Support and concerns: Dutch health care professionals’ views on the use of a childhood obesity prediction toolbox

Abstract

Background

Childhood obesity is a major and increasing public health concern. Early prediction of the risk of childhood obesity may lead to targeted preventative interventions. To develop a prediction-toolbox that is suitable for clinical implementation, it is imperative to align it with the perceptions of health care professionals (HCPs), but this aspect remains relatively underexplored. This study aimed to explore the perceptions of Dutch HCPs regarding the concept of a childhood obesity prediction toolbox.

Methods

A qualitative study design comprising semi-structured interviews (n=15) with Dutch HCPs was used. HCPs included youth health care practitioners, youth health care nurses and policy advisors employed at the municipal health service of Amsterdam. Perceptions were explored regarding the concept of a three-element childhood obesity prediction toolbox of the EndObesity project, which consists of a prediction tool, prevention strategies to support families of high-risk infants, and communication tips for HCPs. The data were analysed through reflexive thematic analysis.

Results

HCPs were positive about early identification of the risk of future childhood obesity and the support of high-risk infants. They acknowledged the potential benefits of personalized care facilitated by such risk prediction, but concerns were raised regarding its validity and its added value compared with the clinical judgement of HCPs. HCPs also expressed some negative connotations regarding risk communication e.g. making parents feel insecure or judged, especially in vulnerable situations. Finally, HCPs acknowledged the complexity of childhood obesity prevention and emphasized the need for a complementary broader approach at both the municipal and national policy levels.

Conclusions

Dutch HCPs generally supported the potential use of a childhood obesity prediction toolbox, but they also expressed concerns regarding the validity, the added value of the toolbox and about risk communication. These concerns must be addressed in further development of the toolbox.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-026-06572-5.

Background

Childhood obesity is a major and increasing public health concern. In the Netherlands, 12.7% of children aged 4–17 years were overweight in 2023, including 4.1% who were classified as obese [1]. Childhood obesity can have adverse effects on both the physical health and psychosocial well-being of children [2, 3]. For instance it is associated with an increased risk of comorbidities in adulthood, including hypertension, type 2 diabetes, dyslipidemia and heart disease [4]. Addressing childhood obesity is, therefore, an urgent priority. The first 1000 days of life, the period from conception to a child’s second birthday, is a critical period for the development of childhood obesity and, thus, represents a unique window of opportunity for childhood obesity prevention [5].

Prediction of childhood obesity risk during the first 1000 days of life may help health care professionals (HCPs) to start early preventative interventions [6–8]. Various statistical models are available that predict the risk of developing childhood obesity in an individual on the basis of risk factors in the first 1000 days of life, such as maternal body mass index (BMI), maternal smoking, and child’s sleep, length and weight [6]. These prediction models can be translated into digital tools for use in clinical practice. These prediction tools help identify infants at risk of developing childhood obesity and provide their families with targeted preventive care such as lifestyle advice and pedagogical support.

An essential component in the development of a prediction tool for use in clinical practice is alignment with the perceptions of HCPs, who are the primary intended users of such a tool. Innovations in which the user’s perspectives are incorporated in the development stage are more likely to be widely and successfully adopted [9]. The translation of a prediction model into a tool for daily practice is quite complex and involves considering various aspects, such as real-world validation, clinical utility, feasibility, acceptability, safety and dissemination [10]. HCPs are involved in many of these aspects, which are influenced by factors such as ethical issues [11, 12], communication with the family [13, 14], the increasing integration of digital tools in health care [15] and incorporating the tool into the daily routines and tasks of HCPs.

