Changing Sedentary Behavior in Children and Adolescents: Understanding Research and Alternative Clues and Cues for Behavioral Formation and Change

Abstract

As children and adolescents who are identified as sedentary or physically inactive fall below the established world-wide physical activity guidelines for daily levels of physical activities, there is a need to examine factors that will influence the formation and change of sedentary behavior. This chapter is an analytical identification and appraisal of recent research and alternative approaches toward changing sedentary and inactive behavior and is founded on two premises: the first is that underlying concepts-related sedentary behavior are discussed and understood and the second is that effective and successful methodological interventions identified in four recent systematic reviews of 310 studies involving over a million children and adolescents that focused on a plethora of health, physical activity, and other related parameters leave clues that generate cues aimed at reducing sedentary and increasing physical activity behaviors. In this chapter, clues and cues related to conceptual and methodological factors, intervention development and evaluation, and alternative approaches with the aim of increasing the physical activity and healthy lifestyle behaviors and decreasing sedentary behaviors of children and adolescents are examined.

1. Introduction

World-wide physical activity guidelines generally require all ages to achieve daily or weekly physical activity levels that involve time and effort parameters. In children and adolescents, the expectation, for example, in the United States is over 60 minutes per day of moderate-to-vigorous physical activity and/or muscle-strengthening activities [1] with anything less seen as a risk of pervasive health implications that, if allowed, will continue into adulthood. Understanding the broader concept of activities of daily living (ADL) is fundamental to understanding sedentary and inactive behaviors. Assuming that if children and adolescents get a good night’s sleep which is recommended from 9 to 12 hours [2], then there is plenty of time awake in the rest of the day for ADL. Within the awake hours, ADL can be seen either as required such as school, work, and homework, or as choice-based such as chores, resting, recreation, physical activities (PAs), and other active behaviors. Identifying children and adolescents who could be considered as sedentary or inactive has been examined in both the required and choice-based contexts. In school populations, there are difficulties during the school day as there are bouts of active (such as recess) and inactive (such as sitting at a desk studying) behaviors which can obscure or compound sedentary and inactive behaviors. After school, at weekends, and during vacations where choices abound, there is no doubt that sedentary and inactive behaviors have increased and were even enforced during the COVID-19 lockdowns and have not necessarily changed since. Increasingly, for many children and adolescents, the easiest choice is to reach for their electronic device such as a smartphone. A potentially healthier but more complicated active choice would be to arrange and complete any form, intensity, and length of PA. The complications that arise can be seen either as internal which includes the role and energy of gatekeepers such as parents who often see barriers rather than facilitating choices [3] or as external which includes seasonal climate and weather, availability and/or distance to recreational facilities, and cost of programs and equipment. As a result, it is often easier to stay at home on an electronic device which leads to less physical activity or inactivity (IA) and more sedentary behavior (SB). With such a variety of required and choice-based ADL and internal and external facilitators/barriers being able to discern who is sedentary or inactive and how to change their behaviors is complicated, this has not stopped a plethora of researchers from various fields, such as health, PA, behavioral, and exercise sciences from trying to ameliorate changes in behavioral decreases in levels of IA and SB and/or increases in PA. Prior to examining how researchers have attempted to ameliorate change, it is necessary for underlying concept-related SB to be discussed and understood, and this premise provides the focus of the next section.

2. The underlying concepts that frame the understanding of research of sedentary and inactive behaviors

The first premise is derived from a need to know how to identify those children and adolescents who are sedentary and inactive. This is not easy as everyone exhibits some sedentary behavior on a daily basis, however, within the various fields involved in SB and IA research, the concern and focus are on those who exhibit excessive or prolonged sedentary behaviors that if persistent over time will then lead to adverse or at-risk health and well-being outcomes. This identification is complicated further as being sedentary or inactive are not medical conditions or diseases per se, but rather are exhibited from a variety of behavioral repertoires. As a result, there were a multitude of operational definitions of what constituted SB and inactive behaviors which made consensus and comparison between studies difficult. However, a conceptual breakthrough or watershed moment occurred in 2017 when the North America Sedentary Behavior Research Network (SBRN, [4]) proposed and agreed consensus conceptual definitions of sedentary and inactive behavior and a number of other related behaviors. The SBRN defined SB as physically active behaviors that only achieved energy expenditure ≤1.5 METs while awake and sitting or in a reclining posture. IA behaviors were characterized by energy expenditure from 1.5 to 2.9 METs such as standing in a line (1.8 METs) or slow walking (2.9 METs) according to the Compendium of Energy Expenditure in Youth (CEEY, [5]). Additionally, the SBRN also provided consensus, conceptual definitions, and age-related caveats for sleep, stationary behavior, standing, screen time, non-screen-based sedentary time, sitting, reclining, lying, as well as for bouts, breaks, and interruptions. These definitions are conceptually sound and are merited but also indicate the complexity of behaviors that can be included or need to be accounted for in the development of sedentariness and inactivity. These underlying concepts of the first premise provide the foundation on which this chapter progresses to the second premise of understanding the clues, derived from methodologies of research of SB and IA, which can become cues for changing children and adolescents’ lifestyles by either increasing physical activity or decreasing sedentary and inactive behaviors.

