Pediatric asthma

C H A P T E R

2 Pediatric asthma Sara E. Voorhees1, Casey Lawless2, Dima Ezmigna3, David A. Fedele1 Department of Clinical & Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States; 2 Pulmonary Medicine Division, Children’s National Health System, Washington, DC, United States; 3 Pediatric Pulmonary Division, Department of Pediatrics in the College of Medicine, University of Florida, Gainesville, FL, United States

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Overview of pediatric asthma Asthma is one of the most common chronic diseases of childhood and remains a burden on healthcare systems worldwide (Masoli, Fabian, Holt, & Beasley, 2004). In the United States, more than 8% of youth are diagnosed with asthma, with higher prevalence in Puerto Ricans, African Americans, and children living in lower socioeconomic conditions (Akinbami, Simon, & Rossen, 2016; National Center for Health Statistics, 2017). It is estimated that 235 million individuals suffer from asthma worldwide and asthma is currently the most common noncommunicable disease among children (Asthma- Key Facts, 2017). Asthma has multiple etiologies resulting in episodes of reversible changes in the airways, including increased mucous production, mucosal swelling, and contraction of airway smooth muscles. Narrowing of airways’ diameter and limitation of airflow results, a condition called obstructive airway disease (National Asthma Education and Prevention Program, 2007).

Etiology Asthma is a polygenic (i.e., controlled by two or more genes) disease with a strong interaction between genes and environment, resulting in different phenotypes and severities (Wilmott et al., 2012). Familial patterns exist, and a family history of asthma or atopy (heightened immune responses to common allergens) increases the likelihood of developing

Adherence and Self-Management in Pediatric Populations https://doi.org/10.1016/B978-0-12-816000-8.00002-5

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asthma (Subbarao, Mandhane, & Sears, 2009). In addition, the hygiene hypothesis suggests that the degree of exposure to environmental microbial antigens, especially early in life, is a major contributor to the likelihood of developing asthma and allergies (Mattes et al., 1999). Exposure to allergens, respiratory infections, tobacco smoke exposure, air pollution, and diet increase the risk of asthma onset (Wilmott et al., 2012). Other risk factors include increased body mass index, active smoking, and prenatal and perinatal factors (e.g., maternal age, medication use) (Beasley, Semprini, & Mitchell, 2015). Sex hormones are also linked to the development of asthma (Yung, Fuseini, & Newcomb, 2018).

Clinical presentation Asthma has a variable clinical presentation with symptoms including cough, wheezing, chest tightness, shortness of breath, and occasionally chest pain. Symptoms are usually episodic, vary in severity, and follow a pattern of intermittent exacerbations and worsening of symptoms late at night or early in the morning with improvement throughout the day. This symptom pattern correlates with physiological changes in lung function and airway obstruction (National Asthma Education and Prevention Program, 2007).

Diagnosis The initial diagnosis of asthma requires an adequate review of medical history to recognize the previously mentioned characteristic pattern of respiratory symptoms suggestive of asthma, as well as objective evidence of reversible airway obstruction during lung function testing. The British Thoracic Society, Scottish Intercollegiate Guidelines Network 2, and Global Initiative for Asthma guidelines emphasize the importance of exclusion of other conditions that mimic asthma presentation (e.g., gastroesophageal reflux disease, allergic rhinitis) (Culver et al., 2017), especially in younger children where lung function testing is challenging or not possible. The National Asthma Education and Prevention Program expert panel recommends performing spirometry, a physiological test that measures inhalation and exhalation of air within a 6 second forced expiration, in individuals 5 years of age and older to assess for reversible airflow limitation (National Asthma Education and Prevention Program, 2007). One commonly used outcome measure of spirometry is the amount of air an individual can exhale within 1 second (forced expiratory volume; FEV1). A normal result is usually above 80% of predicted values for age, gender, race, and height. Spirometry should be performed by expert personnel who are knowledgeable of the American Thoracic Society guidelines for standardized pulmonary function test (Culver et al., 2017). Of note, for

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Overview of pediatric asthma

children <5 years of age, impulse oscillometry is often used to diagnose airway obstruction, which measures airway resistance and reactance as surrogates of airway obstruction. Asthma severity is assessed either retrospectively from the level of medications used to control symptoms or by the frequency of day and night symptoms (i.e., frequency of using quick-relief medications such as albuterol and levalbuterol), the number of exacerbations per year, and lung function impairment. Asthma treatment guidelines (National Asthma Education and Prevention Program, 2007) use a stepwise approach for recommending long-term controller medications based on classification of severity (i.e., mild intermittent, mild persistent, moderate persistent, and severe persistent).

