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A proposed standardized approach to studying attrition in pediatric weight management
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Original Article
A proposed standardized approach to studying attrition in pediatric weight management Nicholas D. Spence a,b , Joseph A. Skelton c,d,e , Geoff D.C. Ball f,g,∗ a
Department of Sociology, University of Toronto, Toronto, ON, Canada Interdisciplinary Center for Health and Society, University of Toronto, Toronto, ON, Canada Department of Pediatrics, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, United States d Brenner FIT (Families in Training) Program, Brenner Children’s Hospital, Medical Center Boulevard, Winston-Salem, NC, United States e Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, United States f Department of Pediatrics, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, Canada g Pediatric Centre for Weight & Health, Stollery Children’s Hospital, Alberta Health Services, Edmonton, AB, Canada b c
a r t i c l e
i n f o
Article history: Received 18 January 2018 Received in revised form 29 July 2019 Accepted 20 November 2019 Keywords: Attrition Pediatric obesity Intervention Weight management
a b s t r a c t Pediatric obesity is a major public health issue. Lifestyle and behavioral interventions are the foundation of pediatric weight management; however, intervention effectiveness is compromised when families (children, youth, and/or parent[s]) discontinue care prematurely. Intervention attrition minimizes the potential health benefits derived from interventions, results in inefficient use of health services resources, and can magnify health disparities. Most attrition research in pediatric weight management has been descriptive, highlighting the need to advance the field, both academically and clinically. Herein, we propose a standard approach to studying attrition in pediatric weight management interventions to enhance our understanding, elevate the quality of research, enable study-to-study comparisons, and inform strategies designed to mitigate its impact. We focus on three issues. First, “Conceptualization and operationalization,” whereby the processes underlying attrition from interventions should be decomposed into clinically important phases that are defined based on intervention characteristics. Relatedly, theoretically relevant variables should be identified with different mechanisms driving attrition in each phase. We propose a matrix of attrition, a tool designed to delineate the relevant stages of attrition and associated variables of analytical value. Second, “Pre-study” underscores the value of developing a plan to study attrition a priori rather than post hoc, including variable and sample size considerations, which broadens the range and quality of analysis. Finally, “Post-study” emphasizes comprehensive reporting of attrition, outlines typical comparisons of analytical interest, and statistical techniques used to handle missing data. Implications for clinical practice in pediatric weight management are discussed. Clinical Trial Registration: Not applicable. © 2019 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Introduction Pediatric obesity is a global public health concern [1]. In Canada [2] and the United States [3], approximately one-third of children are living with overweight or obesity, a condition that is often accompanied by a variety of negative health consequences [4–7]. Lifestyle and behavioral interventions that take
Abbreviations: RCT, randomized controlled trial; BMI, Body Mass Index; GEM, Grid-Enabled Measures; ITT, intention-to-treat. ∗ Corresponding author at: 4-515 Edmonton Clinic Health Academy, University of Alberta, 11405-87th Ave, Edmonton, AB T6G 1C9, Canada. E-mail address: [email protected] (G.D.C. Ball).
a family-based approach represent the cornerstone of managing pediatric obesity and have demonstrated favorable treatment outcomes [8–10]. Despite their potential, attrition from interventions designed for managing pediatric obesity is commonplace. Indeed, up to 83% of families (child, youth, and/or parent[s]) discontinue care prematurely [11], across interventions that have different theoretical frameworks and proposed mechanisms of change (e.g., cognitive behavioral therapy), settings (e.g., outpatient, multidisciplinary pediatric weight management clinics), age ranges (e.g., 6–12 years old), units of intervention focus (e.g., child/youth and parent/primary caregiver, parent/primary caregiver primarily, or child/youth primarily), and outcomes (e.g., weight status and physical activity) [11–13]. In fact, many studies have reported that
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most participants drop out prior to treatment completion [11–13]. The implications of these findings are far reaching. From a clinical perspective, attrition limits the benefits that families can potentially derive from care, may magnify existing health disparities, and has a negative impact on clinicians’ time and efficiency. From an organizational standpoint, health care systems are negatively impacted by the influence of attrition on resource allocation (e.g., clinic space) that could be used by patients and families who are engaged actively in their care. With respect to scientific and academic issues, a high level of drop out can undermine internal and external validity of research findings intended to build the evidence base for managing pediatric obesity. In recent reviews [11,14], we highlighted a lack of consistent findings and definitions across studies of attrition in pediatric weight management. These data revealed substantial diversity in how attrition was conceptualized and operationalized, assumed homogeneity of factors that determined attrition across different types and phases of interventions, and uncovered a shortage of attrition research performed beyond the United States [11,12]. Several categories of variables have been identified as potential drivers of attrition, including demographic, anthropometric, lifestyle, psychological, parent/family, health services, and logistical barriers, but there is little consensus in the literature [11,12,15,16], as many studies have been retrospective, relying on whatever data were available. Based on the evidence to date and our academic and clinical experiences in leading pediatric weight management clinics, we believe there is value in proposing a standardized approach to examining attrition in pediatric weight management. Systematic frameworks have been published to guide the evaluation of weight management interventions [17], but to date, the degree of attention given to attrition has been modest. We believe that a standardized approach will lead to a greater understanding of, and appreciation for, attrition as well as developing, implementing, and testing strategies designed to mitigate attrition so that children/youth and families can derive the greatest possible benefits from pediatric weight management. In writing this paper, our objectives were to (i) describe foundational issues that should be considered by researchers when studying attrition and (ii) provide a framework and example based on real-world experience to share relevant insights with researchers and clinicians working in this area. Step 1: conceptualizing & operationalizing attrition In the pediatric weight management literature, attrition has been defined in numerous ways [11,14,18]. In this regard, we believe that it is instructive to begin by distinguishing between the conceptual definition and operationalization of attrition. The conceptual definition of attrition includes failing to complete any or all parts of a pediatric weight management program, as discussed below (e.g., recruitment, pre-intervention, intervention delivery, and follow-up). The operationalization of attrition is specific to the research context and study focus, which are key sources of variation between studies. For example, a randomized controlled trial (RCT) to study intervention effectiveness may focus on the proportion of participants that fails to receive the required ‘dose’ of an intervention (e.g., number of behavioral change intervention sessions attended) to derive benefits, while a cost-effectiveness study may examine the economic costs of attrition to clinics at pre-intervention (e.g., missed appointments and assessments). Indeed, the heterogeneity of existing research in attrition in pediatric weight management has led to a wide range of estimates on its magnitude and predictors. To date, research has been characterized by assessments of available baseline data