3. Understanding methodologies of successful interventions

The second premise of this chapter is that successful interventions leave clues as to how to ameliorate the impact of IA and SB and lead to behavioral changes that increase physical activity and/or decrease in SB. To provide some insight into the types of interventions that have been recently conducted, four SR [6, 7, 8, 9] were selected to examine how a plethora of variables impacted SB and IA. The choice was based on the following considerations: recency of publication, covering research that was pre- and post-COVID-19 lockdown, and allowing examination on how the intervention studies were developed. These SR covered a total of 310 research studies that examined the outcomes and indicators of adiposity (e.g., BMI), biomarkers (e.g., blood pressure), cognitive indicators (e.g., academic achievement), musculoskeletal growth (e.g., fat-free mass), risks (injury)/harm (e.g., headaches), and social-emotional indicators (e.g., classroom time on task), psychological measures (e.g., self-esteem), health-related fitness (e.g., grip muscular strength), technology (e.g., mobile phones), sociodemographic factors (e.g., SES), health risk factors (e.g., smoking), and other movement behaviors (e.g., physical activity). The studies involved over 1.3 million children and adolescents across an array of socioeconomic contexts in over 50 countries. All four SRs were published in either 2022 or 2023, but the reviewed research studies were published between 2004 and 2021. This review of reviews, presented in the alphabetical order of the first author, focused on the research outline, operational definition of IA and SB, sample selection, study aims, methodological issues, the type of intervention, and analysis of results.

Bauman et al. [6] researched individual mobile (using devices such as smartphones) health interventions to reduce IA and SB in children and adolescents. Given the recency of this phenomenon with children and adolescents, only 11 studies that met the selection criteria were reviewed. Although the SBRN definitions were identified, all sedentary behaviors for this study had to be school-related, rather than related to physical activity guidelines. The sample included healthy, overweight, cancer survivors, and adolescents in the military, while the aims of the studies included reducing obesity, increasing PA, decreasing SB, and promoting health behaviors. The individualized approach of the method was based on the use of mobile/electronic device and therefore was time-consuming in terms of setup. As a result, there were nine unique mobile interventions across 11 studies, and this caused heterogeneity of results which made it difficult to establish the effectiveness of intervention. Bauman and her colleagues analyzed the use of a behavior change technique [10], and this resulted in clusters ranging from 2 to 7 intervention techniques with the most prevalent being goals and planning (10 of 11 studies) and feedback and monitoring (9 of 11 studies). As the interventions were individualized, the fidelity in terms of how consistently the programs were utilized at an individual level would potentially make it difficult to compare between interventions. The authors reported only moderate reductions in inactivity for adolescents, and that there was no support for these interventions working either for SB or children. The approach of involving PA interventions with screen time was novel even with the risks associated with increases in the screentime and has the potential to be more effective with the continued development of better apps and programs.

de Mello et al. [7] developed lifestyle interventions as the basis of identifying clusters and correlates of PA and SB for children and adolescents who ranged in age from 6 to 18 years in an SR of 17 studies. In this review, PA was used instead of IA, while SB was not associated with the SBRN consensus definition. The participants were from macro-projects such as Identifying Determinants of Eating and Activity in Adolescents (IDEA, [11]), while the aims of the studies included reducing obesity, increasing PA, decreasing SB, and promoting health behaviors. In the method, the analysis of lifestyle interventions focused on the development of clusters (e.g., high PA-low SB), which were identified based on cluster input variables (e.g., watching TV). This SR was not concerned with an intervention per se but rather focused on making recommendations for potential lifestyle interventions for separate clusters. The results indicated that few associations were found between sociodemographic variables and all cluster types; however, different cluster patterns of PA and SB were determined and resulted in 12 clusters for boys, 10 for girls, and 9 for boys and girls together. Children and adolescents in the ‘high PA-high SB’ clusters had higher BMI levels, whereas those in the ‘high PA-low SB’ clusters presented lower BMI levels, waist circumference, and overweight and obesity. These clusters show the complexity of the relationships between PA and SB and health correlates.

