This study is part of a larger research program that was initiated between October 2021 and November 2022, with a needs assessment conducted with 114 families at the Groupe de Médecine de Famille Universitaire Saint-Hubert, a suburban family medicine group [47]. This needs assessment confirmed clinicians’ interest in obtaining more information about children’s lifestyle behaviors, highlighted the prevalence of unhealthy behaviors in this population, and revealed parents’ interest in the development of a preappointment screening tool for lifestyle behaviors. The current manuscript describes the subsequent step of tool refinement through focus groups with parents and clinicians.

A first iteration of our SBIRT tool used three inputs: (1) literature on behavioral science frameworks, including nudges and comparisons that improve real-world decision-making [48,49] and health behavior change [49,50] supported by evidence on physical activity [51,52] and nutrition [53-55] in adults and promising pediatrics data [56]; (2) input from clinicians and family partners [25,35,57-59]; and (3) existing tools such as the RIPPLE (Resource Information Program for Parents on Lifestyle and Education) program, an eHealth SBIRT tool developed by Ball and van Mierlo [25,38,58,60] to prevent pediatric obesity.

More specifically, behavioral sciences were used to inform both the structure and the content of the tool given the promise of this domain to strengthen pediatric nutrition interventions. Insights into cognitive biases and parental motivation—which can be sought through the health behavior screening process by inquiring about motivation to change and beliefs about their children’s behaviors relative to group averages—can enable the development of more targeted and effective strategies that support the long-term adoption of healthy eating behaviors in children [49]. Although primarily focused on dietary habits, these strategies are broadly applicable to health behavior change. In this study, we sought to leverage these behavioral science insights through promising approaches such as personalized risk communication [61], the “fresh start effect” [62,63], implementation intentions [64,65], fostering internalization of healthy behaviors [66,67], and strengthening self-regulation [68-70]. The use of these frameworks seeks to enable enhanced parental engagement and facilitate the integration of behavior change into daily family life, notably by establishing a concrete and specific link between a health behavior and the action required to improve it, which may support the repetition of healthier behaviors and eventual automatization [49].

Following the standard approach in the literature [25,38,60], our tool consists of 3 main sections: screening questionnaire, brief intervention, and referral to resources (Table 1).

The focus group discussions served the primary objective of the study: the development and refinement of our screening and intervention tool using end user feedback [46]. Specifically, the focus groups were intended to (1) gain insights into the needs of clinicians and parents regarding a digital tool aimed at promoting healthy behaviors; (2) explore participants’ past experiences with health technology; (3) integrate insights obtained from the first focus group into the tool development process; and (4) assess the perceived usability, relevance, acceptability, and accuracy of the developed tool. In the first and second focus groups, participants engaged with static mock-ups of the interface, which included the intended questions for each health behavior, and discussed and refined the visual outputs. This led to the fully operational screening and personalized intervention tool evaluated in the third focus group. During this focus group, participants interacted with the working interface, including the full screening questionnaire; immediate personalized feedback reports; comparative normative data displays; color-coded results across physical activity, sleep, nutrition, and screen time domains; and embedded links to actionable resources and follow-up guidance. The interactive tool is available on the operational DISCO platform [71].

Two groups of participants were recruited from the Groupe de Médecine de Famille Universitaire (GMF-U) of Saint-Hubert: (1) primary care clinicians and (2) parents or legal guardians of children who are patients of the GMF-U of Saint-Hubert. Purposive and convenience sampling strategies were used to ensure rich, relevant data while promoting in-depth discussion.

Clinicians were recruited through an internal invitation sent by the management of the family medicine clinic. Parents were recruited via email invitations relayed by clinic staff to those with upcoming appointments for children aged 2 to 12 years. Eligibility criteria included being a parent or legal guardian of a child in that age range and being fluent in French or English.

Three semistructured focus groups (August 2024, November 2024, and March 2025), each lasting 60 to 90 minutes, were conducted. Clinicians participated in person in August and virtually thereafter, whereas parents joined virtually in all sessions (via Microsoft Teams). Due to availability constraints, 8 sessions were held as individual interviews. One clinician and 1 parent participated in all 3 focus groups, whereas others joined a single session.

