does not minimize their importance for inclusion in a more comprehensive assessment. Generalizability is another critical component for screening tools. In Minnesota, minority populations are rather small, comprising less than 5% of the student sample. However, Minnesota is not atypical of the rest of the country in terms of the prevalence of adolescent substance abuse, and there is no obvious reason to assume differences with respect to other behavioral and emotional disorders. Nonetheless, studies should be replicated with more varied populations. A final concern relevant to the scoring of any screening tool is the categorization of risk thresholds. Screening tools should never be used to supplant clinical inquiry and judgment. Screening instruments, and the summary results derived from them, are at best a guide and starting point for face-to-face conversations. A brief tool such as the AHR offers an opportunity for information-gathering that otherwise might not be incorporated into routine office visits, but the response to this information and the establishment of a trusting relationship between provider and patient require personal contact. This study was supported in part by federal contract no. 277-951035 awarded by the Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Prevention, and federal grant no. 5 R01 AA12179-02 awarded by the National Institute on Alcohol Abuse and Alcoholism and the Substance Abuse and Mental Health Services Administration, Center for Substance Abuse Treatment. The authors thank Michael G. Luxenberg and Matthew Christenson of Professional Data Analysts, Inc., for data analyses; James A. McRae, Jr., for assistance with scoring algorithms; Kathryn B. Quinlan for assistance with the literature review, and Dan Bellandi and Ted Mika of Fanatic Software Corporation for software development. Anonymous reviewers of an earlier draft of this paper also provided valuable suggestions.
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