The largest of the SR was undertaken by Kurik et al. [8] in over 42 countries and was designed to determine associations between school-related SB and indicators of health and well-being among children and youth. The authors used the definitions of IA and SB from SBRN [4]. The sample included was over 1.3 million participants, and the aims of the studies included reducing obesity, increasing PA, decreasing SB, and promoting health behaviors. In the method, only SB was operationalized and has exposure to school-based behaviors from outcomes/indicators. The exposures were determined either as critical outcomes (adiposity, biomarkers, cognitive, musculoskeletal growth, risks, and socio-emotional indicators) or as important outcomes (fitness and other movement behaviors which included PA, non-school-related SB, and interestingly sleep!). The role of homework, which is a sedentary activity, was not fully discussed. The authors made no recommendations related to SB per se. The studies were grouped according to seven research designs (e.g., clustered RCT). The combinations of critical and important outcomes resulted in 1133 associations that were analyzed but were not interventions per se. The study found favorable health associations for 13.5% of the critical outcomes with the highest levels for cognitive (33%) and socio-economic (32%) outcomes. However, favorable health outcomes were associated with only 4% of important outcomes. There were also unfavorable health associations for adiposity (21%), risk (30%), and socio-economic (26%) outcomes, and for the important outcome of other movement behaviors (35%). The null associations for critical outcomes totaled 68% of all associations and 62% for important outcomes. For the exposure categories, homework (29%) and active lessons (72%) were unfavorable for health when compared to more school-related SB. One interesting outcome was that there was a threshold of homework time greater than or equal to 2 hours per day that caused adverse or unfavorable reactions for health and well-being. This was a large study, but with small outcomes.

Whilhite et al.’s [9] SR focused on PA, SB, and sleep duration in associations with physical, psychological, and educational outcomes in children and adolescents in 141 studies with an inclusion criterion that the studies include at least two or movement behaviors. Rather than using the SBRN definition, there was a willingness to adjust according to the definitions used in the reviewed studies, and this led to screen time being used as SB when necessary. The total sample size was not reported, but one longitudinal study included 3979 participants. The aims of the studies included reducing obesity, increasing PA, decreasing SB, and promoting health behaviors. The authors noted that when screentime was used as the SB definition, there were more negative associated outcomes than when SB was defined as overall time spent being sedentary. The role of sleep, which in the SBRN consensus statement was not considered as not applicable to SB, was an interesting association but was not adequately justified. The notional two movement behaviors cut-off for study inclusion suggested that there was an insufficient conceptual basis for which movement behaviors were important. This study did not identify or include any interventions, but rather was focused on associations between variables. The authors’ analysis determined that high levels of PA and low levels of SB were favorably associated with physical health, psychological health, and education-related outcomes especially when sleep was included. Adolescents reported stronger associations than children for SB when screentime was used to represent SB rather than overall time spent being sedentary.

Having examined the concepts and methodological guidelines, the sample, aims, types of interventions, and results of these four recent SRs of IA and SB, the second premise was to use this knowledge to identify subsequent clues in order to develop and increase successful IA and SB interventions. The overall conclusions from the four SRs were a mixed set of results toward increasing PA and less favorable results toward decreasing SB. Certainly, there were fine margins between favorable and unfavorable results, and therefore, it was pertinent to identify clues regardless of outcomes. Identifying deductive clues requires an implicit need to act upon them and provide inductive cues. The alliterative clues and cues that follow are derived from four areas. The first three clues and cues are from conceptual, methodological, intervention-based issues from the SR, and the fourth set of clues and cues are based on alternative intervention-based approaches not identified or addressed within the SR. Table 1 provides a schematic representation of the clues and the resulting cues for the four areas that follow.

Clues (13)	Cues (26)
Conceptual clues and cues
1. From the definitions of IA and SB is the inclusion of energy expenditure (EE) using MET equivalencies	1. Identify levels of EE when determining samples and examining PA behaviors or interventions.
	2. The importance accumulative time of energy expenditure (EE).
2. From Step Counts per day	1. Use time as a unit for daily step counts and other PA and health parameters.
	2. Walk more as walking at 2.9 MET for longer per day or walking slightly faster at a moderate level 3.6 MET which exceeds the MET levels of being inactive.
3. Determine how much time is undertaken for IA and SB	1. Use the 24-hour movement-based terminology pie-chart [4].
Methodological clues and cues
1. The SR analyses determined it was not possible to complete a meta-analysis.	1. Reduce the number of moving parts and focus on specific or targeted achievable behaviors that can form SB interventions.
2. Reported SB differences between children and adolescents.	1. Focus on either children or adolescents or specific age groups or bands.
	2. Examine all the transitions from one educational level to the next including from high school to university and beyond.
1. A broad array of variables and markers were related to IA and SB with moderate effects at best and in many cases low to ineffective effects.	1. Require consideration of practical significance which is the size of effect and is not confounded by the sample size.
	2. Use ES levels reported in this literature as more relevant in power analysis calculations and for practically significant comparisons rather than traditional ES interpretations [12].
Clues and cues related to interventions
1. Interventions were portrayed differently.	1. Determine what constitutes the intervention of IA and SB and how it impacts behavioral change.
	2. Determine social validity [13].
	3. Sherman’s [14] eight guidelines or cues to meet the needs of PA interventions for SB and IA.
	4. Clear application and evidence that the intervention was completed as planned.
	5. Program evaluation requires awareness of values, audience, preferred methods, and typical evaluation questions.
Alternative clues and cues
1. How does SB develop?	1. Recommend extended longitudinal studies to examine SB development or lifestyles.
	2. Track the lifestyle history of adolescents who are currently sedentary using the 24-hour movement-based terminology pie-chart.
	3. Whether children and adolescents remain in the same cluster pattern or are there changes as they grow up?
2. A more comprehensive approach to SB with a nutritional component of energy.	1. Whether sedentariness alone includes primary drivers of ingestive behavior for SB change.
3. Understanding of behavioral change.	1. Finding the PA that fits each child’s reasoning profile or finding the most prevalent profiles and what PA to target.
	2. Whether inactive and sedentary children and adolescents perceive themselves actually as inactive and sedentary?
4. Aligns to the SBRN [4] definitions of IA and SB	1. Develop a multiplicative composite variable effort-involvement (EIPA) in relation to the SBRN definitions.
5. Emphasize opportunity/organization approaches to PA	1. Advocate for an out-of-the-gym door approach as a cue to getting children to continue the PA
6. With no PE classes in an average week in schools, where and when are children and adolescents going learn lifetime skills?	1. Move many of the lifetime PA benchmarks into lower grades.
	2. Teach children and adolescents how to undertake these PA in all of the options in the opportunity/organizational pyramid
	3. Physical educators prepare all students to create their own opportunities.

