Reducing youth screen time: qualitative metasynthesis of findings on barriers and facilitators.

Health Psychology 2015, Vol. 34, No. 4, 381–397

© 2015 American Psychological Association 0278-6133/15/$12.00 http://dx.doi.org/10.1037/hea0000172

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Reducing Youth Screen Time: Qualitative Metasynthesis of Findings on Barriers and Facilitators Karl E. Minges

Neville Owen

Yale University

Baker IDI Heart and Diabetes Institute, Melbourne, Australia, and University of Melbourne

Jo Salmon

Ariana Chao

Deakin University

Yale University

David W. Dunstan

Robin Whittemore

Baker IDI Heart and Diabetes Institute, Melbourne, Australia, and Monash University

Yale University

Objective: An integrated perspective on the relevant qualitative findings on the experience of screen time in youth can inform the development of hypotheses to be tested in future research and can guide the development of interventions to decrease sedentary behavior. The purpose of this qualitative metasynthesis was to explore parent, youth, and educational professionals’ perceptions of barriers to, and facilitators of, reducing youth screen time. Method: Qualitative metasynthesis techniques were used to analyze and synthesize 15 qualitative studies of screen time among youth (11–18 years) meeting inclusion criteria. The phrases, quotes, and/or author interpretations (i.e., theme or subtheme) were recorded in a data display matrix to facilitate article comparisons. Codes were collapsed into 23 categories of similar conceptual meaning and 3 overarching themes were derived using thematic analysis procedures. Results: Study sample sizes ranged from 6 to 270 participants from 6 countries. Data collection methods included focus groups (n ⫽ 6), interviews (n ⫽ 4), focus group and interviews (n ⫽ 4), and naturalistic observation (n ⫽ 1) with youth and/or parents. Data analysis techniques included thematic analysis (n ⫽ 9), content analysis (n ⫽ 3), grounded theory (n ⫽ 1), observation (n ⫽ 1), and interpretive phenomenological analysis (n ⫽ 1). Three thematic categories were identified: (a) youth’s norms—screen time is an integral part of daily life, and facilitates opportunities for entertainment, social interaction, and escapism; (b) family dynamics and parental roles—parents are conflicted and send mixed messages about the appropriate uses and amounts of screen time; and, (c) resources and environment—engagement in screen time is dependent on school, community, neighborhood, and home environmental contexts. Conclusions: Screen time is an established norm in many youth cultures, presenting barriers to behavior change. Parents recognize the importance of reducing youth screen time, but model and promote engagement themselves. For youth and parents, mutually agreed rules, limits, and parental monitoring of screen time were perceived as likely to be effective. Keywords: television time, sedentary behavior, youth, qualitative, review

Over one third of U.S. middle- and high-school-age youth are now overweight or obese (Ogden, Carroll, Kit, & Flegal, 2012), and this proportion has been projected to double by 2030 (Wild,

Roglic, Green, Sicree, & King, 2004). Physical activity has been a predominant health behavior examined in the context of reducing youth overweight and obesity, even though moderate to vigorous

Karl E. Minges, School of Nursing, Yale University; Neville Owen, Behavioural Epidemiology Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, Australia, and Melbourne School of Population and Global Health, University of Melbourne; Jo Salmon, School of Exercise and Nutrition Sciences, Deakin University; Ariana Chao, School of Nursing, Yale University; David W. Dunstan, Physical Activity Laboratory, Baker IDI Heart and Diabetes Institute, and Department of Epidemiology and Preventive Medicine, Monash University; Robin Whittemore, School of Nursing, Yale University. Karl E. Minges was funded by a predoctoral fellowship from the National Institute of Diabetes and Digestive and Kidney Disease/National Institutes of Health (T32-DK07718). Neville Owen was funded by a National Health and Medical Research Council (NHMRC) Pro-

gram Grant [569940], a Senior Principal Research Fellowship [NHMRC 1003960], and the Victorian Government’s Operational Infrastructure Support Program. Jo Salmon was funded by a Principal Research Fellowship, National Health and Medical Research Council (APP1026216). Ariana Chao was funded by predoctoral fellowships from the Jonas Center for Nursing Excellence and the National Institute of Nursing Research/NIH (T32-NR008346). David W. Dunstan was funded by an Australian Research Council Future Fellowship (FT100100918). Correspondence concerning this article should be addressed to Karl E. Minges, Yale School of Nursing, 400 West Campus Drive, Orange, CT 06477. E-mail: [email protected] 381


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activities only account for 3% of time spent awake (Katzmarzyk, 2010). However, there is now emerging evidence at the population level that sedentary time— engaging in prolonged sitting as distinct from not engaging in moderate to vigorous physical activity—may be related to adverse health consequences that are additional to those attributable to insufficient leisure-time physical activity levels (Owen, Healy, Matthews, & Dunstan, 2010; Pate, O’Neill, & Lobelo, 2008; Rey-López, Vicente-Rodríguez, Biosca, & Moreno, 2008). Sedentary behaviors, which often encompass screen-based activities, involve reclined or sitting posture and do not increase energy expenditure substantially above the resting level of 1.0 to 1.5 metabolic equivalents (Pate et al., 2008). There is evidence linking sedentary behavior to overweight and obesity, type 2 diabetes, cardiovascular disease, cancer, and all-cause mortality (Dunstan et al., 2010; Healy, Dunstan, Salmon, Shaw, et al., 2008; Katzmarzyk, Church, Craig, & Bouchard, 2009; Owen, Bauman, & Brown, 2008). Among youth, a recent systematic review reported that watching TV for more than 2 hr per day was associated with unfavorable body composition, metabolic and cardiovascular disease biomarkers, decreased fitness, lowered scores for self-esteem and prosocial behavior, as well as decreased academic achievement (Tremblay, LeBlanc, Kho, et al., 2011). Decreasing sedentary behavior is increasingly recognized as being an important target for youth obesity prevention efforts (Spanier, Marshall, & Faulkner, 2006). Although sedentary behaviors encompass structured (e.g., sitting at desks in school), unstructured (e.g., leisure TV or computer games), and incidental (e.g., car or bus transportation) time, among research that focuses on youth, “screen time”— including TV viewing time—is the most often used measure of time spent engaged in a sedentary behavior (Tremblay, LeBlanc, Kho, et al., 2011). Not surprisingly, rapid advancements in communication and entertainment technologies, and the ubiquitous presence of screen devices in youth’s lives, provide multiple opportunities for youth to engage in sedentary behaviors (Colley et al., 2011; Matthews et al., 2008). Recent evidence suggests that youth can spend up to 11 hr per day using screen-based technologies, such as smartphones, tablets, computers, and TV (Rideout, Foehr, & Roberts, 2010). Such excessive screen time can be associated with snacking and overeating (Bickham, Blood, Walls, Shrier, & Rich, 2013), and potentially displaces participation in physical activities (Bar-Or et al., 1998; Van den Bulck & Van Mierlo, 2004), with consequent implications for weight gain (Marshall, Biddle, Gorely, Cameron, & Murdey, 2004). Given the health implications and excessive use of screenbased media, the American Academy of Pediatrics (AAP) introduced guidelines in 2001 for total entertainment screen time to not exceed 2 hr per day (American Academy of Pediatrics, 2001). The guideline was recently updated to recommend that youth not have access to the Internet or TV in their bedrooms, and for parents to monitor media use (American Academy of Pediatrics, 2013). Similar guidelines have been adopted from government health agencies in the United States and Canada (National Heart, Lung, and Blood Institute, 2013; Tremblay, LeBlanc, Janssen, et al., 2011). These guidelines and the development of screen-time interventions have been largely derived from studies that employed a quantitative methodology to elucidate the factors that underpin screen time. Quantitatively

derived factors that appear to correlate with sedentary time in youth include sociodemographic attributes (parental income and education, race/ethnicity), access to screen-based media, neighborhood factors, parental behavior, psychosocial (depression, few peers) and family factors (parental and sibling behavior and viewing habits), as well as other health behaviors (physical activity and dietary behavior; Gorely, Marshall, & Biddle, 2004; Salmon, Tremblay, Marshall, & Hume, 2011; Zabinski, Norman, Sallis, Calfas, & Patrick, 2007). Further, several screen-time interventions have been conducted, some of which have focused on the aforementioned correlates of sedentary time to facilitate behavior change. As evaluated by two recent meta-analyses, these interventions have had significant, albeit limited, success in reducing overall screen time in youth (Biddle, O’Connell, & Braithwaite, 2011; Maniccia, Davison, Marshall, Manganello, & Dennison, 2011). However, there is some inconsistency between these findings: Another meta-analysis found no net effect on reductions in screen time or body mass index following screen-time interventions (Wahi, Parkin, Beyene, Uleryk, & Birken, 2011). Qualitative research can complement and advance the knowledge base gained through quantitative studies, as it is discovery-oriented and ideal for hypothesis generation, and takes the lived experience of study participants into consideration (Pope, Mays, & Popay, 2007). Further, qualitative research is particularly useful for exploring perceptions, processes, barriers, and facilitators of complex phenomena (Johnson & Waterfield, 2004), including sedentary behaviors. As demonstrated in a qualitative review of physical activity in youth (Allender, Cowburn, & Foster, 2006), synthesizing qualitative studies provides one avenue for identifying and conceptually defining parental and youth perceptions of behavior. It can also provide a more in-depth understanding of how diverse factors interact, as well as suggest possible cause– effect relationships that can be explored using quantitative methodology. In addition, the examination of parent- and youth-endorsed barriers and facilitators to sedentary behaviors, such as screen time, may identify the strategies that can be used in behavior change interventions to reduce the time that youth are sedentary (Biddle et al., 2011). Investigating insights from both parent and youth perspectives is essential, as youth are often the targets for behavior change, and parents have a strong influence on the participation of their children in sedentary pursuits (Norton, Froelicher, Waters, & Carrieri-Kohlman, 2003). To date, no synthesis of qualitative findings pertaining to sedentary behavior barriers and facilitators in youth has been conducted; however, a more comprehensive exploration of this complex and modifiable health risk behavior may lead to a greater understanding of the obstacles and reveal novel practical strategies to reduce sedentary time. Therefore, the aim of this study was to use qualitative metasynthesis techniques (Sandelowski & Barroso, 2007; Sandelowski, Docherty, & Emden, 1997) to identify and conceptually define the barriers and facilitators to reducing screen time in youth 11 to 18 years of age. The metasynthesis seeks to integrate results from a number of different but interrelated qualitative studies to generate new insights and deepen understanding of the contextual dimensions of a health-related phenomenon (Walsh & Downe, 2005). An inductive approach was taken to derive the barriers and facilitators to reduce screen time from the

SCREEN TIME FACILITATORS AND BARRIERS

extensive and varied raw data that were presented in the primary articles (Thomas, 2006).

