The current scientific literature shows an increasing demand for psychological support within the general population, with even higher levels when considering vulnerable populations exposed to stressful situations [1]. The World Health Organization (WHO) strategy for global mental health is based on principles of inclusivity and scalability, covering the entire arch of mental health promotion and prevention for citizens exposed to the risk of mental distress. The gap between the prevalence of mental health problems and the services available to those in need of specific interventions represents a current public health challenge, and WHO has further underlined this issue through the “mental health Global Action Program” [2], where particular attention is also paid to the potential role of digital technologies in facilitating both availability of services and optimized delivery of the intervention [3]. Digital health is considered a pivotal strategy to promote equitable, affordable, and universal access, reducing the gap between services and those who can benefit from receiving mental health interventions [4]. Indeed, an increasing body of literature confirms the potential of new technologies—including telemedicine, mobile health (mHealth) initiatives, and digital therapeutics (DTx)—for promoting a continuum of care from clinic to home and a stepped-care approach. In particular, low-intensity mental health interventions could be considered appropriate for implementation within digital health solutions [5]. They usually refer to specific programs where the active involvement of health care staff and specialists is not necessarily required. They are based on solid principles from evidence-based psychological interventions embedded into a self-help approach. Among them, WHO is promoting Self-Help Plus (SH+), a low-intensity intervention for stress management initially developed for hard-to-reach vulnerable population groups [6]. These types of interventions are usually designed to be transdiagnostic and easily adaptable in different contexts. Because of their general structure and purpose, low-intensity approaches can be easily used to increase access to viable and evidence-based psychological interventions to a broader target audience, reporting either limited or mild symptoms linked with mental distress or illness within a stepped-care approach [7]. The potential combination of evidence-based, low-intensity interventions and mHealth approaches could lead to an effective, sustainable, and inclusive strategy for improving the scalability of mental health interventions both in terms of prevention and treatment [8].

The primary aims of this paper are as follows:

The development of the intervention leveraged the integration of different expertise, including psychology, eHealth IT, interaction design, and domain knowledge on pregnancy and oncology. A multidisciplinary team was created to account for the users’ different needs and to accommodate for psychological consistency of the intervention and the proper adoption of IT requirements and user-design principles in the process, to ensure high quality in terms of adaptability of the proposed tools in the digital context.

The entire development of the intervention is based on two main methodologies: user-centered [39] and service design [40]. These approaches emphasize understanding and meeting user needs, promoting iteration and continuous improvement based on user feedback. SH+ will be developed iteratively, following the Obesity-Related Behavioral Intervention Trials (ORBIT) model [41], as illustrated in Figure 1. The development process included a literature review; exploration, incorporating input from user representatives, health care providers, and eHealth experts, including designers and developers; intervention content development, which was identified and adjusted from the SH+ intervention manual; iterative software development and formative evaluation; and finally, considerations regarding privacy, security, and organizational anchoring.

After the preliminary phase of literature review and integration of the WHO protocol, we systematically carried out the subsequent steps to develop the ALBA chatbot prototype. Following the ORBIT development process ensures a scientifically step-by-step approach to recognize standardized creation of digital behavior change interventions. We then progressed to the initial stage of the ORBIT model, specifically Phase 1a (Define). This phase is designed to establish a solid foundation for the intervention by clearly defining the clinical problem to be addressed as well as the targets and ensuring that the intervention is conceptually sound and grounded in relevant theory and empirical evidence. In line with this, our goal was to adapt and refine the core components of SH+ prior to feasibility testing. Accordingly, this paper focuses on the initial adaptation methodology, and the process is described in detail in the following sections and summarized in Table S1 (see Multimedia Appendix 1). In contrast, real-world usage metrics, such as dropout rates, session completion, and participant feedback, will be addressed in later phases, including preliminary testing (Proof of Concept and Pilots) first and subsequent efficacy and effectiveness trials. These results will be presented in future publications.

All future studies’ data and our previous preliminary data [44] are confidentially collected in Italian and deidentified with participants’ informed consent. Eventually, confidential audio recordings of semistructured interviews are used for data analysis, and participants are identified only by numeric codes. At the studies’ conclusion, participants can request the research outcomes from the research manager. Participants did not receive any compensation. A local ethics committee will approve all future studies, as with our previous co-designed study [44]. Privacy issues require strict adherence to informed consent protocols and secure data retention compliant with the General Data Protection Regulations. Finally, the participants will be informed of the study’s results through the dissemination of articles.

New technologies can improve the sustainability of the health care system by providing round-the-clock support to patients and optimizing the interventions provided by health care professionals [5]. Nevertheless, the innovations associated with developing and utilizing new technologies for mental health remain a subject of ongoing discussion. Empirical studies on evidence-based digital interventions for mental health, including internet-based CBT, have shown that these interventions are effective, feasible, and acceptable to users [51-53]. However, some limitations have been found, mainly regarding users’ low engagement and completion rates [51,54]. Integrating human coaching and support in digital mental health interventions can help improve adherence and behavior change outcomes [55,56], although this may reduce the scalability of such solutions. In this optic, the use of chatbots for digital mental health interventions has attracted interest in the design community. A growing number of studies are reporting their acceptability and feasibility for users [57,58], as well as their effectiveness in reducing perceived stress [54], thereby improving symptoms of anxiety [59-61], depression [60,61], and insomnia [62]. A recent meta-analysis suggested that internet-delivered CBT is likely as effective as conventional face-to-face CBT. However, there are still unanswered questions about treatment moderators and implementation strategies [63]. Another study highlights the importance of understanding and accommodating diverse patient preferences when implementing self-management applications in cancer care. It underscores the significance of patient engagement in self-help and suggests that digital interventions can empower individuals to control their well-being. However, participant experiences varied, with differing perceptions of added value. Recommendations include refinements for improved user-friendliness and tailoring content to individual preferences through continuous evaluation and collaboration with end users to enhance intervention effectiveness and user experience [64].