Table 1.

Schematic of the clues and cues for conceptual, methodological, interventions, and alternative approaches.

4. Conceptual clues and cues

The first clue from the definitions of IA and SB is the inclusion of energy expenditure (EE) using MET equivalencies. However, none of the four SRs addressed EE in relation to the PA undertaken in the reviewed studies. However, if there is going to be a concerted effort to address behaviors which are based on extremely low levels of energy expenditure, then an initial cue is that there needs to be a willingness to identify levels of EE when determining samples and examining PA behaviors or interventions. This would align with the SBRN consensus definitions, and that determination of energy expenditure for PA completed should be addressed and can involve using CEEY [5] which provides light, moderate, and vigorous expenditures for the included PA/sport, sedentary, transport, schoolwork, self-care, chores and other activities. A second cue derived from the clue of EE components of the IA and SB definitions relates to the daily recommendations of PA and is the importance accumulative time of EE. A third cue was that time was a unit for SB only for Baumann et al. [15] who used pedometers and exercise tracking watches to propose daily step counts for minimum healthy levels reaching 5000 as well as other PA and health parameters. These levels differed from those proposed by Tudor-Locke et al. [16] who recommended boys to average 12,000 to 16,000 steps/day and girls to average 10,000 to 13,000 steps/day with a steady decrease in steps/day to approximately 8000–9000 steps/day for adolescents aged 18. From step counts, an intervention cue for children and adolescents with SB and IA would be to walk more as this is a positive starting point for PA and accumulative effect of walking at 2.9 MET for longer per day or walking slightly faster at a moderate level 3.6 MET which exceeds the MET levels of being inactive. Although not examined here, a future analysis of the SR would be to determine how many studies considered moderate walking as an immediate and effective intervention to resolving inactivity.

A second conceptual clue derived from the SR is determining how much time is undertaken for IA and SB. The amounts of time for each identified intervention in the four SRs varied greatly between weeks [6], years [9], and related to specific behavior measures in minutes, days, and weeks [7, 8]. Currently, it is difficult to know how or what adjustments in the waking hours could occur with time increases in SB or IA. One cue that would be valuable in getting a better sense of time commitments would be to use of a 24-hour movement-based terminology pie-chart [4], which despite needing a catchier name, is an instrument to determine what children and adolescents complete in each behavioral area (see Figure 1). This could be developed into a computer-based [6] program or app allowing children and adolescents to log their time spent in each element with the adjustments adding and subtracting to the amounts of time awake and time asleep. This would be more inclusive in terms of time on tasks and allow interventions to be targeted at times when there is excessive IA or SB. Once developed and providing data, it would be possible to get the fullest picture of how and what active and sedentary behaviors are actually interacting with each other. The importance of such a composite behavioral measure is that everyone has levels of SB in their daily routine. Some of it is enforced such as working at a desk. Some of it is a choice and yet both have the same implications for health outcomes. Indeed, there may be many forms of behavior that make up the time we are sedentary, but this does not help when making recommendations for how to decrease SB. This is especially so if we cannot discern distinct types of SB apart from less than 1.5 METs as it really does not matter what behaviors we decide to do without. However, having waking hours data will allow for targeted interventions, and awareness of good and not-so-good choices of both PA, sedentary time, and time asleep. This has further potential to provide analysis of accumulative and/or pervasive multiday issues for school-week and week-end patterns, which are where the health risks of SB begin to be problematic.

Figure 1.