Asthma medications Quick-relief and long-term control medications are used for asthma control (Table 2.1). Quick-relief medications, or short-acting beta-agonists, TABLE 2.1 Asthma medications. Medication type

Examples

Function

Inhaled short-acting beta-agonists

Albuterol: ProAir HFA, ProAir RespiClick, Proventil HFA, Ventolin HFA Levalbuterol: Xopenex HFA

Relax the airway muscles and provide immediate symptom relief Used as needed (PRN)

Inhaled cholinergic receptor antagonists

Ipratropium bromide HFA: Atrovent HFA

Quick-relief medication

Inhaled corticosteroids

Flovent HFA, Qvar HFA

Combined ICS with long-acting beta-agonists

Advair HFA and Diskus, Symbicort HFA and Diskus

Decrease airway inflammation Used daily for prevention of asthma symptoms Controller/maintenance medication

Leukotriene modifiers

Montelukast (singulair)

Immunomodulators

Omalizumab

Adjunctive therapy directed against the immune mechanism behind some asthma phenotypes (e.g., against IgE molecule) For children older than 6 years of age

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are inhaled bronchodilators (e.g., albuterol and levalbuterol) used as needed that relax the airways, smooth muscles, and prompt symptom relief. Anticholinergics (e.g., ipratropium bromide) are inhaled cholinergic receptor antagonists that are alternative bronchodilators for shortacting beta-agonists. Long-term controller medications are used daily to control persistent asthma and the airway inflammation underlying asthma pathophysiology. Inhaled corticosteroids are the most effective antiinflammatory therapy for long-term asthma control, but other medications such as immunomodulators are used to treat airway inflammation as adjunctive therapy. Systemic steroids (e.g., prednisone) are used in short courses for the treatment of acute symptom exacerbation.

Asthma self-management Asthma self-management includes four main components: monitoring of symptoms, education, control of triggers, and medication management (National Asthma Education and Prevention Program, 2007). National asthma management guidelines indicate that a partnership between the individual with asthma and provider is necessary for effective asthma management (National Asthma Education and Prevention Program, 2007). Self-management education should occur during regular clinic visits with the healthcare provider and include asthma physiology, information on medications, and assessment of youth self-management skills (e.g., how to take medications, self-monitoring of symptoms, use of an asthma action plan). The identification and avoidance of asthma triggers, the precipitating factors that cause asthma symptoms following exposure, plays a critical role in asthma prevention and control. Common asthma triggers include viral upper respiratory infections, exercise, changes in weather, stress, and exposure to irritants such as secondhand smoke and strong smells. Finally, youth should use medications as prescribed. Daily adherence to long-term controller medications, most commonly inhaled corticosteroids, is critical for achieving adequate asthma control and reducing the impact of asthma on an individual’s quality of life (National Asthma Education and Prevention Program, 2007). Despite the longstanding availability of effective medications, adherence to inhaled corticosteroids among youth with asthma is consistently low. Youth take less than 50% of their prescribed doses based on objectively measured data of inhaled corticosteroids using electronic tracking devices (Bender, 2016; Morton, Everard, & Elphick, 2014; Walders et al., 2005). In addition to low rates of adherence, the remaining components of self-management tend to be complex and arduous for youth and families. Youth may encounter difficulties with avoiding exacerbation triggers and symptom perception (Hood, 2005; Janssens, Verleden, De Peuter, Van

Evidence-based assessment

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Diest, & Van den Bergh, 2009), low asthma knowledge (Branstetter-Rost, Berg, Rapoff, & Belmont, 2010), and inconsistent access to care (Flores et al., 2009). Suboptimal pediatric asthma self-management is also associated with a range of poor health outcomes including increased asthma exacerbations, hospitalizations, and healthcare costs; missed school days; activity limitations; and risk of mortality (Akinbami et al., 2016; Anderson, Szefler, & Anderson III, 2015; National Asthma Education and Prevention Program (NAEPP), 2007).