for interventions on completers versus non-completers [19] and self-reported reasons for completing [20] or prematurely discontinuing an intervention [21,22]. Moreover, the choice of variables researchers have included in their analyses and the associated effects are assumed to be homogeneous across different target populations (e.g., parents only versus parent-child dyads), phases (e.g., earlier versus later intervention stages), durations (e.g., 12week versus 12-month), and visit frequencies (e.g., weekly versus monthly). The assumed singular pattern of attrition is inconsistent with the design, delivery, and evaluation of interventions that differ in many practical and conceptual ways. We believe that the processes underlying attrition from interventions should be conceptualized based on clinically important phases. For instance, a clinical phase can be defined based on the characteristics of the intervention, including theoretical underpinnings, outcomes of interest, intervention elements (e.g., duration, audience, intensity, setting), and retention strategies applied (if any). After considering these issues, predictors of attrition could be identified and assessed for each phase based on whether they are theoretically-informed as well as appropriate and feasible. To this end, the matrix of attrition in pediatric weight management (Table 1) is meant to be instructive. While not exhaustive, the columns capture distinct phases of a pediatric weight management intervention: recruitment, pre-intervention, intervention delivery, follow-up, and analysis. Sub-phases within each phase with analytical value can be incorporated into the matrix. For example, ‘intervention delivery’ could include multiple phases with different foci (diet, physical activity) over an extended period, each amenable to attrition analysis. Similarly, ‘follow-up’ could include post-intervention observations at multiple time points over a specified period; thus, one could indicate 6- and 12-months postintervention as clinically important sub-phases of ‘follow-up’, each subject to individual attrition analyses. We begin by defining the key phases of the intervention by examining the ‘characteristics of the intervention’ provided in Table 1. Recruitment represents a distinct phase of the intervention. Often, especially in order to access specialized, multidisciplinary health services, children/youth are referred for weight management by a physician or other health care professional. Children/youth and parents then decide to enroll and may need to satisfy some criteria (e.g., age, parent commitment to participate, weight status) in order to participate. Unfortunately, the limited availability of data for those families who decline participation, which can be as high as 60% [23], limits the extent to which comparisons can be made for an analysis of attrition at this phase. Pre-intervention is a non-intensive therapeutic phase of an intervention, usually with enrolled participants required to complete assessments before sessions commence. This stage also marks the first occasion when participants contribute information, such as demographic, anthropometric, cardiometabolic risk factors, lifestyle behaviors, and psychosocial health of children/youth and parents, which can be burdensome and time-consuming, often spanning more than one clinical appointment. Next, the delivery of the intervention is the most intensive phase along this continuum, with families required to attend and participate in sessions on a regular basis. Because some intervention modalities (e.g., cognitive behavioral therapy) [24] require participants to complete tasks between sessions (e.g., develop and implement goals; plan to overcome barriers related to behavior change; manage ambivalence among other family members in making positive lifestyle changes), this phase can be demanding and challenging, especially in the absence of perceived success or demonstrable improvements in weight or health status. Follow-up, including assessments of outcome measures at post-intervention
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Table 1 Attrition matrix in pediatric weight management, including examples of characteristics to document for conceptualizing, operationalizing, and predicting attrition. Setting: outpatient, multidisciplinary pediatric weight management clinic Target audience: children with obesity and their parent(s) Child age: 6–12 years old Theoretical frameworks: cognitive behavioral therapy and family systems theory Outcomes: child weight status (primary); child cardiometabolic risk factors, child and parent lifestyle habits, child and parent psychosocial health, parenting style and practices (secondary) Mode of delivery: in-person, group-based Frequency of contact: weekly sessions offered for 16 consecutive weeks (4 months) Length of each session: 90–120 min Length of follow-up: 12 months following the completion of the 16 week intervention Data collection: 0 months (pre-intervention), 4 months (post-intervention), 10 months (6-months post-intervention), 16-months (12-months post-intervention) Retention strategies applied: reminder emails and/or phone calls before weekly sessions and data collection appointments Attrition measures (examples): number/proportion of intervention sessions attended; discontinued interventions prematurely (y/n); satisfaction
Intervention characteristics
Conceptualization & operationalization of (sub) phases
Recruitment
Pre-intervention
Eligible, but declined to participate
Enrolled, but did not complete pre-intervention assessments
Follow-up
Analysis
Failed to complete outcome assessments at post-intervention, 6- and/or 12-months post-intervention
Any missing data
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
Lifestyle (child/parent) Physical activity* Diet* Sleep*
√ √ √
√ √ √
√ √ √
√ √ √
√ √ √
Health (child/parent) Anthropometric* Psychological* Cardiometabolic*
√ √ √
√ √ √
√ √ √
√ √ √
√ √ √
Family Family structure* Family function* Stress (child/parent)* Parenting*
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
Health services Quality of service* Interventions* Logistics* Health service coverage* Expectations/satisfaction*
√ √ √ √ √
√ √ √ √ √
√ √ √ √ √
√ √ √ √ √
√ √ √ √ √
Follow up (non) completers: reasons for (non) completion √ √ Self-reported* √ √ Survey*
√ √
√ √
√ √
Variables Demographic (child/parent) Age* Gender Race/ethnicity Socioeconomic status*
Intervention delivery Attended zero sessions
*Indicates a potential dynamic variable that should be assessed for changes over time. √ Indicates the variable is available.