Method


Literature Review The qualitative metasynthesis began with a systematic search of the literature to locate articles that used qualitative methodology to describe barriers and facilitators to sedentary behaviors among youth. Sources were identified by the first and last author through searches of the following electronic bibliographic databases with the assistance of a medical librarian: Ovid MEDLINE, Ovid EMBASE, Ovid PsycINFO, Scopus, and CINAHL between January 2001 and January 2014. Furthermore, use of contemporary screenbased technologies, such as tablets, handheld video games, and personal computers have only expanded in recent years, and these technologies were not widely available prior to the 2000s. Articles published from 2001 onward were selected because of the establishment of public health guidelines that recommend less than 2 hr of screen time per day (American Academy of Pediatrics, 2001). Keywords were selected for the database search focusing on the following fields: (a) behaviors, including such terms as sedentary, sedentary behavior, sedentary lifestyle, physical inactivity, or low energy expenditure; combined with (b) modes, including the terms computer, computer games, video games, TV (watching or viewing), screen time, screen-based entertainment, Internet, indoor, transportation, car, automobile, or bus; combined with (c) age and year limiters, and qualitative clinical queries and keywords. Conducting searches of primary qualitative studies can be a challenging process; therefore, qualitative search strategies were employed to capture the breadth of qualitative literature in each database. Search strategies encompassed oversight from a medical librarian, the use of database filters, and sensitivity and specificity algorithms to identify articles (McKibbon, Wilczynski, & Haynes, 2006; Walters, Wilczynski, Haynes, & Hedges Team, 2006; Wilczynski, Marks, & Haynes, 2007; Wong, Wilczynski, Haynes, & Hedges Team, 2004).

Inclusion and Exclusion Criteria To be eligible for the metasynthesis, articles must have met the following inclusion criteria: (a) published between January 2001 and January 2014; (b) published in English in a peer-reviewed journal; (c) available in full text; (d) contained a qualitative design component; (e) youth, parents, or educational professionals were the subject of research; and (f) mean or median age range of 11 to 18 years. This age range was selected because screen time has been shown to peak in early adolescence, and because older adolescents are among the most sedentary populations, most are still living in the family home, and they have high levels of screen time (Crain, 1985; Gorely, Marshall, Biddle, & Cameron, 2007; Jenkins, 2007; Matthews et al., 2008). Reviews, editorials, intervention and program evaluation articles, unpublished manuscripts, dissertations, and abstracts were excluded. Studies focusing on physical activity barriers and facilitators, when not explicitly linked with sedentary behaviors or screen time, were also excluded.

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Article Review and Data Analysis The first author (a public health researcher with extensive qualitative methodology experience) conducted the data extraction, and this process was facilitated by the use of a data display matrix to extract reliable and consistent data from the primary studies (Miles & Huberman, 1994). Information was extracted relating to the following study characteristics: year, country in which the study was conducted, sample size, interviewee (youth, parent, or educational professional), sample age range, gender and race of participants, environmental context of screen time (home, school, or community), data collection method, qualitative analytic technique, and study aim. Data were also extracted pertaining to type of screen time (TV, computer, electronic media, or other sedentary behavior), and if the study recruited youth experiencing a specific health condition (e.g., youth who were obese or asthmatic). Each article was also critically reviewed to extract data relating to perceived barriers and facilitators to sedentary behavior among youth. The exact phrases, quotes, and/or author interpretations (i.e., theme or subtheme) were recorded in the data display matrix to facilitate article comparisons (Miles & Huberman, 1994). Because authors’ interpretations constitute an important type of collected data and are generally based on the sum of the data, articles comprised of youth outside of the age range were included in the metasynthesis if the mean or median age fell within the target age range. There is no currently agreed upon standard for the quality appraisal of qualitative studies (Dixon-Woods, Shaw, Agarwal, & Smith, 2004; Sandelowski et al., 1997). Nevertheless, the included articles underwent an independent quality assessment by the first, fourth, and last authors. A quality assessment checklist developed by McInnes and Chambers (2008) was used to appraise the methodological rigor of each article and determine a quality rating. This quality appraisal tool utilized information from the Critical Appraisal Skills Program (2002) and the Evaluation Tool for Qualitative Studies (Evaluation Tool for Qualitative Studies, 2006). The quality ratings for each article are available in Table 1, and the quality appraisal criteria are presented in Table 2. Quality appraisal scores should be interpreted cautiously, as authors may have conducted compelling and rich studies that were grounded in the data, but failed to be transparent in terms of presenting methodological procedures (Dixon-Woods et al., 2004). A coding structure was developed by the first and last authors (the latter, an experienced research academic with expertise in qualitative methodology) to code the data on barriers and facilitators to reducing screen time collected in the data display matrix. After all data were coded, codes were iteratively reviewed and collapsed into categories of similar meaning for both barriers and facilitators. Initially, 12 basic codes, encompassing numerous subcodes, were identified as barriers to reducing screen time. Similarly, nine codes, also with several subcodes, were identified as facilitators to reducing screen time (see Table 3). An example of a code encompassing numerous subcodes is “many challenges to enforcing rules and screen time limits.” This code encompassed such subcodes as “efforts to reduce screen time caused family conflict,” “different youth age groups have opposing expectations,” and “screen time is not perceived as a family problem.” Reciprocal relationships were noted, and categories were finalized.

To examine parent and youth attitudes about limiting youth’s television-viewing time

To examine how the family home environment may shape electronic media use within the home

Author: (Granich, Rosenberg, Knuiman, & Timperio, 2010)

To assess parents’ views about their children’s television-viewing, strategies they use to reduce viewing, obstacles faced when trying to implement such strategies and their views of two types of electronic monitors that can be used to restrict television-viewing

To explore new paradigmatic social thinking on the results of empirical research on the role of television in families

To develop a better understanding of factors associated with the maintenance and the decline of sedentary behavior in adolescence

Aim

Author: (Evans, Jordan, & Horner, 2011) Country: U.S.A. QA: 86%

Country: New Zealand QA: 78%

Author: (Dorey et al., 2010)

Country: New Zealand QA: 50%

Author: (Bell, 2011)

Country: Canada QA: 86%

Author: (Bélanger et al., 2011)

Author, country, and quality assessment (QA) score (%)

Table 1 Summary of Reviewed Articles

Youth age range: 6–13 years Interviewee: Youth & parents Environment: Home Gender: 77% mothers; NR% girls Race: 36% White Type of ST: All N ⫽ 92 (54 youth, 38 parents)

Youth age range: 8–13 years Interviewee: Parent Environment: Home Gender: 97% mothers Race: Maori/Pacific; Maori/nonPacific; and non-Maori/nonPacific Type of ST: TV N ⫽ 270 (180 youth, 90 parents)

Youth age range: 10–13 years Interviewee: Youth & parents Environment: Home and school Gender: NR Race: NR Type of ST: TV and electronic media N ⫽ 40

Youth age range: 15–18 years Interviewee: Youth Environment: Home; interviews conducted in school Gender: NR Race: NR Type of ST: All N ⫽ 76 (54 youth, 22 parents)

N ⫽ 56

Sample characteristics

Focus groups (stratified by socioeconomic status); Family interviews

Focus groups (youth and parents separated)

Focus groups (stratified by race)

Interview

Focus groups (stratified by gender and by maintainer and decliners to physical activity)

Data collection method


Thematic analysis

Content analysis

Content analysis

Interpretive analysis

Thematic analysis

Analytic technique

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Author: (Levin-Zamir, Lemish, & Gofin, 2011)

QA: 86%

Country: U.S.A.

