Applying the COM-B model to understand wearable activity tracker use in children and adolescents

Abstract

Aim Wearable activity trackers (wearables) are increasingly popular intervention tools for increasing child and adolescent physical activity (PA) levels. However, the large-scale habitual use of wearables in children and adolescents is unknown. This study investigated the prevalence of wearable use in children and adolescents, and what factors impact their use. Subjects and methods This study utilised a cross-sectional survey and the ‘Capability, Opportunity, Motivation and Behaviour’ (COM-B) model was applied to explore what child/adolescent and parental characteristics impact wearable use. Parents/guardians of 5- to 17-year-olds were invited to complete the survey. The survey was open internationally, and consisted of between 19 and 23 questions, depending on child/adolescent wearable use. Multinomial logistic regression analyses were conducted to explore variables impacting wearable use, in children (5 to 9 years) and adolescents (10 to 17 years). Results The survey was completed by 652 parents, representing 831 children/adolescents. Most children/adolescents had never used a wearable (n = 429; 51.6%), and 252 (30.3%) and 150 (18.1%) currently or had previously used a wearable, respectively. Child age and sex, capability, opportunity and motivation for PA were associated with wearable use, and differences were present between child (5 to 9 years) and adolescent (10 to 17 years) wearable use. Conclusions This study offers a novel contribution to the understanding of child and adolescent habitual wearable use, and what impacts wearable use in these age groups.

Promoting child and adolescent health through wearable technology: A systematic review

“…Lastly, three studies investigated the popularity of wearables and its correlation with health promotion. 20 – 22 Appendix C presents the main results of each study.…”

“…Of the reviewed studies, 10 used theories or models as intervention frameworks to guide the research. These included the Technology Acceptance Model, 24 Theory of Unpleasant Symptoms, 44 Motor Learning Theory, 48 Behavioral Choice Theory, 25 Self-Determination Theory, 27 , 47 , 49 Social Cognitive Theory, 25 , 27 , 49 Social Ecological Model, 50 “Capability, Opportunity, Motivation, and Behavior” (COM-B) model, 20 the Theoretical Domain Framework (TDF), 20 and Health Belief Model. 50 …”

“…In the 53 studies, three studies on the ownership rate of wearable devices did not specify the specific devices used. 20 – 22 Out of the remaining 50 studies, 35 focused on a single wearable technology, while 15 explored the use of two or more wearables. For further analysis, wearables were classified into two categories based on data accuracy: consumer-grade and research-grade.…”

“…Of the studies reviewed, three studies investigated the ownership and use of wearable devices. 20 – 22 In one study, a national survey was conducted with 831 children and adolescents and revealed that most (51.6%) had never used wearable technology, while 252 (30.3%) were current users, and 150 (18.1%) had used wearables in the past. 19 , 20 Another study, conducted with 755 teenagers from the Czech Republic, highlighted a significant adoption of physical activity trackers (PATs).…”

“… 20 – 22 In one study, a national survey was conducted with 831 children and adolescents and revealed that most (51.6%) had never used wearable technology, while 252 (30.3%) were current users, and 150 (18.1%) had used wearables in the past. 19 , 20 Another study, conducted with 755 teenagers from the Czech Republic, highlighted a significant adoption of physical activity trackers (PATs). 22 This finding supports the results of a survey conducted in Finland, which included 8108 teenagers and demonstrated a substantial ownership and usage of PATs.…”