(e.g., 6- and 12-months post-intervention), requires relatively less of a commitment from families in relation to the regular delivery of intervention sessions. In this respect, the intervention and followup periods represent two distinct phases that may correspond to different drivers of attrition. The analysis phase identifies all cases with any missing data over the course of the intervention, which may be the basis for exclusion, although pitfalls of deleting cases with any missing data are well documented, with well-established statistical techniques available for dealing with this issue [25]. While we offer an example of how attrition can be conceptualized and operationalized using the matrix of attrition within the context of a typical intervention in pediatric weight management, other considerations (e.g., data availability, sample size) will also determine how attrition is examined.
Variables Based on our view of the literature [11,12,18,26–34], potential variables associated with attrition are indicated in Table 1. There are six potential categories and each of them spans a number of associated variables. The category entitled, “Follow-up (non) completers and completers: reasons for (non) completion” can include both self-reported and survey data that assess barriers and facilitators, including practical (e.g., logistics, family, school, work), intervention-specific (e.g., expectations, satisfaction, demands of intervention), and psychological (e.g., motivation, self-efficacy) 18,35–40]. Ideally, valid and reliable measures should be applied consistently across attrition studies. As seen in Table 1, potential variables associated with attrition may differ across intervention phases. The asterisk indicates
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potential dynamic variables that should be assessed for changes over time, which may subsequently affect attrition. In our example, in a typical cognitive behavioral therapy intervention, variables of interest that were measured are marked for each phase of the study, including recruitment, pre-intervention, intervention, follow-up, and analysis. Dynamic variables, such as children’s weight, may increase from pre-intervention (baseline) to followup (post-intervention), resulting in the family withdrawing from the study and an absence of outcome data post-intervention. Thoughtful study planning can ensure that potentially relevant variables related to attrition analyses are included. For example, ensuring that interventions are ‘patient- or family-centered’ can include engaging children/youth and families in the development and refinement of curricula [41]. On another note, recruitment may be from an electronic health record database with variables potentially related to non-participation readily available; however, participants choosing not to enroll could be based on complementary data (e.g., parental motivation for treatment and perceptions of children’s weight status) that needs to be collected independently. Additionally, research must go beyond merely identifying empirical associations and develop an understanding of the etiology of attrition, including the classification of mediator and moderator variables. This theory and hypothesis driven research would help to map the time course of attrition; however, issues including the sample size, distribution of responses, and degree and type of attrition at different phases will need to be considered. Theoretically-important variables should be identified given the content of the intervention and proposed mechanism(s) driving attrition. Given the lack of consistent findings in the literature [11,12], it may also be useful to draw on attrition research from other areas (e.g., adult weight management, asthma, chronic pain, mental health, addictions, headaches, cancer, diabetes) to inform this work [18,26–34]. For example, in a review of predictors of attrition from outpatient behavioral medicine programs for adults receiving treatment for a chronic condition, psychological and behavioral factors, particularly experiences and expectations related to weight loss efforts, were the most common predictors of attrition from weight loss interventions, despite a traditional focus on demographic variables, which may be collected more consistently across attrition-related studies [27]. Therefore, a focus on developing and using appropriate psychological and behavioral measures of attrition within pediatric weight management intervention research is a logical way to proceed. However, unlike the individualistic focus in adult weight management attrition research, psychological and behavioral measures must focus on children/youth and their families, including parents, caregivers, and siblings.
Step 2: understanding attrition by design An examination of attrition requires appropriate planning at the design phase of a study. While attrition has not been a primary outcome of interest in pediatric weight management interventions, a lack of consideration results in research with limited capacity to enhance understanding of the issue. To the best of our knowledge, we are unaware of any interventions or RCTs in the pediatric or adult obesity literature that have examined attrition a priori. Instead of simply relying on whatever data happen to be available post hoc, we recommend researchers consider the following:
1) Variables specific to attrition, which may or may not be relevant to the primary outcome of a study. These variables should be based on the growing body of work in the area [11,12], related literature [18,26–34,40], theory, and nature of the intervention.
Each phase of an intervention should identify both fixed (e.g., race/ethnicity) and dynamic (e.g., diet) variables for inclusion. 2) Sample size considerations for interventions are based on power calculations focused exclusively on the primary outcome of interest, such as BMI z-score. Inattention to power issues for variables in attrition analyses limits the ability to test effects of relevant variables. 3) Variables available for inclusion and sample size have consequences for theory-driven research, hypothesis testing, and the statistical models used in analyses; specification bias of models (omitted variables; incorrect functional forms [e.g., interaction effects], etc.); Type II error and statistical power; Type I error and the number of possible comparisons (statistical tests). Step 3: reporting & analysis Concerted efforts have been made to enhance the transparency and standardization of reporting data, a directive that has been operationalized through the use of standardized reporting guidelines and tools, many of which are available publically through the Equator Network (www.equator-network.org). Another relevant initiative called the Grid-Enabled Measures (GEM; https:// www.gem-measures.org/Public/Home.aspx) is a web-based platform designed to promote harmonization of data through the development of standardized measures that are a product of consensus in the scientific community. Despite improvements over time, there are notable gaps [42]; for example, in a recent review of attrition in pediatric weight management interventions, an inadequate description of studies was the most common factor in lowering quality appraisal ratings [11]. In addition, there is sub-optimal and incomplete reporting of RCTs in the field of obesity in general [43], which highlights the need to enhance the methodological rigor in planning, conducting, and reporting obesity research. The appropriate reporting of attrition in pediatric weight management interventions is necessary to compare, assess, and synthesize work in the area. In this respect, it is critical to report the degree and type (e.g., missing completely at random, differential attrition by treatment and control arm) of attrition [44], which is observed at each clinically important phase of the intervention. Moreover, analyses should report the relevant comparisons, which would typically include the following: • Completers versus non-completers with respect to baseline characteristics (e.g., gender, race/ethnicity) for different phases of the intervention; • Completers versus non-completers with respect to selfreported or surveyed reasons (e.g., satisfaction, logistics) for completion/non-completion at different phases of the intervention; • Completers versus non-completers with respect to dynamic variables (e.g., body weight, self-efficacy) at different phases of the intervention, which may change beyond baseline, having a direct influence on attrition. Dynamic variables should be assessed regularly and may occur outside of the data collection time points for variables related to non-attrition outcomes. Statistical techniques for dealing with missing data Missing data can come in different forms, including item non-response (i.e., participant provides incomplete data at data collection points) and unit non-response (i.e., participant does not provide any data at data collection points). For RCTs, an intentionto-treat (ITT) analysis is used to preserve the randomization process of all participants by including those who do not adhere as per the protocol as well as those with item non-response or unit non-