Author: (Jordan, Hersey, McDivitt, & Heitzler, 2006)


Author: (He, Piché, Beynon, Kurtz, & Harris, 2011)

Country: Australia QA: 89%

Author: (Hattersley et al., 2009)



Table 1 (continued)

To design and develop an instrument to characterize and measure media health literacy. The purpose of the qualitative phase of the instrument development was to establish the conceptual basis for the major variables in the research model

To better understand the individual, familial, and sociocultural forces that shape youth’s television viewing in the home to identify possible simple and incremental approaches that pediatricians and others can suggest to help reduce youth’s television-viewing time

To report school principals’ and teachers’ perspectives on youth’s self-reported sedentary behavior, perceived barriers, and their suggested solutions to reducing sedentary behavior

To explore adolescents’ and parents’ perceptions, attitudes, and interactions in regards to adolescents’ screen time within the home environment

Aim

Youth age range: 3 equally-sized groups (6–7, 9–10, 12–13 years) Interviewee: Parent–youth pairs Environment: Home Gender: 50% girls; 77% mothers Race: 36% White Type of ST: TV N ⫽ 60

Youth age range: 10–12 years Interviewee: Principals & teachers Environment: School & home Gender: NR Race: NR Type of ST: TV, all N ⫽ 180

Youth age range: 13–16 years Interviewee: Youth & unrelated parents Environment: Home Gender: 42% girls; 63% mothers Race: NR Type of ST: All N ⫽ 53 (14 principals, 39 teachers)

Youth age range: 11–12 years Interviewee: Youth & parents Environment: Home; interviews conducted in school Gender: 52% girls; 80% mother Race: NR Type of ST: All N ⫽ 63 (31 youth, 32 parents)


Focus groups

Individual interviews; Focus groups

Interviews

Focus groups



(table continues)

Grounded theory

Thematic analysis

Content analysis

Thematic analysis

Analytic technique


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Country: U.K. QA: 89%

Author: (Sebire, Jago, Gorely, Hoyos Cillero, & Biddle, 2011)


Author: (Puglisi, Okely, Pearson, & Vialle, 2010)


Author: (Puglisi, Okely, Pearson, & Vialle, 2013)


To understand young people’s attitudes towards reducing screen viewing and explore their screen viewing reduction strategies

To examine barriers to physical activity and small screen recreation among families with obese youth, and to understand what strategies parents and youth were aware of to overcome any perceived barriers

To develop a deeper understanding of the day-to-day experiences of obese youth, and the weight-related behaviors evident in their everyday lives, to inform future interventions to treat youth obesity

Youth age range: 10–11 years Interviewee: Youth Environment: ST in all contexts Gender: 55% girls Race: NR Type of ST: All

Mean age: 5–12 years Interviewee: Youth & parents Environment: Home Gender: 33% girls Race: NR Type of ST: Small screens N ⫽ 55

Youth age range: 7–12 years Interviewee: Youth & parents Environment: ST in all contexts Gender: 33% girls Race: NR Type of ST: All N ⫽ 9 youth and their parents (all youth were obese)

Youth age range: 15–16 years Interviewee: Youth Environment: ST in all contexts Gender: NR Race: NR Type of ST: All N ⫽ 6 youth and their families (all youth were obese)

N ⫽ 22 (all youth with asthma)

To describe perceptions of screen time and physical activity among youth with and without asthma

Author: (Protudjer et al., 2012)

Sample characteristics Youth age range: 12–17 years Interviewee: Youth Environment: NR Gender: NR Race: NR Type of ST: All

Aim

Country: Israel QA: 69%


Table 1 (continued)

Focus groups

Focus groups; Individual interviews

Naturalistic/ethnographic (participant observation, digital recordings, casual conversation, digital photographs)

Focus groups; Interviews



Thematic analysis

Thematic analysis

Observation

Thematic analysis

Analytic technique

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Note.

To explore perceived individual, social and physical environmental factors associated with youth’s resilience to low physical activity and high screen time

To gain a better understanding of mothers’ perceptions of factors that support youth to be physically active and that help limit time spent in screen-based behaviors, particularly television-viewing and video/ computer games

Aim

ST ⫽ screen time; TV ⫽ television; NR ⫽ not reported; QA ⫽ quality appraisal.


Author: (Veitch, Arundell, Hume, & Ball, 2013)


Author: (Veitch, Hume, Salmon, Crawford, & Ball, 2011)


Table 1 (continued)

Youth age range: 7–13 Interviewee: Youth & mothers Environment: Home ST Gender: 47% girls; 100% mothers Race: NR Type of ST: All

Youth age range: 7–13 years Interviewee: Mothers Environment: Home ST Gender: 100% mothers Race: NR Type of ST: All N ⫽ 76 (38 youth, 38 mothers)

N ⫽ 38


Semistructured interview

Semistructured interviews



Thematic analysis

Thematic analysis

Analytic technique SCREEN TIME FACILITATORS AND BARRIERS

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Table 2 Quality Assessment Criteria Clear aims/research question Design appropriate to answer research question Setting appropriate for research question Recruitment process given Participants appropriate to research question Ethical approval/informed consent given More than one perspective on research question Data collection method adequately described Data sufficiently detailed for research question Researcher bias addressed Clear description of analytical method Clear description of how results derived from analysis Analysis not biased by researcher (more than one analyst, triangulation, checked with participants) Contradictory data considered Findings presented in sufficient detail Findings discussed in context Implications discussed Limitations of study discussed Note. Methodological quality of each study was assessed for each criterion using the following designations: fully met, partially met, not met, and not applicable. Scores were provided for each criterion as follows: fully met (⫹1), partially met (⫹0.5), not met (–1.0), and not applicable (0). Total scores were generated, and the percentage score was derived by dividing the total by the number of criteria. Individual study scores are provided in Table 1.

When applicable, the antecedents and consequences to sedentary behavior were described. To generate the key themes, the categories, codes, and data were iteratively examined to identify coherent patterns within the data. Categories were continually combined into a broader representation of the data using the constant comparative method (Jensen &

Allen, 1996). As the synthesis evolved, it became apparent that the domains of barriers and facilitators to reducing screen time fit into similar categories. Thus, in total, three descriptive and overarching thematic categories that encompassed both barriers and facilitators to reduce screen time were identified. To enhance rigor, the coding process was independently reviewed and verified with three authors (the first, fourth [a doctoral student with qualitative research experience], and last authors) to assure the integrity, trustworthiness, and conceptual fit of the data. Concise statements were then developed by all of the authors to comprehensively capture the content (Sandelowski & Barroso, 2007).

Sample Description A total of 805 articles were identified and imported into Endnote software (see Figure 1). Duplicates were removed via the Endnote duplicate function and any remaining duplicates were manually removed, leaving a total of 458 articles. A thorough review of all article titles and abstracts was conducted to identify articles to review in full text (N ⫽ 28). The removal of inapplicable articles refers to cases in which it was clear from the title and abstract that those articles did not meet the inclusion and exclusion criteria for proceeding to the full-text review stage. The majority of articles excluded after review of their title or abstract were related to mean or median sample age outside of the target age range, and no evidence of a qualitative methodology. In cases in which this information was missing or ambiguous, the article underwent full-text review. After full-text review, 15 of the 28 articles were excluded, most often because of sample age, because no qualitative data were reported, or because the studies were review articles. Reference lists from those articles reviewed in full text were also examined to identify articles missing from the electronic

Table 3 Thematic Representation of Barriers and Facilitators to Screen Time Youth norms of use Barriers (N ⫽ 12) Screen-based media is routinized in everyday life and not perceived as being excessive “Addictive” nature of screen time Source of enjoyment, entertainment, communication, and confidence- and skill-building Lack of active social network

Facilitators (N ⫽ 9) Youth perceive time spent engaged with screen-based media is excessive and are interested in reducing screen time Finite skill limit of small-screen entertainment (i.e., computer games)

Family dynamics and parental roles

Resources and environment

Screen time is an important shared family activity (coviewing)

Easy accessibility to and ubiquitous presence of screens in the home and bedroom

Parents role model engagement with screenbased media

Safe and affordable school- and community-based opportunities to reduce sedentary behavior are lacking Neighborhood and environmental barriers

Screen time used as a “babysitter” Many challenges to enforcing rules and screen-time limits Parental perception of screen-time benefits for youth Rules, limits, and parental monitoring of screen-based media content and time

Removal of screen-based media from youth’s bedroom

Ability of youth to self-regulate screen time

Engagement in extracurricular school-based activities Dog ownership

Awareness of health consequences of excessive screen time

Access to a large backyard or rural community that promotes outdoor recreation


Potential articles based on search in 5 databases 805 records


Removal of duplicate articles 347 records

Titles and abstracts read 458 records

Removal of inapplicable articles 430 records

Selection criteria applied to full manuscripts 28 records

Exclusions (N = 15) Sample age outside of range 6 records No qualitative data reported 3 records Review article 3 records Focus on physical activity 3 records

Articles added from reference lists 2 records

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pair, and youth–nonparent pair. Of those studies including youth, both boys and girls were represented, and the participants emanated from a variety of socioeconomic and geographic backgrounds. In all studies, screen time was the sedentary behavior that was assessed, and TV watching was the primary mode of screenbased activity. Therefore, henceforth, the term “sedentary behavior” will be replaced with “screen time.” Only two studies conducted purposeful sampling with a specific population (youth who were obese and youth diagnosed with asthma). There were also instances in which multiple articles appear to have been published using the same study sample. Specifically, Puglisi, Okely, Pearson, and Vialle (2010; 2013) describe the experiences of youth who were obese, but each article uses different data collection methods and reports on different interviewees. Similarly, Veitch, Hume, Salmon, Crawford, and Ball (2013) and Veitch, Arundell, Hume, and Ball (2013) report on findings from distinct interviewees, including mothers and youth and their mothers, respectively. Geographically, six studies were conducted in Australia, three in Canada, two in the United States, two in New Zealand, and one each in Israel and the United Kingdom. The environmental context of most studies pertained to screen time in the home; three reported all contexts, which comprised home, school, and neighborhood; and two specifically focused on the home and school settings. All studies reported their data collection method, comprising six focus groups, four interviews, four focus groups and interviews, and one naturalistic approach. All studies either reported the qualitative data analysis method, or it could be inferred from the data analysis section. Most studies conducted thematic analysis (n ⫽ 9), three employed content analysis techniques, and one study was conducted for each of grounded theory, interpretive phenomenological analysis, and observation. All studies had a cross-sectional design.

