Self-management programs are recognized as a valuable approach to supporting people with long-term conditions, such as stroke, in managing their daily lives. Bridges Self-Management (Bridges) focuses on how practitioners interact and support patients’ confidence, skills, and knowledge, and it is an example of a complex intervention. Bridges has been developed and used across multiple health care pathways in the United Kingdom and is theoretically informed by social cognition theory and self-efficacy principles. Evidence shows that self-management programs based on the construct of self-efficacy can be effective. There is still much to learn about how health care services or pathways should implement support for self-management in a sustainable way and whether this implementation process is different depending on the context or culture of the team or service provided.The aim of this study is to tailor and evaluate an intervention (Bridges) to support self-management after stroke in a Swedish context.We will use a pretest-posttest design with a case study approach to evaluate the feasibility and implementation of self-management support in two stroke settings. This project includes a complex intervention and depends on the actions of individuals, different contexts, and the adaptation of behavior over time. A mixed methods approach was chosen to understand both outcomes and mechanisms of impact. Data collection will comprise outcome measurements and assessment tools as well as qualitative interviews. Data will be collected concurrently and integrated into a mixed methods design.Recruitment and data collection for the first site of the project ran from September 1, 2021, to January 17, 2022. The intervention at the first site was conducted from November 1, 2021, to March 5, 2022. The evaluation will start after the implementation phase. The second site has been recruited, and the baseline data collection will start in spring 2022. The intervention will start in early autumn 2022. Data collection will be completed by the end of 2022.This study represents a unique, highly relevant, and innovative opportunity to maximize knowledge and minimize practice gaps in rehabilitation stroke care. The study will produce robust data on the intervention and in-depth data on the contextual factors and mechanisms related to the feasibility of the intervention and for whom it is feasible. Bridges has been used in the United Kingdom for more than 10 years, and this study will explore its contextualization and implementation within a Swedish stroke environment. The evaluation will study results at the patient, staff, and organizational levels and provide recommendations for the adoption and refinement of future efforts to support self-management.DERR1-10.2196/37672 Self-management programs are recognized as a valuable approach to supporting people with long-term conditions, such as stroke, to manage their daily lives ,2. The eStroke is an acute condition but can have a long-term impact on individuals and families; despite a reduction in the incidence through advances in prevention and emergency care, support for life after stroke and the long-term effects on the individual and families remain inadequate in most health care systems in Europe . Recent Definitions of what constitutes self-management support vary, but it has been conceptualized as a process in which the person living with a long-term condition, such as stroke, is supported to be an active partner in their recovery process ; this deWhile there is a move toward more collaborative health care and partnership working models, some critics of self-management programs have highlighted their limitations, particularly when they are professionally led and limited to didactic methods of providing health education to individuals and their families ,19. SelfGiven the high numbers of people who experience cognitive or communication problems and mood disorders poststroke ,24, therSelf-efficacy beliefs can determine how people feel, think, motivate themselves, and behave concerning their health by determining the goals people set, how much effort they invest in achieving those goals, and their resilience when faced with difficulties or failure. Self-efficacy can be considered a mediator and an outcome, and studies have shown a relationship between self-efficacy, activity performance, disability, mood, and quality of life poststroke . CurrentSelf-management support integrated into everyday health care practice could be one way to avoid the constructions and practice of self-management as an add-on to health care -33, but The implementation of new ways of working in health care is always context dependent, and careful consideration is required to develop feasible implementation strategies . The intAs a complex intervention, Bridges  focuses The proposed project aims to evaluate a self-management program intervention and study the implementation process. The specific aims are to explore the following:The feasibility of refining Bridges training for stroke teams and integrating it into Swedish stroke settings.The self-efficacy, health, well-being, self-management, and perceived participation in rehabilitation of patients with stroke pre- and postimplementation.The conceptualization and description of the intervention as a self-management approach by persons with stroke and staff.The ability of the intervention to change the nature of interactions between patients and staff.The critical mechanisms in the implementation process required for integrating self-management support at the individual and ward levels.We will use a pretest-posttest design with a case study approach to evaluate the feasibility and implementation of self-management support in two stroke care settings. Case studies can provide rich data and are particularly useful when understanding the implementation of a complex intervention in a real-world setting in which the process or context cannot be controlled . As thiswork together to achieve a practice that is being implemented through four fundamental mechanisms that affect whether a new practice or way of working becomes normalized and embedded in everyday practice. These mechanisms relate to activity performed with the following objectives:Normalization process theory (NPT) will guide data collection, analysis, and interpretation . NPT focTo make sense of the practice change and gain a shared understanding of the purpose and value of the change and how the new practice differs from previous practice (coherence).To participate and have sustained engagement in the activity (cognitive participation).To successfully work together with the new practice within its setting (collective action).To reflect on and appraise the impacts of the activity in ways that can be used to improve the process for those involved (reflexive monitoring).In developing the study protocol, we followed the SPIRIT  statement . In addiThe project consists of three phases . The aimTo tailor the intervention to the Swedish context, the UK Bridges team will hold additional discovery interviews to explore existing experiences of self-management support, goal setting, and discharge planning methods, as well as any critical issues regarding staff caseloads and organizational challenges. Staff taking part in the training will be asked to provide case studies or personas about patients they are currently working with or have worked with in the past that depict self-management successes and challenges. These case studies will be used to contextualize training in the Swedish setting.The second phase involves the training of the staff according to the Bridges program, followed by an implementation phase, where the rehabilitation team will implement the intervention  in their everyday clinical practice. The implementation phase will last approximately 6 months, which will allow the staff to adopt the intervention and embed it into routine practice. The third phase will involve analysis and reporting on the project’s implementation and its outcomes.The logic model  that guiThe study will be conducted at two stroke units in Sweden. We will purposefully recruit stroke units that provide rehabilitation across inpatient and home settings. The 3-year study will be conducted from 2021 to 2023 and will have a mix of multidisciplinary skills.The participants in the study will be staff and patients in stroke settings. In regard to the staff, there will be different numbers of staff who carry out the workshop for the intervention depending on the staff size. We expect most people in a staff group to participate. Those who participate are expected to attend all workshops, participate in the discussions, and carry out the intervention tasks. The staff groups will be mixed based on the staff composition of the unit .We will also interview approximately 15 staff members in each of the two units to answer questions regarding the organization and integration of self-management in clinical work before and after the implementation of the intervention. The inclusion criterion for the participants in these interviews will be that they should have been working in rehabilitation for at least 6 months.A total of 40 patients will be recruited prior to the implementation of the intervention in the standard care context , and 40 will be recruited after the intervention has been implemented in the units (20 at each site). As such, the participants in the preintervention patient group will be different from the participants in the patient group after the implementation of the intervention. The inclusion criteria for the persons with stroke will be as follows: aged 18 years of age or older, 3 to 6 months after stroke onset, discharge from rehabilitation at the hospital or day care, fulfillment of the criteria for a clinical diagnosis of stroke, ability to comprehend study goals and procedures, and knowledge of the Swedish language to such a degree that no interpreter will be required. The participants will also identify a family member who will be asked to participate. The time frame of 3 to 6 months after stroke onset was chosen based on the expectation that patients’ physical recovery would be stabilized. However, they might still face difficulties in everyday life that have become evident after engaging in daily activities in their environment after discharge.Initially, stroke unit staff from participating stroke units will be asked to identify potential stroke participants based on the inclusion criteria . Patients who fulfill the inclusion criteria will receive an information letter; they will be asked if