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response, inclusive of individuals withdrawing from the study. In terms of attrition, following up with non-completers to obtain outcome data is ideal, but often impractical. Consistent with ITT analysis, the use of advanced statistical techniques to handle missing data (e.g., multiple imputation and selection models) [25] in pediatric weight management intervention studies is recommended [45]. These models do, however, make assumptions about the missing data process; thus, as the evidence base on attrition develops, we anticipate that there will be improvements in the models. Financial and non-financial considerations to study attrition Practically, studying attrition requires varying degrees of participant and researcher burden, as well as costs associated with collecting additional data. Clinical research teams endeavor to maximize the collection of intervention data associated with primary and secondary outcomes; therefore, collecting additional information related to attrition may be burdensome. In some instances, relevant data may be available through electronic health records or collected as part of the intervention, while other data may only be obtained by trying to follow up with participants who dropped out, who may have a low commitment to pediatric weight management. Despite these issues, understanding attrition by design forces researchers to develop approaches a priori and in the context of an intervention. Consideration of financial and non-financial costs, as well as the allocation of research study resources, would be built into any study of attrition. In some cases, an examination of attrition may simply not be feasible. However, we believe that consideration of the issues we have raised will enhance the capacity to optimize approaches to study and address attrition. Implications for clinical teams in the real-world The approach we have laid out represents an attempt to provide a thoughtful and deliberate manner to study attrition in pediatric weight management interventions, based on both theory and practice. Such an approach could be useful for clinical teams in the real world in terms of planning and studying their own intervention drop out or pursuing quality improvement projects to increase retention so that families can derive optimal benefit. These efforts can be considered as strategies to minimize existing health disparities. Along with social and environmental factors, the organization and delivery of health services has a direct impact on disparities, with those families in greatest need of pediatric weight management treatment potentially at highest risk of dropping out of care. While it may be impossible to eliminate attrition, the approach we described herein is an opportunity for clinicians and researchers to create interventions, with proper attention towards minimizing the magnitude and understanding the type of attrition, as well as identifying associated strengths and weaknesses in the way interventions are constructed and provided. There are a variety of points to consider, ranging from a critical examination of all aspects of the characteristics of the intervention, including retention strategies, to a careful decomposition of attrition at each (sub) phase of the intervention. In terms of the latter, identifying the points at which attrition is most likely to occur creates an opportunity to plan or reflect on the content and process of administering the intervention, which should be understood in light of all theoretically and empirically relevant variables influencing attrition. In some settings, a lack of financial and human resources may limit providers’ ability or capacity to address risk of attrition in a concerted manner; in other situations, inadequate training of research staff or even the broader health service context where the intervention is administered could be contributing factors. Since attrition from pediatric weight management interventions carries financial and
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non-financial costs from both the clinical and health care system perspectives, we believe there is utility in understanding the successes and pitfalls in order to enhance patient care and health care delivery. Pediatric weight management teams can draw on the conceptual insights contained herein in planning, implementing, and evaluating real world interventions. Conclusion Although a high degree of attrition from pediatric weight management interventions represents a challenge from clinical, research, and patient perspectives, answers to address this issue remain elusive. Understanding attrition has been limited due to the inconsistent manner in which the issue has been investigated. It is our hope that considering the issues outlined in this paper will help to enhance the evidence-base and facilitate the development of strategies to minimize attrition so that children and youth with obesity and their families can achieve optimal health. Efforts are currently underway by our team members to gather data associated with a model of adherence [46], across three pediatric weight management sites in the United States to identify the characteristics of individuals at risk of attrition. The goal is to integrate these findings into health service provision by modifying treatment approaches. Funding source No funding was secured for this study. Financial disclosure The authors have no financial relationships relevant to this article to disclose. GDCB was supported by an Alberta Health Services Chair in Obesity Research. Declarations of interest None. Contributors’ statement Drs. Spence, Skelton, and Ball conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. References [1] de Onis M, Blossner M, Borghi E. Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr 2010;92:1257–64. [2] Rodd C, Sharma A. Recent trends in the prevalence of overweight and obesity among Canadian children. CMAJ 2016;188:313–20. [3] Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA Pediatr 2014;168:561–6. [4] Skinner A, Perrin E, Moss L, Skelton J. Cardiometabolic risks and severity of obesity in children and young adults. N Engl J Med 2015;373:1307–17. [5] Kelly AS, Barlow SE, Rao G, Inge TH, Hayman LL, Steinberger J, et al. Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: a scientific statement from the American Heart Association. Circulation 2013;128:1689–712. [6] Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obes Relat Metab Disord 1999;23:S2–11. [7] Puhl RM, Latner JD. Stigma, obesity, and the health of the nation’s children. Psychol Bull 2007;133:557–80. [8] Whitlock EP, O’Connor EA, Williams SB, Beil TL, Lutz KW. Effectiveness of weight management interventions in children: a targeted systematic review for the USPSTF. Pediatrics 2010;125:396–418. [9] Ells LJ, Rees K, Brown T, Mead E, Al-Khudairy L, Azevedo L, et al. Interventions for treating children and adolescents with overweight and obesity: an overview of Cochrane reviews. Int J Obes (Lond) 2018;42:1823–33.
