Using Simulation Modeling to Guide the Design of the Girl Scouts Fierce & Fit Program

Abstract

The study aim was to help the Girl Scouts of Central Maryland evaluate, quantify, and potentially modify the Girl Scouts Fierce & Fit program. Methods: From 2018 to 2019, our Public Health Informatics, Computational, and Operations Research team developed a computational simulation model representing the 250 adolescent girls participating in the Fierce & Fit program and how their diets and physical activity affected their BMI and subsequent outcomes, including costs. Results: Changing the Fierce & Fit program from a 6-week program meeting twice a week, with 5 minutes of physical activity each session, to a 12-week program meeting twice a week with 30 minutes of physical activity

A systematic review of economic evaluations of interventions targeting childhood overweight and obesity

“…The volume of published studies tended to increase over 5‐year periods from 2001, with the greatest number of studies published between 2016 and 2020. Only 9 studies of the 151 included studies were conducted in low and middle‐income countries (LMICs) 30–38 compared with 143 studies from high‐income countries 31,39–180 . One study published in 2010 was set in a high‐income country and six LMICs 31 …”

“…Other LMIC settings included Brazil, 31,37 Argentina, 37 El Salvador, 37 Trinidad and Tobago, 37 Peru, 38 India, 31 Russia, 31 and South Africa 31 . The United States was the most represented among the high‐income countries, with 50 studies 51–80,132,141,143,144,147,151,152,155,158–161,164,166,167,171,175,176,178,180 . After the United States, the United Kingdom, 31,41,46,47,81–98,137,142,153,154,156,157,165,169,170,174 and Australia 39,43,44,48–50,99–114,133,136,139,140,145,146,149,150,177 accounted for the majority of the remaining studies from high‐income countries, with 32 and 31 studies, respectively.…”

“…Across the three intervention groups (prevention‐only, 30,39–50 prevention and treatment, 31–38,51–142 and treatment‐only 143–180 ), intervention components were predominantly aimed at changing individual behavior …”

“…159,180 Most of the included studies were undertaken from a societal perspective, which took into account productivity costs such as absence from work and travel time of parents or caregivers, absenteeism from school, workplace absenteeism in adulthood, and early retirement attributable to the development of body weight-related diseases. 30,34,40,42,45,51,52,54,56,69,73,78,[100][101][102]115,116,125,158,163,164 A few studies considered a limited or modified societal perspective where costs accrued by the public and non-governmental sectors were captured, but some downstream consequences of lost productivity were omitted. 60,61,67,75,76,106,107,109,111,112,167 The economic evaluation of e-health interventions ("the use of information and communications technology in support of health and health-related fields" 184 ) and interventions with m-health (a subset of ehealth based on mobile wireless technologies 185 ) components at their core emerged only within the past 5 years.…”

“…Of all the included studies, 18 reported variations of non-anthropometric measures as the primary outcome. 53,[57][58][59]66,72,85,92,113,114,132,133,135,[139][140][141]179,180 In two studies, consequences were measured primarily as a change in the proportion of schools that adhered to a canteen policy, 108 [33][34][35][66][67][68][69][70][71][72][73][74][75][76][77][78][79][84][85][86][87][88][89][90][91][92][93][94][95][96]…”