24-hour movement and nonmovement behaviors pie-chart [4]. Note: The pie-chart organizes movements that take place throughout the day into two components: 1) The inner ring (darker colors) that represent the main behavior categories using energy expenditure. 2) The outer ring (Lighter colors) representing general posture categories. The proportion of space occupied by each behavior is not prescriptive of time that should be sent in these behaviors each day. Adapted from: Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, et al. Sedentary Behavior Research Network (SBRN) – Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act. 2017; 14:75. https://doi.org/10.1186/s12966-017-0525-8. BioMed Central Ltd Publishers.

5. Methodological clues and cues

In this section, the first methodological clue was that the four SR completed analyses that determined it was not possible to complete a meta-analysis due to levels of heterogeneity between the reviewed studies. The irony being that, in an analysis of IA and SB, there were often too many ‘moving parts’ being analyzed which restricted to ability to discern meaningfulness of what was occurring in the interventions, clusters, and associations. As a consequence, a cue would be to reduce the number of moving parts and focus on specific or targeted achievable behaviors that can form SB interventions. This should become easier as a plethora of outcome behaviors were ineffective in the four SRs and therefore can be avoided or more carefully considered in the future studies.

A second methodological clue derived from the four SRs was that, although the samples ranged from 5 to 21 years, there were reported differences between children and adolescents. The resulting cue is that there are sufficiently different results to propose that research studies focus on either children or adolescents or specific age groups or bands. This leads to an additional cue of examining the changes that occur in the transition from childhood to adolescence which generally aligns with the transition from elementary to middle/junior high school. A third and related cue would be to extend this examination to all the transitions from one educational level to the next including from high school to university and beyond where IA and SB are both likely to increase and PA is likely to be reduced or discontinued completely.

A third methodological clue is that a broad array of variables and indicators were related to IA and SB with moderate effects at best and in many cases low to ineffective effects. How much of this was due to the components of the method is always part of every discussion. Some commonalities in the method were that samples were small or included a number of different subsamples such as those with obesity or different PA levels. As a result, a cue for the effectiveness of interventions would be to require consideration of practical significance which is the size of the effect and is not confounded by the sample size. In studies with small sample size, this provides the size of the difference that can be reported as intervention effectiveness via ES and 95% CI rather than statistical significance which is inferred from the precision of the estimate [17]. Practical significance also requires examination of whether the confidence intervals include zero, especially in the case of small effect sizes. Another cue would be to use ES levels reported in this literature as more relevant in power analysis calculations and for practically significant comparisons rather than traditional ES interpretations [12].

A fourth methodological clue evident in all studies is that there is no evidence of the prevalence levels of children and adolescents who can be identified as sedentary and inactive. This is quite different from the prevalence of SB that has been established across a multitude of behaviors [13]. Part of this is due to many studies not discerning energy expenditure as identified in the SBRN definitions but may also be due to the definitions not including time as a mitigating factor. This clue led to an attempt to discern prevalence for those that are sedentary and inactive from the SBRN definitions using data from the 2021 CDC’s biannual Youth Risk Behavior Survey (YRBS, [15]). From this survey, it was possible to determine a four-variable form of sedentariness (see Table 2). Despite different units of time being used, all four questions had a zero-time answer option. From the sample of 15,997 adolescents who completed the survey, 860 (5.41%) adolescents reported the zero-time option for all four questions and were considered as sedentary under the SBRN definition. Additionally, there were 370 (2.31%) adolescents who reported three zero-time behaviors and one with the lowest time level on the remaining question. These lowest reported levels are above zero and would suggest from the SBRN definition that these adolescents are inactive. Interestingly, there were different prevalence levels of inactivity based on the question that provided a positive physical activity level in Table 2. However, there were caveats. The first is that the data for the MVPA question does not account for adolescents who may be active for less than 60 minutes per day and could well complete enough PA in minutes to be considered inactive or low active; unfortunately, the composition of this latter group is no longer determined by the CDC in the YRBS survey. A second caveat was that the prevalence of these populations based on a large sample is rarely reported and is unique. This clue leads to suggested cues of having complex or multibehavior determinants of sedentariness and inactivity, and an understanding that the prevalence of SB and IA is relatively low in this large population and could set a benchmark for prevalence rates in future research studies.

During the past seven days, how many days were you physically active for a total of at least 60 minutes per day?	In an average week when you are in school, how many days do you go to physical education (PE) classes?	During the past 12 months, how many sports teams did you play?	During the past seven days, how many days did you do exercises to strengthen or tone your muscles, such as push-ups, sit-ups, or weightlifting?	Total samples; (n = 15,997)	Level of physical activity
0 days	0 days	0 teams	0 days	860 (5.41%)	Sedentary
1 day	0 days	0 teams	0 days	189 (1.18%)	Inactive
0 days	1 day	0 teams	0 days	16 (0.001%)	Inactive
0 days	0 days	1 team	0 days	125 (0.007%)	Inactive
0 days	0 days	0 teams	1 day	40 (0.002%)	Inactive

Table 2.