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Original Article
A proposed standardized approach to studying attrition in pediatric weight management Nicholas D. Spence a,b , Joseph A. Skelton c,d,e , Geoff D.C. Ball f,g,∗ a
Department of Sociology, University of Toronto, Toronto, ON, Canada Interdisciplinary Center for Health and Society, University of Toronto, Toronto, ON, Canada Department of Pediatrics, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, United States d Brenner FIT (Families in Training) Program, Brenner Children’s Hospital, Medical Center Boulevard, Winston-Salem, NC, United States e Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, United States f Department of Pediatrics, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, Canada g Pediatric Centre for Weight & Health, Stollery Children’s Hospital, Alberta Health Services, Edmonton, AB, Canada b c
a r t i c l e
i n f o
Article history: Received 18 January 2018 Received in revised form 29 July 2019 Accepted 20 November 2019 Keywords: Attrition Pediatric obesity Intervention Weight management
a b s t r a c t Pediatric obesity is a major public health issue. Lifestyle and behavioral interventions are the foundation of pediatric weight management; however, intervention effectiveness is compromised when families (children, youth, and/or parent[s]) discontinue care prematurely. Intervention attrition minimizes the potential health benefits derived from interventions, results in inefficient use of health services resources, and can magnify health disparities. Most attrition research in pediatric weight management has been descriptive, highlighting the need to advance the field, both academically and clinically. Herein, we propose a standard approach to studying attrition in pediatric weight management interventions to enhance our understanding, elevate the quality of research, enable study-to-study comparisons, and inform strategies designed to mitigate its impact. We focus on three issues. First, “Conceptualization and operationalization,” whereby the processes underlying attrition from interventions should be decomposed into clinically important phases that are defined based on intervention characteristics. Relatedly, theoretically relevant variables should be identified with different mechanisms driving attrition in each phase. We propose a matrix of attrition, a tool designed to delineate the relevant stages of attrition and associated variables of analytical value. Second, “Pre-study” underscores the value of developing a plan to study attrition a priori rather than post hoc, including variable and sample size considerations, which broadens the range and quality of analysis. Finally, “Post-study” emphasizes comprehensive reporting of attrition, outlines typical comparisons of analytical interest, and statistical techniques used to handle missing data. Implications for clinical practice in pediatric weight management are discussed. Clinical Trial Registration: Not applicable. © 2019 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Introduction Pediatric obesity is a global public health concern [1]. In Canada [2] and the United States [3], approximately one-third of children are living with overweight or obesity, a condition that is often accompanied by a variety of negative health consequences [4–7]. Lifestyle and behavioral interventions that take
Abbreviations: RCT, randomized controlled trial; BMI, Body Mass Index; GEM, Grid-Enabled Measures; ITT, intention-to-treat. ∗ Corresponding author at: 4-515 Edmonton Clinic Health Academy, University of Alberta, 11405-87th Ave, Edmonton, AB T6G 1C9, Canada. E-mail address: [email protected] (G.D.C. Ball).
a family-based approach represent the cornerstone of managing pediatric obesity and have demonstrated favorable treatment outcomes [8–10]. Despite their potential, attrition from interventions designed for managing pediatric obesity is commonplace. Indeed, up to 83% of families (child, youth, and/or parent[s]) discontinue care prematurely [11], across interventions that have different theoretical frameworks and proposed mechanisms of change (e.g., cognitive behavioral therapy), settings (e.g., outpatient, multidisciplinary pediatric weight management clinics), age ranges (e.g., 6–12 years old), units of intervention focus (e.g., child/youth and parent/primary caregiver, parent/primary caregiver primarily, or child/youth primarily), and outcomes (e.g., weight status and physical activity) [11–13]. In fact, many studies have reported that
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most participants drop out prior to treatment completion [11–13]. The implications of these findings are far reaching. From a clinical perspective, attrition limits the benefits that families can potentially derive from care, may magnify existing health disparities, and has a negative impact on clinicians’ time and efficiency. From an organizational standpoint, health care systems are negatively impacted by the influence of attrition on resource allocation (e.g., clinic space) that could be used by patients and families who are engaged actively in their care. With respect to scientific and academic issues, a high level of drop out can undermine internal and external validity of research findings intended to build the evidence base for managing pediatric obesity. In recent reviews [11,14], we highlighted a lack of consistent findings and definitions across studies of attrition in pediatric weight management. These data revealed substantial diversity in how attrition was conceptualized and operationalized, assumed homogeneity of factors that determined attrition across different types and phases of interventions, and uncovered a shortage of attrition research performed beyond the United States [11,12]. Several categories of variables have been identified as potential drivers of attrition, including demographic, anthropometric, lifestyle, psychological, parent/family, health services, and logistical barriers, but there is little consensus in the literature [11,12,15,16], as many studies have been retrospective, relying on whatever data were available. Based on the evidence to date and our academic and clinical experiences in leading pediatric weight management clinics, we believe there is value in proposing a standardized approach to examining attrition in pediatric weight management. Systematic frameworks have been published to guide the evaluation of weight management interventions [17], but to date, the degree of attention given to attrition has been modest. We believe that a standardized approach will lead to a greater understanding of, and appreciation for, attrition as well as developing, implementing, and testing strategies designed to mitigate attrition so that children/youth and families can derive the greatest possible benefits from pediatric weight management. In writing this paper, our objectives were to (i) describe foundational issues that should be considered by researchers when studying attrition and (ii) provide a framework and example based on real-world experience to share relevant insights with researchers and clinicians working in this area. Step 1: conceptualizing & operationalizing attrition In the pediatric weight management literature, attrition has been defined in numerous ways [11,14,18]. In this regard, we believe that it is instructive to begin by distinguishing between the conceptual definition and operationalization of attrition. The conceptual definition of attrition includes failing to complete any or all parts of a pediatric weight management program, as discussed below (e.g., recruitment, pre-intervention, intervention delivery, and follow-up). The operationalization of attrition is specific to the research context and study focus, which are key sources of variation between studies. For example, a randomized controlled trial (RCT) to study intervention effectiveness may focus on the proportion of participants that fails to receive the required ‘dose’ of an intervention (e.g., number of behavioral change intervention sessions attended) to derive benefits, while a cost-effectiveness study may examine the economic costs of attrition to clinics at pre-intervention (e.g., missed appointments and assessments). Indeed, the heterogeneity of existing research in attrition in pediatric weight management has led to a wide range of estimates on its magnitude and predictors. To date, research has been characterized by assessments of available baseline data