Despite the availability of a wide range of prediction models for childhood obesity, we know of only three models that have been developed into tools for use in clinical practice: the smartphone application called ‘Healthy Infant Weight’ [16], the tablet application called ‘ProAsk’ [17], and the web tool ‘SLOPE CORE’ [18]. However, to the best of our knowledge, none of these tools have been implemented in routine practice. The researchers of the ‘Healthy Infant Weight’ application planned to conduct qualitative work to understand how the tool would be received by HCPs, but unfortunately, the application was discontinued due to a lack of funding (Santorelli, 2017 in [19]). In the case of ‘ProAsk’, a feasibility study produced disappointing results: issues were encountered with study recruitment and protocol adherence, and intervention compliance was low. Additionally, health visitors, who are nurses or midwives with additional training in public health nursing, expressed concerns about assessing and communicating overweight risk to parents of young infants. Regarding ‘SLOPE CORE’, a recent study on its feasibility, acceptability and usability indicated its potential for use in clinical practice. However, further research is required before broader implementation. These studies highlight the importance of providing appropriate support for families and guidance for HCPs on communicating risk prediction and overweight. Only a few studies worldwide, two in England [18, 20] and one in Australia [21], have examined the views of HCPs regarding the use of a childhood obesity prediction tool. Thus, studying the perceptions of HCPs regarding a prediction tool represents a valuable contribution to the literature as this area has been relatively underexplored.

The European EndObesity project aims to develop a childhood obesity prediction toolbox for HCPs to be used in clinical practice, consisting of (1) a prediction tool based on a prediction model currently in development within the EndObesity consortium, (2) prevention strategies to support families of infants at high risk of developing childhood obesity and (3) communication tips for HCPs to support conversations on risk communication, overweight and obesity with parents. The aim of this study was to explore the perceptions of Dutch HCPs regarding this concept toolbox. Insights from this study may aid in the successful development and successful implementation of this toolbox in daily practice to prevent childhood obesity in early life.

Methods

Design and context

This qualitative study is part of the European research project ‘EndObesity’, which aims to develop, implement and evaluate innovative, multidisciplinary strategies for the prevention of childhood obesity by targeting family-based lifestyle factors in the first 1000 days of life. This study is embedded in the Sarphati Amsterdam research institute, in which the municipal health service (in Dutch: GGD) of Amsterdam and academic institutions in Amsterdam, the Netherlands, collaborate in innovative and multidisciplinary research [22]. In the Netherlands, youth health care (YHC) practitioners and YHC nurses are employed at municipal health services and offer preventive care and early intervention support for all children aged 0–19 years, whereas paediatricians are medical specialists and provide only secondary or tertiary care. YHC practitioners and YHC nurses do not provide maternity care during pregnancy, that care is provided independently by midwives in a separate healthcare system. Midwives do not have the capacity to refer to preventative interventions; they primarily focus on medical monitoring during pregnancy and assist with delivery. YHC policy advisors develop, implement, and evaluate health policies at the local and national level aimed at promoting the well-being, development, and preventive care of children aged 0–19 years. For example, they facilitate the integration of new approaches to childhood obesity prevention and oversee the allocation of additional healthcare funding.

In this study, we explored HCPs’ (YHC practitioners, YHC nurses and YHC policy advisors) perceptions on a concept of a childhood obesity prediction toolbox by conducting semi-structured individual interviews. In this study, we followed the social constructivism paradigm, in which research relies on the participants’ subjective views, which are varied and multiple and formed through interaction with others. Social constructivism also focuses on the specific contexts in which people live and work to understand the historical and cultural setting of participants [23].

Childhood obesity prediction toolbox

The aim of the childhood obesity prediction toolbox is to support HCPs in the early signalling and support of infants at high risk of developing childhood obesity. The toolbox is currently a concept under development and is not yet being used in routine practice. The toolbox consists of three elements of which the combination was considered essential, including a prediction tool, prevention strategies and communication tips (Table 1). The prediction tool aims to help HCPs identify infants at high risk of developing childhood obesity. Subsequently, HCPs can use the prevention strategies to provide the families of these infants with relevant support. The communication tips guide HCPs in discussing risk predictions with parents and facilitate conversations about lifestyle changes and overweight. Development of this toolbox is part of the EndObesity project.