Prevalence rates of sedentariness and inactivity in adolescents who completed the 2021 YRBS survey.

6. Clues and cues related to interventions

A clue from all four SRs was that interventions were portrayed differently. Two focused on direct interventions and included Bauman et al.’s novel approach of mobile smartphone programs using behavior change techniques as the intervention [6] and Kuzik et al.’s interventions which were portrayed as exposures [8]. In contrast to these direct approaches to the intervention, the other two SRs indirectly involved interventions, as de Mello et al. [7] only involved the clustering of IA and SB with a range of modifiable correlates to better inform intervention strategies for behavior change, while Whilhite et al. [9] made no mention of interventions other than to recommend including sleep in more longitudinal and intervention research! From this clue, a cue is to determine what constitutes the intervention of IA and SB, be it from a therapeutic, behavior modification, or educational perspective and how it impacts behavioral change. Given that when the participants engaged in some form of PA intervention, the procedures are as important as the outcomes. To frame this cue, I highlight three approaches to program evaluation [14, 18, 19] from a variety of paradigmatic approaches that can function as cues in their own right when considering the importance of the intervention in impacting the program or study outcomes.

1. The first approach is social validity [14] which, from a clinical behavioral analyst perspective, includes social importance and acceptability of intervention goals, social acceptance of program procedures, and social importance of program outcomes for the participants. All programs or interventions have goals. The goals of the program are the reasons why parents enroll their child or adolescent in a PA intervention program. Goals were part of the behavior change theory [10] in Baumann’s [6] reviewed studies, but were not participant-related, but this is the closest any of the SRs get to dealing with evaluating the intervention. How and what children and adolescents engage in during the intervention is the social acceptance of the program’s procedures. Obviously, there was no expectation of social validation being evident in these SRs, but the children directly and parents indirectly through their child(ren) evaluated their experiences, nonetheless. Simply, if they enjoy the program procedures they will return, if they do not, they will not, and, as such, attendance rates are the most telling measure of procedural validity. The intervention outcomes detail how children and adolescents achieved reductions or increases in behaviors relative to the goals of the intervention and can be formally reported by program staff or informally gauged by parents. Partial or nonachievement of outcomes leads to continuation in the program, whereas achievement of the outcomes leads to some form of graduation from the program. All three forms of social validity can form a cue for future evaluating interventions of SB and IA.

2. The second approach is more systematic as Sherman [18] in examining yoga interventions provided eight excellent guidelines or cues that can be altered to meet the needs of PA interventions for SB and IA, and these were style of PA; dose and delivery – how often and for how long; components of the intervention; specific class sequences; dealing with modifications; selection of instructors; facilitating home practice; and measurement of intervention fidelity over time. Of these, the most important is the fidelity of intervention and is a cue here. Fidelity is the extent to which the intervention was undertaken as it was intended, and without this, all the other guidelines lack credibility or validity. The importance of fidelity is that three of the SRs [6, 8, 9] suggested recommendations from their results for policymakers, professional, parents, and schoolteachers; however, without the awareness of whether the intervention was completed as planned, it is difficult to know whether what is being recommended as the intervention is repeatable. The cue is to make sure that there is clear application and evidence that the intervention was completed as planned.

3. Fidelity also is related to Greene’s [19] examination of qualitative program evaluation as the third alternative approach. Program evaluation requires awareness of values, audience, preferred methods, and typical evaluation questions which are shaped by which philosophical framework, be it postpositivist, pragmatist, interpretivist, or critical stance that the research evaluator prefers. Given the distinct levels of authority and involvement from parents to policymakers that accompany intervention programs as a result, there are different or even conflicting levels of interest and advocacy between these stakeholders. This means that recommendations may have to differ depending on the specific audience. Making such recommendations was part of both Kuzik et al. and Whilhite et al.’s conclusions [8, 9] and involved different stakeholders and requires awareness of evaluative processes, such as of social validity, and how the fidelity of the program’s procedures impacted the achievement of outcomes of the program goals as this is required for continued (financial, resource, workforce, or volunteer) support for the intervention.

An original premise of this review of reviews was that successful and also less successful interventions leave clues in both methods and interventions. To summarize, some of these clues can be traced back to similar methodological issues that prompted the development of the SBRN [4] consensus statements and the operational definitions of IA and SB. However, despite the four SRs covering a plethora of outcomes and being well-conducted analyses, the impact on SB and IA was rather underwhelming. However, this is not discouraging as these SRs still delivered important clues regardless of the outcome as any results are important in developing future decisions about which method and intervention cues are worth continuation.