Evidence-based assessment Assessment of asthma self-management components is critical to inform asthma care and intervention strategies with the majority of research focused on inhaled corticosteroid adherence. Clinician judgments about inhaled corticosteroid adherence and overall selfmanagement tend to be suboptimal, and healthcare providers often have trouble identifying which individuals are nonadherent (Burgess, Sly, Morawska, & Devadason, 2008). A variety of self-management assessment techniques exist, including objective and subjective methods. Average adherence when measured via objective monitors is around 50%, whereas subjective methods reveal adherence rates greater than 80% (Bender et al., 2000).

Objective methods Electronic monitoring Electronic device monitors including Doser, Propeller Health, SmartTouch, and T-Haler (Kikidis, Konstantinos, Tzovaras, & Usmani, 2015) are increasingly used to assess adherence to asthma medications (Burgess et al., 2008; Rand et al., 2012; Spaulding, Devine, Duncan, Wilson, & Hogan, 2012). These devices are attached to inhaled corticosteroids and count the number of times the inhaler is actuated. Electronic device monitoring can increase cost to assessing adherence; however, benefits include the ability to identify patterns of use and assess doseeresponse relationships (Riekert & Rand, 2002). Pharmacy/medical records Refill data from pharmacy, insurance, or medical records can be used to draw inferences about self-management patterns (e.g., healthcare system interactions) and medication adherence (Rand & Wise, 1994; Tan et al., 2009). The medication possession ratio, the number of times a prescription was filled divided by the period of time youth were prescribed the medication (Engelkes, Janssens, de Jongste, Sturkenboom, & Verhamme,

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2015), is used to assess asthma medication adherence; however, they do not guarantee medication use despite being helpful for understanding medication possession (Hess, Raebel, Conner, & Malone, 2006).

Subjective methods Self-report A number of validated self-report questionnaires assess youth asthma knowledge and engagement in appropriate self-management behaviors. For example, the Knowledge, Attitude, and Self-efficacy Asthma Questionnaire assesses asthma education, health beliefs, and confidence in managing asthma (Wigal et al., 1993). The Asthma Self-management Questionnaire assesses a variety of self-management components including proper use of inhalers, differences between rescue and controller medications, and avoidance of triggers (Mancuso, Sayles, & Allegrante, 2009). The Asthma Responsibility Questionnaire assesses the division of family responsibility for asthma management tasks (McQuaid et al., 2001), and the Asthma Routines Questionnaire assesses family routines associated with asthma management (Fiese, Wamboldt, & Anbar, 2005). The Pediatric Inhaler Adherence Questionnaire (Martinez, Sossa, & Rand, 2007), the Medication Adherence Report Scale for Asthma (Cohen et al., 2009), and medication diaries are commonly used in the context of clinical care to assess adherence since they are cost-effective and relatively easy to obtain. However, these measures tend to overestimate adherence (Brown & Bussell, 2011; Gillissen, 2007; Krishnan et al., 2012); their accuracy degrades in individuals with lower education and when requesting information across long periods of time and requesting increasingly detailed information (Bender, 2016). Self-report assessment is best when it is used in conjunction with more objective and valid asthma adherence measures (Rand et al., 2012). Interviews Interviews potentially allow for more depth and flexibility in the assessment of asthma self-management in research and clinical settings. The Disease Management Interview-Asthma (Modi & Quittner, 2006) involves separately asking children and their caregivers when, how often, and how much of each medication was taken. The Family Asthma Management Systems Scale is a semistructured interview that allows families to discuss aspects of asthma management including knowledge, medication adherence, response to symptoms, management of environment and triggers, and relationship with a provider (Klinnert, Gavin, & McQuaid, 1997).