Results

Articles included in qualitative metasynthesis N = 15 Figure 1. Flow diagram of literature search strategy.

search, which elicited two additional studies. Thus, a final sample of 15 articles was identified for this qualitative metasynthesis. Table 1 summarizes the characteristics of the included studies. Sample sizes ranged from 6 to 270 participants. Participants’ age varied widely across studies, and the majority of studies (n ⫽ 10) included participants who were younger than 11 years of age. Studies that had youth younger than the age range were included, provided that youth within this study’s targeted age range were also included. Few studies in the sample reported exclusively on older adolescents (16 –18 years), whereas most focused on pre- to early adolescents (11–13 years). A number of studies interviewed both parents and youth (n ⫽ 6), and of those, a larger proportion of mothers than fathers participated. Six studies comprised youth and parents, four were youth only, two were parents only, and one each was composed of principals and schoolteachers, parent–youth

Three overarching themes describing perceived barriers and facilitators to reducing screen time in youth were identified: (a) youth’s norms—screen time is an integral part of daily life, and facilitates opportunities for entertainment, social interaction, and escapism; (b) family dynamics and parental roles—parents are conflicted and send mixed messages about the appropriate uses and amounts of screen time; and (c) resources and environment— engagement in screen time is dependent on school, community, neighborhood, and home environmental contexts. Each theme is discussed in detail next, including an introduction to the theme, and, when applicable and available, illustrative examples from the raw data are provided.

Youth’s Norms: Screen Time Is an Integral Part of Daily Life, and Facilitates Opportunities for Entertainment, Social Interaction, and Escapism Norms of screen-time use refers to the ubiquitous nature and engagement of screen-based media in youth’s lives. Barriers to reducing screen time include its “addictive” nature and routinized integration into everyday life. Youth often perceived their engagement with screen-based media as reasonable, whereas some felt that time spent engaged with screen-based media was excessive and were interested in reducing screen time. Most studies reported that youth found screen time to be enjoyable, entertaining, and


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confidence- and skill-building, and enabled communication with peers from a similarly sedentary and physically inactive social network. However, some youth identified that small-screen entertainment had a finite skill limit, such as ability to win a video game, which facilitated participation in physical activity and higher-valued sedentary activities. Studies found that youth and parents acknowledged screen time as a part of daily life and as playing a dominant role in youth’s lives. This is evidenced in that most youth in the studies reviewed spent 3 to 4 hr per weekday on various screen-related activities, which increased based on temporality of weekends, social gatherings, and school breaks. Time spent engaged with screens also had an “addictive” component, as demonstrated by the reaction of a girl to the suggestion of reducing screen time: “They bring out new episodes of what channels we like and I think if we stop watching what we want, like we miss the new episodes” (quotation by Youth; Sebire, Jago, Gorely, Hoyos Cillero, & Biddle, 2011, p. 304). Further, screen time, particularly TV time, was interspersed throughout the day and was often a part of family meals. The routinized presence of screen time in the home was stated by one boy: (I) get up watch TV, have breakfast, get ready, watch TV (for) half an hour, go to school, come home watch TV (for) about an hour or so, go to sport, watch TV after sport. Watch for about half an hour or so or maybe an hour depends, have dinner, and after dinner I watch about another hour and a half maybe two hours until bedtime. (Youth; Granich, Rosenberg, Knuiman, & Timperio, 2008, p. 202)

Engagement with screen-based media presented an opportunity for youth to interact with peers via small-screen recreation (e.g., gaming consoles), and to be entertained by other devices such as televisions or DVDs. Screen time was often used as a default activity for unstructured leisure time, as exemplified by a parent: My youth . . . if they are not watching TV, they’re either on the Xbox, and if it’s not the Xbox then they’re on the computer . . . They rotate [the TV, Xbox and the computer], there’s three [youth] and there’s no-one who will go outside. (quotation by Parent; Dorey et al., 2010, p. 416)

Engagement with screen time was also perceived by youth to be a deliberate opportunity to rest, relax, and have personal time, as exemplified by one girl: Um, I normally come home from school, watch a bit of TV and have a snack and a drink and then I decide to do something else. I kind of, like [participant] said, almost recharge. I have enough energy to do something else. (Youth; Sebire et al., 2011, p. 304)

Some youth in the reviewed studies also noted that they used screen time as a coping mechanism for family conflict or other stressful matters, as stated by one boy: “If you have like a bad day, you can just take your mind off it just by watching (TV)” (Youth; Bell, 2011, p. 394). In addition, some youth reported escapism through the use of screen-based entertainment to retreat from the banality and challenges of everyday life. Youth also reported that they enjoyed engaging with screentime activities, such as playing video and computer games, because these activities improved self-esteem and confidence, and it was perceived to be easier to excel at them than physical activities.

Youth also used screen time as an opportunity to communicate via text, e-mail, or social networking. Despite the pervasive use of screen time in the home setting, youth viewed the quantity of screen time as excessive at times, prompting a desire to reduce screen time despite not knowing what activity could replace screen time, as stated by one girl: “I think it would be quite useful because sometimes you find yourself watching tele just because you don’t know what else to do” (Youth; Sebire et al., 2011, p. 304). One study that examined strategies to reduce screen time among highly active youth found that youth’s individual preference to be physically active, including a preference for spending time playing outside or sport, was the main factor that influenced the amount of time they spent engaged in screen time (Veitch, Arundell, et al., 2013). Youth often acknowledged other types of higher-valued sedentary activities to replace screen time, such as reading, writing, homework, or practicing a musical instrument. Parents endorsed these alternatives, suggesting that the goal is to reduce low-value screen time (such as TV), not to reduce time spent in sedentary behaviors. However, other youth simply suggested switching to another screen-based media device, as stated by one girl: I try and not watch the TV as much because it is something that you are kind of lazy with, you don’t have to press any buttons or do anything. It is easier to do than going on an iPod or Nintendo. (Youth; Sebire et al., 2011, p. 304)

Living in an environment that lacked localized peer social support networks was perceived as promoting screen time, as exemplified by one boy: “My weekends and afternoons are generally the same. I don’t really do much. I just sit around ‘cause there’s not much to do and no one to do anything with” (Youth; Puglisi et al., 2013, p. 46). Conversely, the presence of an active social network of peers and siblings appeared to increase interest in physical activity participation in lieu of time spent engaged in screen-based media. Indeed, some youth rebuked the notion of screen time as skill-builder, maintaining that “there is no limit to what you can do with your sports” (Protudjer et al., 2012, p. 298) juxtaposed to computer and video games that have a finite skill limit. Thus, screen time is an established norm in many youth cultures, presenting barriers to change this behavior. However, youth were open-minded and willing to reduce screen time, and suggest replacing it with higher-valued activities, such as reading, homework, and physical activities.

Family Dynamics and Parental Roles: Parents Are Conflicted and Send Mixed Messages About the Appropriate Uses and Amounts of Screen Time The category of family dynamics pertains to the parental roles of inhibiting or promoting sedentary behaviors in the family and home setting, as well as the strategies that describe the process of reducing youth screen time. Antecedents and enablers to youth screen-time usage included parental perception of viewing tendencies and the health benefits of screen time for youth; parental role modeling of screen-time behavior; TV coviewing as an important and shared family activity; and using screen time as a babysitter. Consequences of reducing screen time from this perspective included challenges to the enforcement of rules or screen-time limits,



thereby demonstrating the reciprocal nature of this complex behavior. Strategies that families evoked to reduce screen time included setting rules, limits, and parental monitoring of screen-time content and time spent engaged with screen-based media, as well as the awareness of health consequences of excessive screen time and deliberate allocation of time for physical activity. Youthdriven strategies were also endorsed and included the perceived ability of youth to self-regulate and self-manage screen-time use, particularly among older adolescents. Antecedents and enablers to family dynamics occur before or during screen time. When asked to reflect on the amount of time that their children spent engaged with screen time, some parents in the reviewed studies perceived that it was not in excess and complemented a broad array of other active and leisurely activities their children engage in, and that youth should be able to decide how to spend their leisure time. The perception of not needing to limit TV use was also conceptualized in the context of other families: “A lot of these kids are overweight or they are couch potatoes . . . but not my kids” (Parent; Jordan, Hersey, McDivitt, & Heitzler 2006, p. 1306). Parents also perceived that time spent engaged with screen-based activities was inevitable, especially with defiant youth, as exemplified here: “I don’t know what else you can do, I mean you can’t do somersaults in the lounge room” (Parent; Puglisi et al., 2010, p. e37). Perceived health benefits of screen time also presented a barrier and consequence to reduce screen time. In particular, parents felt TV viewing provided youth with a time to relax after a demanding school day, and even assisted with regulating sleep patterns. Conversely, some parents placed time limits in the form of a bed curfew on TV viewing, as stated by one mother: “Recently we have said no TV after 9:00 p.m. because the kids are just too tired. We can see it (TV) starting to have an effect on the kids. They are having trouble waking up (in the morning)” (Parent; Granich et al., 2008, p. 205). Indeed, other potentially adverse health outcomes were observed and identified as facilitators to reducing screen time. Specifically, cognitive, psychosocial, and physiological consequences of excessive screen time were of concern. Parents and educational professionals perceived that screen time may impact social functioning, interaction and social skill-building, as exemplified by a school teacher: “Fitness of kids is decreasing, their social skills are weak . . . (they have) difficulties talking to peers . . . their problem solving skills are poor” (Sebire et al., 2011, p. 34). Some parents were also concerned that excessive screen time impacts sleep and may contribute to injuries, such as repetitive strain injury. Although most parents endorsed replacing screen time with physical activity when prompted, parents also often replaced screen time with higher-valued sedentary activities, such as homework, reading, or playing an instrument. Parents often role modeled engagement in screen time to their children, as demonstrated by one youth: “We have a family laptop so when she (mum) wants to go on it she’ll say, ‘get off the laptop.’ Then like I do the same to her, but she’ll say, ‘Wait’” (Youth; Sebire et al., 2011, p. 306). Parents also expressed reluctance and found it difficult to change their own viewing behaviors. One mother stated, “My husband and I would really have to get out of the comfort zone of sitting down and watching TV as well” (Parent; Jordan et al., 2006, p. e1307). Further, some parents and youth noted dissimilar par-