7. Alternative clues and cues

Apart from evidence from the SR, there are clues and cues from alternative approaches involving lifestyle, PA groupings, and behavioral change that could be applicable to children and adolescents who are identified as inactive or sedentary. The first alternative clue is derived from trying to answer the following inter-related questions: How does SB develop? Do children and adolescents through poor choices, or limited choices, or no choices, or a lack of opportunities, or by not being opportune just stop undertaking PA? How influential is lifestyle and how much control do children and adolescents have over it? Certainly, in terms of the definition of SB, there is little or no PA to speak of, but was this always the case for children and adolescents currently identified as inactive and sedentary? Whilhite’s [9] recommendation of extended longitudinal studies would be a valuable cue to answer the questions of SB development or lifestyles that would need to examine a range of SB options between the two extremes of a child who is sedentary at the age of five and still sedentary at 15 and a child who is highly active at five who becomes sedentary at 15. This would require 10-year longitudinal studies which are not exactly de rigueur in many fields of research! It would also require a substantial and longevous sample. An alternative cue would be to track the lifestyle history of adolescents who are currently sedentary potentially through the use of the 24-hour movement-based terminology pie-chart ([4]; see Figure 1) to see what factors were instrumental in them becoming sedentary. What may become evident is a range of cluster patterns such as those proposed by de Mello [7] will develop as children grow into adolescents. A related cue would be whether children and adolescents remain in the same cluster pattern or are there changes as they grow up? It would be expected that there will be a continuum of patterns based on increasing or decreasing levels of PA, and many of the other factors identified in all four SRs will be influential especially as behavioral change occurs, but how this impacts individual children and adolescents remains an open question.

A second alternative clue develops from the inclusion of energy expenditure in the SBRN definitions identified earlier for those individuals who are inactive and sedentary. In this instance, the cue is related to a more comprehensive approach to the SB already proposed with the use of the 24-hour pie chart and the nutritional component of energy from the calories-in calories-out approach of Chaput and Sharma [20] who, in relation to obesity, provide some valuable cues that are pertinent in the role that food, nutrition, and energy expenditure play in impacting IA and SB. Given the lack of calories-out EE from inactive and sedentary children and adolescents, it is the calories-in approach that has more relevancy especially where there is an overlap between those children and adolescents who are inactive-obese and sedentary-obese. The calories-in proposal is that “a substantial proportion of the variance in the contribution of exercise on body weight can be explained by the positive effects of exercise on the ingestive behavior in individuals in whom overeating is primarily driven by stress, depression, poor self-esteem, or unrestorative sleep, all of which can be improved with regular exercise” (p. 1768). Whether sedentariness alone or in some combination with obesity includes these primary drivers of the ingestive behavior as a cue for SB change is for future analysis and will possibly relate to only certain clusters of children and adolescents who are inactive and sedentary [7].

Another alternative clue relates the understanding of behavioral change. Forming and changing behavior requires challenging values and beliefs, and changes in intentions which relate to how ready individuals are in the pre-contemplative and contemplative stages of readiness [21] are also relevant in this context and were examined by De Mello et al. [7]. My colleague and I [22] examined attitudes which are theoretically linked to changing behavior through intentions in the theory of planned behavior [23]. Using a CATPA [24] scale, we took an alternative view to attitudes by looking at profiles of eight participatory reasons to become more active and can be closely related to de Mello et al.’s [7] clusters. The eight participatory reasons were social growth, health and fitness, vertigo, ascetic cathartic, fitness, esthetic, and aerobic and provide a broad array of reasoning to participate in PA either as a singular antecedent or in one of a number of combinations that can reach 15,625 permutations! This approach avoided the pitfalls of traditional applications of the survey, which aggregate the reasons into one score, and by doing so, we were able to look at ways that the groups of adolescents created their attitudes as a profile of participatory reasons that factor into an attitude toward completing a PA with the expectation that this would be valuable in terms of changing behaviors. The cue is finding the PA that fits each child’s reasoning profile or finding the most prevalent profiles and what PA to target. In reality, this is the foundational basis of developmental sports options on Saturday mornings across America where children try different PAs and where there tend to be more misses than hits! The reasoning for this alternative cue is that many traditional approaches to behavioral change for children and adolescents who are obese and overweight are not specific enough especially when, as Janiszewski [25] indicated, BMI does not reflect lifestyle. Indeed, evidence [24] from nine profiles cross-tabulated from two composite variables of EIPA and WSFit indicated that the 29 individuals who reported being obese were identified within five of the nine PA profiles (see Table 3). Another question asked the participants: Do you consider yourself underweight, normal weight, or overweight? These results show variation across the various levels of perceived weight status. This leads to another cue for further research which is whether inactive and sedentary children and adolescents perceive themselves actually as inactive and sedentary? This will have influence in how to approach them to initiate behavioral change especially if they do not perceive a need to change what they consider to be acceptable behavior.

	Profile 2	Profile 3	Profile 6	Profile 8	Profile 9
Profile of; EIPA-WSFit	Low EIPA-; mid WSFit	Low EIPA-; high WSFit	Mid EIPA-; high WSFit	High EIPA-; mid WSFit	High EIPA-; high WSFit
Number of Adolescents with Obesity	1	11	5	5	8
Perceived weight status2	Normal = 1	Normal = 2 Overweight = 4	Underweight = 1; Normal = 1; Overweight = 2	Normal = 5; Overweight = 2	Normal = 2; Overweight = 4

Table 3.

