Q2. Review the article by Brown (2013). Did the author use the strategies identified in your required readings and article in searching for the best evidence? If not, why not. Support your response with evidence from your knowledge of the readings and assigned articles.
Evidence Review
A Review of the Evidence on Technology-Based Interventions for the Treatment of Tobacco Dependence in College Health
Joanne Brown, APRN, DNP, WHNP, FNP, CTTS
ABSTRACT
Background: The college years are a critical time in the development of smoking behavior and tobacco use. Smoking is linked to 30% of cancer deaths, 80% of deaths from chronic obstructive pulmonary disease, and early cardiovascular disease and death. Effective cessation interventions at this time provide an opportunity to drastically reduce premature morbidity and mortality.
Aims: To review available evidence on Internet interventions with young adults, including methodology, theoretical frameworks and outcome measures for tobacco treatment to guide the development of a program in college health.
Methods: A comprehensive literature search for studies published from January 1999 to February 2011, in multiple databases was conducted, along with hand-searching of reference lists. Inclusion criteria were: participants aged 18–30 years, intervention involved the Internet through either Web sites or e-mail or texting, and outcome measurement of tobacco cessation/abstinence. Studies were evaluated utilizing a tool synthesized from guidelines presented by the Cochrane Collaboration.
Findings: Eight studies met the inclusion criteria (four randomized controlled trials, four cohort studies). Theoretical frameworks utilized were the Transtheoretical Model of Change, Health Belief Model, Theory of Social Support, and social cognitive theory. Interventions varied and included computer-generated advice letters, Web-based cessation guides, computer-generated text messages, and peer e-mail support. With smoking abstinence as the primary outcome measure, there was a statistically significant improvement in quit rates. Because of the use of multiple components, differences in interventions and the number of contacts, it is not clear what types of computer-based applications are most effective. Small sample sizes, lack of control groups, and inconsistency in outcome measures limit the ability to provide conclusive evidence to support these interventions—but support the feasibility to use in the design of future programs.
Conclusions: Use of technology-based interventions, such as the Internet, may be an effective tool for tobacco treatment interventions, especially with college students. There is great potential to reach large numbers of students, many who may not identify themselves as smokers or seek traditional methods for treatment. Additional research is needed to determine which technology- based interventions are most effective and to provide more conclusive evidence.
BACKGROUND
The Importance of Targeting Tobacco use in Young Adults or College Students The college years are a critical time in the development of smoking behavior and tobacco use. Despite knowledge of the long-term health effects of tobacco (Budd & Preston, 2001), one-third of college students start smoking or become reg- ular smokers during their undergraduate years (Centers for Disease Control [CDC], 2011a; Freedman, Nelson, & Felman,
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2011; DeBernardo & Aldinger, 1999; Hammond, 2005; Lantz, 2003; Substance Abuse and Mental Health Services Admin- istration [SAMHSA], 2007, 2009). If all tobacco products are included, the results are even more alarming. Including cigar use, snus, smokeless tobacco, and hookah or waterpipe, it is estimated that between 28.8% and 48.3% of college students have used one or more tobacco products in the prior 1-month period (CDC, 2010; Rigotti, Lee, & Wechsler, 2000; Rigotti, Moran, & Wechsler, 2005).
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Smoking is linked to at least 30% of all cancer deaths, almost 80% of deaths from chronic obstructive pulmonary disease, and to early cardiovascular disease and death (CDC, 2008). More immediate health effects on young adults include in- creased respiratory symptoms, such as shortness of breath, increased breathlessness after exercise, persistent cough, and wheezing (Berg, 2009; Vianna, 2008). For young women, smoking increases the risk for developing high-grade cervi- cal lesions and cervical cancer (Castellsasgue & Munoz, 2003; Collins, Rollason, Young, & Woodman, 2010) as well as pre- menstrual syndrome (Bertone-Johnson, Hankinson, Johnson, & Manson, 2008). Tobacco use may also have harmful effects on academic success (DeBernardo & Aldinger, 1999; Rigotti et al., 2000).
