Supporting health-related parenting: A scoping review of programs assisted by the Internet and related technologies

Exploring the Use of the Behavior Change Technique Taxonomy and the Persuasive System Design Model in Defining Parent-Focused eHealth Interventions: Scoping Review

BACKGROUND

Taxonomies and models are useful tools for defining eHealth content and intervention features, enabling comparison and analysis of research across studies and disciplines. The Behavior Change Technique Taxonomy version 1 (BCTTv1) was developed to decrease ambiguity in defining specific characteristics inherent in health interventions, but it was developed outside the context of digital technology. In contrast, the Persuasive System Design Model (PSDM) was developed to define and evaluate the persuasive content in software solutions but did not have a specific focus on health. Both the BCTTv1 and PSDM have been used to define eHealth interventions in the literature, with some researchers combining or reducing the taxonomies to simplify their application. It is unclear how well the taxonomies accurately define eHealth and whether they should be used alone or in combination.

OBJECTIVE

This scoping review explored how the BCTTv1 and PSDM capture the content and intervention features of parent-focused eHealth as part of a program of studies investigating the use of technology to support parents with therapy home programs for children with special health care needs. It explored the active ingredients and persuasive technology features commonly found in parent-focused eHealth interventions for children with special health care needs and how the descriptions overlap and interact with respect to the BCTTv1 and PSDM taxonomies.

METHODS

A scoping review was used to clarify concepts in the literature related to these taxonomies. Keywords related to parent-focused eHealth were defined and used to systematically search several electronic databases for parent-focused eHealth publications. Publications referencing the same intervention were combined to provide comprehensive intervention details. The data set was coded using codebooks developed from the taxonomies in NVivo (version 12; QSR International) and qualitatively analyzed using matrix queries.

RESULTS

The systematic search found 23 parent-focused eHealth interventions described in 42 articles from various countries; delivered to parents with children aged 1 to 18 years; and covering medical, behavioral, and developmental issues. The predominant active ingredients and intervention features in parent-focused eHealth were concerned with teaching parents behavioral skills, encouraging them to practice and monitor the new skills, and tracking the outcomes of performing the new skills. No category had a complete set of active ingredients or intervention features coded. The two taxonomies conceptually captured different constructs even when their labels appeared to overlap in meaning. In addition, coding by category missed important active ingredients and intervention features.

CONCLUSIONS

The taxonomies were found to code different constructs related to behavior change and persuasive technology, discouraging the merging or reduction of the taxonomies. This scoping review highlighted the benefit of using both taxonomies in their entirety to capture active ingredients and intervention features important for comparing and analyzing eHealth across different studies and disciplines.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-doi.org/10.15619/nzjp/47.1.05.

MICA: Motivational Interviewing Conversational Agent for Parents as Proxies for their Children in Healthy Eating (Preprint)

Background

Increased adoption of off-the-shelf conversational agents (CAs) brings opportunities to integrate therapeutic interventions. Motivational Interviewing (MI) can then be integrated with CAs for cost-effective access to it. MI can be especially beneficial for parents who often have low motivation because of limited time and resources to eat healthy together with their children.

Objective

We developed a Motivational Interviewing Conversational Agent (MICA) to improve healthy eating in parents who serve as a proxy for health behavior change in their children. Proxy relationships involve a person serving as a catalyst for behavior change in another person. Parents, serving as proxies, can bring about behavior change in their children.

Methods

We conducted user test sessions of the MICA prototype to understand the perceived acceptability and usefulness of the MICA prototype by parents. A total of 24 parents of young children participated in 2 user test sessions with MICA, approximately 2 weeks apart. After parents’ interaction with the MICA prototype in each user test session, we used qualitative interviews to understand parents’ perceptions and suggestions for improvements in MICA.

Results

Findings showed participants’ perceived usefulness of MICAs for helping them self-reflect and motivating them to adopt healthier eating habits together with their children. Participants further suggested various ways in which MICA can help them safely manage their children’s eating behaviors and provide customized support for their proxy needs and goals.