Guiding theories in asthma self-management

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Guiding theories in asthma self-management A variety of broad health behavior theories apply to pediatric asthma with Self-determination Theory (Ryan, Patrick, Deci, & Williams, 2008), Social Cognitive Theory (Bandura, 1998), and Self-regulation Theory being the most common. The recently developed Pediatric Self-management Model (Modi et al., 2012) also applies to provide a synthesis of influential factors related to asthma self-management at multiple levels. Finally, several theories specific to asthma such as the Adolescent Asthma Selfmanagement Model (Mammen & Rhee, 2012) and the Multilevel Asthma Disparities Model (Canino, McQuaid, & Rand, 2009) are commonly used to understand asthma self-management behaviors.

Self-determination Theory Self-determination Theory posits that autonomy, competence, and relatedness are key factors for youth to achieve motivation for behavior change. To improve medication adherence, individuals must identify the importance of the behavior, develop competence and confidence in completing self-management tasks, and feel a connection to healthcare providers (Ryan et al., 2008). Adherence to asthma medications is significantly associated with the Self-determination Theory variables of importance, confidence, and family routines in African American adolescents (Bruzzese, Idalski Carcone, Lam, Ellis, & Naar-King, 2014). That is, asthma adherence rates are higher when individuals feel that aspects of self-management are important. Adherence is also higher when they have confidence about the components of self-management and when behaviors are integrated into family routines (Bruzzese et al., 2014). Accordingly, Self-determination Theory could serve as a framework for understanding higher rates of nonadherence among adolescents as compared with young children. Adolescents often have increased desire to manage asthma independently (McQuaid et al., 2001), but they may lack understanding of the importance of necessary behaviors.

Social cognitive theory Social Cognitive Theory suggests that self-efficacy, or belief in one’s ability to accomplish a specific task, is the pathway through which most behavior change occurs (Bandura, 2004). Learning develops through a social context of reciprocal interactions between person, environment, and behavior (Bandura, 2004), and self-efficacy in self-management behaviors impacts the decision to engage in these behaviors, motivation to do so, and perseverance when barriers are encountered (Zebracki, Drotar, 2004). Self-efficacy is associated with medication adherence,

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help-seeking behaviors, and overall asthma control in youth with asthma (Lavoie et al., 2008; Zebracki et al., 2004).

Self-regulation Theory Self-regulation Theory stems from Social Cognitive Theory and posits that disease management strategies are learned through continuous and reciprocal self-regulatory processes, namely observation, judgment, and reaction (Clark, Gong, & Kaciroti, 2001). When applied to asthma, caregiver abilities to effectively observe, judge, and react to a child’s asthma symptoms are associated with increased use of asthma management strategies (e.g., reducing exposure to triggers, giving appropriate medications, seeking help when necessary) (Clark et al., 2001). Monitoring patterns in asthma control and medication is also presented as a component in improving asthma self-management (Sage et al., 2017).

Pediatric self-management model The Pediatric Self-management Model describes associations among self-management, adherence, and disease outcomes by considering behaviors that occur within four domains: individual, family, community, and the healthcare system (Modi et al., 2012). Asthma self-management among adolescents is influenced by factors encompassing all domains of the Pediatric Self-management Model. Modifiable influences of asthma management at the individual level include youth perception of asthma severity, belief in efficacy of medication, knowledge of asthma symptoms and triggers, and remembering to take medications. Additional modifiable influence includes youths’ forgetfulness about taking their medication (Lee et al., 2015; Naimi et al., 2009), varying beliefs in how medication works (Joseph et al., 2010), embarrassment about taking their medications (Wamboldt, Bender, & Rankin, 2011), oppositional behavior, and difficulties with time management (Modi & Quittner, 2006). Unwillingness to give up enjoyable activities and “trying to forget” that they have asthma are also barriers to self-management that may reduce trigger avoidance or appropriate response to symptoms (Rhee, Belyea, Ciurzynski, & Brasch, 2009). Age is the most commonly reported nonmodifiable individual risk factor for suboptimal adherence, with older adolescents being less adherent (Butler & Cooper, 2004; McQuaid et al., 2012; Wamboldt et al., 2011). Research on sex differences in adherence is inconclusive, with some studies finding no differences (Berg, Rapoff, Snyder, & Belmont, 2007; McQuaid, Kopel, Klein, & Fritz, 2003; Naimi et al., 2009) and others finding that females are more adherent (Butler & Cooper, 2004; Sawicki

