Kindergarten Children's Knowledge and Perceptions of Alcohol, Tobacco, and Other Drugs.
Little research exists regarding young children's knowledge of ATODs. This fact may be due to a lack of appropriate measures of children's knowledge and to the erroneous conclusion that young children are unaware of ATODs. Tennan studied 46 preschool children and determined their awareness of substance abuse behaviors. Children identified pictures depicting drug abuse, alcohol consumption, smoking, and other behaviors. The concept of nonmedical drug use was recognized by 33% of the children. The same number of children could name a health hazard associated with alcohol abuse. Zucker et al found that children as young as three years of age with alcoholic parents were more likely to identify at least one alcoholic beverage than young children of nonalcoholic parents. Shute et a found that the majority (92%) of preschool and first grade children recognized cigarettes. About one-half of the children who had seen tobacco products in the home said they would use them, compared to 11% of the children who had not seen tobacco products in the home.
Children whose parents use or abuse ATODs are at higher risk for substance use than children whose parents do not use or abuse ATODs.[10-13] Adolescents who progress from experimentation with cigarettes to established smoking are more likely to have parents who smoke. Multiple substance dependence by both parents has a significant adverse effect on boys' problem behaviors and also increases their risk for substance abuse later in life. Young children (ages 2-8) whose mothers use drugs are more likely to have social problems; boys are more likely than girls to exhibit behavior problems.
Data for this cross-sectional study were collected in the preintervention phase of a prevention trial testing the effectiveness of a school and home-based ATOD prevention program for parents and 5- and 6-year-old children. Parent and child data were collected from November 1997-February 1998 in school and home settings.
Three elementary schools were randomly selected from a population of 15 high-risk elementary schools in Lexington, Ky. Schools were classified as high-risk if more than 40% of the students received free- or reduced-lunch. Children and parents were recruited by materials sent home with all kindergarten children and at school events. Teachers also distributed information about the study during parent conferences. From an accessible population of 257, 126 parent-child dyads agreed to participate (49%).
Of 126 children, 44% were male and 56% female; 43% qualified for free- or reduced-lunch. Thirty percent of the children were minority including African American (22%) and Hispanic (7%). Almost three-fourths (70%) were non-minority (Caucasian). Mean age of the children was 5.8 years (SD = .4).
Of the 126 parents, four were male and 122 female. The biological parent participated in all but 10 cases, in which grandparents or guardians were interviewed. The average age of the parents was 32.4 years (SD = 8.9). More than one-third (37%) were single, divorced, or separated. Eight of 10 had at least a high school education. The majority (55%) earned less than $25,000 annually, and 37% were unemployed.
Children's knowledge of ATODs, defined as their ability to perceptually identify substances, was measured using the Child Drug Awareness Inventory (CDAI). Adapted from the Preschooler Attitude Assessment Inventory (PreAAI), the CDAI measures young children's knowledge, feelings, and attitudes toward alcohol, tobacco, and other drugs. The CDAI is a pictorial inventory of 18 pictures administered to the child individually by a trained interviewer. The main character is a young bear named Bunchy who is depicted with a parent bear performing various tasks. Six items are neutral (eg, eating or reading). In 11 pictures, Bunchy observes the parent using alcohol, tobacco, and other drugs or giving Bunchy a sip of alcohol. In the picture of LSD, "sister" is substituted for "parent" based on typical use patterns in the community as reported by the narcotics police chief.
The CDAI differs from other pictorial inventories that merely show the substance. Knowledge is measured by asking the child, "What is the parent doing in the picture?" The interviewer rates the child's ability to recognize alcohol (beer, wine, liquor), tobacco (cigarettes, smokeless tobacco), and illicit drugs (marijuana, cocaine, LSD, injectable drugs) as correct (1) or incorrect (0). Knowledge scores consist of the sum of these items and range from 0-12. Feelings are assessed by asking the child, "How does Bunchy feel about the parent [doing] -- ?" Feelings are rated by the child as happy, sad, or mad. The question, "Does Bunchy think it is good or bad that the parent is [doing] -- ?," is used to assess attitudes. The child rates attitudes as good or bad. Feelings and attitudes are counted only if the ATOD is correctly identified.