Table 1.

Definitions, examples, and the scientific foundation behind the development of the various elements of the childhood obesity prediction toolbox within the Endobesity project

	Prediction tool	Prevention strategies	Communication tips
Definition	Digital tool predicting childhood obesity risk in mid and late-childhood in 0-2-year-old children. In this way, infants with a high risk of developing childhood obesity can be identified.	Information, advice and referral around lifestyle, pedagogical support, and help from the social domain. Provided by the HCP directly to the family from the consultation room. Is partially included in usual care and local support.	Practical communication tip sheet for HCPs on how to discuss the results from the prediction tool, and how to talk about lifestyle change and overweight
Example	The HCP identifies a list of risk factors for the child, and if these factors exceed a certain threshold, the tool provides s a high-risk score.	The HCP might refer the family of an infant with a high risk of childhood obesity to play activities or provides information about screen time.	The tip sheet offers guiding on how to: - explain the purpose of the prediction tool - communicate the risk in a clear and transparent manner - communicate the prevention strategies
Research foundation behind development of the different elements of the toolbox	- Clinical translation of the childhood obesity prediction model of the EndObesity consortium (in development) - Interviews with HCPs (this study)	- Systematic review on key features for childhood obesity prevention in early childhood through optimizing lifestyle (submitted) - Interviews with HCPs (this study) - YHC guideline on prevention of overweight [24]	- Literature on communication from HCP to parents about prevention and prediction of overweight, and health risk communication - Interviews with HCPs (this study) - Focus group with HCPs to discuss draft tip sheet

HCP Health care professional, YHC Youth health care

Participants and recruitment

HCPs employed at the municipal health service of Amsterdam were recruited to take part in the study. To be included, YHC practitioners and YHC nurses had to have experience in YHC with 0-4-year-old children, and policy advisors had to work within YHC. We aimed to recruit HCPs working in city districts that have populations with diverse socioeconomic positions (SEPs) and diverse cultural backgrounds, because overweight and obesity are more prevalent among groups with lower SEPs and specific cultural backgrounds [25].

First, a purposive sampling method was used to recruit participants. A project leader of Sarphati Amsterdam, also a YHC practitioner, compiled a list of possible participants in her network and sent them recruitment e-mails. These potential participants were mainly people active in the topic of the first 1000 days of life. We subsequently used snowball sampling by asking the recruited participants whether they knew other potential participants. No rewards or incentives were offered to the participants. However, the municipal health service of Amsterdam was financially compensated for the participation of their employees in this study. In total, 38 HCPs were approached for an interview by e-mail and 16 agreed to participate. One person cancelled due to illness resulting in 15 participants for the interviews, which we pragmatically considered sufficient for exploration [26].

Data collection

The interviews were conducted between April and May 2023 either online via Microsoft Teams or face-to-face at a location (mostly their consultation room) chosen by the HCP, depending on their preference. On average, the interviews lasted 60 min. The interviews were conducted by AM and / or NM. A semi-structured interview guide, presented in Additional file 1, was developed for the interviews based on the Measurement Instrument for Determinants of Innovations of Fleuren et al. [27]. The interview consisted of two sections. First, the participant was asked about the current policy of the YHC regarding overweight and obesity prevention in infants. Subsequently, the aim and ideas of the different elements of the concept childhood obesity prediction toolbox were explained to the participant by showing a visual figure based on Table 1, followed by questions regarding their perception of the potential use of toolbox. Personal characteristics that did not come up in the interview were asked about at the end of the interview. AM and NM wrote field notes both during and after the interviews. All the interviews were audio recorded and transcribed verbatim by NM.