they are interested in participating in the study and if they will allow a person from the research group to contact them. Within 1 to 2 weeks, potential participants will be contacted by telephone, and those who express an interest in participating will be scheduled for an interview. Before the interview, all self-reported instruments will be sent home to the person so they can fill in the questionnaires before the interviews. At the beginning of each interview, the participants will be informed about the study again and will have the opportunity to ask questions. Informed consent will be recorded.The recruitment of stroke units will be based on suitability . The staff at the included sites will receive an information letter about the study, and they will give their written informed consent to participate.In this project, the intervention is conceptualized as a staged approach to training staff using Bridges and implementing key principles and strategies within everyday practice with stroke patients. The training will be delivered online and weekly using a staged approach across nine sessions, each lasting between 60 and 90 minutes. Every session will cover critical themes, such as emphasizing the importance of the patient’s narrative, past life experiences, skills, and assets; enhancing self-efficacy through mastery and vicarious experiences; supporting key self-management skills, such as goal setting and reflection; and exploring hopes and fears as motivators and drivers for action. The staff will have key activities to implement in their work after each session. Individually and collectively, they will agree on strategies for implementation in their everyday work and ways to sustain support for self-management posttraining. The training will be co-delivered by an experienced health care academic and practitioner and a person with lived experience of an acute and long-term condition. Staff will receive weekly reminders about key aspects of each session and reminders about their targets for putting Bridges into action. They will also receive access to additional resources, such as an interactive handbook, key evidence, posters, and crib sheets. Staff will be provided with support by an internal, educated, self-management facilitator .Data collection to investigate the implementation, feasibility, role of the context, and influencing mechanisms will take place according to the MRC process evaluation . Data wiResearchers will take field notes to observe the sessions throughout the intervention process. The notes will contain observations of how the training sessions and communication work. These data will be complemented by interviews with the Bridges team, who will provide the intervention. The interviews will cover experiences of the intervention, such as delivery method, dose, content, and specific components. The interviews will also cover how closely the participants follow the intervention guide.The experiences of the intervention from the staff’s perspective will be collected through interviews after the intervention. The questions will cover experiences of the intervention, such as delivery method, dose, and the content of the sessions. In addition, a sample of interactions between patients and staff will be observed using an observational framework for case studies and implementation studies developed by Morgan et al . For exaThe interviews will be recorded and transcribed verbatim.To explore the staff’s experiences of the intervention and any potential changes in working methods after the intervention, interviews will be conducted before and after the intervention. The interviews will be semistructured and will capture the staff’s experiences of their work processes and use of self-management strategies in daily work. Questions will cover the work process and how staff support patients’ self-management in a person-centered way. In addition, questions about how they support patient participation will also be asked.We will also strive to capture patients’ experiences of how the staff supports self-management and provides opportunities to participate before and after the intervention. Questions will be asked to patients about how they experience the staff supporting them in self-management strategies and the way the staff create opportunities for them to be involved in their care and rehabilitation. The same questions will be asked to each cohort of patients before and after the intervention.The interviews will be recorded and transcribed verbatim.We will evaluate outcomes at two time points—pre- and postimplementation of the self-management program—using self-reported measurements and interviews pre- and postimplementation. Data from the staff will be collected before and after the intervention in each setting. Data will be collected from patients and relatives in two cohorts before and after the intervention.The following demographic data will be collected from the staff: sex, age, professional occupation, number of years in stroke care and rehabilitation, and the participating site.Qualitative interviews will be completed to explore the staff’s knowledge, skills, attitudes, and experiences in performing self-management support. The interviews will be semistructured and conducted before and after the intervention. The questions will capture experiences of self-management and the rehabilitation process as well as how the process affects their work. After the intervention, questions will be added about the experience of the intervention. Issues will specifically focus on how the staff adopt strategies for self-management in their contact with patients. The interviews will also explore the experiences of previous uses and potential news and insights into necessary changes after the intervention. The interviews will be recorded and transcribed verbatim.Integration of self-management in usual practice will be assessed using the Swedish version of the Normalization Measure Development questionnaire (NoMAD) , which mWe will evaluate outcomes at two time points—pre- and postimplementation of the self-management program—by asking two open-ended questions and using self-reported measurements before and after the implementation. The two questions will be as follows: (1) Can you tell me how the staff supported you in gaining confidence, skills, and knowledge [to self-manage]? and (2) Can you tell me how the staff created opportunities for you to be involved in your care and treatment? In addition, standardized self-reported measures that reflect the mechanism of impact, such as self-efficacy for self-management measured by the Stroke Self-efficacy Questionnaire (SSEQ) , will bePerceived health will be measured using a single item from the five-level EQ-5D (EQ-5D-5L) instrument , which cAdditionally, the Stroke Impact Scale-16 (SIS-16) will be employed to assess self-reported physical function . The SISWe will also use a specially developed scale for self-management, co-designed with stroke survivors and used across the United Kingdom in stroke improvement work and Bridges . The shoDemographic data such as sex, age, diagnosis, and level of stroke burden will also be collected from participating patients. A detailed data collection plan with all the measures is presented in Anonymized data will be entered into SPSS Statistics for Windows (IBM Corp)  and secuData will be analyzed between and within the two units, allowing us to understand what factors impact the staff during training and implementation and patients’ health and well-being related to the intervention. This will allow us to understand the implementation process of the intervention within a real-world setting and identify the main factors influencing this process.Data from the questionnaires will be analyzed using descriptive statistics, and the qualitative data from interviews and observations will be analyzed using thematic analysis , supportEthical approval was given by the Swedish Ethical Review Authority (2020-02116). Patients and staff have been thoroughly informed of all aspects of the research protocol in which they might be included, and patients have been assigned numbers for anonymization purposes. All data will be collected by phone or using paper questionnaires. Data will be kept in a password-protected database on the research leaders’ institutional server, and paper questionnaires will be kept in a locked container at the university.As of March 2022, the first and second phases were performed at site 1. This means that 20 patients have been enrolled and have completed all baseline measurements. A total of 10 significant others have been interviewed. Observations of the organization and staff interviews have been conducted. The intervention has been performed online by the Bridges team. A total of eight workshops have been conducted online. The researchers have observed workshops, during which they made field notes. Data are being transferred to SPSS and analysis will start when the implementation is completed. However, phase 3 has not started yet, since the implementation had not been completed.The second site has been recruited, and data collection of baseline data will begin in spring 2022 and will continue for another 6 to 12 months. The intervention is planned to take place in early autumn 2022.As one of the first studies to examine the feasibility and implementation of a stroke self-management program integrated into a Swedish stroke setting, this study will contribute to (1) a better understanding of the benefits of a self-management approach that specifically targets changing the ways that care providers work with and support patients with stroke and (2) exploring the value of embedding implementation science approaches into the study of complex interventions in stroke, in order to better inform policy makers’ decisions about, and implementation of, stroke service delivery.The qualitative data from the interviews will provide valuable insights as to whether, from a patient perspective, self-management support provided through an adapted Bridges program will reflect greater perceptions of more person-centered care. The study will also provide data to explore whether there have been improvements in perceived health, as well as corresponding improvements according to the underpinning principles and fidelity of Bridges, following a period of staff working in the “Bridges way.”From a clinical perspective, the study will provide new knowledge of whether using a self-management support program based on the concept of self-efficacy and principles to support self-efficacy for self-management will improve