The narcotics chief of police and local prevention specialists reviewed the CDAI for content validity, and several pictures were slightly modified to reflect regional patterns of ATOD use. In this study, each of the 12 interviewers independently rated a videotaped interview with a child and scored the CDAI. Their ratings were compared with those of the principal investigator and at least 91% agreement was obtained for each interviewer.
Parent ATOD use was measured by selected items from the National Household Drug Survey including items on tobacco, alcohol, marijuana, and cocaine, substances commonly used by parents of young children.[19,20] Current cigarette use was defined as smoking one or more cigarettes per day. A current alcohol user was defined as having at least one alcoholic drink within the past month. Parents who used marijuana at least 1-2 times per month were considered current users. Lifetime ATOD use was defined as ever having used the particular substance in their lifetime.
The study was approved by the University's Medical Institutional Review Board. In addition, a federal certificate of confidentiality was obtained to protect study participants. Parents gave written informed consent for interviews with themselves and their children. Ten undergraduate and two graduate nursing students received eight hours of intensive training on the administration of the CDAI with children. All parent interviewers received intensive training including Spanish-speaking interviewers who collected data from the Hispanic children and parents. Preparation of student interviewers and test administration was consistent with the recommendations for using picture identification tools as outlined by Wiley and Hendricks. Children were interviewed individually in a private setting at school to avoid distractions. Answers were recorded immediately with any comments made by the child about the picture. Child interviews lasted an average of 12 minutes (SD = 4). Parent interviews were conducted in-home by experienced female interviewers. Parents received $10 for participation.
Descriptive statistics were used to examine children's ATOD knowledge and parent ATOD use. Chi-square was used to examine the association between sociodemographic characteristics and ATOD knowledge and the relationship between children's knowledge and parent use. Multiple logistic regression was used to identify sociodemographic predictors of children's illicit drug knowledge. Variables considered as potential predictors were income ([is less than] $20,000 vs [is greater than] $20,000), ethnic group (minority vs. non-minority), marital status (married vs. other), and gender of the child. Interactions between ethnicity and marital status, ethnicity and income, and income and marital status also were included in the model to investigate potential multiplicative effects of these factors.
Of the 12 ATOD items, children recognized an average of 2.8 pictures (SD = 2.0), with a range of 0-8 (Table 1). Almost all (95%) kindergarten children recognized cigarettes. At least one alcoholic beverage was correctly identified by 56% of the children. One-half the children recognized drinking and driving. Sixteen children (12.7%) correctly identified marijuana. Seventeen percent (n = 21) of these 5- and 6-year-olds recognized at least one illicit drug including marijuana, powder or crack cocaine, LSD, and injectable drugs.
Kindergarten Children's Knowledge, Feelings, and Attitudes about Alcohol, Tobacco, and Other Drugs (N = 126)
Knowledgeable n % 1. Parent smoking a cigarette. 120 95.2 2. Parent using smokeless tobacco. 3 2.4 3. Parent giving Bunchy a sip of hard liquor. 18 14.3 4. Parent drinking a lot of hard liquor. 44 34.9 5. Parent smoking marijuana. 16 12.7 6. Parent giving Bunchy a sip of beer. 23 18.3 7. Parent smoking crack. 2 1.6 8. Parent drinking a lot of beer. 53 42.1 9. Parent drinking beer and driving. 63 50.0 10. Parent snorting cocaine. 7 5.6 11. Parent using injectable drug. 3 2.4 12. Sister taking LSD. 2 1.6 Positive Feelings n % 1. Parent smoking a cigarette. 7 5.8 2. Parent using smokeless tobacco. 0 -- 3. Parent giving Bunchy a sip of hard liquor. 3 16.7 4. Parent drinking a lot of hard liquor. 4 9.1 5. Parent smoking marijuana. 0 -- 6. Parent giving Bunchy a sip of beer. 6 26.1 7. Parent smoking crack. 0 -- 8. Parent drinking a lot of beer. 3 5.7 9. Parent drinking beer and driving. 5 7.9 10. Parent snorting cocaine. 1 14.3 11. Parent using injectable drug. 1 33.3 12. Sister taking LSD. 1 50.0 Positive Attitudes n % 1. Parent smoking a cigarette. 6 5.0 2. Parent using smokeless tobacco. 0 -- 3. Parent giving Bunchy a sip of hard liquor. 3 16.7 4. Parent drinking a lot of hard liquor. 3 6.8 5. Parent smoking marijuana. 0 -- 6. Parent giving Bunchy a sip of beer. 3 13.0 7. Parent smoking crack. 0 -- 8. Parent drinking a lot of beer. 3 5.7 9. Parent drinking beer and driving. 3 5.8 10. Parent snorting cocaine. 1 14.3 11. Parent using injectable drug. 1 33.3 12. Sister taking LSD. 1 50.0