According to the United States Surgeon General, research suggests that most of the deaths related to smoking and to- bacco use can be eliminated with successful cessation before age 30 years (Doll, 2004; U.S. Department of Health and Hu- man Services, 2010). Effective interventions treating tobacco dependence during young adulthood provide an opportunity to drastically reduce premature morbidity and mortality and may also improve academic achievement. The purpose of this paper is to review the available evidence on e-mail, texting, and Inter- net interventions with young adults, including methodology, theoretical frameworks, and outcome measures for tobacco de- pendence treatment to assist in the design of interventions in college health.
Interventions for the Treatment of Tobacco use and Dependence The updated U.S. Public Health Service-sponsored Clinical Practice Guideline (CPG) for treating tobacco use and de- pendence (Fiore et al., 2008) provides recommendations for clinical interventions for treatment in adolescents and adults. This systematic review of 8,700 articles and abstracts provides the basis for more than 35 meta-analyses of interventions and also provides guidance on evaluating outcomes of studies. Although the gold standard for follow-up after the intervention is 6 months, shorter time frames are acceptable according to the CPG (Fiore et al., 2008). Abstinence data should be reported based on the occurrence of tobacco use within a specified time period or point prevalence (usually 7 days) prior to the follow-up assessment and should use an intention- to-treat (ITT) approach in which all subjects are included in the denominator, even those lost to follow-up (Fiore et al., 2008). Biochemical confirmation of self-reported abstinence of tobacco use with exhaled carbon monoxided (CO) or salivary cotinine is desirable, but not necessary (Fiore et al., 2008).
Key guideline recommendations include: (1) identifying to- bacco use by “asking” at every visit; (2) “assessing” the tobacco users’ willingness to make a quit attempt; (3) “advising” them to quit; (4) “assisting” in quitting by providing counseling and one of the seven first-line medications; and (5) “arranging”
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Evidence Review
for follow-up contact (Fiore et al., 2008). Brief interventions, motivational interviewing techniques and telephone quit-lines were found to be effective strategies in adults. For adolescents, interventions that varied in intensity, format, and content yielded significant results, but there were too few studies to per- form meta-analysis on specific counseling techniques and little evidence on the use of medications (Fiore et al., 2008). The group aged 18–24 years is sometimes included in discussions about adolescents and other times included in discussions on adults; specific recommendations for the population of young adults and college students are not outlined in the guideline.
An algorithm for choosing among smoking cessation treat- ments presented by Hughes (2008), using an evidence-based approach, suggests a brief assessment of the smoker’s prior quitting history followed by one or two medications and coun- seling in most people. Internet counseling formats are recom- mended as second-line treatment due to limited but efficacious studies (Hughes, 2008). Hughes’ population focus was adults; he did not specify treatments for younger adults or college students.
Internet Interventions
According to Fiore et al. (2008), e-health or Internet based in- terventions show promise as an effective delivery system and may be combined with more traditional therapies; they may in- clude e-mail, Web sites, computer-generated reports or other components. A systematic review of Internet-based interven- tions for smoking cessation (Civljak, Sheikh, Stead, & Car, 2010) suggests that although these types of interventions may assist with cessation, there is a lack of consistent results. In- terventions that are interactive, requesting information from participants about their tobacco usage and triggers to tailor in- formation, may be more effective than more passive methods where material is displayed on static Web sites (Civljak et al., 2010). Larger effects may also be seen when Internet interven- tions are included along with other more traditional methods (Civljak et al., 2010). A meta-analysis of randomized controlled trials (RCT) with 29,549 participants enrolled in Web-based or computer-based smoking cessation programs and 13, 499 en- rolled in control groups indicated sufficient clinical evidence to support the use of these programs for adult smokers (Myung, McDonell, Kazinets, Seo, & Moskowitz, 2009). Although ado- lescents and young adults were included in the meta-analysis, the mean age of participants was 38 years. The discussion to follow focuses on a variety of interventions targeting young adults or college students.