Guiding theories in asthma self-management

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et al., 2010). There are also mixed findings about asthma severity and adherence (Sawicki et al., 2010; Wood et al., 2006). Family-level correlates, such as asthma knowledge, socioeconomic status, and race/ethnicity, are common factors influencing self-management in pediatric asthma (Gray et al., 2018). Some factors are modifiable and can be targeted via interventions to improve self-management. For example, lower asthma knowledge is associated with lower rates of adherence (Butler & Cooper, 2004; Celano et al., 2010; Ellis, King, & NaarKing, 2016), including inaccurate beliefs about medications (Armstrong, Duncan, Stokes, & Pereira, 2014; McQuaid et al., 2012) and concerns about medication side effects (Handelman, Rich, Bridgemohan, & Schneider, 2004). Concerns about limitations on physical activity also contribute to suboptimal response to symptoms or trigger avoidance (Mansour, Lanphear, & Dewitt, 2000). Poorer family functioning is also associated with worse asthma management (Bender et al., 2000). Findings are mixed on the influence of caregiver psychological functioning on medication adherence (Gray et al., 2018). Although caregiver stress is associated with increased adherence in some studies (DeMore et al., 2005), depressive symptoms are associated with lower rates of adherence (Bartlett et al., 2004; Celano et al., 2010). Greater caregiver involvement, including reminding children to take medications, monitoring asthma symptoms, and input in asthma treatment plan, is also associated with improvements in self-management (Bartlett et al., 2004; Wamboldt et al., 2011). However, a variety of family factors are nonmodifiable. Families from racial/ethnic minority populations and those with limited English proficiency are at risk for lower rates of adherence (Martin et al., 2012; OrrellValente et al., 2008). However, many studies have not found a relationship between caregiver education level and adherence (Berg et al., 2007; Martin et al., 2012), whereas some show that higher caregiver education is associated with increased rates of adherence (Branstetter-Rost et al., 2010). There are also mixed findings about associations between socioeconomic status (SES) and adherence, with some finding no association (Berg et al., 2007; Naimi et al., 2009) and others finding associations between low SES and low rates of adherence (Wamboldt et al., 2011). Familial financial barriers also negatively impact self-management due to inability to purchase medications or make recommended environmental changes (e.g., replacing carpet) (Mansour et al., 2000). Community-level influences. Improving school-based medication access and healthcare provider involvement in a child’s asthma can reduce barriers to effective asthma self-management (Penza-Clyve, Mansell, & McQuaid, 2004); however, more research is needed on nonmodifiable community factors that may be related to self-management, such as air pollution and availability of pharmacies (Gray et al., 2018).

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At the healthcare system level, provider factors such as engaging families in collaborative discussions, involving them in decision-making, and increasing amount of time spent with individuals with asthma are linked to better asthma self-management (Gray et al., 2018) as is including caregiver input into a child’s asthma treatment plan (Sleath et al., 2012). At the nonmodifiable level, decreased access to healthcare resources is associated with lower rates of adherence (Sawicki et al., 2010). For example, urban minority youth with asthma experience decreased access to specialty care; lack of an asthma plan; increased asthma symptoms, exacerbations, missed school days; and hospitalizations (Flores et al., 2009).