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enting practices regarding role modeling, such that fathers were perceived to disproportionately engage in more screen time than mothers, and mothers often acted in the role of screen-time moderator. Role modeling was compounded when youth were engaged in screen time by merit of coviewing with their parents, which was often recognized as part of the social fabric and family life. Coviewing of TV, in particular, was perceived as a valuable asset to parents, in that it stimulated communication and bonding between youth and their parents, as well as facilitated discussion of sensitive issues through fictional, but relevant, life circumstances that their youth may experience, particularly among older adolescents. Nonetheless, parents felt that coviewing with their children was not “counted” toward overall screen time, as it was reported to be an important shared family activity and was distinct from youth-initiated screen time. Screen time also acted as the role of a babysitter for parents by helping them to regulate youth’s behavior, even among the typically more independent group of older adolescents. The utility of screen time for distraction purposes was highlighted by Evans, Jordan, and Horner (2011), who found that 56 of 60 parents who attended focus groups perceived that screen time was helpful. Specifically, screen-time babysitting was observed as a safe and affordable distraction for youth to provide parents with uninterrupted time to complete chores, relax, work, and to promote peace of mind knowing that youth were out of trouble (i.e., “stranger danger”). For example, one mother revealed that the time left to be undistracted was highly valued: “If she watches less . . . I become the entertainer. And I’m cooking dinner” (Mother; Jordan et al., 2006, p. 1307). Parents and youth perceived that an absence of explicit rules and restrictions regarding engagement with screen-based media was a barrier. Consequently, parents often recommended the implementation of rules, regulations, and monitors as facilitators to reduce screen time. Parents often cited rules related to temporality, such that youth could not engage in screen time during mealtimes. Setting time limits for a youth to use screenbased media was another suggested method, and was facilitated by using rosters or screen-time charts to indicate total time usage. Time limits to screen time were most useful when implemented during the school week, either before or immediately after school, thereby proving an opportunity for youth to participate in activities that depend on the daylight, such as being outdoors with peers. In circumstances when youth would visit split-parent homes, youth suggested that each of the homes conform to the same rules and exercise consistent discipline with enforcing them. Nonetheless, parents’ perceptions of adhering to the American Academy of Pediatrics’ (2001) guideline of less than 2 hr of screen viewing were observed to be good in theory, but difficult to implement in practice. Many other youth and parents stated that it was unacceptable and unrealistic. For instance, one girl stated, “To be honest I don’t think anybody actually listens to them (guidelines)” (Youth; Sebire et al., 2011, p. 305). Employing electronic or machine monitoring devices like programmed cable channels and remote controls, or utilizing a voucher system to control or assist in the management of TV viewing, were other effective options reported by some parents to regulate youth’s screen time. Parents also advocated for the


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use of screen time as a reward for doing other tasks, such as physical activities (e.g., household chores, mowing the lawn). However, often these tasks were also related to other sedentary activities, such as homework, consistent with the finding that parents often replaced screen time with a sedentary activity of higher value. Youth perceived the use of such rewards as effective in the short term, but expressed concern that conflict may occur if rewards were to be withdrawn or allotted inconsistently. Further, concern and apprehension about the content that their youth might be exposed to if the parent is not home to monitor the programs was a facilitator to establishing rules and guidelines around reducing screen time. As one parent stated, “Some of the programs that have got war things and murders, I don’t really like them watching those . . . it affects the youth and I’ve found that some of the things come through in their play” (Parent; Dorey et al., 2010, p. 416). Yet notably, parents of older adolescents appeared to institute fewer rules than parents of pre- to early adolescents (Bélanger et al., 2011; Hattersley et al., 2009). Not surprisingly, the implementation and enforcement of such rules and regulations often caused family conflict, especially between siblings. Youth frequently observed parentendorsed time limits as unfair if they were either ineffective or the youth was not part of the decision making. In such circumstances, youth would often attempt to circumvent the rules, causing family conflict. To avoid such conflict, some parents and youth in the reviewed studies recommended that youthcentered rules and regulations could be developed that place the onus on the youth to self-regulate their screen-time behavior. This approach may also be ideal for families in which excessive screen time is not an issue, and to ensure that it does not evolve into one, as one mother stated: They’re pretty good at self-regulating. I’m not very often in that situation to have to tell them to turn it off. They know themselves pretty much that the weather’s nice, it’s time to get out and do something else. So, I don’t really have to crack the whip. (Parent; Veitch, Hume, et al., 2013, p. 99)

Many studies suggested that a discussion between the parent and youth regarding simple self-monitoring of screen time was warranted. Of course this approach may not work for all youth, as some parents indicated that conversations about screen-time limits were confrontational and frequently escalated into shouting and arguments (Hattersley et al., 2009). When conflict ensued, many parents often eased the restriction, which, interestingly, youth attributed to a poor strategy. Instead, youth suggested that parents were better off being steadfast to the instituted rules, despite the youth’s attempt to overcome them, and thus be an effective agent of change for the maladaptive behavior. In summary, family dynamics posed a unique challenge to reducing screen time, mainly because of parental role modeling and coviewing that fostered communication and enjoyment for families, yet several strategies existed to curtail excessive engagement in screen-based activities. Ultimately this responsibility fell on the parents, as family structure and dynamics were the key factors that made strategies to reducing screen time difficult to implement.

Resources and Environment: Engagement in Screen Time Is Dependent on School, Community, Neighborhood, and Home Environmental Contexts This category refers to the family resources and environment that provides or prohibits excess, access, or absence of screen time in youth’s lives. Barriers to reduce screen time included easy access to, and ubiquitous presence of, screens in the home and bedroom; access to safe and affordable school- and communitybased opportunities to reduce sedentary behavior and promote physical activity; as well as neighborhood and environmental factors such as neighborhood safety, weather-related concerns, and localized social support networks. Facilitators to reduce screen time included the removal of screen-based media from bedrooms, engagement in extracurricular school-based activities, dog ownership, as well as access to a large backyard or rural community that promoted outdoor recreation. Increased access to screen time pertains to the ubiquitous presence of screen-based media in homes, which encourages excessive amount of time spent in small-screen recreation—as one father stated, “Go and watch a different TV. There are four others in the house. Pick one upstairs so at least you get the exercise walking up” (Parent; Puglisi et al., 2013, p. 46). Specific to this thematic category, youth frequently stated that they had access to screenbased media in their bedroom, and the devices most often included TV, gaming consoles, and computers. Access to these technologies enabled screen time before and after school, as well as at bedtime, and was identified as a barrier to reducing screen exposure and encouraging other higher-valued sedentary or physical activities. Indeed, parents endorsed the removal of such screen-based media in the bedroom as a strategy to reduce screen time. However, this often triggered much opposition, particularly from older adolescents, who determined that this was not an “appropriate solution” to the problem. Notably, no studies, including those that were recently published, explored the use of newer technologies such as tablets or smartphones in the home or bedroom environments. Parents and youth perceived the absence of safe, affordable, and entertaining facilities outside the home, school, or community as a barrier to reducing screen time, as illustrated by one girl: I used to go out all the time with my friends but there’s nothing to do around [home location], there’s just loads of shops and houses . . . we like to do fun activities but there isn’t any, that’s why mostly I’m at home and on the computer. (Youth; Sebire et al., 2011, p. 305)

Similarly, some parents in the reviewed studies perceived that it was difficult to find entertaining nonscreen activities to participate with their children in, especially as they matured, as exemplified by one mother: We knew what to do with them when they were younger. It’s hard to figure out what to do with them now. I mean, we can’t take them to the Franklin Institute [a science museum in the city] anymore— they’re bored with that. (Parent; Evans et al., 2011, p. 10)

Homes located in unsafe environments prompted a fear of “stranger danger” that led to leisure time spent indoors and the subsequent increase in screen time. Further, many youth expressed interest in participating in physical activities, but felt that the home environment either did not have access to ade-


quate physical space or the backyard was too small for physical activity, as stated by one boy: I think there is a leisure center and there is loads of facilities there but I don’t really like swimming and all the other ones you have to pay for. If they had a public basketball and football court I would really like that. (Youth; Sebire et al., 2011, p. 305)


Parents also observed the disadvantage of having inadequate recreational space and its relation to overweight: Well when we moved here he was only two and he didn’t have a weight problem before we moved here . . . they used to always be in the backyard and now because he doesn’t have that option of having a big backyard he’ll say, “I’ll watch a movie instead” or he’ll sit in his room instead. (Parent; Puglisi et al., 2010, p. e36)

Conversely, families who lived in rural communities, and those families that owned a dog, often perceived that increased access to recreational space and pet ownership and its associated responsibility promoted a more active and less sedentary lifestyle, as exemplified by one mother: “If I’m walking the dog I’ll ask him [her son] to come with me. Also, it’s good rather than just maybe sort of coming home from school and sitting in front of the telly or the computer” (Parent; Veitch, Hume, et al., 2013, p. 98). The impact of an environment with ample opportunities for sedentary behavior was not limited to the home or community settings. Teachers and principals of schools also expressed concern that the school environment promoted sedentary lifestyles and that other academic disciplines take priority over physical activity opportunities (e.g., physical education and recess). School facilities were perceived to provide an opportunity to promote physical activity and higher-valued sedentary opportunities through the supervision of inexpensive recreational activities and creative afterschool clubs and sports, thereby enhancing youth’s skill sets and providing alternatives to screen time. However, a means of transportation was mentioned as a barrier for some families if the parents or the youth did not have access to a vehicle to return home after the activity. Other barriers to reducing screen time included environmental hazards, such as weather-related events that forced youth to stay inside and thus promoted the use of screen-based media. In summary, engagement in screen time is often dependent on the school, community, neighborhood, and home environmental contexts. These settings act as both barriers of, and facilitators to, reducing screen time, and point to potentially modifiable environmental factors that may promote a more active and less sedentary lifestyle.