Discussions explored users’ experience with the digital health tool; perceived usability and relevance of the prototype; satisfaction; and suggestions for content, format, and delivery (Multimedia Appendix 1). Iterative refinement of the tool was based on feedback collected throughout the sessions. For example, after the first session, visual mock-ups were developed based on user expectations; the second session focused on reactions to various features (eg, feedback messages); and the third session examined acceptability and emotional responses to the tool. All data were collected and analyzed in French and translated into English for reporting.

Data collection continued until thematic saturation was reached, defined as the point when themes became repetitive across groups and no new themes emerged during iterative coding. At this stage, participants’ contributions reinforced and stabilized existing themes. In this study, saturation reflects internal coherence rather than statistical representativeness [72]. The same saturation criteria were applied to both parents and clinicians.

All focus group recordings were transcribed verbatim and reviewed for accuracy. An iterative, hybrid analysis—combining inductive and deductive approaches—was conducted. Deductive codes were elaborated using a published framework covering 7 constructs of usability, acceptability, and satisfaction (affective attitude, burden, perceived effectiveness, ethicality, coherence, opportunity costs, and self-efficacy) [73]. Furthermore, initial coding involved open coding aiming to identify emerging meaning units (ideas, experiences, and suggestions), followed by axial coding to identify conceptual relationships and central themes.

Data were analyzed at the group level using thematic analysis to describe and interpret patterns of meaning [74]. The process was managed using Microsoft Excel. To ensure coherence and transparency, the coder conducted systematic internal checks through repeated readings, comparison of the codes across cycles, and iterative refinement of the categories. Emerging themes were also discussed with the research team to strengthen analytic credibility [75]. Following a sequential cocreation approach inspired by the development of the RIPPLE pediatric obesity prevention tool [25,38,58,60], emerging themes from participants’ feedback guided refinements to the tool, including clarifying content, improving ergonomics, and simplifying usability.

This study received ethics approval from the research ethics boards of the Centre intégré de santé et de services sociaux de la Montérégie-Centre and the Sainte-Justine University Hospital Centre (application MP-04-2024-889 – DISCO – Focus Groups).

All participants provided informed consent prior to taking part and consented to the use and publication of their data. Each participant received a compensation of CAD $25 (US $18) per session.

Data were stored securely on the servers of Research Centre of the Sainte-Justine University Hospital Centre.

Six discussions were conducted with a total of 8 participants, including 5 parents of children and 3 clinicians. Sessions were held either as individual interviews or dyadic discussions. All participants were female except for 1 clinician. Clinicians were family physicians with 5 to 6 years of professional experience. Participating parents had 1 to 3 children aged between 3 and 14 years.

Clinicians found the refined version of the tool efficient and user-friendly:

Its brevity was seen as a strength that facilitated dialogue:

Both clinicians and parents viewed it as time-saving and accessible. One parent noted the following:

Clinicians highlighted three key strengths of the tool: (1) time savings (“It will save us time...and it aligns with a motivational interviewing approach since you’ve already started the work”), (2) initiation of the behavior change process (“prompting them to come with an answer, a rationale, or a potential solution at the next appointment. I think that could be beneficial”), and (3) increased parental engagement (“I think it’s good to send this to all parents in any consultation context; I think it can be a good opportunity to just raise their awareness”).

However, the tool’s perceived value varied by family. Parents with prior knowledge or motivation felt that it might be too basic, whereas those with less awareness could find it overwhelming:

Through our focus groups aimed at refining our digital screening and intervention tool to promote healthy lifestyle habits in children, we found that the tool’s key features, such as personalized, immediate, and normative feedback and access to concrete resources, were consistently valued by participants and align with known drivers of engagement and sustained behavior change [81,82]. Overall, parents reported feeling that the tool’s questions were relevant and that the approach to offering support in behavior change and tailoring follow-ups, as well as the resources offered, was helpful and acceptable. Clinicians found the refined version of the tool efficient and user-friendly, and while they expressed concerns about barriers to completing the screening in the clinic, they felt that it was relevant to use a tool of this nature to perform lifestyle behavior screening between appointments and that the data presented were insightful, especially as clinical follow-up becomes less frequent as children grow older.