Data analysis

To analyse the data, we performed a reflexive thematic analysis by Braun & Clarke [28]. Reflexive thematic analysis emphasizes the researcher’s active role and subjectivity in the analysis. The codes and themes generated reflect the researcher’s interpretations. We performed the following six steps of reflexive thematic analysis within an inductive, interpretative approach [28, 29]: (1) familiarizing with the data, (2) generating initial codes, (3) grouping codes into potential overarching themes, (4) reviewing themes, (5) specifying and describing themes and (6) producing the report. Two researchers, NM and AM, performed the first two steps independently. For this article, in step 3 we specifically filtered the data for this research question to focus on participants’ perceptions regarding the concept of the toolbox, due to the broad variation in data which also included other aspects such as preconditions of the prediction tool and implementation factors. This filtering was accomplished by including only the initial coding groups related to perceptions, while excluding coding groups addressing other aspects. Excluded groups were reviewed for any relevant codes to include. Steps 3 to 6 were performed in consultation with the entire research team. Atlas.ti 23 for Windows was used to analyse the data, and MindManager 2019 for Windows was used to construct a thematic map. After the data was complete, the authors translated all the themes and quotes into English. ChatGPT was used to improve the English and sentence structure of the article. No participant information or quotes were entered into ChatGPT.

Research team description

AM, a junior researcher with a background in nutrition and health and additional training in qualitative research, set up the research protocol and conducted the interviews together with NM, a Health Sciences master’s student. The research team also consisted of JS, a professor in nutrition and health; CD, a senior nutritionist and epidemiologist; and BG, a communication scientist and expert in qualitative research. The diverse team with research expertise in the first 1000 days of life and qualitative methods enhanced the data collection and analysis. There were no relationships between the researchers and participants before the research.

Ethical and quality considerations

All participants received an information letter about the study and provided written informed consent for participating in the study. The interviews were transcribed verbatim and were anonymized by removing identifying characteristics from the data. Audio recordings were deleted after transcription. This study was approved by the research ethics review committee of the faculty of science of the Vrije Universiteit Amsterdam (review number 22–49). The Journal Article Reporting Standards for Qualitative Research (JARS-Qual) [30], shown in Additional file 2, were considered in reporting the study.

Results

In total, 15 HCPs working in four of the eight different city districts of the municipality of Amsterdam were interviewed. Among the participants, there were seven YHC nurses, six YHC practitioners, one policy advisor and one individual who served as both a YHC practitioner and policy advisor. All participants were female. The years of experience of the participants ranged from less than 2 years to more than 30 years, and approximately half of the participants had an additional function (Table 2).

Table 2.

Participant characteristics (n=15)

Characteristics	Participants n
Profession
YHC nurse	7
YHC practitioner	6
Policy advisor	1
Dual function: YHC practitioner + policy advisor	1
Age
18-34	4
35-44	6
45-64	5
Sex
Female	15
Male	0
Years of practising as clinician
<5	4
5-10	3
10-20	6
>20	2
Additional function (multiple additional functions were also possible)
Attention coordinator ‘first 1000 days of life’	3
Attention coordinator ‘overweight’	1
Parent participation advisor	2
Team leader	1
Researcher	2
Coordinating professional	1

YHC Youth health care

Four main themes were generated from the data that captured the perceptions of the HCPs regarding the childhood obesity prediction toolbox and include the following: (1) The toolbox provides HCPs guidance in identifying and supporting high-risk infants; (2) The benefits and concerns of risk prediction in health care; (3) Negative connotations associated with risk communication; and (4) The toolbox is no simple fix for a complex problem.

The toolbox provides HCPs guidance in identifying and supporting high-risk infants

Almost all HCPs were positive about the concept of early detection of risk factors to identify and support infants at high risk of developing childhood obesity. They expressed that it would help them identify children who require extra attention. Moreover, some HCPs mentioned that it contributes to HCPs’ awareness of risk factors associated with childhood obesity.