rehabilitation through a new integrated way of working into existing health care interactions where people’s needs and skills are taken into account during the first interaction. The intervention is integrated into the way of working rather than being perceived as an add-on to care. We hope that the intervention will foster a better anchoring of patients’ and families’ needs in the rehabilitation process, reducing the risk that the health care professional is the one who defines the problems. In addition, the intervention is intended to favor more active participation by the patient and family and all members of the rehabilitation team; this will be explored through the qualitative and quantitative data from the study.Having used implementation science approaches throughout the study design, we expect to obtain deep insights into the implementation process from an individual to a macro perspective. Although each of the domains of the NPT may be necessary for ultimate success, health professional associations have a distinct role, from a macro perspective, in both coherence and cognitive participation, essentially in the sensemaking and relational work required to enact change. Considering the NPT at this level may strengthen the theory and suggest unique factors when looking beyond individuals within a team. Findings from this study will inform best practices guidelines by providing empirical data on effective implementation processes of self-management support, both in general and with relevance for scale-up and spread of this approach to other services in the Swedish context.The dissemination of results will not only take place through academic publications, but will also focus on communicating research results to practitioners and the public in appropriate trade journals, newspapers, and meeting forums, both in face-to-face meetings and online. Dissemination of popular science articles outside the academic world will take place by various members of the research group.We anticipate that the findings of the study, overall, will address the current call for health care to move toward more self-management and generate new knowledge about what contributes to successful and sustainable self-management support for people with long-term conditions, which is still underresearched in Swedish health care. The project has advantages, as it makes use of existing service time and can be used by all health care professionals in the context of the patient. From a patient perspective, self-management support will mean more person-centered care focused on the patient’s ability and opportunity to take an active part in the care of their health in everyday life. The patient will have support beyond that of earlier self-management interventions that relied too heavily on an individualistic approach, and that focused on personal agency without considering personal circumstances, including social capital, networks, health literacy, ethnicity, and cultural aspects .The proposed study design is a case study design, and the impact on patients’ health, well-being, and self-efficacy will need to be tested with a more experimental design. However, our case study research will contribute to a comprehensive and multifaceted exploration of an intervention in a natural uncontrolled setting. We will collect quantitative and qualitative data to understand the implementation process, context-dependent insights, and the feasibility of the intervention when adapted to the Swedish context.This study represents a unique, highly relevant, and innovative opportunity to maximize knowledge and minimize practice gaps in rehabilitation stroke care. The study will produce robust data on the effectiveness of the intervention and in-depth data on the contextual factors and mechanisms related to its effectiveness, for whom it is effective, and how it is effective. Participating health care providers will gain the resources to engage patients and families and develop their interprofessional self-management skills, which are crucial to meeting patients’ needs and to significantly improving patient self-management support and the rehabilitation process.


Culturally adapted CBT (CA CBT) is a well-evaluated, culture-sensitive intervention for refugees that utilizes psychoeducation, problem solving training, meditation, and stretching exercises. However, there is a lack of standard procedures for adapting psychotherapeutic interventions to a specific cultural context. Our working group adapted CA CBT for Afghan refugees at two different stages, which yielded promising results from a pilot trial and an RCT with a waitlist control group. This article aimed to illustrate the ongoing adaptation process of CA CBT for Afghan refugees over the course of several trials and to highlight potential limitations by evaluating how systematic adaptations were performed.The adaptation process of CA CBT was described in detail, including the methods and rationale for changes to the protocol. This process was analyzed according to a new set of proposed reporting criteria.According to the defined target population and based on multiple research strategies, culturally-specific components, such as the rationales for interventions, metaphors, and idioms of distress, were adapted. Relevant surface adaptations were implemented. However, although the steps of our adaptation process corresponded with the reporting criteria, some of the adaptation processes did not follow explicit criteria but resulted from implicit judgments.In the future, compliance with and the documentation of adaptation processes following explicit guidelines are crucial for the transfer of evidence-based approaches for managing the diversity of refugee populations. The reporting criteria  can be applied to analyze the documentation process of cultural adaptation in a post hoc analysis.The documentation process of culturally adapted CBT for Afghan refugees shows a high agreement with the reporting criteria.This detailed documentation of the adaptation process for Afghan refugees may facilitate the cultural adaptation for similar subgroups in future studies. Approximately 18% of the refugees arriving in Germany in 2016 originated from Afghanistan. Epidemiological studies revealed high prevalence rates for PTSD (32.2%), affective disorders (21.9%), and anxiety disorders (33.9%) among Afghan refugees . In AfghAs a low-threshold and easily accessible program, culturally adapted CBT (CA CBT), which was developed by The program is conceptualized as being resilience-focused and subclinical, and it can be delivered in an individual or group setting and includes 14 sessions. Interventions, such as psychoeducation, stretching, meditation, guided imagery, and cognitive techniques , are a part of each session. It should be mentioned that due to its resilience-focused and transdiagnostic nature, CA CBT does not include prolonged exposure to trauma memories; instead, it focuses on emotional regulation and addresses different psychopathological symptoms, including depression, anxiety disorders, and somatic symptoms, as well as related disorders.The original CA CBT group program by Hinton contained transcultural concepts and key idioms of distress, such as “thinking a lot” , which aN = 7 participants who had participated in the group program and whose native language was Farsi/Dari; additionally, the participants were male and over 18 years of age. The interview was conducted for approximately one hour and was audio-recorded, transcribed, and translated into German. The results were discussed by a group of experts, native speakers, and key informants. No specific qualitative analysis of the data was applied.Subsequently, for the pilot trial , a focusExperts were defined as professionals who had been working in the field of counseling psychotherapy with refugees or migrants for at least three years.In the following, cultural adaptions of the CA CBT are described based on the Reporting Criteria by At an early stage, we defined Farsi- and Dari-speaking refugees as the target population. In addition to Afghan and Syrian refugees, Iranian refugees constituted the third largest group of refugees in Germany in 2015 . We discWe mostly derived the cultural concept of distress (CCD) for Afghan and Iranian refugees from qualitative studies that were conducted via interviews with Afghan populations . After aFirst, we evaluated CA CBT in individual treatments of Afghan refugees. After the treatment, we interviewed the respective patients and integrated specific suggestions into the first group manual. Many patients expressed concerns that “[they] might go crazy” and that the occurrence of the symptoms was a consequence of personal sin. Although we did not systematically analyze the qualitative data, we extended the CCD by the information that was gathered through these interviews. Further idioms of distress were identified through interviews with key informants and experts.Although the main aspects of the adaption process in addition to the publications of the pilot trial and the RCT  were repWe documented the statements of the experts, key informants, and native speakers who were involved in the adaptation process. Nevertheless, we did not systematically document how specific decisions were derived.Professor Devon E. Hinton, Associate Professor of Psychiatry, developed the original protocol of CA CBT for several ethnic groups .Professor Ulrich Stangier, Professor in Clinical Psychology and Psychotherapy, who is the head of the Center for Psychotherapy and of the counseling center for refugees, as well as a supervisor and licensed psychotherapist.Ph.D. Sarah Ayoughi, who had many years of experience in counseling in Kabul, Afghanistan, and in speaking Farsi/Dari.The adaptation process did not follow a documentation or monitoring methodology.All of the diagnostic interviews were conducted by independent Farsi-speaking postgraduate psychologists. The M.I.N.I. in the original English version  was usedIf they were not already available and validated in Farsi, all of the instruments were translated and back-translated, in accordance with the suggested standard procedure that were proposed by Inner Child Metaphor. Some trauma-focused approaches to PTSD use the inner child metaphor to explain symptoms and trauma-related catastrophic cognitions  and culturally understandable  manner. Our therapists were native speakers, which included different nonspecific components, such as a sense of belonging-and familiarity.All of the interventions  were explained in short written handouts in Farsi. To improve the comprehension of