Though most children who correctly identified substances had negative attitudes (bad vs. good) and feelings (sad or mad) toward drug use, some children viewed drug use as positive. For example, seven children said that Bunchy Bear was happy that the parent was smoking cigarettes, and six said that smoking cigarettes was good. More than one-fourth of the children said Bunchy felt happy that the parent was giving the child bear a sip of beer. Non-minority children were more likely to say Bunchy felt happy about the sip of beer than were minority children (43% vs. 0%; p-value for Fisher's exact test = .05). Boys and girls did not differ on this item. Examples of children's correct responses to the 12 substance use pictures are in Table 2.
Table 2 Examples of Children's Correct Responses to the Child Drug Awareness Inventory
Picture of the Substance Selected Children's Responses 1. Parent smoking a cigarette "Smoking a cigarette. Bunchy doesn't want no one to smoke by him." 2. Parent using smokeless tobacco. "Spitting tobacco." 3. Parent giving Bunchy a sip of "Beer makes you drunk ... my hard liquor. dad got drunk at my 4th birthday. I thought it was bad cause it tastes yucky." 4. Parent drinking a lot of hard "Drinking wine ... drinking a liquor. lot ... parent acts crazy." 5. Parent smoking marijuana. "Paper and drugs ... he made it ... I don't feel good when my grandma is like that." 6. Parent giving Bunchy a sip of "Letting her little boy or girl beer. drink beer." 7. Parent smoking crack. "Cigarette with wood and fire." 8. Parent drinking a lot of beer. "My dad drinks beer ... a whole bunch of beer. He gets one every day." 9. Parent drinking beer and "Drinking beer and driving. driving ... you might run into something and have a crash." 10. Parent snorting cocaine. "Doing drugs ... police can get you, got me ... I have to go back to jail at 2 o'clock." 11. Parent using injectable drug. "Giving a shot of drugs mixed with water." 12. Sister taking LSD. No correct responses.
In the logistic regression analysis, none of the sociodemographic characteristics predicted children's recognition of cigarettes or alcohol. Ethnicity was the only significant predictor of illicit drug knowledge ([MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], p = .004). Of the non-minority children, 10% correctly identified at least one illicit drug, in contrast to 31% of the minority children. Minority children were nearly four times more likely to be knowledgeable about illicit drugs than non-minority children (estimated OR = 3.9, 95% CI = 1.5-10.1).
Parent ATOD Use
More than one-third of parents reported current cigarette (36%) and alcohol use (40%). Prevalence of current illicit drug use was very low, with only 2% reporting current marijuana use. Lifetime ATOD use was much higher for all types of substances. Reported lifetime use was 72% for cigarettes and 85% for alcohol. Almost one-half (47%) the parents had used marijuana in the past, and 7% reported having used either powder or crack cocaine. Children's knowledge of alcohol or other drugs as measured by the CDAI was not correlated with the parents' reported current alcohol or other drug use ([chi square] = 0.21,p = .64). Since almost all children (95%) recognized cigarettes, the association between children's knowledge of tobacco and parent tobacco use was not assessed.
It is a misconception to assume that young children are not knowledgeable about ATODs. Most of the kindergarten children participating in this study correctly identified cigarettes and more than one-half recognized alcoholic beverages. The high level of recognition of cigarettes is consistent with a prior study of preschool and first-grade children's awareness of tobacco products. A surprisingly high number of children also recognized at least one illicit drug. Though there was a high level of ATOD recognition and perceived impact on the child and family, it was encouraging that the majority of children had appropriate attitudes and feelings toward substance use. However, it was disturbing that more than one-fourth of these children thought Bunchy was happy about the parent giving Bunchy a sip of beer. These findings indicate the importance of early ATOD prevention programs for families with young children.