“Well, the prediction tool does seem interesting to me, because if you can predict who will become it [obese] or who you do have to pay extra attention to for example. (…) Then you can kind of start with lifestyle from early on you do have the pedagogical tips and things like that you just named, that does seem useful to me, because the earlier you start with the problem, the faster and the better you can solve it though.” – R10, YHC practitioner

Some HCPs expected that parents would appreciate the early detection of childhood obesity risk as they want the best for their child, although most HCPs emphasized that some parents could react differently.

“Well, the group that wants to do something with this or already thinks, ‘I may have to pay attention to this’, or ‘it’s nice that they’re thing along’, they might experience it less unpleasant. But the group that, for whatever reason, has already had to deal with a lot of ‘I have to change’, or ‘my weight is not okay’, and experienced that as very negative, well I think for them it will be difficult to also start talking about the weight of their young child” – R5, YHC practitioner + policy advisor

The HCPs expressed that it would be helpful to have more guidance or tools for childhood obesity prevention for the first two years of life. They explained that they use BMI curves for monitoring weight development from the age of 2 onwards, whereas tools or guidance before the age of 2 are limited and exists of offering families general lifestyle advice and parental skill support. Often, HCPs rely primarily on their personal experiences accumulated over the years to guide their actions. Therefore, the toolbox provides a means to standardize their practices and health care policies aimed at preventing childhood obesity in children aged 0–2 years.

“I think it’s very nice to have a prediction tool for that period [0–2 years of age] that can at least give you some kind of prediction of which way it’s going, right? Then maybe we can intervene earlier than at 2 years of 2.5 years. I think (…) that’s still a gap now and it’s nice that that [the toolbox] is coming there now to bridge that, yes.” - R3, YHC nurse + coordinating professional + researcher + parent participation advisor

HCPs also appreciated the practical nature of the toolbox, particularly emphasizing the importance of the included communication tips. The HCPs expressed a need for guidance in discussing childhood obesity and risk prediction with parents, recognizing the sensitivity of the topic and the potential challenges it brings for HCPs.

“Certainly also those communication tips I think are very good that you include that, because it is indeed quite a sensitive topic.” – R12, YHC nurse

The benefits and concerns of risk prediction in health care

The data-driven nature of the prediction tool poses both benefits and concerns for HCPs. A first benefit lies in the facilitation of more personalized care. The HCPs valued the fact that the prediction tool is based on personal factors, which enables them to focus care on children who need it. In addition, the HCPs indicated that the toolbox concept aligns with the current vision of the Dutch YHC, emphasizing a shift towards prevention and personalized care.

“But if there’s a tool that combines all those factors, then yes, I think it’s going to help and at least it will maybe help to see someone more often in terms of tailored care or to give more advice.”- R11, YHC practitioner + researcher

Some HCPs expressed doubts regarding the added value of the toolbox in comparison with the clinical judgement of the professional. Some HCPs indicated that they are already acquainted with the predictive factors that are included in the toolbox, often relying on their gut intuition and experiences to determine which children require attention.

“Well, I wonder with such a prediction tool, those are statistical models with factors from the first 1000 days, to what extent do you get a result from that’s different from what the YHC nurse might have in gut or background feeling about the family anyway.”- R8, policy advisor

In addition, they emphasized that the toolbox must serve as complementary to existing practice. The primary focus in this approach should remain on the family and the expertise and experience of the professional.

“I believe you should always try to support professionals wherever possible with systems and tools, but the professional still has to be in tune with the families and assess and evaluate. What is needed here in this family? Because otherwise, then you do something that simply doesn’t work and those families keep coming back every time and then not much change.” – R3, YHC nurse + coordinating professional + researcher + parent participation advisor

Furthermore, some HCPs expressed doubts regarding the validity of the prediction tool. For example, they questioned whether the presented risk factors are the right factors to predict childhood obesity or argued that a prediction cannot be captured in numbers.