Adolescent asthma self-management model The Adolescent Asthma Self-management Model defines selfmanagement of asthma as a set of factors encompassing four domains of behavior: symptom prevention, symptom monitoring, acute symptom management, and communication (Mammen & Rhee, 2012). Symptom prevention refers to avoiding triggers, adherence to medications, and attending follow-up appointments. Symptom monitoring includes youth perception of asthma symptoms, use of a peak flow meter, a handheld device used to measure airflow expiration, and use of a daily symptom diary. Acute symptom management involves adherence to an asthma action plan, which should detail signs and symptoms that indicate appropriate use of quick-relief medications, urgent healthcare, and activity modifications. Finally, communication with important others is posited as a key component to optimal self-management. As adolescents become increasingly more responsible for asthma care, poor communication with family, friends, and healthcare providers may compromise their ability to effectively manage their asthma (Mammen & Rhee, 2012).

Multilevel asthma disparities model The Multilevel Asthma Disparities Model suggests that differences in asthma management can stem from multiple interrelated factors within the healthcare and individual/community systems (Canino et al., 2009). Contributory healthcare domain factors include healthcare policies, operation of the healthcare system, and provider-level variables (e.g., bias/stereotyping, training experience, prescription practices), whereas individual/community factors include the socioenvironmental context (e.g., poverty, pollution, environmental stress) and the individual/family context (e.g., biological factors, health literacy, health beliefs) (Canino et al., 2009). The Multilevel Asthma Disparities Model suggests that disparities arise when factors within these domains, such as individual beliefs about medication, barriers in access to care, and a lack of cultural

Evidence-based interventions and promising interventions

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competence among providers, interact with one another. The interaction among these factors then impacts the process of care that individuals receive (access and quality) and treatment outcomes (e.g., quality of life, asthma control) (Canino et al., 2009). Components of the Multilevel Asthma Disparities Model are well substantiated in pediatric asthma (Canino et al., 2009). Asthma medication adherence is complex and influenced by the individual, family, provider, and healthcare system, and medication beliefs vary based on racial and ethnic background. At the individual or caregiver level, beliefs about medications may influence whether or not the child is taking their medication; caregivers worry about dependence, medication complications, and side effects (Koinis-Mitchell et al., 2008). For example, Latino caregivers tend to report more concerns about the use of daily asthma medications, and they typically express a stronger preference for natural treatment remedies compared with nonminority caregivers (McQuaid et al., 2009). These medication beliefs can be harmful for children with asthma since delay in delivery of rescue medication or failing to adhere to inhaled corticosteroids can have serious health consequences. Within the community, ethnic minority families are more likely to live with worse built environment conditions (Hood, 2005), which reduces the ability to avoid triggers.

Evidence-based interventions and promising interventions Effective interventions for improving asthma self-management typically leverage intervention frameworks that draw from one or more of the previously discussed theories to target common barriers to effective selfmanagement. Asthma management guidelines recommend intervention at several ecological levels (National Asthma Education and Prevention Program, 2007), and thus, interventions often aim to address multiple barriers to adherence (e.g., individual and family factors). Asthma interventions that use a behavioral approach (Mosnaim, Akkoyun, Eng, & Shalowitz, 2017) to increase self-management behaviors, many of which are multicomponent, are described next. It is important to note that the asthma intervention literature is extensive, and thus, this section should be viewed as highlights of asthma management interventions.

Self-management education Self-management education interventions are effective in increasing rates of medication adherence, resulting in clinically significant health improvements among youth with asthma. A Cochrane review of pediatric self-management education interventions revealed reduced symptoms and symptom-related impairment within 6 months and improvements in

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healthcare utilization within 1 year (Wolf, Guevara, Grum, Clark, & Cates, 2010). Key components of these interventions include the use of asthma action plans, training in self-monitoring of symptoms, and regular followup appointments with medical providers (Gibson et al., 2003).

Family-based interventions Multisystemic therapy, initially developed to target behavior problems in youth, may be effective for improving asthma management and lung function among children with asthma and oppositional behaviors (NaarKing et al., 2014). Home-based interventions focused on limiting environmental factors that contribute to asthma symptomatology are effective in reducing asthma symptoms and improving quality of life (Crocker et al., 2011). Additionally, collaborative relationships among caregivers and children are important to achieving effective asthma management. Caregivereyouth teamwork interventions are efficacious at improving medication adherence and health outcomes among youth with asthma, as well as helping youth take more responsibility in caring for their asthma (Duncan et al., 2013).