Interventions for Young Adults or College Students
Grimshaw and Stanton (2006) evaluated the effectiveness of strategies designed to help young people quit smoking, but limited their review to ages 20 years and younger. Their systematic review of 15 trials (n = 3,605) suggests that com- plex interventions addressing characteristics of young adult smoking and incorporating elements sensitive to the stages
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ratio (OR) at 1 year of 1.70 (95% CI 1.25–22.33; Grimshaw & Stanton, 2006). Studies evaluating pharmacological interventions in adolescents did not achieve statistical significance or were very small scale (Grimshaw & Stanton, 2006).
Over half of college-aged smokers would like to quit, but many underestimate the addictive power of nicotine and most did not use any of the recommended treatment methods during prior quit attempts (Bader, Travis, & Skinner, 2007; Carpenter, Baker, Gray, & Upadhyaya, 2010; CDC, 2011b; DeBernardo & Aldinger, 1999; Ling & Glantz 2004). Significant proportions of the young adult population can be reached by offering tobacco dependence treatment through their educational settings, including college health service (Lantz, 2003). In a previous review of interventions to reduce tobacco use on U.S. campuses, Murphy-Hoefer et al. (2005) found 14 studies, of which only 5 received a “satisfactory” rating, mainly due to the lack of random sampling or a comparison group. One study used computer-administered interventions targeting cigarette smoking; based on the TTM, it demonstrated a higher, though non-significant cessation rate in the intervention group (Murphy-Hoefer et al., 2005). There was wide variability in definitions of current tobacco use, quit status and duration of abstinence for the studies, but published reports indicate that interventions can have a positive effect on college tobacco use (Murphy-Hoefer et al., 2005).
Self-help programs may be more appealing to young adults and cost effective, especially when tailored to key character- istics of students and based on stages of change (Kishchuk, Tremblay, Heneman, & O’Loughlin, 2004; Travis & Lawrance, 2009). In a RCT of an age-tailored, self-help program for college students, 11.4% of students quit smoking compared to 5.6% using the adult-oriented usual care kit (Travis & Lawrance, 2009). Innovative strategies utilizing multi-media, mobile phones, and the Internet have shown some success and may be a promising way to assist traditionally hard to reach groups (Li, 2009; Severtson, Haas, Neftzger, Purvis, & Rula, 2009). Young adults are technologically savvy; most have ac- cess at home or at school to computers and many college classes involve online discussion groups.
Use of the Internet and mobile phones may increase ac- cessibility to treatment during times more desirable to college students. Unlike the traditional therapies underutilized by young adults, technology-based programs offer convenience and anonymity. Use of these modalities may provide timely, effective interventions to assist in tobacco treatment efforts in this population, but research is lacking or inconsistent (Fiore et al., 2008; Grimshaw & Stanton, 2006; Lantz, 2003). Previous research has either focused on treatment for tobacco dependence in older adults or primary prevention in adoles- cents. Young adulthood is a key period in the transition to regular tobacco use; a systematic review of the available litera- ture on effective, innovative, technology-based strategies in this population will add to this relatively new body of knowledge.
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METHODS
Identification of Research
The following question guided the search for evidence: What is the available evidence on Internet interventions for to- bacco treatment in young adult or college tobacco users? The Cochrane Handbook for Systematic Reviews of Interventions (ver- sion 5.0.2) provided guidance in the preparation of the review (Higgins & Green, 2009). The search strategy involved a com- prehensive literature search for studies published between Jan- uary 1, 1999 and the second week in February 2011. Criteria for considering studies was initially limited to include only RCT; however, when those limits were applied only a few articles were retrieved, so studies with quasi-experimental designs and cohort studies were also included. Participants included those aged 18–30 years who used any tobacco product in the past 30 days without exclusion based on gender, ethnicity, or language spoken. Any type of Internet, computer or technology-based intervention (e.g., e-mail, static, or interactive Web sites), in all settings, with or without other therapies, were included. Stud- ies that only used the Internet for recruitment into smoking cessation programs, or did not include outcome data, were ex- cluded. The primary outcome measure was status of tobacco use 6 months after the start of the intervention as recom- mended by the CPG, but trials with shorter term follow-up were also included.