Discussion This qualitative metasynthesis highlights the complex interplay of youth and parent perceptions of engagement in screen time—an obesity-related health risk behavior. Three broad themes encompassed the barriers to, and facilitators of, reducing youth screen time, including the integration of screen time in youth’s daily lives, parental roles and family dynamics surrounding screen-time use and limits, and the contextual factors related to resources and environment. This new synthesis of findings from primary qualitative studies provides a broader-based and integrated conceptual understanding of screen-time barriers and facilitators among

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youth. Importantly, this review has revealed obstacles as well as potential practical strategies to reduce screen time that have and have not been previously tested in interventions that target this behavior in youth. Screen time is an established norm in many youth cultures, indicating significant barriers to behavior change. Nevertheless, in the context of this metasynthesis, several practical behavior change strategies have been identified to reduce time spent sedentary. For instance, parents and youth often identified similar barriers to reducing screen time, and often had parallel perceptions regarding the deleterious health implications of excessive screen time. In addition, youth and parents identified that rules, limits, and parental monitoring of screen time were effective mechanisms of behavior change. This suggests that an open and collaborative discussion between youth and parents regarding barriers may point to mutually agreed facilitators to reduce screen time, such as setting screen-time limits or removal of electronic media from youth’s bedrooms. Indeed, many intervention studies have delivered similar behavioral and educational components, such as goal setting, rewards, parental rules and monitoring of viewing, educational materials to students and parents, or a child and/or parent developed screen-time contract or budget, but findings were mixed in terms of reductions in screen time (Gortmaker et al., 1999; Paw, Singh, Brug, & van Mechelen, 2008; Robinson et al., 2003). Another strategy identified by parents in this study was the use of an electronic time-monitor or voucher system. Although several interventions have now shown these to be efficacious tools to reduce and budget screen time (Ford, McDonald, Owens, & Robinson, 2002; Goldfield et al., 2006), some have not (Ni Mhurchu et al., 2009), even reporting that the device contributed to family conflict related to inability to watch TV. In this regard, more work is needed to examine the mediators and moderators of screen-time interventions to illuminate psychobehavioral mechanisms and determine reasons for successful outcomes. Importantly, youth perceived that parents ought to be steadfast to the implementation of the agreed-upon arrangements to be an effective agent of behavior change. Indeed, parents should avoid reinforcement of excessive screen time by limiting coviewing with youth, relying on screen time as a babysitter, or restricting their own time spent engaged with electronic media (i.e., role modeling), an observation also noted in correlational studies (Hardy et al., 2006; Salmon et al., 2011). Because screen time, and TV time in particular, is perceived to be an important shared family activity, a balanced and collaborative approach to moderation of screen time may be warranted to mitigate family conflict, as contrasted with the discontinuation of screen-based media altogether. Several quantitative observational studies have shown coviewing and role modeling to be significant predictors of screen time (Hoyos Cillero & Jago, 2010); however, interventions have yet to target this approach. In addition, it was apparent in this study that parent- and youth-guided self-reflection and self-regulating strategies of monitoring screen time could be beneficial, particularly among older adolescents, as this developmental stage is associated with increased decision-making autonomy (Crain, 1985). Interventions have, with some success, employed the behavior change strategy of having youth identify alternative activities to screen time, although findings from this metasynthesis suggest that such proposed alternatives may comprise higher-valued sedentary behaviors instead of physical activities. Incorporating standing or


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physical activity “breaks” in screen time may be one promising behavioral strategy to both moderate screen time and reduce cardiometabolic risk for both youth and parents (Healy, Dunstan, Salmon, Cerin, et al., 2008; Healy, Matthews, Dunstan, Winkler, & Owen, 2011). Promoting the use of active video games may be another alternative, which has been shown to acutely increase light- to moderate-intensity physical activity in youth, but findings related to increases in habitual physical activity and decreases in sedentary behavior are less clear (LeBlanc et al., 2013). As summarized above, several modifiable determinants of screen-time behavior exist, from the individual (e.g., youth, parent), interpersonal (e.g., youth-parent, family), and community/ environmental (e.g., school, neighborhood) levels. This interaction between individual and socioecological factors may be synthesized within the ecological model of sedentary behavior (Owen et al., 2011), as screen time is an activity that is predominantly spent sedentary. The following components of that model are illustrated by the reciprocal relationships between the perception and process of barriers and facilitators to reduce and/or restrict screen time. Individual-level attributes include those related to preferences, enjoyment, or barriers of sedentary behavior. In the context of this study, some of the individual-level factors included youth and parent perception that screen time was not in excess and provided a time for youth to relax and rest. Youth perceived engagement with screen-based media as a source of enjoyment, entertainment, and confidence and skill-building. Similarly, although some parents in the reviewed studies recognized the importance of reducing youth screen time, they also recognized that they modeled and promoted engagement in screen time. Interpersonal-level attributes are included in the “proximal-social” domain of the model, and comprise those sedentary behaviors related to family demands and social norms, networks, and support. Some of the interpersonal-level factors identified in this synthesis included youth using screen-based media as a communication tool, oftentimes with a sedentary and physically inactive social network. Families also often perceived screen time as an opportunity to participate in a shared family activity, while many parents utilized screen-based media as a babysitter. Community/environmental factors operate to influence sedentary behaviors in specific contexts that make prolonged sitting more feasible. Our synthesis identified the ubiquitous presence of screens (e.g., TV, computer) in the home, and in the bedroom specifically, as promoting youth screen time, and the removal of such screens was identified as a facilitator to reducing screen time. Further, the lack of alternative safe and affordable school- and community-based opportunities were perceived as barriers to reducing screen time. Moreover, these findings point to potential practical strategies to reduce youth screen time, many of which could be tested in future intervention studies. For example, the targeting of parents’ own screen time, family coviewing, or parental coaching may help parents to implement and adhere to screen-time limits and rules more effectively. Another strategy may be to reduce access to screen-based media in the bedroom, as both youth and parents endorsed this facilitator, and several observational studies have confirmed this association (Gorely et al., 2004; Salmon et al., 2011). Further, an evaluation of screen time on social functioning, interaction, and social skill-building may also identify behavior change opportunities within social networks. Future qualitative research is also needed to explore the barriers and facilitators of

the contemporary use of screen-based mobile devices, such as tablets and smartphones, as well as define how youth engage in sedentary behaviors in general. Another research area that may be harnessed to reduce screen time is the method of media delivery (e.g., on-demand programming, digital video recorder), which may be used to better structure screen time. Importantly, findings and recommendations ought to be publicly reported in such a way that parents are aware of strategies that may reduce youth screen time. Findings derived from this qualitative metasynthesis must be interpreted in the context of the following limitations. First, although exhaustive search methods were used to eliminate any potential bias, it is possible that not all qualitative studies were identified. In addition, the exclusion of unpublished and gray literature may have contributed an element of publication bias, with potential implications for the robustness of the findings. Second, the sample characteristics of race/ethnicity and gender were omitted from several of the reviewed studies, potentially influencing the generalizability of the findings to other contexts. However, many of the perceived barriers and facilitators were similar, despite the range of countries in which the primary study was conducted. Third, the majority of reviewed studies employed focus-group methodology, which presents a possible social desirability bias. Fourth, the inclusion of some articles with youth outside of our specified age range may have resulted in capturing data that were more relevant to younger developmental stages. Nonetheless, the approach we have adopted is consistent with what has been used in previous studies (e.g., Hnatiuk, Salmon, Hinkley, Okely, & Trost, 2014). Lastly, as inherent with any qualitative design, interpretation bias may have skewed the identification of themes; however, three authors independently reviewed the code structure to assure the integrity of the data.

Conclusion Youth screen time is a universal, yet modifiable, sedentary behavior, and has multiple levels of influence (individual, interpersonal, community/environmental) in various domains (home, school, community). Despite the preliminary nature of the findings, this metasynthesis has underscored the importance of further research to understand the complex interaction of youth norms, family dynamics and parental roles, and resources and environmental factors that potentially could be addressed in order to improve sedentary behavior change initiatives. Given the prevalence of childhood obesity, the ubiquitous presence of screen devices in youth’s lives, and the limited success of existing screen-time interventions, researchers ought to integrate both qualitative and quantitative methods to progress the field by identifying key factors related to screen time. These factors will point to intervention pathways that researchers, practitioners, and policymakers can test and implement to reduce youth screen time and improve overall health outcomes.

References References marked with an asterisk indicate studies included in the metasynthesis. Allender, S., Cowburn, G., & Foster, C. (2006). Understanding participation in sport and physical activity among children and adults: A review