Clinic-based interventions Asthma action plans (Inkelas, Garro, McQuaid, & Ortega, 2008; Marosi & Stiesmeyer, 2001), peak flow meter education (Feldman et al., 2012), self-management education (Marosi & Stiesmeyer, 2001; Rice et al., 2015), and adherence feedback (Rohan et al., 2013; Spaulding et al., 2012) within the healthcare system are associated with increased adherence. Other healthcare factors that improve adherence are refill reminder phone calls and Internet-based care management and education programs (Bender et al., 2015). Electronic monitoring is used as part of interventions to improve and maintain medication adherence when combined with feedback from providers, along with improving inhaled corticosteroid inhaler technique, reducing excess use of rescue inhalers, and increasing lung function among youth (Spaulding et al., 2012). Training pediatric healthcare providers to conduct monitoring interventions that focus on problem-solving and feedback for increasing adherence in asthma is feasible and effective (Rohan et al., 2013). Interpersonal cognitive factors such as self-efficacy and motivation are also barriers to asthma medication adherence, especially in adolescents (Gillissen, 2007; Mammen & Rhee, 2012). Motivational interviewing is a patient-centered technique that includes empathetic listening to facilitate change talk, collaboratively helping the individual develop discrepancies between their actions and values or goals, rolling with the individual’s resistance to change, and supporting the individual’s self-efficacy for

Evidence-based interventions and promising interventions

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change (Riekert, Borrelli, Bilderback, & Rand, 2011). Motivational interviewing is used to help increase youth and caregiver motivation to engage in self-management behaviors, such as adhering to prescribed medications (Riekert et al., 2011), and can be used during medical appointments or brief consultations (Lundahl et al., 2013).

School-based interventions School-based programs such as self-management interventions (Bruzzese et al., 2011; Horner, Brown, Brown, Rew, & Brown Sharon, 2016) and improving accommodations at schools (Penza-Clyve et al., 2004) improve medication adherence. A systematic review of school-based educational interventions found significant improvements in asthmarelated hospitalizations, emergency department visits, days of restricted activity, and quality of life in youth following intervention (Harris et al., 2018). Using peer asthma educators also increases adherence (Garbutt et al., 2015), whereas increased stigma about asthma and medication use is associated with lower adherence (Penza-Clyve et al., 2004; Wamboldt et al., 2011).

Technology-based interventions Daily medication reminder system interventions can decrease forgetting medications and improve time management skills. Reminder-based interventions include reminders in the form of text messages, phone calls, and audiovisual reminder devices with varying frequency of reminders and their content. Regardless of variations in methodology, reminder-based interventions increase medication adherence among individuals with asthma (Tran, Coffman, Sumino, & Cabana, 2014). With advancing technology and increasing availability of smartphones, mobile technology interventions (e.g., text messaging, smartphone applications) are an appealing intervention modality for individuals, families, and providers. Components of these interventions often involve education, action planning, self-monitoring, feedback, and reminder prompts or cues. Clinically significant effects of mobile technology interventions on controller medication adherence and clinical outcomes occur when compared with control groups, and similar effects occur when compared with paper-based intervention (Miller, Schu¨z, Walters, & Walters, 2017). Web-based platforms, computer programs or games, and interactive voice response systems demonstrate preliminary efficacy in improving adherence in children with asthma using similar strategies (e.g., education, reminders, self-monitoring and feedback; Chan et al., 2018).