Electronic searches were conducted in PubMed, MEDLINE, Web of Science, The Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, and the Cochrane Central Register of Controlled Trials (CENTRAL) using ex- ploded MeSH terms: “young adult,” “Internet,” and “tobacco cessation” as well as searching terms “tobacco” or “smoking” and “internet” or “e-mail” or “Web” or “texting” and “young adult” in the topic, title or abstract with limiting factors for “research,” “human” and “RCT.” Terms were searched inde- pendently first and then in combination with one other term, then all terms together. Hand searching of reference lists of articles yielded additional studies for review.
Selection of Studies
Seventy-six studies were initially identified and their ab- stracts reviewed. After duplicate studies selected from different databases were identified, either by identical title or descrip- tion in the abstract, 11 articles were excluded. An additional 47 studies did not meet the review criteria. Full-text reports for the remaining 18 studies were examined for compliance with eligibility criteria. Seven studies were excluded because, despite including participants aged 18–30 years, the majority were middle aged (mean age ranged from 31.2 to 43.9 years). An additional three studies were excluded because the partici- pants were high school students (mean age range 14–17 years). Eight studies were identified that met the established inclusion criteria (Abroms, Windsor, & Simons-Morton, 2008; An et al., 2008; Escoffery, McCormick, & Bateman, 2004; Gala et al., 2008; Obermayer, Riley, Asif, & Jean-Mary, 2004; Prokhorov et al., 2008; Riley, Obermayer, & Jean-Mary, 2008; Rodgers et al., 2005).
Data from relevant trials were extracted according to rec- ommendations by the Cochrane Collaboration to include the following: study design, method of randomization and blind- ing; participant selection, demographic characteristics, tobacco usage; theoretical framework; intervention description; and outcome measures, including length of abstinence, attrition rate and results (Tables 1 and 2). Publication bias was assessed by examining the randomization process, “blinding,” compa- rability of baseline measurements and outcome measures.
Study Quality Assessment
After reviewing the articles, they were assessed using guide- lines presented by Melnyk and Fineout-Overholt (2005) and the Cochrane Collaboration (van Tulder et al., 2003). According to Melnyk and Fineout-Overholt (2005), key critical appraisal questions need to be answered when evaluating evidence: what are the results of the study; are those results valid; and will the results help me in caring for my patient? Two different work- sheets were created that synthesized recommendations from Melnyk and Fineout-Overholt (2005), the Newcastle Ottawa Scale (Higgins & Green, 2009), Titler (2002) and the Cochrane Collaboration (van Tulder et al., 2003) to evaluate the RCTs and the cohort studies. These were utilized to evaluate individual articles for characteristics of the population, design, study vari- ables, relevant outcome criteria, data analysis, and results. The reviewer scored each criterion with a score of “0” if the cri- terion was not met or not clearly stated or “1” if the criterion was met. According to the Cochrane Collaboration (van Tulder et al., 2003) for RCTs, if there are no serious design flaws, a study is methodologically sound if the total score is at least six. Tables 3 and 4 reflect the assessments of quality for the selected studies.
In the RCTs, all participants were randomly assigned via computer-generated programs into treatment or control groups either individually or by group with blinding to assessors, but not providers (Abroms et al., 2008; An et al., 2008; Prokhorov et al., 2008; Rodgers et al., 2005), an important indicator of internal validity. There were detailed descriptions comparing baseline characteristics of the two groups in all of the RCTs. The characteristics of the participants in the cohort studies were similar (Escoffery et al., 2004; Gala et al., 2008; Ober- mayer et al., 2004; Riley et al., 2008). All of the authors except one (Gala et al., 2008) also reported outcomes using ITT by classifying missing data as if participants were still smoking or using tobacco. The highest attrition rate (Escoffery et al., 2004) was 46% at 6 months, but using a conservative ITT analysis the results were still significant.
Data Synthesis and Analysis
After data were extracted from the full articles it was entered in tables and summarized using a narrative approach. Quan- titative analysis was not carried out for this review due to the heterogeneity of the interventions. Instead, detailed informa-
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tion regarding the characteristics of the interventions, dose and duration, conceptual framework, and outcome measurements is presented along with comments related to study quality.