for interventions on completers versus non-completers [19] and self-reported reasons for completing [20] or prematurely discontinuing an intervention [21,22]. Moreover, the choice of variables researchers have included in their analyses and the associated effects are assumed to be homogeneous across different target populations (e.g., parents only versus parent-child dyads), phases (e.g., earlier versus later intervention stages), durations (e.g., 12week versus 12-month), and visit frequencies (e.g., weekly versus monthly). The assumed singular pattern of attrition is inconsistent with the design, delivery, and evaluation of interventions that differ in many practical and conceptual ways. We believe that the processes underlying attrition from interventions should be conceptualized based on clinically important phases. For instance, a clinical phase can be defined based on the characteristics of the intervention, including theoretical underpinnings, outcomes of interest, intervention elements (e.g., duration, audience, intensity, setting), and retention strategies applied (if any). After considering these issues, predictors of attrition could be identified and assessed for each phase based on whether they are theoretically-informed as well as appropriate and feasible. To this end, the matrix of attrition in pediatric weight management (Table 1) is meant to be instructive. While not exhaustive, the columns capture distinct phases of a pediatric weight management intervention: recruitment, pre-intervention, intervention delivery, follow-up, and analysis. Sub-phases within each phase with analytical value can be incorporated into the matrix. For example, ‘intervention delivery’ could include multiple phases with different foci (diet, physical activity) over an extended period, each amenable to attrition analysis. Similarly, ‘follow-up’ could include post-intervention observations at multiple time points over a specified period; thus, one could indicate 6- and 12-months postintervention as clinically important sub-phases of ‘follow-up’, each subject to individual attrition analyses. We begin by defining the key phases of the intervention by examining the ‘characteristics of the intervention’ provided in Table 1. Recruitment represents a distinct phase of the intervention. Often, especially in order to access specialized, multidisciplinary health services, children/youth are referred for weight management by a physician or other health care professional. Children/youth and parents then decide to enroll and may need to satisfy some criteria (e.g., age, parent commitment to participate, weight status) in order to participate. Unfortunately, the limited availability of data for those families who decline participation, which can be as high as 60% [23], limits the extent to which comparisons can be made for an analysis of attrition at this phase. Pre-intervention is a non-intensive therapeutic phase of an intervention, usually with enrolled participants required to complete assessments before sessions commence. This stage also marks the first occasion when participants contribute information, such as demographic, anthropometric, cardiometabolic risk factors, lifestyle behaviors, and psychosocial health of children/youth and parents, which can be burdensome and time-consuming, often spanning more than one clinical appointment. Next, the delivery of the intervention is the most intensive phase along this continuum, with families required to attend and participate in sessions on a regular basis. Because some intervention modalities (e.g., cognitive behavioral therapy) [24] require participants to complete tasks between sessions (e.g., develop and implement goals; plan to overcome barriers related to behavior change; manage ambivalence among other family members in making positive lifestyle changes), this phase can be demanding and challenging, especially in the absence of perceived success or demonstrable improvements in weight or health status. Follow-up, including assessments of outcome measures at post-intervention
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Table 1 Attrition matrix in pediatric weight management, including examples of characteristics to document for conceptualizing, operationalizing, and predicting attrition. Setting: outpatient, multidisciplinary pediatric weight management clinic Target audience: children with obesity and their parent(s) Child age: 6–12 years old Theoretical frameworks: cognitive behavioral therapy and family systems theory Outcomes: child weight status (primary); child cardiometabolic risk factors, child and parent lifestyle habits, child and parent psychosocial health, parenting style and practices (secondary) Mode of delivery: in-person, group-based Frequency of contact: weekly sessions offered for 16 consecutive weeks (4 months) Length of each session: 90–120 min Length of follow-up: 12 months following the completion of the 16 week intervention Data collection: 0 months (pre-intervention), 4 months (post-intervention), 10 months (6-months post-intervention), 16-months (12-months post-intervention) Retention strategies applied: reminder emails and/or phone calls before weekly sessions and data collection appointments Attrition measures (examples): number/proportion of intervention sessions attended; discontinued interventions prematurely (y/n); satisfaction
Intervention characteristics
Conceptualization & operationalization of (sub) phases
Recruitment
Pre-intervention
Eligible, but declined to participate
Enrolled, but did not complete pre-intervention assessments
Follow-up
Analysis
Failed to complete outcome assessments at post-intervention, 6- and/or 12-months post-intervention
Any missing data
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
Lifestyle (child/parent) Physical activity* Diet* Sleep*
√ √ √
√ √ √
√ √ √
√ √ √
√ √ √
Health (child/parent) Anthropometric* Psychological* Cardiometabolic*
√ √ √
√ √ √
√ √ √
√ √ √
√ √ √
Family Family structure* Family function* Stress (child/parent)* Parenting*
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
√ √ √ √
Health services Quality of service* Interventions* Logistics* Health service coverage* Expectations/satisfaction*
√ √ √ √ √
√ √ √ √ √
√ √ √ √ √
√ √ √ √ √
√ √ √ √ √
Follow up (non) completers: reasons for (non) completion √ √ Self-reported* √ √ Survey*
√ √
√ √
√ √
Variables Demographic (child/parent) Age* Gender Race/ethnicity Socioeconomic status*
Intervention delivery Attended zero sessions
*Indicates a potential dynamic variable that should be assessed for changes over time. √ Indicates the variable is available.