SCREEN TIME FACILITATORS AND BARRIERS of qualitative studies. Health Education Research, 21, 826 – 835. http:// dx.doi.org/10.1093/her/cyl063 American Academy of Pediatrics. (2001). American Academy of Pediatrics: Children, adolescents, and television. Pediatrics, 107, 423– 426. http://dx.doi.org/10.1542/peds.107.2.423 American Academy of Pediatrics. (2013). Council on Communications Media: Children, adolescents, and the media. Pediatrics, 958 –961. Advance online publication. Bar-Or, O., Foreyt, J., Bouchard, C., Brownell, K. D., Dietz, W. H., Ravussin, E., . . . Torun, B. (1998). Physical activity, genetic, and nutritional considerations in childhood weight management. Medicine & Science in Sports & Exercise, 30, 2–10. http://dx.doi.org/10.1097/ 00005768-199801000-00002 ⴱ Bélanger, M., Casey, M., Cormier, M., Filion, A. L., Martin, G., Aubut, S., . . . Beauchamp, J. (2011). Maintenance and decline of physical activity during adolescence: Insights from a qualitative study. The International Journal of Behavioral Nutrition and Physical Activity, 8, 117. http://dx.doi.org/10.1186/1479-5868-8-117 ⴱ Bell, M. (2011). The feel of mobility: How children use sedentary lifestyles as a site of resistance. Sport, Education and Society, 16, 385–397. http://dx.doi.org/10.1080/13573322.2011.571882 Bickham, D. S., Blood, E. A., Walls, C. E., Shrier, L. A., & Rich, M. (2013). Characteristics of screen media use associated with higher BMI in young adolescents. Pediatrics, 131, 935–941. http://dx.doi.org/ 10.1542/peds.2012-1197 Biddle, S. J., O’Connell, S., & Braithwaite, R. E. (2011). Sedentary behaviour interventions in young people: A meta-analysis. British Journal of Sports Medicine, 45, 937–942. http://dx.doi.org/10.1136/bjsports2011-090205 Colley, R. C., Garriguet, D., Janssen, I., Craig, C. L., Clarke, J., & Tremblay, M. S. (2011). Physical activity of Canadian children and youth: Accelerometer results from the 2007 to 2009 Canadian Health Measures Survey. Health Reports, 22, 15–23. Crain, W. C. (1985). Theories of development: Concepts and applications. Englewood Cliffs, NJ: Prentice Hall. Critical Appraisal Skills Programme. (2002). Making sense of evidence: 10 questions to help you make sense of qualitative research. Retrieved from http://www.casp-uk.net/ Dixon-Woods, M., Shaw, R. L., Agarwal, S., & Smith, J. A. (2004). The problem of appraising qualitative research. Quality & Safety in Health Care, 13, 223–225. http://dx.doi.org/10.1136/qshc.2003.008714 ⴱ Dorey, E., Roberts, V., Maddison, R., Meagher-Lundberg, P., Dixon, R., & Ni Mhurchu, C. (2010). Children and television watching: A qualitative study of New Zealand parents’ perceptions and views. Child: Care, Health and Development, 36, 414 – 420. http://dx.doi.org/10.1111/ j.1365-2214.2009.01031.x Dunstan, D. W., Barr, E. L., Healy, G. N., Salmon, J., Shaw, J. E., Balkau, B., . . . Owen, N. (2010). Television viewing time and mortality: The Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Circulation, 121, 384 –391. http://dx.doi.org/10.1161/CIRCULATIONAHA .109.894824 Evaluation Tool for Qualitative Studies. (2006). Evaluation Tool for Qualitative Studies. Salford, UK: University of Salford. Retrieved from http://usir.salford.ac.uk/12970/1/Evaluation_Tool_for_Qualitative _Studies.pdf ⴱ Evans, C. A., Jordan, A. B., & Horner, J. (2011). Only two hours?: A qualitative study of the challenges parents perceive in restricting child television time. Journal of Family Issues, 32, 1223–1244. http://dx.doi .org/10.1177/0192513X11400558 Ford, B. S., McDonald, T. E., Owens, A. S., & Robinson, T. N. (2002). Primary care interventions to reduce television viewing in AfricanAmerican children. American Journal of Preventive Medicine, 22, 106 – 109. http://dx.doi.org/10.1016/S0749-3797(01)00410-X

395

Goldfield, G. S., Mallory, R., Parker, T., Cunningham, T., Legg, C., Lumb, A., . . . Adamo, K. B. (2006). Effects of open-loop feedback on physical activity and television viewing in overweight and obese children: A randomized, controlled trial. Pediatrics, 118, e157– e166. http://dx.doi .org/10.1542/peds.2005-3052 Gorely, T., Marshall, S. J., & Biddle, S. J. (2004). Couch kids: Correlates of television viewing among youth. International Journal of Behavioral Medicine, 11, 152–163. http://dx.doi.org/10.1207/s15327558ijbm1103_4 Gorely, T., Marshall, S. J., Biddle, S. J. H., & Cameron, N. (2007). Patterns of sedentary behaviour and physical activity among adolescents in the United Kingdom: Project STIL. Journal of Behavioral Medicine, 30, 521–531. http://dx.doi.org/10.1007/s10865-007-9126-3 Gortmaker, S. L., Peterson, K., Wiecha, J., Sobol, A. M., Dixit, S., Fox, M. K., & Laird, N. (1999). Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health. Archives of Pediatrics & Adolescent Medicine, 153, 409 – 418. http://dx.doi.org/10.1001/ archpedi.153.4.409 ⴱ Granich, J., Rosenberg, M., Knuiman, M., & Timperio, A. (2008). Understanding children’s sedentary behaviour: A qualitative study of the family home environment. Health Education Research, 25, 199 –210. http://dx.doi.org/10.1093/her/cyn025 Hardy, L. L., Baur, L. A., Garnett, S. P., Crawford, D., Campbell, K. J., Shrewsbury, V. A., . . . Salmon, J. (2006). Family and home correlates of television viewing in 12–13 year old adolescents: The Nepean Study. The International Journal of Behavioral Nutrition and Physical Activity, 3, 24. http://dx.doi.org/10.1186/1479-5868-3-24 ⴱ Hattersley, L. A., Shrewsbury, V. A., King, L. A., Howlett, S. A., Hardy, L. L., & Baur, L. A. (2009). Adolescent-parent interactions and attitudes around screen time and sugary drink consumption: A qualitative study. The International Journal of Behavioral Nutrition and Physical Activity, 6, 61. http://dx.doi.org/10.1186/1479-5868-6-61 ⴱ He, M., Piché, L., Beynon, C., Kurtz, J., & Harris, S. (2011). Screenrelated sedentary behaviours of school-aged children: Principals’ and teachers’ perspectives. Health Education Journal, 70, 32–38. http://dx .doi.org/10.1177/0017896910363332 Healy, G. N., Dunstan, D. W., Salmon, J., Cerin, E., Shaw, J. E., Zimmet, P. Z., & Owen, N. (2008). Breaks in sedentary time: Beneficial associations with metabolic risk. Diabetes Care, 31, 661– 666. http://dx.doi .org/10.2337/dc07-2046 Healy, G. N., Dunstan, D. W., Salmon, J., Shaw, J. E., Zimmet, P. Z., & Owen, N. (2008). Television time and continuous metabolic risk in physically active adults. Medicine and Science in Sports and Exercise, 40, 639 – 645. http://dx.doi.org/10.1249/MSS.0b013e3181607421 Healy, G. N., Matthews, C. E., Dunstan, D. W., Winkler, E. A., & Owen, N. (2011). Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003– 06. European Heart Journal, 32, 590 –597. http://dx.doi.org/10.1093/eurheartj/ehq451 Hnatiuk, J. A., Salmon, J., Hinkley, T., Okely, A. D., & Trost, S. (2014). A review of preschool children’s physical activity and sedentary time using objective measures. American Journal of Preventive Medicine, 47, 487– 497. http://dx.doi.org/10.1016/j.amepre.2014.05.042 Hoyos Cillero, I., & Jago, R. (2010). Systematic review of correlates of screen-viewing among young children. Preventive Medicine: An International Journal Devoted to Practice and Theory, 51, 3–10. http://dx .doi.org/10.1016/j.ypmed.2010.04.012 Jenkins, R. R. (2007). The epidemiology of adolescent health problems. In R. M. Kliegman (Ed.), Nelson textbook of pediatrics (Vol. 18, chap. 110). Philadelphia, PA: Saunders Elsevier. Jensen, L. A., & Allen, M. N. (1996). Meta-synthesis of qualitative findings. Qualitative Health Research, 6, 553–560. http://dx.doi.org/ 10.1177/104973239600600407 Johnson, R., & Waterfield, J. (2004). Making words count: The value of qualitative research. Physiotherapy Research International, 9, 121–131. http://dx.doi.org/10.1002/pri.312

396


ⴱ

MINGES ET AL.

Jordan, A. B., Hersey, J. C., McDivitt, J. A., & Heitzler, C. D. (2006). Reducing children’s television-viewing time: A qualitative study of parents and their children. Pediatrics, 118, e1303– e1310. http://dx.doi .org/10.1542/peds.2006-0732 Katzmarzyk, P. T. (2010). Physical activity, sedentary behavior, and health: Paradigm paralysis or paradigm shift? Diabetes, 59, 2717–2725. http://dx.doi.org/10.2337/db10-0822 Katzmarzyk, P. T., Church, T. S., Craig, C. L., & Bouchard, C. (2009). Sitting time and mortality from all causes, cardiovascular disease, and cancer. Medicine and Science in Sports and Exercise, 41, 998 –1005. http://dx.doi.org/10.1249/MSS.0b013e3181930355 LeBlanc, A. G., Chaput, J.-P., McFarlane, A., Colley, R. C., Thivel, D., Biddle, S. J. H., . . . Tremblay, M. S. (2013). Active video games and health indicators in children and youth: A systematic review. PLoS ONE, 8, e65351. http://dx.doi.org/10.1371/journal.pone.0065351 ⴱ Levin-Zamir, D., Lemish, D., & Gofin, R. (2011). Media Health Literacy (MHL): Development and measurement of the concept among adolescents. Health Education Research, 26, 323–335. http://dx.doi.org/ 10.1093/her/cyr007 Maniccia, D. M., Davison, K. K., Marshall, S. J., Manganello, J. A., & Dennison, B. A. (2011). A meta-analysis of interventions that target children’s screen time for reduction. Pediatrics, 128, e193– e210. http:// dx.doi.org/10.1542/peds.2010-2353 Marshall, S. J., Biddle, S. J., Gorely, T., Cameron, N., & Murdey, I. (2004). Relationships between media use, body fatness and physical activity in children and youth: A meta-analysis. International Journal of Obesity, 28, 1238 –1246. http://dx.doi.org/10.1038/sj.ijo.0802706 Matthews, C. E., Chen, K. Y., Freedson, P. S., Buchowski, M. S., Beech, B. M., Pate, R. R., & Troiano, R. P. (2008). Amount of time spent in sedentary behaviors in the United States, 2003–2004. American Journal of Epidemiology, 167, 875– 881. http://dx.doi.org/10.1093/aje/kwm390 McInnes, R. J., & Chambers, J. A. (2008). Supporting breastfeeding mothers: Qualitative synthesis. Journal of Advanced Nursing, 62, 407– 427. http://dx.doi.org/10.1111/j.1365-2648.2008.04618.x McKibbon, K. A., Wilczynski, N. L., & Haynes, R. B. (2006). Developing optimal search strategies for retrieving qualitative studies in PsycINFO. Evaluation & the Health Professions, 29, 440 – 454. http://dx.doi.org/ 10.1177/0163278706293400 Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Thousand Oaks, CA: Sage. National Heart, Lung, and Blood Institute. (2013). We can! Tips to reduce screen time. Retrieved from http://www.nhlbi.nih.gov/health/public/ heart/obesity/wecan/reduce-screen-time/tips-to-reduce-screen-time.htm Ni Mhurchu, C., Roberts, V., Maddison, R., Dorey, E., Jiang, Y., Jull, A., & Tin Tin, S. (2009). Effect of electronic time monitors on children’s television watching: Pilot trial of a home-based intervention. Preventive Medicine: An International Journal Devoted to Practice and Theory, 49, 413– 417. http://dx.doi.org/10.1016/j.ypmed.2009.09.003 Norton, D. E., Froelicher, E. S., Waters, C. M., & Carrieri-Kohlman, V. (2003). Parental influence on models of primary prevention of cardiovascular disease in children. European Journal of Cardiovascular Nursing, 2, 311–322. http://dx.doi.org/10.1016/S1474-5151(03)00072-0 Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2012). Prevalence of obesity and trends in body mass index among US children and adolescents, 1999 –2010. Journal of the American Medical Association, 307, 483– 490. http://dx.doi.org/10.1001/jama.2012.40 Owen, N., Bauman, A., & Brown, W. (2008). Too much sitting: A novel and important predictor of chronic disease risk? British Journal of Sports Medicine, 43, 81– 83. http://dx.doi.org/10.1136/bjsm.2008.055269 Owen, N., Healy, G. N., Matthews, C. E., & Dunstan, D. W. (2010). Too much sitting: The population health science of sedentary behavior. Exercise and Sport Sciences Reviews, 38, 105–113. http://dx.doi.org/ 10.1097/JES.0b013e3181e373a2