RESULTS
Four RCT were included in this review (Abroms et al., 2008; An et al., 2008; Prokhorov et al., 2008; Rodgers et al., 2005) and four cohort studies (Escoffery et al., 2004; Obermayer et al., 2004; Gala et al., 2008; Riley et al., 2008). Table 1 summarizes the extracted data.
Demographics of Study Samples
The average age of participants ranged from 18 to 25 years for all of the studies; most were recruited from U.S. colleges or univer- sity campuses. Overall, there were slightly more females rep- resented than males and most of the participants were white, non-Hispanic. Two of the studies (An et al., 2008; Prokhorov et al., 2008) included all smokers, regardless of interest in to- bacco dependence treatment. All other participants indicated an interest in quitting. There were wide variability in the defi- nitions of smoker or tobacco user, from smoking any cigarettes in the past 30 days (An et al., 2008), smoking 1 cigarette per day (Abroms et al., 2008; Prokhorov et al., 2008; Rodgers et al., 2005), smoking more than 28 cigarettes per week (Obermayer et al., 2004; Riley et al., 2008) or use of smokeless tobacco within the past 30 days (Gala et al., 2008). Participants were light smokers, smoking from 9 to 15 cigarettes per day (cpd) at baseline, consistent with use in the young adult population (Ahijevych & Ford, 2010; SAMHSA, 2009; Wetter et al., 2004). Follow-up periods ranged from 6 weeks to 10 months.
Theoretical Frameworks
Of the eight studies included in this review, five were based on or included elements of the TTM (Escoffery et al., 2004; Gala et al., 2008; Obermayer et al., 2004; Prokhorov et al., 2008; Riley et al., 2008). TTM outlines a series or stages of change involved in the process of behavior change: precontemplation, contemplation, preparation, action, maintenance and termi- nation (DiClemente et al., 1991; Prochaska, 2008). Two uti- lized some variation of social cognitive learning (Abroms et al., 2008; An et al., 2008) which stresses the dynamic relation- ship between cognition, behavior, and environment (Bandura, 1986). Rodgers (2005) did not specify a framework.
Intervention Components
Most of the interventions involved limited or no human in- teraction. One intervention consisted of computer-generated feedback delivered by counselors (Prokhorov et al., 2008). An- other began with a 15-minute in-person counseling session with the remainder of the intervention via e-mail (Abroms et al., 2008). Three had personal counseling e-mail letters generated by computer programs or peer coaches tailored to stages of change or social cognitive theory either weekly for 4–30 weeks or 10–12 e-mails over a 6-month period (Abroms et al., 2008;
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An et al., 2008; Gala et al., 2008). Three had personalized, automated text messages generated by computer programs and sent to participants’ mobile phones at intervals based on user characteristics and specified quit dates (Obermayer et al., 2004; Riley et al., 2008; Rodgers et al., 2005). Other interventions in- cluded Web-based cessation guides, chat rooms, or discussion boards (An et al., 2008; Escoffery et al., 2004; Gala et al., 2008; Obermayer et al., 2004; Riley et al., 2008) and feedback provided by computerized questionnaires (Prokhorov et al.,
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2008). One site required weekly visits and interactive quizzes over 30 weeks (An et al., 2008); another consisted of four Web- based sessions with tailored feedback (Escoffery et al., 2004).
Outcomes
The primary outcome measure for all of the studies was smok- ing or tobacco abstinence (Table 2). How this was defined varied in duration of abstinence and timing of assessment. Five of the studies evaluated self-report of 7-day point prevalence
abstinence with biochemical validation using salivary cotinine (Abroms et al., 2008; Obermayer et al., 2004; Prokhorov et al., 2008; Riley et al., 2008; Rodgers et al., 2005). Both An (2008) and Gala (2008) reported 30-day point prevalence abstinence, but only An included biochemical validation using exhaled CO. Escoffery’s (2004) primary outcome was self-report of quitting, but without indication of duration of abstinence or biochemical validation. Gala (2008), Obermayer (2004), Riley (2008) and Rodgers (2005) reported assessment 4–6 weeks after intervention, while Abroms (2008), An (2008), Escoffery (2004), and Prokhorov (2008) followed participants for at least 6 months. Secondary outcomes in four of the studies included self-reports of a reduction in the quantity and frequency smoked or number of dips and chews per day (Abroms et al., 2008; Gala et al., 2008; Riley et al., 2008; Rodgers et al., 2005), while the remaining three reported number of quit attempts (An et al., 2008; Obermayer et al., 2004; Prokhorov et al., 2008). Assessment of participants’ perspectives on change or movement in stage of change (Prokhorov et al., 2008), coping and self-efficacy (Gala et al., 2008; Prokhorov et al., 2008; Riley et al., 2008) or program usage (Escoffery et al., 2004) were also included.