“I understand that as researchers you want numbers, but a lot of the work we do is also kind of intuitive. You see something, you hear something, and that’s when you start to pay attention and think, oh, wait a minute, I need to be careful here because there’s just a bit too much feeding going on.” - R7, YHC nurse + attention coordinator ‘first 1000 days of life’

Negative connotations associated with risk communication

HCPs highlighted several negative connotations that they associated with the communication of childhood obesity risk prediction with families. They emphasized that both obesity and risk prediction are sensitive topics to discuss, and that the bond of trust between parents and HCPs plays a crucial role in this context. The associated connotations included making parents insecure about parenthood and accusing and profiling families.

“How do you address this in communication without it coming across as an attack or as categorizing, or culturally discriminatory? Everything is on a scale these days. Everyone feels attacked very quickly. Unsolicited advice is simply not wanted, and making predictions can lead to dismay, disgust, frustration, and actually destroy the trust relationship you want to have with parents.” – R4, YHC nurse + attention coordinator ‘first 1000 days of life’

We found that HCPs had some preconceptions about the reactions of parents as they indicated that some parents may feel accused and discriminated against through communication around the use of the toolbox, especially those of families living in precarious situations. Some HCPs mentioned that the conversation around the risk of future obesity could accentuate vulnerable topics that parents struggle with or are insecure about, such as poverty, level of education, cultural habits or their own weight. This accentuation is undesirable, as it does not benefit the receptiveness of parents to receiving support from HCPs.

“I can also imagine that parents might find it a bit discriminatory because there are always variables such as origin, income, low socioeconomic status, education, which is how you define the vulnerable group. So, a tool like that would also use those same variables, so then again it’s a target that profiles them on the things they’re not good at.”– R3, YHC nurse + coordinating professional + researcher + parent participation advisor

The toolbox is no simple fix for a complex problem

HCPs acknowledged the complex nature of childhood obesity prevention in practice and express that the toolbox nor the YHC organization cannot solve the problem alone. To illustrate this complexity, the HCPs emphasized that many families with overweight face multiple problems, such as poverty, social problems and household issues, which often lead to high-stress levels among families that hinder the adoption of a healthy lifestyle.

“And what if you’re stressed, experiencing poverty and you don’t know how to make ends meet? Then these advices simply don’t register, it’s about survival, and you have to first ensure that the stress levels recede into the background.” – R6, YHC nurse + team leader

Additionally, HCPs noted the role of health literacy and parenting skills in the development of childhood obesity. HCPs mentioned that parents frequently pass on their own (unhealthy) lifestyle habits to their children and often exhibit unfavourable parenting behaviour, such as not correctly recognizing and acting on signals from children and setting no clear boundaries.

“That child just goes along with all the unhealthy things the parents do. It’s also very difficult to break that cycle.” – R2, YHC nurse + attention coordinator ‘overweight’

Moreover, they point out that childhood obesity is not solely a family-centred problem; its complexity is shaped by environmental factors such as political influences, food advertising, the food retail industry, manufacturing practices, the food supply in the neighbourhood and the food supply and food policy at schools. Finally, certain HCPs feel that the perception of the YHC organization as patronizing by parents, as it is a governmental institute, contributes to the inability to address this entire problem by the YHC alone.

“I think, yes, one of the challenges we face is the national policy, just the marketing of baby products in supermarkets, unhealthy baby products, things like that. If all of that were better, then we would have much less work to do in terms of explaining things to parents.” – R11, YHC practitioner + researcher

Owing to the limited impact that the YHC organization alone can make in this intricate context, some professionals reported feelings of demotivation and helplessness. Many HCPs emphasized that effectively addressing the complex problem of childhood obesity requires a broader approach at both the municipal and national policy levels.