The elements of the intervention that were guided by behavioral science principles, such as comparisons to peers and norms and personalized feedback, were well accepted by participants. The persuasive potential of behavioral sciences relies on modifying choice architecture (ie, the decision-making context in which individuals act [83]). These interventions aim to guide behaviors toward outcomes considered beneficial while preserving freedom of choice as no options are removed or restricted [84]; therefore, guiding behaviors without unduly influencing or exerting coercive pressure that may limit informed decision-making [85]. In our development of the tool and implementation of strategies from behavioral science frameworks, we carefully considered the balance between behavioral effectiveness and respect for autonomy [86] and, through our focus group discussions, ensured that we elicited any autonomy-related concerns from stakeholders about the intervention; none were raised.

Overall, our study highlights the potential of a codeveloped digital tool for screening and promotion of healthy lifestyle habits in pediatric primary care. The participatory approach enabled iterative refinement based on clinicians’ and parents’ input, ensuring high acceptability, usability, and relevance (Multimedia Appendices 2 and 3).

While the integration of stakeholders supports participatory design, organizational factors such as timing of distribution, follow-up mechanisms, appointment coordination, and communication between families and professionals must be addressed for effective clinical implementation. These align with known implementation challenges in feedback-based interventions, where mode, frequency, and source of feedback influence the impact [87]. Future phases of this research project will leverage the early insights gleaned in this study and seek to address them to elucidate the most effective path forward.

As mentioned by participants, equitable access remains challenging, especially for families facing structural barriers (eg, financial constraints, fragmented services, and logistical difficulties). To address this, the tool was codeveloped with parents and clinicians, and tailored strategies with concrete support were prioritized to reduce contextual barriers and foster engagement [88]. Still, the recruitment process may have introduced selection bias as participating clinicians were likely more engaged in lifestyle-related screening and some parents may have been more motivated or available. The small sample size of this study and the self-selected nature of participants (all from a single clinical site) further limit the generalizability of the tool in development.

This could limit the tool’s applicability to less engaged or more vulnerable populations—the very groups for whom equitable access is most critical. However, the primary objective was to gain insights into key concepts essential for tool development rather than produce exhaustive results. Future phases of this program of research will involve implementing and evaluating the tool in more generalizable settings, including through open-label testing in larger and more diverse populations, and using the screening and brief intervention tool to facilitate access to lifestyle behavior screening, all while collecting data on feasibility and acceptability from a more diverse population, leading to eventual implementation in clinical and other pediatric settings.

Verbatim translation from French into English may have introduced bias; efforts were made to preserve meaning within feasibility constraints [89]. Additionally, the sample size and the mix of focus groups and individual interviews may have influenced interaction dynamics, although the consistency of perspectives across formats strengthens the credibility of the findings [90].

Despite these limitations, this study lays a strong foundation for future work. Subsequent phases will include a feasibility study and broader engagement with stakeholders to assess the tool’s adaptability. This will be followed by a pilot study and a randomized controlled trial to rigorously evaluate the tool’s effectiveness in improving pediatric health outcomes.

To our knowledge, no similar preappointment screening tool exists in general pediatric care. This study provides early evidence on the feasibility and relevance of a codeveloped digital tool to promote healthy lifestyle behaviors in pediatric primary care. Its participatory design and user-valued features support its potential for future evaluation and implementation. This work represents the initial phase of its development. Future phases of the project will evaluate tool completion rates, repeat engagement, uptake across clinic-specific instances, and workflow integration metrics. Secondary outcomes will include changes in parent-reported child lifestyle behaviors across physical activity, sleep, nutrition, and screen time domains. These next-stage outcomes are guided by the broader implementation principle that, while there are an increasing number of validated tools and evidence, dissemination remains a major barrier to real-world reach and impact. In this context, infrastructure determines equity and access, and future phases will specifically assess the scalability of deployment across various settings, including pediatric clinics, family medicine groups, and nonclinical environments such as schools and community centers, particularly to reach children and families who may not otherwise have timely access to traditional care settings [91].