this information, these handouts were also audio-recorded, and both the written handouts and audiotaped information were uploaded on a website that was accessible by the participants .CA CBT is available as an individual and as a group treatment. We chose a group setting for the following reasons: destigmatization through exchanges about symptoms with members of the same culture or peer group, the use of group cohesion to enhance feelings of connectedness, and dialogue about one’s experience regarding the asylum procedures.Due to the fact that all of the group therapists were native speakers, no translations were required in addition to the material.All of the material was edited in a culturally sensitive manner and translated into Farsi/Dari via translation and retranslation. Cultural sensitivity, as for all of the other aspects of the adaptation procedure, implies the consideration of the cultural concepts of distress, gender, or religious aspects that may conflict with the values that are present in Afghan society . To ensuSome of the on-the-fly adaptions were incorporated into the group manual . For exaThe examination of how we adapted CA CBT to Afghan refugees in Germany comprised a complex sequence of implicit and explicit developmental steps over three years. To analyze this process in a post hoc manner, we applied the criteria as suggested by The process clearly showed that cultural adaptation contains multiple levels and aspects of an intervention, and the feedback of our interviews demonstrated its major contribution to the acceptance and, thereby, to the potentially increased effectiveness of an intervention. Due to the staged nature of cultural adaptation, even in our case of adapting an intervention that was already adapted to another culture, it remains a highly difficult and nearly impossible challenge to document all of the facets. This can be illustrated by the Farsi idiom for “thinking too much”. After the decision for the Farsi idiom “fekro khial”, we had experiences with several interpreters who suggested other translations that would be more adequate regarding the meaning of the original idiom. Throughout the varying translations of “thinking too much”, we also experienced mixed reactions from patients. The specific interpretation of the idiom that was used was dependent on the region that the patient came from. This effect demonstrated how cultural adaptation can be a meandering procedure at various times. Detailed documentation may enable other mental health professionals to profit from the thoughts, ideas, and particular adaptation steps for their own adaptation process. Our documentation shows adaptation at different steps in a way that can possibly be exemplary for other professionals. When regarding adaptation to other target groups, it may be possible to transfer or adjust adaptations, due to detailed documentation.In the clinical context, we assume that a complete traceability of adaptations will enhance the adherence of therapists for adaptations that may seem alien to them. Furthermore, knowledge of the reasons for adaptations will increase the cultural sensitivity of mental health professionals, not only for the specific intervention, but also for the entire treatment situation. This may prevent other misunderstandings.Nevertheless, this complexity in the communication between therapists and refugees highlights how important it is to control as much of the process as possible, in order to make the process as transparent and comprehensive as possible. Only through a standardized approach for cultural adaptation can the need for culturally sensitive psychotherapy be met. The application of explicit criteria is an important tool for establishing a standard procedure for cultural adaptations.


Background: With their influence on health behavior of children, families are important addressees in health promotion and prevention of chronic diseases. However, they are often difficult to reach, partly due to the open approach of health promotion services. Therefore, they should be addressed directly and be involved in shaping their living environment. The aim is to examine which approaches are used in participatory family health promotion and what practical experiences are made. Methods: A systematic literature search in PubMed, Web of Science, LIVIVO and a supplementary hand search were conducted. Ten of 718 screened publications were analyzed qualitatively. Results: Most included publications applied the community-led participatory approach CBPR. In seven publications, family actors could make decisions at any or all project phases. One finding is that positive effects on desired behavior change and improved health of target groups were observed. Frequently described success factors are the type of interaction, and a common goal. Conclusion: The forms of family participation in health promotion vary widely, with the lack of participatory practices being a major challenge. Family participation is a useful approach in shaping health promotion and should be further developed. This overview provides support for planning future participatory projects with families. Families play a crucial role in health promotion and prevention of chronic diseases . FamilieAlthough families occupy a crucial position in health promotion, access to them is difficult in practice. The family does not represent a spatially fixed and defined setting, such as the institutions of school, kindergarten, or a workplace . MoreoveThe participation of families as addresses in the design and implementation of health promotion actions is helpful for increased acceptance and utilization . The WorIn terms of participatory health promotion projects, the goals, planning, implementation, and evaluation of interventions should be developed in partnership . ThroughThere are various approaches from the Anglo-American area within the broad spectrum of participatory health promotion and participatory research in health promotion projects, such as community-based participatory research (CBPR)  and partThe search strategy, selection process and data analysis were based on the preliminary guidelines of the Cochrane Rapid Reviews Methods Group  and are In the period from September to October 2021, a systematic literature search was conducted in the databases PubMed, Web of Science and LIVIVO and supplemented by an additional hand search. The following search strategy was applied in PubMed and transferred to the other databases: ((((((((family*[Title]) OR parent*[Title]) OR pregnan*[Title]) OR Famili*[Title]) OR Elter*[Title]) OR schwanger*[Title])) AND  OR prevent*[Title]) OR health*[Title])) OR (((Gesundheitsförder*[Title]) OR Prävent*[Title]) OR Gesundheit*[Title]))) AND (((((participat*[Title]) OR participatory research[Title]) OR participatory action research[Title]) OR participatory evaluation[Title]) OR participatory health research[Title]) OR community based participatory research[Title]) OR Partizipat*[Title]) OR partizipative Forschung[Title]) OR partizipative Qualitätsentwicklung[Title]) OR partizipative Gesundheitsforschung[Title]).Publications were considered that were written in English or German, referred to industrialized nations and were published in the period 2010–2020. Included publications were on the topic of participatory health promotion or primary prevention, in which preliminary stages or stages of participation with families were applied along the lines of Wright et al. (2008). In addition, the family should be considered as a system and family health promotion should take place in primary socialization  or in secondary socialization . Studies were excluded that had no participatory components, presented participation as mere participation in an offer, or took place outside the named socialization phases, such as in family care for the elderly or in the care of relatives. Apart from the existence of a full text, no specifications were made regarding the type of manuscript.Study identification and data extraction were carried out independently by two research assistants. The ten publications included different types of publications  and came from different countries (USA (7), DE (2), FI (1)). The health promotion interventions and the addressees of the projects were also different. The participatory approaches and methods of the projects and their relation to the research questions are discussed below. Subsequently, the practical experiences in the use and application of the contributions are presented under the identified topics of the observed effects and the described success factors for family participation. For a uniform clustering, the described inhibiting factors were reformulated into facilitating factors.To enable an overview and comparability, the participatory approaches and methods described in the included publications were differentiated according to six criteria concerning the research question, and are presented below. The seven US publications used the CBPR approach, which aims at creating structures for the participation of the addressees in the research process and shared decision-making power among the actors involved . Ferré eA total of seven publications referred to a theory or model. They either referred to participation, such as the citizen health care model ,23,25,27Parents were explicitly mentioned as involved actors in five publications, families in three publications and children in one publication. These publications referred to school, kindergarten, or community settings. Berge et al. (2016) and Carney et al. (2012) not only explicitly named families and parents, but also referred to the community in which they live. Some mentioned the community without further differentiation of the actors involved ,26,30.Three of the ten publications included only descriptions of preliminary stages of participation, such as informing, listening, or involving the addressees ,28,29. JFollowing the public health action cycle , all pubParticipatory methods used can be divided into four categories. Seven times each, in different combinations, it was described that regular meetings  were held ,25,26,27Various observations and experiences regarding the impact of the participatory approach were reported. Most publications mention the formation and strengthening of partnerships ,26,28,30Most success factors are found in process design. The most frequently described factor is respectful interaction and communication on an equal level ,26,27,30Some publications refer to general framework conditions such as financial and human resources ,24,27,29Regarding specific aspects of