The fact that minority children were the most knowledgeable about illicit drugs and were more likely to have appropriate feelings about Bunchy sipping beer warrants further investigation. Environmental influences (eg, television and video exposure to drugs) beyond the scope of this study may have accounted for this difference. Ethnic differences in the amount of television watched were found in a study by Williams et al. Both male and female minority college students watched more television compared to non-minority college students.
Parent self-report of their current ATOD behavior was inconsistent in some cases with a National Household Drug Survey random sample of females aged 26-34. Parents in this study reported slightly higher current cigarette use (36% vs. 32%), but lower alcohol (40% vs. 53%), marijuana (2% vs. 4%), and cocaine use (0% vs. 0.7%) compared to the national random sample. Reported lifetime use among parents was more consistent with the national sample, with the exception of cocaine use (7% vs. 17%). Low reports of current alcohol and other drug use among the parents in this study may indicate that the heavier ATOD users did not participate.
Lack of congruence between children's knowledge of alcohol, tobacco, and other drugs and parents' reported ATOD use was contrary to staff expectations and to the literature. Three plausible explanations exist for this finding. First, other people living in the household may have been using ATODs. The study did not examine drug use by others in the home. Shute et al reported that young children who saw tobacco products in the home were more likely to say they would try them. ATOD use by all family members should be assessed in future studies of children's ATOD knowledge as has been done elsewhere. Second, self-report measures of ATOD use may not accurately reflect actual drug use. Though the interviewers took careful steps to ensure confidentiality and promote a comfortable, trusting climate during the interview, some parents may not have answered the ATOD use questions truthfully. Lack of biological measures to confirm parent self-report was a limitation of this study. Third, children are exposed to ATODs not only at home, but at school and in the community. The advertising and promotion of alcohol and tobacco products is highly visible through television, movies, billboards, and at a variety of community locations such as grocery stores, gas stations, and convenience stores. Of 50 G-rated children's animated films, 34 showed at least one instance of alcohol or tobacco use (68%). More subtle promotion of alcohol and tobacco products appears on clothing and games that many children own. Children's exposure to alcohol and tobacco advertising and promotion should be assessed in future studies.
Prevention research has been hampered by a lack of effective methods to assess young children's ATOD knowledge. Developmentally appropriate measures of young children's knowledge of ATODs are limited. Picture identification provides an effective method of determining young children's level of knowledge, skill, or behavior.[21,24] The CDAI proved useful in measuring children's knowledge, feelings, and attitudes about ATODs. It also may be useful for monitoring the effects of drug prevention programs over time.
[1.] Kann L, Kinchen S, Williams B, et al. Tobacco use among high school students -United States, 1997. MMWR. 1998:47(SS-3):1-89.
[2.] Fergusson DM, Lynskey MT, Horwood LJ. Childhood exposure to alcohol and adolescent drinking patterns. Addiction. 1994;89:1007-1016.
[3.] Jackson C, Dickinson D. Early indeed: onset of alcohol and tobacco use in a sample of rural elementary school children. J Drug Educ. in press.
[4.] Centers for Disease Control and Prevention. Incidence of initiation of cigarette smoking - United States, 1965-1996. MMWR. 1998;47: 837-840.
[5.] Preliminary Results from the 1997 National Household Survey on Drug Abuse. Rockville, Md: Substance Abuse and Mental Health Services Administration, Office of Applied Studies; 1998.
[6.] Blinn-Pike LM, Bell T, Devereaux M, Doyle H, Tittsworth S, Von Bargen J. Assessing what high risk young children know about drugs: verbal versus pictorial methods. J Drug Educ. 1993;23:151-169.
[7.] Tennant FS. Awareness of substance abuse and other health-related behaviors among preschool children. J Drug Educ. 1979;9:119-127.
[8.] Zucker RA, Kincaid SB, Fitzgerald HE, Bingham CR. Alcohol schema acquisition in preschoolers: differences between children of alcoholics and children of nonalcoholics. Alcohol Clin Exp Res. 1995;19:1 1011-1017.