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Case study Thomas is a 16-year-old male with severe persistent asthma. Thomas is prescribed an inhaled corticosteroid/long-acting beta-agonist daily preventive controller medication and short-acting beta-agonist as needed. Thomas has used oral corticosteroids for asthma exacerbations a few times within the past year and was recently hospitalized. He resides with his mother; his father has not been actively involved in his upbringing for several years. Thomas’ mother has tried numerous strategies to engage Thomas in following his asthma action plan and for him to be more active in his self-management including removing privileges, providing him reminders to take his medications, and emphasizing the importance of taking his asthma management regimen seriously to avoid future exacerbations. Thomas’ behavior has remained unchanged during the past several years. Thomas recently presented to a follow-up appointment at the outpatient pediatric pulmonology subspecialty clinic. Spirometry testing revealed that his lung function was poor (i.e., FEV1 ¼ 60% predicted), and his responses on the Asthma Control Test (Nathan et al., 2004) indicated that his asthma was interfering with multiple domains of his life (e.g., frequent activity limitations, waking up during the night because of symptoms, using short-acting beta-agonist for symptom control). Thomas was disengaged during the appointment and ambivalent about making any changes related to following his asthma regimen. Thomas’ ongoing pattern of asthma self-management difficulties led the medical team to refer him to a pediatric psychologist. The psychologist used motivational interviewing as an initial method to align with Thomas in an attempt to engage him in his asthma care. The therapist began by listening to his ambivalent feelings and frustrations regarding his asthma self-management responsibilities. He expressed wanting to be autonomous with his care and identified that he seems to always be in conflict with his mother surrounding his asthma care. The psychologist reinforced Thomas’ change talk (e.g., desire to reduce conflict with his mother) and noted discrepancies between his reluctance to engage in asthma self-management behaviors and his goals (e.g., reduce how often he misses school, be able to play soccer more often). Subsequently, Thomas agreed to take part in family sessions that focused on collaborative goal setting. Thomas and his mother learned the importance of having a clear delineation of responsibility for Thomas’ asthma regimen (e.g., who is responsible for ensuring that Thomas takes his evening inhaled corticosteroid/long-acting beta-agonist dose). They worked together to identify adherence goals that were specific, objectively measurable, attainable, and time-limited. This included having Thomas track his inhaled corticosteroid/long-acting beta-agonist usage each

References

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evening. His mother initially checked in with Thomas to ensure he took his medication and reinforce his efforts. She gradually reduced her checking across time as Thomas became consistent in taking his evening medication dose. Additionally, Thomas earned privileges (e.g., having a friend over to play video games). Time was also spent reviewing how to collaboratively problem-solve strategies that could be implemented when they encountered barriers. Thomas’s self-efficacy for asthma selfmanagement and his adherence to his inhaled corticosteroid steadily increased across treatment.

Emerging areas and conclusions There is a pressing need for asthma self-management interventions that are cost effective, translatable, and concurrently individually tailored to make substantial changes at a broad level (Bender, 2016). Examples of cost-effective interventions include healthcare provider training interventions that reduce asthma morbidity, demonstrate a return on investment, and can be broadly disseminated to primary care providers (Cloutier, Grosse, Wakefield, Nurmagambetov, & Brown, 2009). Ensuring that asthma self-management interventions are implemented at multiple levels is an ongoing area of emphasis especially recently established guidelines for school-based asthma management (Lemanske et al., 2016). Furthermore, using well-known models (e.g., Reach Effectiveness Adoption Implementation Maintenance; RE-AIM) to guide implementation science efforts in pediatric asthma and using participatory design methods are encouraged (Wallerstein & Duran, 2006). Patient-centered care provides a promising framework because it takes cultural background into account while focusing on individual needs, desired health outcomes, and barriers to adherence (Bender, 2017). An increased focus on tailoring interventions for specific youth and their family members and using shared decision-making may help increase self-management in asthma (Sleath et al., 2011).

References Akinbami, L. J., Simon, A. E., & Rossen, L. M. (2016). Changing trends in asthma prevalence among children. Pediatrics, 137(1). https://doi.org/10.1542/peds.2015-2354. Anderson, W. C., 3rd, Szefler, S. J., & Anderson, W. C., III (2015). New and future strategies to improve asthma control in children. The Journal of Allergy and Clinical Immunology, 136(4), 848e859. https://doi.org/10.1016/j.jaci.2015.07.007. Armstrong, M. L., Duncan, C. L., Stokes, J. O., & Pereira, D. (2014). Association of caregiver health beliefs and parenting stress with medication adherence in preschoolers with asthma. Journal of Asthma, 51(4), 366e372. https://doi.org/10.3109/02770903.2013. 876431.

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