participation, the commitment of the participants and their desire for change are mentioned several times as beneficial ,25,27,28The geographical imbalance of the search hits could indicate possible limitations in the search terms used, e.g., that the keywords used only relate to research practice in the USA. Clar and Wright 2020) emphasize that participatory approaches are not considered research by many practitioners who use these approaches. As a result, some experiences with using participatory approaches may not be found in academic journals and standard databases. Given the current data situation, future methodological approaches may benefit from following the recommendation for limited use of grey literature and supplementary internet research in the preliminary guide to the rapid review method ,,34], is Overall, the number of included publications exemplifies that the participation of families in the process of health promotion projects is not yet widespread and has not been sufficiently investigated scientifically. In the large number of excluded publications, participation was often equated with pure participation and not with a decision-making competence of the addressees in the design of a health-promoting offer. For scientific research on participation in family health promotion, the development of a uniform understanding of participation is necessary, as is repeatedly demanded in the participatory research culture . A commoThe accumulation of hits in the Anglo-American area is partly due to a longer history of development of participatory research in North America . In the Some publications describe actions to reduce risk factors for chronic diseases. Similar to the WHO Global Action Plan for the Prevention and Control of NCDs 2013–2020, different determinants were addressed. Three publications describe projects dealing with nutrition and obesity ,25,30, iFamilies consist of different family members who are to be reached in participatory health promotion . The resThe results show that for large groups the levels “informing” and “listening” were used, and for defined small groups members were given decision-making competencies and powers. This illustrates that different levels of participation can be present during a project and that these are oriented towards the circumstances and existing possibilities of the project. Preliminary stages of participation and actual participation thus have their place in the project process. However, when working with the addressees, regular checks should be made on how decision-making powers and responsibilities can be transferred to them and whether the opportunities for participation are being fully maximized . A varieA suitable project phase for the participation of family actors seems to be the development phase. In all publications, participation took place in this phase. Participation here and in the preceding joint analysis phase is necessary for the course of the project, as this can lead to tailored actions that positively influence effectiveness and sustainability . It can The results show that there are many positive effects on different levels through family participation. The fact that family participation strengthens and forms new partnerships coincides with the general impact of participatory projects on relationships . It expaThe preliminary stage of participation can already have positive effects, and since the research and health promotion culture in Europe is still not very participatory, applying this stage would form a foundation for participation and health promotion. Higher acceptance of actions and a decrease of health inequalities, precise recommendations for action are needed. It is unclear how the complexity in the development of effects  can be aA successful process requires the inclusion of families in health promotion projects, fundamental aspects such as respectful interaction, communication as equals, and agreement on a goal. These factors, and the need for additional resources , do not differ from health promotion projects  but gainThe engagement of the participants through their desire for change illustrates the relevance and opportunity that are commonly defined goals. A balance of research and action needs to be considered in the planning and implementation of projects. This desire for action presumably correlates to the challenge of joint research and the evaluation of actions and processes described above.Empowerment and participatory attitudes (participatory culture in the setting) are a core element of participatory health research, yet are only addressed in a few publications . It is pThere are only a few publications on participatory family health promotion projects, and there is a great need for theoretical and methodological development, especially outside the Anglo-American area, i.e., Europe.Form and method of participation must be adapted to individual circumstances, and continuous consideration should be given to how the highest possible form of participation can be achieved.Participation in family health promotion leads to effects on different levels, including strengthening partnerships and a higher acceptance of actions, and can be used to develop interventions that reduce chronic diseases.As with other participation processes, particularly suitable framework conditions and attitudes contribute to success, whereby flexibility in the form of participation is of particular importance in family participation.In conclusion, the following aspects can be summarized with respect to the research questions:The participatory approach and its impact are complex, as is the behavioral change that results from participatory action. This is probably why this outcome is so rarely explored in publications. This review shows that the participatory approach nevertheless has many effects that will, over time, trigger behavior changes in the family and the respective environment or community. The approach is, therefore, very promising because behavior can be influenced in the entire living environment.


N = 12) were able to develop an understanding of how AI and chatbots will affect their future daily work. Although basic attitudes toward the use of AI were positive, the students also expressed concerns. There were high levels of agreement regarding the use of AI in administrative settings (83.3%) and research with health-related data (91.7%). However, participants expressed concerns that data protection may be insufficiently guaranteed (33.3%) and that they might be increasingly monitored at work in the future (58.3%). The evaluations indicated that future physicians want to engage more intensively with AI in medicine. In view of future developments, AI and data competencies should be taught in a structured way during the medical curriculum and integrated into curricular teaching.Artificial intelligence (AI) in medicine and digital assistance systems such as chatbots will play an increasingly important role in future doctor – patient communication. To benefit from the potential of this technical innovation and ensure optimal patient care, future physicians should be equipped with the appropriate skills. Accordingly, a suitable place for the management and adaptation of digital assistance systems must be found in the medical education curriculum. To determine the existing levels of knowledge of medical students about AI chatbots in particular in the healthcare setting, this study surveyed medical students of the University of Luebeck and the University Hospital of Tuebingen. Using standardized quantitative questionnaires and qualitative analysis of group discussions, the attitudes of medical students toward AI and chatbots in medicine were investigated. From this, relevant requirements for the future integration of AI into the medical curriculum could be identified. The aim was to establish a basic understanding of the opportunities, limitations, and risks, as well as potential areas of application of the technology. The participants ( The healthcare system is undergoing a digital transformation, and artificial intelligence (AI) will play a significant role in defining everyday medical practice . The locFurthermore, the digital networking of patients, hospitals, physicians and other healthcare services is enabling a shift from a physician-centric approach to more patient-centered treatment . To explA look at the national competence-based learning objectives catalog for medicine (NKLM)  shows thWhat attitudes do medical students have about artificial intelligence and the use of chatbots in medicine?Does their view of chatbots change after learning more about medical chatbots in the course?Therefore, the question arose for us, how to successfully prepare medical professionals for this new scenario during their medical training. This study is intended as basic research relating to AI in the medical curriculum. We aimed to provide an overview of the current knowledge and attitudes of medical students regarding AI technologies to determine what is necessary for future implementation in the curriculum. Therefore, the following questions arose regarding the implementation of AI in medical education:N = 12 medical students learned about conditions of doctor – patient communication in general, possible uses of chatbots in healthcare, the ethical framework of AI, how chatbots work in general and what it takes to create a ready-to-go bot. The course combined classical teaching of theoretical knowledge  and practical competence acquisition in the form of exercises and group work during a synchronous online format via Zoom.This study followed the Standards for Reporting Qualitative Research  and presThe attitudes of participants regarding the topic of AI in medicine were quantitatively assessed by means of a standardized questionnaire before and after the course via the learning management software ILIAS. Qualitative methods such as group discussions supplemented the detailed, subjective and individual attitudes of the medical students to the topic.The study received ethical approval from the Ethics Committee of Tuebingen Medical Faculty (no. 824/2021BO2). Participation was voluntary, and students provided their informed consent and received no compensation. All responses and data were kept anonymous.We combined quantitative and qualitative research methods in this study to achieve an in-depth analysis of the collected data .To conduct the quantitative survey, the medical students were asked to complete a self-developed standardized questionnaire at the beginning of the course to assess subjective attitudes toward AI in medicine. The questionnaire was divided into three subsections, with items including five-point Likert scales and multiple-choice questions. The first subsection aimed to gather demographic data including age, gender and general attitudes toward technology and AI. Attitudes toward technology use were assessed using a shortened version of the validated short scale for assessing individual differences in the willingness of technology, as per Neyer et al.  .p < .05.As one student did not complete the course, we used the mean imputation procedure for the missing values after testing for normal distribution using the Kolmogorov-Smirnov test procedure [Statistical analysis of the questionnaire was performed using IBM SPSS version 27. Mean values (M), standard deviations (SD), sum values, frequencies and percentages of the relevant items were obtained. The Pearson correlation coefficient was calculated to capture linear relationships between the relevant variables. We used the Wilcoxon test to analyze the statistical significance of the differences between the two repeated items after the course; the level of significance was rocedure ,25.The results of the students’ group work were recorded, transcribed and coded by three different authors . Following discussions in regular meetings, findings were summarized and a category system consisting of main and subcategories  was agreed upon . SelecteThe course was attended by 12 medical students from the clinical and preclinical study sections, who were able (at least partly) to give a broad explanation of AI. For further information, please see M = 21; SD = 3.1, min. 18, max. 31).The participating students stated that they could explain the main features and applications of AI (50.0%) and that they could at least give a broad definition of AI (50.0%). Evaluation of the technology commitment according to Neyer et al. 2016 showed that the study participants displayed a moderate willingness to use technology (Many students were not afraid of the future changes that AI could bring. The majority (83.3%) were not afraid of losing their jobs because of AI or of being overwhelmed by using AI (83.3%). However, some students agreed that they were afraid of increasing surveillance at their future workplaces (58.3% agreement vs. 25.0% disagreement) and decreasing transparency regarding the use of personal data (33.3% agreement vs. 33.3% disagreement)  Plot A.As shown in Students saw the use of AI in medicine primarily as an opportunity to reduce the administrative burden on physicians. At the same time, however, they also believed that the new technology would be able to make diagnoses faster and more accurate in the future and ultimately also make access to medical advice more sustainable  Plot A.At the beginning of the course 692% of the students never have used a medical chatbot before. However, the students had great confidence in chatbots, especially for organizational tasks. In task areas with high levels of responsibility, such as diagnosis or treatment suggestions, opinions tended to diverge and were more critical, but the students were not completely opposed to the use of AI in general  Plot B.p = 0.02) less critical about privacy and the use of medical chatbots after the course. Prior to the course, 500% of students believed that data privacy and security could not be fully guaranteed, 41.7% were undecided, and only 8.3% did not believe this. After the course, only 36.4% were still critical of data protection, 18.2% were undecided and 45.5% did not believe that data protection cannot be guaranteed with med. Chatbots (see Table A3). Only a few statements showed a clear positive or negative tendency. For example, the majority agreed that using chatbots saved time  and money . However, medical students felt that chatbots were not yet sufficiently established and that long-term success had yet to materialize (81.8%). There was also a fear of communication problems (81.8%) and loss of personal contact with patients (63.6%) because of the lack of maturity of the technology.As shown in Tables A2 and A3 in the appendix, no major differences in attitudes held before and after the course were detected. However, students were significantly  may not be familiar with modern technology or chatbots. The medical students also proposed a minimum age of 18 years and an alternative language mode specifically aimed at children.The students felt that with the use of emojis, artificial delays, small talk and customization, there was an opportunity to provide the most human-like and realistic conversation possible with a chatbot. Furthermore, the development of the chatbot should take into account the context in which it would be used . However, according to the students’ evaluations, technical implementation was not sufficiently mature or flexible because of the limited and rigid algorithms used.The use of chatbots as therapy tools or interactive diaries for patients was considered by the students to be a good opportunity to reduce anonymity, shyness and shame about disclosing personal and painful information. However, it was thought that doctor – patient communication could deteriorate as a result of non-verbal communication with a chatbot and interpersonal information may get lost. Thus, the first personal conversation between doctor and patient was considered indispensable.The students perceived the use of therapy chatbots in medicine as potentially supportive and complementary diagnostic tools that could be used independently by patients but did not understand them as a substitute for therapy. As an example, the students mentioned the possibility of technical errors or the risk of increasing social withdrawal in depressed persons due to the lack of personal contact. Therefore, human contact and empathy were considered essential for the success of therapy, which could be reduced by the use of chatbots.The participants enjoyed gaining a fundamental insight into the topic of chatbots and AI, which was completely new for some of them. In addition, the interactive design and hybrid format contributed to the positive evaluation of the course. In general, the students gained a new perspective on chatbots and their associated problems, as well as a basic understanding of how chatbots function, where they can be used and the effort involved in implementing them.In the context of digitalization in healthcare, applications that use AI are becoming increasingly important . This stMedical chatbots are an example of how artificial intelligence and technology are being integrated into healthcare. As such, it would be beneficial for medical students in Germany to learn about this technology as part of their medical curriculum. This will help ensure that they are well-equipped to work with and utilize medical chatbots in their future practice, in order to provide high-quality and efficient care to patients. Additionally, learning about medical chatbots would provide medical students with a better understanding of the role that technology plays in healthcare and how it is likely to continue to shape the medical profession in the future.This study revealed that the attitudes and expectations of medical students were generally optimistic about the use of AI and chatbots in relation to a variety of purposes in medicine, including in areas such as administration, research and diagnostic imaging techniques , Plot B.As other studies have demonstrated, it cannot be assumed that the generation of people who have grown up with digital technologies and are proficient in their use (similar to our cohort) are also aware of all the options and ethical consequences of the use of new technologies in their professional field. However, this is not synonymous with the simultaneous development of digital competencies in the professional field ,29. The While students saw a great deal of potential for the use of chatbots in medicine, they had many concerns about using them in areas that went beyond organizational activities such as making patient appointments. Above all, they believed that the technology was not yet sufficiently developed and that in the context of healthcare, patients needed a human counterpart. Neutral attitudes to chatbots were also evident from many statements in the questionnaire, which confirmed the thesis that there is not yet enough knowledge about the topic of AI in medicine for the study participants to have developed distinct opinions. In the questions about chatbots, in particular, which were repeated after the course, we could not identify any significant changes in attitudes. However, our study was able to give medical students, as non-computer scientists, a good initial overview of how a chatbot works, a basic understanding of how much data needs to be provided for an AI, and also potential future uses of AI in medicine and medical chatbots.The perceived challenges and concerns of students relating to the use of AI and chatbots in healthcare must be addressed and taken seriously before future physicians are exposed to such tools . AI is sAlthough the students were very interested in the topic of chatbots in medicine, and the topic of AI is also gaining increasing importance in medicine in general, the results of our study are limited in terms of representing the perspectives of the student population due to the small number of participants. Also, the course duration of three months was too short for sustainable changes in viewpoints or information gain to occur. However, the goal of this work was not to draw representative conclusions for all German medical students, but rather to understand the state of knowledge and perceptions of medical students regarding AI and chatbots in medicine, which we believe was achieved with our sample. The next step will be to investigate which AI competencies should be included in the curriculum.This study indicated that future physicians in Germany are willing to engage more intensively with AI in medicine. In our study, they were able to develop a basic understanding of how AI and chatbots will affect their future daily work. Although their basic attitude toward the use of clinical AI was positive, medical students also had concerns, especially with regard to the lack of data protection and declining personal contact with patients. With a view to future developments in the workplace, we can only emphasize once again how urgently medical curricula need to be supplemented with these new core competencies so that doctors can help to shape the technological course of patient treatment in an informed and self-confident manner.