(e.g., 6- and 12-months post-intervention), requires relatively less of a commitment from families in relation to the regular delivery of intervention sessions. In this respect, the intervention and followup periods represent two distinct phases that may correspond to different drivers of attrition. The analysis phase identifies all cases with any missing data over the course of the intervention, which may be the basis for exclusion, although pitfalls of deleting cases with any missing data are well documented, with well-established statistical techniques available for dealing with this issue [25]. While we offer an example of how attrition can be conceptualized and operationalized using the matrix of attrition within the context of a typical intervention in pediatric weight management, other considerations (e.g., data availability, sample size) will also determine how attrition is examined.
Variables Based on our view of the literature [11,12,18,26–34], potential variables associated with attrition are indicated in Table 1. There are six potential categories and each of them spans a number of associated variables. The category entitled, “Follow-up (non) completers and completers: reasons for (non) completion” can include both self-reported and survey data that assess barriers and facilitators, including practical (e.g., logistics, family, school, work), intervention-specific (e.g., expectations, satisfaction, demands of intervention), and psychological (e.g., motivation, self-efficacy) 18,35–40]. Ideally, valid and reliable measures should be applied consistently across attrition studies. As seen in Table 1, potential variables associated with attrition may differ across intervention phases. The asterisk indicates
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potential dynamic variables that should be assessed for changes over time, which may subsequently affect attrition. In our example, in a typical cognitive behavioral therapy intervention, variables of interest that were measured are marked for each phase of the study, including recruitment, pre-intervention, intervention, follow-up, and analysis. Dynamic variables, such as children’s weight, may increase from pre-intervention (baseline) to followup (post-intervention), resulting in the family withdrawing from the study and an absence of outcome data post-intervention. Thoughtful study planning can ensure that potentially relevant variables related to attrition analyses are included. For example, ensuring that interventions are ‘patient- or family-centered’ can include engaging children/youth and families in the development and refinement of curricula [41]. On another note, recruitment may be from an electronic health record database with variables potentially related to non-participation readily available; however, participants choosing not to enroll could be based on complementary data (e.g., parental motivation for treatment and perceptions of children’s weight status) that needs to be collected independently. Additionally, research must go beyond merely identifying empirical associations and develop an understanding of the etiology of attrition, including the classification of mediator and moderator variables. This theory and hypothesis driven research would help to map the time course of attrition; however, issues including the sample size, distribution of responses, and degree and type of attrition at different phases will need to be considered. Theoretically-important variables should be identified given the content of the intervention and proposed mechanism(s) driving attrition. Given the lack of consistent findings in the literature [11,12], it may also be useful to draw on attrition research from other areas (e.g., adult weight management, asthma, chronic pain, mental health, addictions, headaches, cancer, diabetes) to inform this work [18,26–34]. For example, in a review of predictors of attrition from outpatient behavioral medicine programs for adults receiving treatment for a chronic condition, psychological and behavioral factors, particularly experiences and expectations related to weight loss efforts, were the most common predictors of attrition from weight loss interventions, despite a traditional focus on demographic variables, which may be collected more consistently across attrition-related studies [27]. Therefore, a focus on developing and using appropriate psychological and behavioral measures of attrition within pediatric weight management intervention research is a logical way to proceed. However, unlike the individualistic focus in adult weight management attrition research, psychological and behavioral measures must focus on children/youth and their families, including parents, caregivers, and siblings.
Step 2: understanding attrition by design An examination of attrition requires appropriate planning at the design phase of a study. While attrition has not been a primary outcome of interest in pediatric weight management interventions, a lack of consideration results in research with limited capacity to enhance understanding of the issue. To the best of our knowledge, we are unaware of any interventions or RCTs in the pediatric or adult obesity literature that have examined attrition a priori. Instead of simply relying on whatever data happen to be available post hoc, we recommend researchers consider the following:
1) Variables specific to attrition, which may or may not be relevant to the primary outcome of a study. These variables should be based on the growing body of work in the area [11,12], related literature [18,26–34,40], theory, and nature of the intervention.
Each phase of an intervention should identify both fixed (e.g., race/ethnicity) and dynamic (e.g., diet) variables for inclusion. 2) Sample size considerations for interventions are based on power calculations focused exclusively on the primary outcome of interest, such as BMI z-score. Inattention to power issues for variables in attrition analyses limits the ability to test effects of relevant variables. 3) Variables available for inclusion and sample size have consequences for theory-driven research, hypothesis testing, and the statistical models used in analyses; specification bias of models (omitted variables; incorrect functional forms [e.g., interaction effects], etc.); Type II error and statistical power; Type I error and the number of possible comparisons (statistical tests). Step 3: reporting & analysis Concerted efforts have been made to enhance the transparency and standardization of reporting data, a directive that has been operationalized through the use of standardized reporting guidelines and tools, many of which are available publically through the Equator Network (www.equator-network.org). Another relevant initiative called the Grid-Enabled Measures (GEM; https:// www.gem-measures.org/Public/Home.aspx) is a web-based platform designed to promote harmonization of data through the development of standardized measures that are a product of consensus in the scientific community. Despite improvements over time, there are notable gaps [42]; for example, in a recent review of attrition in pediatric weight management interventions, an inadequate description of studies was the most common factor in lowering quality appraisal ratings [11]. In addition, there is sub-optimal and incomplete reporting of RCTs in the field of obesity in general [43], which highlights the need to enhance the methodological rigor in planning, conducting, and reporting obesity research. The appropriate reporting of attrition in pediatric weight management interventions is necessary to compare, assess, and synthesize work in the area. In this respect, it is critical to report the degree and type (e.g., missing completely at random, differential attrition by treatment and control arm) of attrition [44], which is observed at each clinically important phase of the intervention. Moreover, analyses should report the relevant comparisons, which would typically include the following: • Completers versus non-completers with respect to baseline characteristics (e.g., gender, race/ethnicity) for different phases of the intervention; • Completers versus non-completers with respect to selfreported or surveyed reasons (e.g., satisfaction, logistics) for completion/non-completion at different phases of the intervention; • Completers versus non-completers with respect to dynamic variables (e.g., body weight, self-efficacy) at different phases of the intervention, which may change beyond baseline, having a direct influence on attrition. Dynamic variables should be assessed regularly and may occur outside of the data collection time points for variables related to non-attrition outcomes. Statistical techniques for dealing with missing data Missing data can come in different forms, including item non-response (i.e., participant provides incomplete data at data collection points) and unit non-response (i.e., participant does not provide any data at data collection points). For RCTs, an intentionto-treat (ITT) analysis is used to preserve the randomization process of all participants by including those who do not adhere as per the protocol as well as those with item non-response or unit non-