Owen, N., Sugiyama, T., Eakin, E. E., Gardiner, P. A., Tremblay, M. S., & Sallis, J. F. (2011). Adults’ sedentary behavior determinants and interventions. American Journal of Preventive Medicine, 41, 189 –196. http:// dx.doi.org/10.1016/j.amepre.2011.05.013 Pate, R. R., O’Neill, J. R., & Lobelo, F. (2008). The evolving definition of “sedentary.” Exercise and Sport Sciences Reviews, 36, 173–178. http:// dx.doi.org/10.1097/JES.0b013e3181877d1a Paw, M. J. M. C. A., Singh, A. S., Brug, J., & van Mechelen, W. (2008). Why did soft drink consumption decrease but screen time not? Mediating mechanisms in a school-based obesity prevention program. The International Journal of Behavioral Nutrition and Physical Activity, 5, 41. Pope, C., Mays, N., & Popay, J. (2007). Synthesizing qualitative and quantitative health research: A guide to methods. Berkshire, UK: Open University Press. ⴱ Protudjer, J. L., McGavock, J. M., Ramsey, C. D., Sevenhuysen, G. P., Kozyrskyj, A. L., & Becker, A. B. (2012). “Asthma isn’t an excuse, it’s just a condition”: Youths’ perceptions of physical activity and screen time. Journal of Asthma, 49, 496 –501. http://dx.doi.org/10.3109/ 02770903.2012.680637 ⴱ Puglisi, L. M., Okely, A. D., Pearson, P., & Vialle, W. (2010). Barriers to increasing physical activity and limiting small screen recreation among obese children. Obesity Research & Clinical Practice, 4, e33– e82. http://dx.doi.org/10.1016/j.orcp.2009.07.004 ⴱ Puglisi, L. M., Okely, A. D., Pearson, P., & Vialle, W. (2013). Understanding the day-to-day lives of obese children and their families. Family & Community Health: The Journal of Health Promotion & Maintenance, 36, 42–50. http://dx.doi.org/10.1097/FCH.0b013e31826d75dc Rey-López, J. P., Vicente-Rodríguez, G., Biosca, M., & Moreno, L. A. (2008). Sedentary behaviour and obesity development in children and adolescents. Nutrition, Metabolism, and Cardiovascular Diseases, 18, 242–251. http://dx.doi.org/10.1016/j.numecd.2007.07.008 Rideout, V. J., Foehr, U. G., & Roberts, D. F. (2010). Generation M2: Media in the lives of 8- to 18-year-olds. Menlo Park, CA: Henry J. Kaiser Family Foundation. Robinson, T. N., Killen, J. D., Kraemer, H. C., Wilson, D. M., Matheson, D. M., Haskell, W. L., . . . Varady, A. (2003). Dance and reducing television viewing to prevent weight gain in African-American girls: The Stanford GEMS pilot study. Ethnicity & Disease, 13(Suppl. 1), S65–S77. Salmon, J., Tremblay, M. S., Marshall, S. J., & Hume, C. (2011). Health risks, correlates, and interventions to reduce sedentary behavior in young people. American Journal of Preventive Medicine, 41, 197–206. http:// dx.doi.org/10.1016/j.amepre.2011.05.001 Sandelowski, M., & Barroso, J. (2007). Handbook for synthesizing qualitative research. New York, NY: Springer. Sandelowski, M., Docherty, S., & Emden, C. (1997). Qualitative metasynthesis: Issues and techniques. Research in Nursing & Health, 20, 365– 371. http://dx.doi.org/10.1002/(SICI)1098-240X(199708)20:4⬍365:: AID-NUR9⬎3.0.CO;2-E ⴱ Sebire, S. J., Jago, R., Gorely, T., Hoyos Cillero, I., & Biddle, S. J. (2011). “If there wasn’t the technology then I would probably be out everyday”: A qualitative study of children’s strategies to reduce their screen viewing. Preventive Medicine: An International Journal Devoted to Practice and Theory, 53, 303–308. http://dx.doi.org/10.1016/j.ypmed.2011.08 .019 Spanier, P. A., Marshall, S. J., & Faulkner, G. E. (2006). Tackling the obesity pandemic: A call for sedentary behaviour research. Canadian Journal of Public Health, 97, 255–257. Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27, 237–246. http://dx.doi.org/10.1177/1098214005283748 Tremblay, M. S., Leblanc, A. G., Janssen, I., Kho, M. E., Hicks, A., Murumets, K., . . . Duggan, M. (2011). Canadian sedentary behaviour


SCREEN TIME FACILITATORS AND BARRIERS guidelines for children and youth. Applied Physiology, Nutrition, and Metabolism, 36, 59 – 64, 65–71. http://dx.doi.org/10.1139/H11-012 Tremblay, M. S., Leblanc, A. G., Kho, M. E., Saunders, T. J., Larouche, R., Colley, R. C., . . . Gorber, S. (2011). Systematic review of sedentary behaviour and health indicators in school-aged children and youth. The International Journal of Behavioral Nutrition and Physical Activity, 8, 98. http://dx.doi.org/10.1186/1479-5868-8-98 Van den Bulck, J., & Van Mierlo, J. (2004). Energy intake associated with television viewing in adolescents, a cross sectional study. Appetite, 43, 181–184. http://dx.doi.org/10.1016/j.appet.2004.04.007 ⴱ Veitch, J., Arundell, L., Hume, C., & Ball, K. (2013). Children’s perceptions of the factors helping them to be ‘resilient’ to sedentary lifestyles. Health Education Research, 28, 692–703. http://dx.doi.org/10.1093/her/ cyt063 ⴱ Veitch, J., Hume, C., Salmon, J., Crawford, D., & Ball, K. (2013). What helps children to be more active and less sedentary? Perceptions of mothers living in disadvantaged neighbourhoods. Child: Care, Health and Development, 39, 94 –102. http://dx.doi.org/10.1111/j.1365-2214 .2011.01321.x Wahi, G., Parkin, P. C., Beyene, J., Uleryk, E. M., & Birken, C. S. (2011). Effectiveness of interventions aimed at reducing screen time in children: A systematic review and meta-analysis of randomized controlled trials. Archives of Pediatrics & Adolescent Medicine, 165, 979 –986. http://dx .doi.org/10.1001/archpediatrics.2011.122

397

Walsh, D., & Downe, S. (2005). Meta-synthesis method for qualitative research: A literature review. Journal of Advanced Nursing, 50, 204 – 211. http://dx.doi.org/10.1111/j.1365-2648.2005.03380.x Walters, L. A., Wilczynski, N. L., & Haynes, R. B., & Hedges Team. (2006). Developing optimal search strategies for retrieving clinically relevant qualitative studies in EMBASE. Qualitative Health Research, 16, 162–168. http://dx.doi.org/10.1177/1049732305284027 Wilczynski, N. L., Marks, S., & Haynes, R. B. (2007). Search strategies for identifying qualitative studies in CINAHL. Qualitative Health Research, 17, 705–710. http://dx.doi.org/10.1177/1049732306294515 Wild, S., Roglic, G., Green, A., Sicree, R., & King, H. (2004). Global prevalence of diabetes: Estimates for the year 2000 and projections for 2030. Diabetes Care, 27, 1047–1053. http://dx.doi.org/10.2337/diacare .27.5.1047 Wong, S. S., Wilczynski, N. L., & Haynes, R. B., & Hedges Team. (2004). Developing optimal search strategies for detecting clinically relevant qualitative studies in MEDLINE. Studies in Health Technology and Informatics, 107, 311–316. Zabinski, M. F., Norman, G. J., Sallis, J. F., Calfas, K. J., & Patrick, K. (2007). Patterns of sedentary behavior among adolescents. Health Psychology, 26, 113–120. http://dx.doi.org/10.1037/0278-6133.26.1.113

Received February 5, 2014 Revision received September 3, 2014 Accepted September 10, 2014 䡲

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