“I’ve been working here for quite a while now, and in the beginning I was really motivated and I wanted to help a lot of people change. But actually I see so little results from what I do, and even if you try your best and try to motivate people and reach out to other health care professionals, there are just so many families dealing with overweight and obesity, and there are so many factors at play that I feel… and it’s not just me, but I’ve also discussed it with colleagues… that there trully need to be other things in place for this approach to succeed, and we can’t do it alone just from the consultation room.” – R2, YHC nurse + attention coordinator ‘overweight’

Discussion

In this study, we explored the perceptions of Dutch HCPs regarding a concept childhood obesity prediction toolbox consisting of a prediction tool, prevention strategies and communication tips. HCPs supported the concept of early identification of childhood obesity and support of high-risk infants, recognizing the need for early detection tools. They valued personalized care facilitated by risk prediction but questioned its validity and added value of risk prediction over clinical judgement. Additionally, HCPs expressed concerns that communicating childhood obesity risk prediction may make parents feel insecure or accused, especially in vulnerable situations. Finally, HCPs emphasized the complexity of childhood obesity prevention, advocating for a broader approach beyond individual interventions by health care organizations.

Our study found a positive attitude among HCPs regarding the concept of early prediction in childhood obesity. This aligns with findings from Canfell et al. [21], who explored HCPs’ perceptions concerning the prediction of childhood obesity in infants in Australia, and Grove et al. [18], who explored HCPs’ experiences with a childhood obesity prediction tool in the UK. This positive attitude can be interpreted as an indication of acceptability, defined as ‘the extent to which people delivering or receiving a healthcare intervention consider it to be appropriate, on the basis of anticipated or experienced cognitive and emotional responses to the intervention’ [31]. Therefore, this suggests a promising foundation for future acceptability of the toolbox; however, it is important to note that the critical notes of HCPs identified in this study also influence acceptability and need to be addressed in further development.

In addition to the expressed benefits, the HCPs in this study simultaneously raised concerns regarding health risk prediction, including the validity and added value of such a prediction tool compared with their clinical judgement. This duality of opinion can also be found in research on health risk prediction in other areas. While benefits such as identifying high-risk patients, explaining potential risk to patients and improving lifestyle behaviour are reported [32–34], there are also concerns. These concerns include for example mistrust in the risk outcome of the prediction tool, the potential to mislead less experienced clinicians and the preference to rely on clinical intuition rather than risk-score based [20, 32–34]. Further research into how this intuition relates to guidelines and to what extent this intuition should be leading, would be valuable. Addressing concerns regarding the concept of prediction requires ensuring that HCPs comprehend the underlying prediction model. This includes understanding the risk factors used to develop the prediction model and how to interpret the results of the model, with sufficient time and attention [35]. Additionally, the added value of risk prediction should be assessed in a pilot study before implementation, to build trust among HCPs.

Effective communication between HCPs and parents is of utmost importance in childhood obesity prevention because of the large role parents play in their child’s future health [36, 37]. Our study underscored the sensitivity of communicating with parents about overweight, obesity, and health risk prediction, making communication around these topics challenging for HCPs. The perceived patronizing image of the YHC organization exacerbates these communication challenges. The inclusion of communication tips in the toolbox was therefore considered highly valuable. The sensitivity and stigma around discussing overweight and obesity with parents are well known in the literature [14, 38]. Other qualitative studies have also shown the importance of the bond of trust between HCPs and parents in discussing these topics, which was highlighted by HCPs in our study [39, 40]. Concerning our results towards the sensitivity around health risk prediction, we found that HCPs had some preconceptions about the reactions of parents. Similar results were reported in other qualitative studies [18, 20, 21] with HCPs expressing concerns that talking about a high risk of obesity could elicit negative reactions from parents, such as feelings of judgement, guilt or shame. These issues also align with a review describing ethical issues around obesity risk prediction such as stigmatization, parental guilt and labelling of young children [11]. Interestingly, studies examining parental attitudes toward receiving obesity risk scores for their child indicate that despite anticipating negative feelings, most parents do have the desire to hear if their infant is at risk, viewing it as a call to action [18, 20, 21, 41, 42]. These findings highlight the need for nonjudgemental, culturally sensitive, and tailored communication when conveying risk information to parents, as addressed by the communication tips. They also highlighted the importance of providing support or training for HCPs in effective communication around the prediction tool.