Effectiveness
The expected success rate for adults making quit attempts without intervention is 4%–7% percent (Fiore et al., 2008); all of the studies reported larger effects with their interven- tions. Only Abroms (2008), An (2008), and Prokhorov (2008) included self-report of 7-day or 30-day abstinence with bio- chemical validation at follow-up of at least 6 months as rec-
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ommended by the CPG. Abstinence rates were 10.2%–33.1% for their intervention groups compared to 5.7%–16.9% in the control groups; analysis performed by t tests and chi-square (p < .05; Abroms et al., 2008), logistic regression modeling (p < .001; An et al., 2008) and linear mixed model regres- sion (two-sided p = .068; Prokhorov et al., 2008). Obermayer (2004), Rodgers (2005), and Riley (2008) also reported bio- chemically validated self-report of 7-day abstinence, but only 6 weeks after enrollment. In the study by Rodgers (2005), 13.9% of those in the intervention group quit compared to 6.2% in the control group by chi-square analysis (p < .0001). Ober- mayer (2004) and Riley (2008) reported continine-validated 7-day abstinence rates of 175–45% for their cohorts at 6 weeks. Gala (2008) indicated that 8% (n = 1) of participants abstained from smokeless tobacco for 30 days 4 weeks after enrollment; no biochemical verification. At a 6-month assessment, 25.7% of Escoffery’s (2004) participants reported quitting, without defining what that meant or validating biochemically. There was no difference found in prolonged quit rates (continuous abstinence for 24 weeks) in the studies by An (2008) or Rodgers (2005).
Secondary outcomes evaluated additional measures. Con- sumption was reduced by five to eight cpd (Riley et al., 2008; Rodgers et al., 2005) and spit tobacco reduced from 3.9 to 2.9 chews per day (Gala et al., 2008) for those who continued to use tobacco. One of the studies (An et al., 2008) noted a decrease in the number of days smoking (from 18.1 to 12.3 days per month), but no difference in the number of cigarettes smoked on those days. Process evaluation indicated participants felt en- gaged with most of the interventions, with most indicating they read e-mails, text messages, and Web site information (Abroms et al., 2008; An et al., 2008; Gala et al., 2008; Obermayer et al., 2004). One study lost almost half of its participants before the 6-month follow-up and reported low participation in the discus- sion board and “Ask-the-Expert” components (Escoffery et al., 2004).
DISCUSSION
Overall, this review suggests that Internet, e-mail, text messag- ing, computer, or Web-based designs have potential for use in interventions for the treatment of tobacco dependence in young adults but much more testing is necessary, particularly RCTs. Using ITT, and including those lost to follow-up, all of the stud- ies demonstrated statistically significant improvements in quit rates. Compared to quit rates of 12–33% in reviews of other in- terventions for young adults and college students (Grimshaw & Stanton, 2006; Murphy-Hoefer et al., 2005), quit rates of 10–45% presented in this review offer encouraging evidence for strategies in this hard to reach group, but should be viewed with caution. The lack of control groups and short follow-up assessment in studies included in this review fails to produce convincing evidence.
Baseline characteristics of the participants were consistent with those of college tobacco users, strengthening the ability to generalize the results. All of the studies reported data us- ing conservative ITT analyses, which minimizes bias. Four of the studies followed participants for at least 6 months as rec- ommended by CPG (Abroms et al., 2008; An et al., 2008; Escoffery et al., 2004; Prokhorov et al., 2008). Most also in- cluded biochemical verification of self-reports of abstinence (Abroms et al., 2008; An et al., 2008; Obermayer et al., 2004; Prokhorov et al., 2008; Riley et al., 2008; Rodgers et al., 2005).