Conclusions

We have discussed how the user experience of CAs can be improved to uniquely offer support to parents who serve as proxies in changing the behavior of their children. We have concluded with implications for a larger context of designing MI-based CAs for supporting proxy relationships for health behavior change.

SmartFeeding4Kids, an online self-guided parenting intervention to promote positive feeding practices and healthy diet in young children: study protocol for a randomized controlled trial

Background

Caregivers’ influence on young children’s eating behaviors is widely recognized. Nutritional interventions that focus on the promotion of children’s healthy diet should actively involve parents, focusing on their feeding behaviors and practices.

Methods

This work aims to describe the development and study protocol of the SmartFeeding4Kids (SF4K) program, an online self-guided 7-session intervention for parents of young (2–6 years old) children. The program is informed by social cognitive, self-regulation, and habit formation theoretical models and uses self-regulatory techniques as self-monitoring, goal setting, and feedback to promote behavior change. We propose to examine the intervention efficacy on children’s intake of fruit, vegetables, and added sugars, and parental feeding practices with a two-arm randomized controlled with four times repeated measures design (baseline, immediately, 3 and 6 months after intervention). Parental perceived barriers about food and feeding, food parenting self-efficacy, and motivation to change will be analyzed as secondary outcomes. The study of the predictors of parents’ dropout rates and the trajectories of parents’ and children’s outcomes are also objectives of this work.

Discussion

The SmartFeeding4Kids program relies on technological resources to deliver parents’ self-regulation techniques that proved effective in promoting health behaviors. The study design can enhance the knowledge about the most effective methodologies to change parental feeding practices and children’s food intake. As a self-guided online program, SmartFeeding4Kids might overcome parents’ attrition more effectively, besides being easy to disseminate and cost-effective.

Trial registration

The study was registered in ClinicalTrials.gov (NCT04591496) on October 19, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05897-z.

Use of Technology to Promote Child Behavioral Health in the Context of Pediatric Care: A Scoping Review and Applications to Low- and Middle-Income Countries

Background: The burden of mental, neurological, and substance (MNS) disorders is greater in low- and middle-income countries (LMICs). The rapid growth of digital health (i.e., eHealth) approaches offer new solutions for transforming pediatric mental health services and have the potential to address multiple resource and system barriers. However, little work has been done in applying eHealth to promote young children's mental health in LMICs. It is also not clear how eHealth has been and might be applied to translating existing evidence-based practices/strategies (EBPs) to enable broader access to child mental health interventions and services. Methods: A scoping review was conducted to summarize current eHealth applications and evidence in child mental health. The review focuses on 1) providing an overview of existing eHealth applications, research methods, and effectiveness evidence in child mental health promotion (focused on children of 0-12 years of age) across diverse service contexts; and 2) drawing lessons learned from the existing research about eHealth design strategies and usability data in order to inform future eHealth design in LMICs. Results: Thirty-two (32) articles fitting our inclusion criteria were reviewed. The child mental health eHealth studies were grouped into three areas: i) eHealth interventions targeting families that promote child and family wellbeing; ii) eHealth for improving school mental health services (e.g., promote school staff's knowledge and management skills); and iii) eHealth for improving behavioral health care in the pediatric care system (e.g., promote use of integrated patient-portal and electronic decision support systems). Most eHealth studies have reported positive impacts. Although most pediatric eHealth studies were conducted in high-income countries, many eHealth design strategies can be adapted and modified to fit LMIC contexts. Most user-engagement strategies identified from high-income countries are also relevant for populations in LMICs. Conclusions: This review synthesizes patterns of eHealth use across a spectrum of individual/family and system level of eHealth interventions that can be applied to promote child mental health and strengthen mental health service systems. This review also summarizes critical lessons to guide future eHealth design and delivery models in LMICs. However, more research in testing combinations of eHealth strategies in LMICs is needed.