[9.] Shute RE, St. Pierre RW, Lubell EG. Smoking awareness and practices of urban preschool and first grade children. J Sch Health. 1981;51:347-351.
[10.] Anderson AR, Henry CS. Family system characteristics and parental behaviors as predictors of adolescent substance use. Adolescence. 1994;29:405-420.
[11.] Brook JS, Whiteman M, Gordon AS, Brook DW. The role of older brothers in younger brothers' drug use viewed in the context of parent and peer influences. J Genet Psychol. 1988;151:59-75.
[12.] 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.
[13.] Hops H, Duncan TE, Duncan SC, Stoolmiller M. Parent substance use as a predictor of adolescent use: a six-year lagged analysis. Ann Behav Med. 1996;18:157-164.
[14.] Distefan JM, Gilpin EA, Choi WS, Pierce JP. Parental influences predict adolescent smoking in the United States, 1989-1993. J Adolesc Health. 1998;22:466-474.
[15.] Moss HB, Vanyukov M, Majimder PP, Kirisci L, Tarter RE. Prepubertal sons of substance abusers: Influences of parental and familial substance abuse on behavioral disposition, IQ, and school achievement. Addict Behav. 1995;20:345-358.
[16.] Stein JA, Newcomb MD, Bentler PM. Differential effects of parent and grandparent drug use on behavior problems of male and female children. Dev Psychol. 1993;29:31-43.
[17.] Hahn EJ. Child Drug Awareness Inventory (CDAI). (unpublished instrument, 1997).
[18.] Hahn EJ. Parent participation and preschool drug prevent on programs. Addict Nurs Network. 1991;3:115-120.
[19.] Hahn EJ. Predictors of Parent Involvement in Drug Prevention [dissertation]. Ann Arbor, Mich: Indiana University; 1992.
[20.] Hahn EJ. Parental alcohol and other drug (AOD) use and health beliefs about parent involvement in AOD prevention. Issues Ment Health Nurs. 1993;14:237-247.
[21.] Wiley DC, Hendricks CM. Using picture identification for research with preschool children. J Sch Health. 1998;68:227-230.
[22.] Williams CD, Sallis JF, Calfas KJ, Burke R. Psychosocial and demographic correlates of television viewing. Am J Health Promo. 1999; 13:207-214.
[23.] Goldstein AO, Sobel RA, Newman GR. Tobacco and alcohol use in G-rated children's animated films. JAMA. 1999;281:1131-1136.
[24.] Hendricks CM, Peterson F, Windsor R, Poehler D, Young M. Reliability of health knowledge measurement in very young children. [J Sch Health. 1988;58:21-25.
Ellen J. Hahn, DNS, RN, Associate Professor, College of Nursing; or <email@example.com> ; Lynne A. Hall, DrPH, RN, Professor, College of Nursing and Dept. of Behavioral Science, College of Medicine and Assistant Dean for Research and Doctoral Studies, College of Nursing: Mary Kay Rayens, PhD, Research Assistant Professor, College of Nursing and College of Medicine, Associate Director, Biostatistics Consulting Unit, Chandler Medical Center; April V. Burt, BSN, Research Assistant; Donna Corley, MSN, RN, Research Assistant; and Kristy Lea Sheffel, Research Assistant, College of Nursing, University of Kentucky. Rose Street, Lexington, KY 40536-0232. This study was funded by the National Institute of Nursing Research, National Institutes of Health. Grant #1 R15 NR/OD04216-01A1 awarded to Drs. Hahn, Hall, and Rayens. This article was submitted April 26, 1999, and revised and accepted for publication November 22, 1999.
|Printer friendly Cite/link Email Feedback|
|Author:||Hahn, Ellen J.; Hall, Lynne A.; Rayens, Mary Kay; Burt, April V.; Corley, Donna; Sheffel, Kristy Lea|
|Publication:||Journal of School Health|
|Date:||Feb 1, 2000|
|Previous Article:||A Model for Mapping Linkages Between Health and Education Agencies to Improve School Health.|
|Next Article:||Utilizing the SIECUS Guidelines to Assess Sexuality Education in One State: Content Scope and Importance.|