In response to rapid population ageing, digital technology represents the greatest resource in supporting the implementation of active and healthy ageing principles at clinical and service levels. However, digital information platforms that deliver coordinated health and social care services for older people to cover their needs comprehensively and adequately are still not widespread. The present work is part of a project that focuses on creating a new personalised healthcare and social assistance model to enhance older people’s quality of life. This model aims to prevent acute events to favour the elderly staying healthy in their own home while reducing hospitalisations. In this context, the prompt identification of criticalities and vulnerabilities through ICT devices and services is crucial. According to the human-centred care vision, this paper proposes a decision-support algorithm for the automatic and patient-specific assignment of tailored sets of devices and local services based on adults’ health and social needs. This decision-support tool, which uses a tree-like model, contains conditional control statements. Using sequences of binary divisions drives the assignation of products and services to each user. Based on many predictive factors of frailty, the algorithm aims to be efficient and time-effective. This goal is achieved by adequately combining specific features, thresholds, and constraints related to the ICT devices and patients’ characteristics. The validation was carried out on 50 participants. To test the algorithm, its output was compared to clinicians’ decisions during the multidimensional evaluation. The algorithm reported a high sensitivity  and a lower specificity . Results highlight the preventive and protective behaviour of the algorithm. Throughout the world, every country is experiencing the population ageing phenomenon. This global transformation mainly concerns two counterposed effects: a significant increase in life expectancy and a rapid decrease in birth rate. Consequently, considerable changes in the age distribution of societies will occur. People aged 65 years and over are expected to live an additional 17–19 years from 2015 to 2050. The world will have a higher number of older adults than children. Elders will grow from 9% in 2019 to 16% in 2050 [Although longevity is undoubtedly one of the most remarkable successes in human history, physiological changes, including the loss of both intrinsic capacity and functional ability and the onset of chronic diseases, may occur with increasing age. Therefore, this demographic transformation will create challenges within the health and social care systems, causing economic and social implications. However, it will also allow modern societies to explore new healthy and active ageing strategies .Information and Communication Technology (ICT) may be crucial for implementing such an innovative approach, being the key enablers of digital tools supporting the health and social care sectors. Indeed, they can promote person-centred care and prevent or delay frailty conditions by improving quality of life, health, and well-being. Several ICT solutions and services have experimented with various settings. Some of these paradigms positively impact eldercare . SpecifiMOSAICO—Models, products, and services to make the life of frailty people socially active and inclusive in communities spread across the territory”. MOSAICO is an initiative that has received funding from the Ministry of Enterprises and Made in Italy (ex Ministry of Economic Development) and Marche Region under the grant agreement for innovation. The project aims to identify a new concept of assistance model and develop an innovative software platform (MOSAICO) to facilitate the design, management, and supervision of health and social services for the elderly. The MOSAICO system aims to enhance the quality of life of older people living in remote and low-density urbanisation areas of Central Italy, thanks to the adoption of personalised paths. The main objective is to prevent acute events, favour the elderly staying healthy at home while reducing hospitalisations, and make them active and independent in their countries. The second, but not less important objective, is to contrast the increasing depopulation phenomenon in the areas damaged by the earthquake in 2016. Those areas will be revitalised with improved and more accessible services.The present work is part of the Italian National Project called “For this purpose, local organisations and cooperatives are essential resources to be included in the project. They build a solid community-based network to support older people by addressing their specific needs. To meet the challenges posed by the ageing of the population, the project employs solutions entailing ICT that is driving the current digital transformation of health and well-being . Mobile and wearable devices embedded with sensors have a fundamental role in this new health monitoring concept , enhanciThe core of this interconnected digital framework for ageing is the MOSAICO platform. It is used  to collect patients’ clinical and social information acquired during the multidimensional screening phase of the project and from the ICT devices during the subsequent telemonitoring phase. The first phase consists of a wide-range assessment of the elderly, including motor-functional, cardiological, nutritional, psychological, and social domains. In the second phase, the patient is provided with a personalised set of products and services based on their characteristics and requirements. This software platform is not intended as a telemedicine system. However, it was designed to eventually interact with and complement one to extract relevant data while monitoring and self-monitoring the patient’s condition .The purpose of the work and its significance lie in the counteraction against the frailty condition of elders. Crucial is the prompt identification of criticalities and vulnerabilities and the promotion of active and healthy habits. This approach to preventing or at least delaying frailty progression fits into a more comprehensive framework that desires to positively impact the traditional care model of the National Health System . The goaIn this context, the present work aims to define and implement a decision-support algorithm that automatically assigns devices and services tailored to seniors’ clinical and social needs. Platform functionalities must be improved by including a logical method to identify the best health and social services model. This essential joining link between patient’s information and interventions would help professionals analyse the specific fragilities and contribute to carrying out a personalised path for elders. Importantly, technological solutions considered by the algorithm to improve self-sufficiency and awareness make it stand out among other studies focusing on integrated care programmes for the elderly . Thus, tThe proposed algorithm, implemented on the MOSAICO software platform, will make the product–service assignment more efficient and time-effective, thanks to the proper combination of specific features, thresholds, and constraints related to the ICT devices and patients’ characteristics. The adoption of a holistic approach is an indispensable condition for outlining a comprehensive profile of the patient. Conversely, the large amount of generated data may be challenging to manage; using an automatic decision-support tool becomes fundamental for proper patient-specific assignment.The case study was carried out on a target population of 50 participants recruited from the MOSAICO project. Data involved a combination of self-reported, sensor-, and questionnaire-based information from the multidimensional sessions of the screening to explore the multifactorial nature of the frailty condition. These input data were used to feed a decision tree algorithm designed to match the specific characteristics of the patient’s profile and their inclination to the technology, as well as the technical features of the devices, and to generate as output the best set of devices and social services for that patient. This combined care plan established by the algorithm aspires to detect early markers of physical and mental declines in older people and to reverse or delay them through appropriate monitoring and care. Validation results are promising and show high sensitivity in patient-specific matching.The present work aims to study and develop a decision-support algorithm to help clinicians find the best set of devices and services for older people based on their social and clinical needs. A personalised approach is fundamental to understanding the heterogeneous nature of the elderly population, which is characterised by high variability and numerous specificities and is influenced by complex factors, both intrinsic and extrinsic to the individual. Multidimensional assessment: elders’ health evaluation by a multidisciplinary staff of clinical and social operators. The multidimensional screening of elders’ health allows for gathering the information representing the knowledge base of the reasoning system to determine a course of