A strength of this study is its novelty in the Dutch context and the first examination of perceptions regarding a three-element childhood obesity prediction toolbox. Another strength is the diverse sample of participants, including individuals from various city districts with varying years of experience. A limitation of this study is that we were only able to recruit two policy advisors due to their high workloads, which may have led to limited input regarding the integration and implementation of the toolbox. Additionally, we used a purposive sampling method due to the high number of HCPs working in Amsterdam and the need for a personal approach given their high workload. This method may have resulted in a selection bias, favouring participants who are particularly enthusiastic about the topic of the first 1000 days and, consequently interventions related to this topic. Another limitation is that we did not included midwives in our study. For future research, this would be a valuable consideration. A final limitation may be that this study provides insights in the local situation in Amsterdam, because participants are recruited in this city. We included a thick description of the local situation, to maximalise the transferability to a broader context.

Implications for research, policy and practice

Integrating the toolbox into clinical practice holds promise for enhancing early identification and management of childhood obesity risk. Looking ahead, for further development and implementation it is important to work towards a pilot study in which the implementation process and short- and long-term effectiveness of the toolbox should be investigated. HCPs and parents should be engaged in all steps to foster adoption [9]. Moreover, collaboration between research and youth health care policy and practice is crucial in this process of further development and implementation to address the several critical barriers identified in this study, such as concerns regarding validity and added value, negative connotations regarding risk prediction and the complexity of childhood obesity prevention. For example, efforts are needed to mitigate resistance surrounding profiling and discrimination by risk prediction, and to change beliefs on validity and added value of the prediction tool. This could be done through for example a training for HCPs in (1) understanding the underlying prediction model and (2) tailored, sensitive communication with parents around the use of the toolbox, alongside the communication tips. In the further development of these communication tips, it is important to address how to prevent feelings of blame, shame and stigma. For example, HCPs can explain that the prediction tool is used in the interest of health growth and development during a very important period in life, emphasize that the use of the prediction tool is part of the standard care routine, and explain that overweight is not an individual responsibility but influenced by various biological, psychological, environmental, and lifestyle factors. Health care organisations could consider collaborating with key community figures to convey messages effectively to parents, as parents might be more receptive to information from familiar people who they trust. Finally, health care organizations could collaborate with national and local institutes and initiatives as much as possible to commonly address the complex interplay of factors contributing to childhood obesity.

Conclusions

To conclude, HCPs in Amsterdam generally supported the potential use of a childhood obesity prediction toolbox in clinical practice to identify and support infants at high risk of developing childhood obesity but also expressed concerns regarding the validity, added value of the toolbox and the complexity of adequate risk communication. These concerns must be addressed in further development and implementation of the toolbox.

Abbreviations

BMI

Body mass index

HCPs

Health care professionals

SEPs

Socioeconomic positions

YHC

Youth health care

JARS-Qual

Journal Article Reporting Standards for Qualitative Research

Authors’ contributions

AM, CD and JS designed this study. AM coordinated and performed the data collection together with NM. AM, BG and CD analysed the data. AM wrote the manuscript. All authors provided critical input and feedback on the manuscript and approved the final manuscript.

Funding

This project has received funding from the European Union’s Horizon 2020 research and innovation program under the ERA-NET Cofund action (No. 727565), European Joint Programming Initiative “A Healthy Diet for a Healthy Life” (JPI HDHL), EndObesity, ZonMW Netherlands (No. 529051026).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Research Ethics Review Committee of the Faculty of Science of the Vrije Universiteit Amsterdam (BETHCIE). Review number of approval letter: 22–49. Informed consent was obtained from all participants, who were all over 18 years of age. Clinical trial number: not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.