A major limitation of this review was the paucity of RCTs. Most of the participants indicated an interest in smoking ces- sation and identified themselves as smokers, contrary to many young adults. Many of the studies’ participants were regular, although lighter users of tobacco, smoking 9–15 cpd (Abroms et al., 2008; An et al., 2008; Escoffery et al., 2004; Prokhorov et al., 2008; Riley et al., 2008) when compared to the 25.4 cpd in their adult counterparts (CDC, 2011a; Lindson, Aveyard, & Hughes, 2010). Social or occasional users of tobacco, common in college settings, were only included in one study (An et al., 2008). Other than smokeless tobacco, other forms of tobacco use, such as snus or hookah, were not addressed.
Participants were primarily white college students, limiting the ability to generalize findings to minority populations and young adults not enrolled in post-secondary education. Stud- ies also neglected to address sub-populations such as lesbian- gay-bisexual-transgender groups who may be a higher risk for tobacco dependence (Remafedi, Jurek, & Oakes, 2008).
Studies not meeting the criterion for follow-up 6 months after the quit date limit the ability to generalize for longer-term success (Gala et al., 2008; Obermayer et al., 2004; Riley et al., 2008; Rodgers et al., 2005). Participants who were recruited by
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self-selection may limit the ability to generalize to the broader population and results may not apply to those in the precontem- plation stage of change. In addition, high attrition rates of up to 46% (Escoffery et al., 2004; Prokhorov et al., 2008) threatened the internal validity of those studies. Although using ITT is standard practice in adult studies, young adults might be lost to follow-up for a variety of reasons not related to continued tobacco use and therefore bias the findings toward no effect (Grimshaw & Stanton, 2006).
Several studies (Escoffery et al., 2004; Gala et al., 2008) did not use biochemical verification of abstinence. According to the Society for Research in Nicotine and Tobacco (SRNT) Subcommittee on Biochemical Verification (2002), this may not be necessary or desired because it does not affect outcomes when data collection is done via the Internet with no face-to-face contact for adults. Although An (2008) and Riley (2008) did not find significant differences between those self-reporting abstinence and those in which this was verified, other studies found significant rates of over-reporting of quit status. At 6 months, self-reported quit rates decreased from 25% to 10.2% when validated with cotinine levels in Abroms’ study (2008), from 22% to 17% in Obermayer’s (2004) study and from 28.1% to 13.9% for Rodgers (2005). Other studies have found similar rates of overreporting, making the argument for bio- chemical verification in this population (Grimshaw & Stanton, 2006).
In studies with multiple components or multiple contacts (Abroms et al., 2008; An et al., 2008; Escoffery et al., 2004; Gala et al., 2008; Obermayer et al., 2004; Riley et al., 2008), it may be difficult to determine the relative contribution of each aspect. One of the interventions utilized computer tech- nology, but was delivered in-person (Prokhorov et al., 2008). Because of the use of multiple components, differences in in- terventions and number of contacts, it is not clear what types of computer-based applications are most effective. E-mail and tex- ting, however, are effective ways to communicate with college students and psychological support can be effectively conveyed (Brendryn, Drozd, & Kraft, 2008; Klatt et al., 2008). Additon- ally, the theoretical frameworks used in the studies are simi- lar to those used for more traditional interventions for young adults and provide insight into the value of including tailored messages along with cognitive framing and peer support in treatment strategies (Murphy-Hoefer et al., 2005).
There is wide discrepancy in the definition of what consti- tutes “abstinence” and length of time for follow-up, making it difficult to determine efficacy. There are limited studies evalu- ating the evidence for any treatment programs in this age group and even fewer that evaluate strategies using current technolo- gies embraced by this population. The paucity of studies in the young adult population hinders efforts to develop effective evidence-based strategies for the prevention of the transforma- tion of occasional smokers to daily smokers and for treatment in this population. However, the potential for developing useful evidence through research in this area seems strong.