In line with these new emerging technological tools to face sociopsychological demands, this paper seeks to provide insights beyond the end user interfaces, delving into the complexities of an mHealth app for stress management development, ALBA. This ongoing research adapts the transdiagnostic SH+ package to a chatbot intervention for women with breast cancer and pregnant women in Italy. ALBA replaces human facilitators, delivering text, audio, video, and graphics content; guiding participants; initiating interactions; and ensuring exercise implementation. The adaptation process involved careful consideration of cultural nuances and the psychological states of the target populations. The adaptation process required evaluating psychological states, tailoring materials, and customizing content for the users’ specific needs. Moreover, the intervention was adapted to individual support: The chatbot-mediated approach aims to provide a resource-efficient and innovative way to help through digital translation, allowing flexible session delivery with personalized sessions and reminders to enhance adherence to the stress management path. The chatbot incorporates gamification elements, assigning homework, monitoring progress, and providing feedback through a diary section with badges as favorable reinforcement. Gamification principles enhance engagement and motivation, making the intervention more effective and enjoyable for end users.

This research underscores the inherent value of consistent daily engagement with virtual coaches, surpassing sporadic interactions with human specialists and thus mitigating constraints stemming from their limited availability [2,3]. Moreover, considering the link between costs and human interaction, the shift from group-based interventions to individualized approaches is explored. Although this shift may increase accessibility and affordability, it simultaneously triggers reflections on the communal synergy and interpersonal involvement integral to group interventions. Nevertheless, the chatbot offers a prospect to decipher the precise impact of virtual coaching interventions not burdened by an array of confounding variables [16]. This study also contributes to understanding their potential within the mental health landscape by delineating the nuanced advantages and considerations surrounding virtual coaching applications.

Another aim is to draw clinical attention to new target populations’ stress triggers and management through the delicate and underestimated design phases. In all the adaptation steps, the end user viewpoint was considered. The research emphasizes the importance of considering end users and their perspectives in enhancing the accessibility of the intervention through a user-friendly, chatbot-guided system. The commitment to tailoring the intervention for Italian women is a comprehensive approach aimed at meeting the specific needs of the target demographic. Indeed, the need for support from these two populations is increasingly evident. The transposition of CBT techniques into digital tools is the most functional according to the literature both for pregnant women [65] and women with a breast cancer diagnosis [35], decreasing anxiety and depression symptoms. The application of digital CBT therapies is still open to experimentation, and this digital intervention will be included in this panorama.

The adaptation work for a digital stress management app has highlighted several practical challenges. One significant challenge is the need for intermediaries to guide during or between sessions, necessitating the anticipation and embedding of potential user queries or uncertainties within the application framework. To address difficulties such as comprehension issues, the app will offer feedback based on a manual and provide avenues for further assistance, including technical support or access to a psychologist.

Engagement maintenance during the transition from group to individual digital sessions is another key challenge addressed through gamification elements and interactive exercises with feedback and reminders. Subsequent empirical investigations are needed to validate these strategies and assumptions.

Future research questions and challenges include participant recruitment and privacy concerns. Although stress management’s universal relevance aids recruitment prospects, obstacles may arise from stigma and health care access barriers. Alternative recruitment channels such as voluntary participation and partnerships are being explored.

ALBA will adhere to the successive stages of the ORBIT model. The initial emphasis will be on Phase Ib, followed by the comprehensive redefinition of components through standardized co-design investigations. Subsequent efforts will encompass the methodical assessment of prototype usability, in terms of app architecture, design iterations, and technical performance, and the evaluation of app efficacy after its revision in randomized control trials. These steps are needed to understand the user experience and acceptability of the app, proving its clinical efficacy and facilitating its possible successful implementation in real-world settings with these specific target populations. Every specification inherent to possible end user app utilization will be deeply considered and empirically validated.

An additional advancement involves examining the practical implications of utilizing this app within real-world settings. This would encompass a comprehensive evaluation of the intervention’s efficacy and efficiency in rendering support and facilitating progressive care for the designated populations. It could shed light on sustainability in terms of the resource allocation and human capital expenditures stemming from implementing this preventative and low-intensity support framework. From a broader perspective, the potential exists for the creation of analogous applications, exhibiting tailored cultural and linguistic adaptations to address the needs of diverse target demographics, encompassing women who have breast cancer as well as pregnant women from varying cultural backgrounds.

Introducing ALBA, a new mobile tool designed for some vulnerable female populations, enriches the mHealth scientific literature. This innovation involves implementing an SH+ validated intervention using a new delivery tool, incorporating the previously outlined and targeted modifications. Using the SH+ protocol will shed light on the exploration in assessing the efficacy of the chatbot as an innovative intervention strategy, along with evaluating the impact of the evidence-based intervention on these specific groups. The commitment extends to comprehensive implementation research, delving into clinical outcomes and examining app implementation-related factors such as feasibility, fidelity, and accessibility.