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response, inclusive of individuals withdrawing from the study. In terms of attrition, following up with non-completers to obtain outcome data is ideal, but often impractical. Consistent with ITT analysis, the use of advanced statistical techniques to handle missing data (e.g., multiple imputation and selection models) [25] in pediatric weight management intervention studies is recommended [45]. These models do, however, make assumptions about the missing data process; thus, as the evidence base on attrition develops, we anticipate that there will be improvements in the models. Financial and non-financial considerations to study attrition Practically, studying attrition requires varying degrees of participant and researcher burden, as well as costs associated with collecting additional data. Clinical research teams endeavor to maximize the collection of intervention data associated with primary and secondary outcomes; therefore, collecting additional information related to attrition may be burdensome. In some instances, relevant data may be available through electronic health records or collected as part of the intervention, while other data may only be obtained by trying to follow up with participants who dropped out, who may have a low commitment to pediatric weight management. Despite these issues, understanding attrition by design forces researchers to develop approaches a priori and in the context of an intervention. Consideration of financial and non-financial costs, as well as the allocation of research study resources, would be built into any study of attrition. In some cases, an examination of attrition may simply not be feasible. However, we believe that consideration of the issues we have raised will enhance the capacity to optimize approaches to study and address attrition. Implications for clinical teams in the real-world The approach we have laid out represents an attempt to provide a thoughtful and deliberate manner to study attrition in pediatric weight management interventions, based on both theory and practice. Such an approach could be useful for clinical teams in the real world in terms of planning and studying their own intervention drop out or pursuing quality improvement projects to increase retention so that families can derive optimal benefit. These efforts can be considered as strategies to minimize existing health disparities. Along with social and environmental factors, the organization and delivery of health services has a direct impact on disparities, with those families in greatest need of pediatric weight management treatment potentially at highest risk of dropping out of care. While it may be impossible to eliminate attrition, the approach we described herein is an opportunity for clinicians and researchers to create interventions, with proper attention towards minimizing the magnitude and understanding the type of attrition, as well as identifying associated strengths and weaknesses in the way interventions are constructed and provided. There are a variety of points to consider, ranging from a critical examination of all aspects of the characteristics of the intervention, including retention strategies, to a careful decomposition of attrition at each (sub) phase of the intervention. In terms of the latter, identifying the points at which attrition is most likely to occur creates an opportunity to plan or reflect on the content and process of administering the intervention, which should be understood in light of all theoretically and empirically relevant variables influencing attrition. In some settings, a lack of financial and human resources may limit providers’ ability or capacity to address risk of attrition in a concerted manner; in other situations, inadequate training of research staff or even the broader health service context where the intervention is administered could be contributing factors. Since attrition from pediatric weight management interventions carries financial and
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non-financial costs from both the clinical and health care system perspectives, we believe there is utility in understanding the successes and pitfalls in order to enhance patient care and health care delivery. Pediatric weight management teams can draw on the conceptual insights contained herein in planning, implementing, and evaluating real world interventions. Conclusion Although a high degree of attrition from pediatric weight management interventions represents a challenge from clinical, research, and patient perspectives, answers to address this issue remain elusive. Understanding attrition has been limited due to the inconsistent manner in which the issue has been investigated. It is our hope that considering the issues outlined in this paper will help to enhance the evidence-base and facilitate the development of strategies to minimize attrition so that children and youth with obesity and their families can achieve optimal health. Efforts are currently underway by our team members to gather data associated with a model of adherence [46], across three pediatric weight management sites in the United States to identify the characteristics of individuals at risk of attrition. The goal is to integrate these findings into health service provision by modifying treatment approaches. Funding source No funding was secured for this study. Financial disclosure The authors have no financial relationships relevant to this article to disclose. GDCB was supported by an Alberta Health Services Chair in Obesity Research. Declarations of interest None. Contributors’ statement Drs. Spence, Skelton, and Ball conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. References [1] de Onis M, Blossner M, Borghi E. Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr 2010;92:1257–64. [2] Rodd C, Sharma A. Recent trends in the prevalence of overweight and obesity among Canadian children. CMAJ 2016;188:313–20. [3] Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA Pediatr 2014;168:561–6. [4] Skinner A, Perrin E, Moss L, Skelton J. Cardiometabolic risks and severity of obesity in children and young adults. N Engl J Med 2015;373:1307–17. [5] Kelly AS, Barlow SE, Rao G, Inge TH, Hayman LL, Steinberger J, et al. Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: a scientific statement from the American Heart Association. Circulation 2013;128:1689–712. [6] Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obes Relat Metab Disord 1999;23:S2–11. [7] Puhl RM, Latner JD. Stigma, obesity, and the health of the nation’s children. Psychol Bull 2007;133:557–80. [8] Whitlock EP, O’Connor EA, Williams SB, Beil TL, Lutz KW. Effectiveness of weight management interventions in children: a targeted systematic review for the USPSTF. Pediatrics 2010;125:396–418. [9] Ells LJ, Rees K, Brown T, Mead E, Al-Khudairy L, Azevedo L, et al. Interventions for treating children and adolescents with overweight and obesity: an overview of Cochrane reviews. Int J Obes (Lond) 2018;42:1823–33.
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Please cite this article in press as: Spence ND, et al. A proposed standardized approach to studying attrition in pediatric weight management. Obes Res Clin Pract (2019), https://doi.org/10.1016/j.orcp.2019.11.004