Distribution of adolescents with obesity in profiles of physical activity1.

¹

Data from Meek & Prasad [24].

²

Not all adolescents reported their perceived weight status.

An alternative clue that aligns to the SBRN [4] definitions of IA and SB requires magnitude coding [26] of PA completed for the magnitude of effort using MET codes from the CEEY [5] and to determine effort and time involvement of each PA. In [22, 27], we used 10-minute increments from 0 to 60, and this was a reaction to YRBS, and most PA guidelines being solely concerned with meeting the 60-minute threshold. For many children and adolescents who are inactive or sedentary, this is a high bar, but many of them see this as continuous rather than cumulative and often fail to account for walking as a physical activity. The cue, having determined effort in METS for PA and involvement in time, is the development of a multiplicative composite variable effort-involvement [EIPA] which can be interpreted in relation to the SBRN definitions with scores for an inactive adolescent being between 16 and 29 and for sedentary adolescent being less than or equal to 15. Obviously, more direct measures of PA and energy expenditure can be generated from various personal electronic devices, but in large samples, this may not be possible in which case determining EIPA can be calculated and a valuable alternative especially when PA is undertaken in group sessions of a fixed time.

Currently, there a few alternative clues from the opportunities and organizations within the community that would provide cues for the PA to become a regular and maintained behavior. This final alternative clue is based on the need to have greater emphasis on opportunity/organization approaches to PA that can mobilize those who are inactive and sedentary. As part of getting children and adolescents to continue with physical activity that they had learned in their school PE curriculum, I developed and continue to advocate for an out-of-the-gym door approach as a cue to getting children to continue the PA [28]. In Figure 2, the doors through which they pass are replete with personal participation processes such as intentions to try [29], and participation advocacy such as community awareness of opportunities via a community resource guide that they learn either directly or indirectly in PE and are key to continuance. However, without a clear understanding of the opportunity/organizational pyramid and how to use it in the community, children and adolescents can slip past the pyramid and into the world of inactivity. The opportunity/organizational pyramid provides many options about how to complete or perform PA. Toward the top of the pyramid are some traditional organizational opportunities in various forms of sports that are not remotely plausible for those who are inactive and sedentary, but the biggest sections in terms of their opportunities are at the base of the pyramid and are recreational opportunities in unstructured and structured participation that have individual, home, and small group options for nearly all PAs and importantly for everybody. This model fits with the National PE Standards [30], and the overarching goal of pursuing a lifetime of healthful physical activity. Unfortunately, YRBS 2021 [15] indicates that 53.2% of adolescents have no PE classes in an average week in schools which raises the question: Where and when are they going learn these lifetime skills? One cue would be to move many of the lifetime PA benchmarks into lower grades, especially as high school PE is being waived not only for sports team participation, but also for marching band which does have a walking component! Another cue would be for physical educators to provide not only a broad and balanced set of PA opportunities but more importantly teach children and adolescents how to undertake these PAs in all of the options in the opportunity/organizational pyramid that are not traditionally taught in PE. The lack of opportunities came into full focus during the COVID-19 lockdown when my PEHE teaching internship students had to develop online PE classes only to find that many children did not have access to or own a small ball, such as a tennis ball, in their home. A final cue is that physical educators must prepare all students to create their own opportunities and take them as soon as PE classes are over. The moment you walk out of the gym door, you are in an unstructured participation setting be it in your home or surrounding milieu, and the best of all, you are moving quite literally from SB to IA.

Figure 2.

Opportunity-organizational participation within the gym doors and beyond approach to establishing physical activity participation from school physical education.

8. Conclusion

This chapter highlighted approaches to determine the prevalence of sedentary and inactive adolescents and examined two premises which are the foundation of research-based behavior change in IA and SB. By examining recently completed SR of behavioral change to reduce IA and SB, this chapter identified methodological, intervention, and alternative clues that challenge and extend the current approaches derived from an SR of 310 studies focused on indicators, clusters, associations, factors, and variables that can ameliorate reductions in sedentary and inactive behavior. The success was that there were clues and cues regardless of outcomes. Altogether, there were 13 clues and 26 cues presented, and while these cannot guarantee success in the aim of reducing SB and IA and increasing PA, they can provide a broader scope as to how researchers are trying to understand how to change behaviors in children and adolescents who are sedentary and inactive. Ultimately, it is unlikely for one panacea to change SB and IA in children and adolescents, and with so many clues and cues, there is a good chance that there will be many solutions. What is critical is to determine what the future panaceas will be that help children and adolescents find their own way of changing their behaviors from being sedentary and toward being more active and healthier. This is a worthy cause that requires researchers, physical educators, children, and adolescents alike to take a cue.