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Technology-Based Tobacco Treatment Interventions
IMPLICATIONS FOR PRACTICE AND FUTURE RESEARCH Increased rigor with definitions of smoking/tobacco use, con- sistency in interventions used and standardized outcome mea- surements are needed to determine which technology-based methods are most effective. Head-to-head comparisons of dif- ferent Internet or texting interventions with only one different component in the treatment group would be helpful to deter- mine which aspect of the program is most favorable. Theoreti- cal foundations should be utilized in the design and implemen- tation of programs. An approach for college students using a combination of theories such as TTM with social cognitive the- ory would address many of the factors associated with tobacco use in this population.
All programs should use evaluation of self-reported 7-day abstinence 6 months after the start of the intervention as the primary outcome measure to allow for better compari- son between strategies. Even with the challenges posed by over-reporting and loss to follow-up due to graduation, trans- fers and such, it would provide a consistent starting point for appraisal. Ideally biochemical validation should be included, but this may not be practical for smaller studies and those without funding for lab testing. Secondary outcomes should include evaluation of prolonged abstinence through more rig- orous measures of 30-day abstinence or number of days of continued abstinence (not even a puff) as recommended by the Cochrane Review (Grimshaw & Stanton, 2006) to better assess the more transient nature of tobacco use and quitting in young adults. Shorter time frames might overestimate ab- stinence in this population with higher proportions of light and intermittent smokers. Measures of sustained, continuous quitting at least 6 months after an intervention have been pro- posed as the “gold standard” for evaluation (Grimshaw & Stan- ton, 2006; West, Hajeck, Stead, & Stapleton, 2005). Outcomes should include use of all tobacco products such as smokeless, hookah, and cigars to assess polyuse and ensure participants are not switching to another form of tobacco. Additional well- designed RCTs are needed for young adults with evaluation of at least 6 months. Studies should include all smokers, not just those interested in cessation to determine the best methods for increasing motivation to quit.
The Internet and/or text messaging may be useful adjuncts to other therapies such as clinic visits or telephone support. Even the addition of one e-mail or text message weekly or monthly by providers may help prevent relapse in a group with the highest rate of quit attempts and highest prevalence of current smoking. Treatment for tobacco dependence is cost- effective when compared to other commonly used disease prevention interventions. According to the CPG (Fiore et al., 2008), the cost of tobacco dependence treatment per life-year saved is estimated at $3,539 compared to $5,200 for hyperten- sion screening in men aged 45–54. The cost per quit for more traditional treatment methods ranges from a few hundred to a few thousand dollars (Fiore et al., 2008). Abroms’ (2009) e-mail intervention cost an average of $39.33 per participant.
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This cost is incremental per user, with possibilities for a high reach, cost-effective strategy to impact behavior in this popula- tion.
CONCLUSIONS
Use of technologies such as the Internet and text messaging have potential as effective tools for behavior-change, particu- larly with young adults, but more study is needed. Although this review demonstrated limited evidence for technology-based in- terventions in this population, knowledge was gained regarding their potential and feasibility. Conclusive evidence is lacking due to small sample sizes, under-representation of intermit- tent and all tobacco users, short follow-up time frames and lack of control groups with randomization. There is a need for affordable, personalized, age-appropriate interventions for tobacco treatment. College health services are moving to elec- tronic medical records with the ability to communicate via e- mail in a secure, private manner. This has the potential to reach large numbers of students, many who may not identify themselves as smokers or seek traditional methods for treat- ment. The cost is minimal per user and may provide a means to impact behavior in this challenging population. WVN
Author information
Joanne Brown, Doctor of Nursing Practice, University Health Service, University of Kentucky, Lexington, KY. The author is grateful for the mentorship and guidance of Carolyn A. Williams, RN, PhD, FAAN, and Ellen J. Hahn, RN, PhD, FAAN, University of Kentucky, College of Nursing. Address correspondence to Joanne Brown, University Health Service, University of Kentucky, 830 South Limestone Street, Lexington, KY 40536-0582; joanne.brown@uky.edu
Accepted 26 July 2012 Copyright ⃝C 2013, Sigma Theta Tau International
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