Development of a theory-based questionnaire to assess structure and control in parent feeding (SCPF)

Abstract Background Parents shape children\u2019s eating environments and act as powerful socialization agents, impacting young children\u2019s behavioral controls of food intake. Most feeding measures assess parents\u2019 use of control to manage children\u2019s intake of energy dense foods. The Structure and Control in Parent Feeding (SCPF) questionnaire was developed to assess more positive aspects of feeding practices with their young children \u2014setting limits, providing routines\u2014that promote self-regulation, as well as controlling feeding practices. Methods A mixed method approach was used to develop the SCPF. In 2013, cognitive interviews informed the modification, deletion and/or replacement of items. In 2014, the survey was distributed statewide to mothers of toddlers aged 12 to 36\ua0months participating in the Women, Infants, and Children program. In 2016, exploratory factor analyses was conducted to test our theoretical parenting model and content validity and criterion validity were assessed ( n \u2009=\u2009334). Results Exploratory factor analysis (EFA) and second-order EFA revealed a 2-factor, 22-item Structure model and a 2-factor, 12-item Control model. Internal consistencies for all factors exceeded 0.70. As predicted, the Structure superfactor was positivity associated with responsiveness, whereas the Control superfactor was positively associated with demandingness on the Caregiver\u2019s Feeding Styles Questionnaire. The Structure subscales were also positively associated with mealtime behaviors and Control subscales were positively associated with control-oriented feeding measures from the Control in Parent Feeding Practices questionnaire. Conclusion The SCPF questionnaire is a reliable tool that can be used to assess aspects of structure- and control-based feeding practices to better understand how parents feed their toddlers

Optimizing a community-engaged multi-level group intervention to reduce substance use: an application of the multiphase optimization strategy

Abstract Background Rates of alcohol and illicit drug use (AIDU) are consistently similar across racial groups (Windsor and Negi, J Addict Dis 28:258–68, 2009; Keyes et al. Soc Sci Med 124:132–41, 2015). Yet AIDU has significantly higher consequences for residents in distressed communities with concentrations of African Americans (DCAA - i.e., localities with high rates of poverty and crime) who also have considerably less access to effective treatment of substance use disorders (SUD). This project is optimizing Community Wise, an innovative multi-level behavioral-health intervention created in partnership with service providers and residents of distressed communities with histories of SUD and incarceration, to reduce health inequalities related to AIDU. Methods Grounded in critical consciousness theory, community-based participatory research principles (CBPR), and the multiphase optimization strategy (MOST), this study employs a 2 × 2 × 2 × 2 factorial design to engineer the most efficient, effective, and scalable version of Community Wise that can be delivered for US$250 per person or less. This study is fully powered to detect change in AIDU in a sample of 528 men with a histories of SUD and incarceration, residing in Newark, NJ in the United States. A community collaborative board oversees recruitment using a variety of strategies including indigenous field worker sampling, facility-based sampling, community advertisement through fliers, and street outreach. Participants are randomly assigned to one of 16 conditions that include a combination of the following candidate intervention components: peer or licensed facilitator, group dialogue, personal goal development, and community organizing. All participants receive a core critical-thinking component. Data are collected at baseline plus five post-baseline monthly follow ups. Once the optimized Community Wise intervention is identified, it will be evaluated against an existing standard of care in a future randomized clinical trial. Discussion This paper describes the protocol of the first ever study using CBPR and MOST to optimize a substance use intervention targeting a marginalized population. Data from this study will culminate in an optimized Community Wise manual; enhanced methodological strategies to develop multi-component scalable interventions using MOST and CBPR; and a better understanding of the application of critical consciousness theory to the field of health inequalities related to AIDU. Trial registration ClinicalTrials.gov, NCT02951455 . Registered on 1 November 2016.https://deepblue.lib.umich.edu/bitstream/2027.42/143194/1/13063_2018_Article_2624.pd

Application of the multiphase optimization strategy to a pilot study: an empirical example targeting obesity among children of low-income mothers

Abstract Background Emerging approaches to building more efficient and effective behavioral interventions are becoming more widely available. The current paper provides an empirical example of the use of the engineering-inspired multiphase optimization strategy (MOST) to build a remotely delivered responsive parenting intervention to prevent obesity among children of low-income mothers with and without depressive symptoms. Methods Participants were 107 mothers with (n = 45) and without (n = 62) depressive symptoms who had a child aged 12 to 42 months participating in the Women, Infants and Children program. Participants were randomized to one of sixteen experimental conditions using a factorial design that included a combination of the following eight remotely delivered intervention components: responsive feeding curriculum (given to all participants), parenting curriculum, portion size guidance, obesogenic risk assessment, personalized feedback on mealtime routines, feeding curriculum counseling, goal setting, mobile messaging, and social support. This design enabled efficient identification of components with low feasibility and acceptability. Results Completion rates were high (85%) and did not statistically differ by depressive symptoms. However, mothers with depressive symptoms who received obesogenic risk assessment and personalized feedback on mealtime routines components had lower completion rates than mothers without depressive symptoms. All intervention components were feasible to implement except the social support component. Regardless of experimental condition, most participants reported that the program increased their awareness of what, when, and how to feed their children. Conclusions MOST provided an efficient way to assess the feasibility of components prior to testing them with a fully powered experiment. This framework helped identify potentially challenging combinations of remotely delivered intervention components. Consideration of how these results can inform future studies focused on the optimization phase of MOST is discussed

Increasing the public health impact of evidence-based interventions in behavioral medicine: new approaches and future directions

The dissemination and implementation of evidence-based behavioral medicine interventions into real world practice has been limited. The purpose of this paper is to discuss specific limitations of current behavioral medicine research within the context of the RE-AIM framework, and potential opportunities to increase public health impact by applying novel intervention designs and data collection approaches. The MOST framework has recently emerged as an alternative approach to development and evaluation that aims to optimize multicomponent behavioral and bio-behavioral interventions. SMART designs, imbedded within the MOST framework, are an approach to optimize adaptive interventions. In addition to innovative design strategies, novel data collection approaches that have the potential to improve the public-health dissemination include mHealth approaches and considering environment as a potential data source. Finally, becoming involved in advocacy via policy related work may help to improve the impact of evidence-based behavioral interventions. Innovative methods, if increasingly implemented, may have the ability to increase the public health impact of evidence-based behavioral interventions to prevent disease