action.Data preprocessing: this is a crucial phase to make the data available for algorithm development. Data are cleaned and coded in a standardised format according to the nature of the acquired variables.Algorithm development: this is a crucial step in the developed methodology since it refers to the logic behind the decision-support tool. It follows a decision tree approach showing the various outcomes from a series of decisions. The identification of products and services is based on the patient’s profile.Algorithm implementation: it describes the process of converting the decisional model into code. Visual Basic for Applications (VBA) was chosen as the programming language for its ease of use, which is indispensable in a preliminary study.Validation: evaluation of the reliability and consistency of the algorithm itself through a specific validation protocol applied to a sample of participants.The proposed methodology to develop the decision-support model is shown in In This section highlights the variables assumed as input to the developed matching algorithm.As a normal ageing process, the integrity and functionality of physiological systems reduce over time. The higher the biological age, the higher the probability of experiencing an adverse event such as falls or cardiovascular (CV) problems. Beyond non-modifiable risk factors , the presence of comorbidities , and polypharmacy, there are additional factors that can be modified to prevent such adverse events. Behavioural factors include lifestyle aspects that can improve life quality and reduce morbidity and mortality among older adults. Adequate physical activity, healthy nutritional habits, good sleep quality, quitting smoking, limiting alcohol consumption, and being aware of environmental hazards are essential for healthy ageing.Despite the most direct fall and CV factors involving the physical and clinical domains, issues are also related to psychological and social spheres. Indeed, the fear of falling can lead to loss of confidence, social isolation, and solitude, which are associated with a higher risk of falling , developBased on the main determinants for falls and cardiovascular events, the participants were evaluated through an extended multidimensional evaluation by a specialised team of clinical and social operators. Data on the global health of each individual were collected among several health domains  to outline a multidimensional health profile of the patient. Each health and social care professional expressed their epicrisis modulated by an interdisciplinary discussion. The screening of the frailty condition included face-to-face interviews for anamnestic information, validated questionnaires, and risk scales  to assesThe proposed decision algorithm aims to support clinicians in prescribing a health prevention strategy customised to the elders’ needs. The algorithm’s output is represented by the assignment of a personalised set of devices and services, chosen according to the elders’ clinical and social needs, arising from the multidimensional assessment. Technological devices are non-invasive and easy-to-use systems that provide continuous assistance to the patient at home and outside. They also monitor health status while improving social inclusion. The main focus is to prevent severe circumstances, such as a fall or acute events  by enhancing their lifestyle quality and monitoring the related vital signs.The technological devices were identified based on the type of monitoring , device , and user compliance during usage. The selected technologies can be adapted to the functional abilities of the elderly, being customisable in the interfaces and settings.Fall monitoring devices include an ambient sensor, a wearable smartwatch, and a pendant. Due to privacy issues, a radio frequency-based fall ambient detector was preferred. Indeed, optic sensors are perceived to violate privacy due to the feeling of being continuously observed . Older p®) is mounted on the wall or ceiling of the room. It uses a Wi-fi connection for 24/7 monitoring of the elderly. Falls are automatically detected by the system, which sends an SMS to the caregiver for prompt intervention, increasing the safety and well-being of the patient. This solution is suggested for those who spend time at home. Regardless, it is incompatible with the presence of cohabitants or house pets for the reasons mentioned above.Given that older adults falling occurs inside the house almost half of the time, the rooms at higher risk of falling are the kitchen (25%), the bedroom (22%), inner and outer stairs (20%), and the bathroom (13%) . Radiofr®, developing a wearable sensor as a necklace or attached to the belt. It is based on an accelerometer with customisable sensitivity able to automatically detect a fall and trigger an alert via phone call and SMS. It takes advantage of GPS technology to inform relatives and caregivers on the position coordinates of the elderly patient at any time through real-time geolocation. Security zones can also be set up that send a notification whenever the senior enters or exits them. Moreover, the device allows receiving and sending voice calls by pushing a big SOS button. Apple® provides a further solution through a smartwatch able to automatically detect a fall event and alert the emergency services for prompt intervention. When the watch detects an abrupt change in motion and stillness for about 30 s, it alerts the patient with a vibration on the wrist and an audible alarm. It displays an alert message so the person can tap the emergency SOS or reset the alarm if they are okay. This device is not limited to fall detection. Indeed, it has several functionalities for multiparametric monitoring. It is, thus, possible to use an ECG (series 4 and later) to find atrial fibrillation or rhythm alterations, measure heartbeats at rest or during physical activity, and measure the oxygen level in the blood through an infrared sensor (series 6).A different solution is provided by MICROTECNO® requires higher technological abilities from the patient. Moreover, it is not suggested for patients with prostheses in both hands, to not compromise the efficacy of the use of the device itself. It is also not recommended for those who present implanted cardiac devices, such as PMK or ICD, for safety reasons, because dangerous electrical interferences may be generated.Concerning the previous fall detection system, the use of an Apple Watch®), which consists of a mobile single- or six-lead ECG device for remote patient monitoring. Everywhere and anytime, this pocket electrocardiograph records ECG and heartbeat. ECG can be shared with the medical doctor to diagnose or manage cardiac anomalies. Even in this case, patients with both hands prostheses, as well as PMK or DFB implanted, are advised against the use of this device. Therefore, since slightly more complex operations are required to be performed with the KardiaMobile to obtain an ECG track, this kind of monitoring is suggested for patients with higher technological abilities.An alternative device to the smartwatch is the pocket-sized KardiaMobile  permits deep body composition analysis by keeping track of body weight, BMI, body fat, water percentages, skeletal muscle, fat-free body weight, muscle mass, bone mass, proteins, etc. Goals can be set, and progress can be tracked so that the patient can be monitored in their weight condition or adherence to a specific diet, for example.In contrast, the smart body scale (by Renpho®) can be used with dual functionality. On one side, as a communication device, it enables the elderly to remain in contact with their relatives and friends and the medical doctor. This device prevents social exclusion and may positively impact the psychological and emotional status of the patient. On the other side, it proposes games and activities for recreational function or cognitive improvement.Finally, the tablet device  engage the elderly in group activities with other peers. It favours social interaction, participation, and positive emotional and behavioural responses, improving the quality of life.A transport service is suggested for people with walking mobility problems or who are not car owners and would like to reach desired areas of interest.Finally, besides social services, there are also healthcare services related to follow-up visits for the investigation of specific conditions: neurological, nutritional , renal functionality, hearing, vision, and fall-related examinations.The decisional algorithm takes as inputs the previously described variables from the multidimensional assessment  and the selected product and services. As output, the algorithm produces a specific and personalised kit based on user needs.Data preprocessing is a crucial step for subsequent analysis. First, all data from the multidimensional assessment were classified as continuous and dichotomous variables. Continuous variables  were acquired as numerical values, whilst dichotomous variables  were coded in binary form as 0 or 1 based on the absence or the presence of the deficit, respectively. The algorithm was conceived as a decision tree. This decision-support tool, which uses a tree-like model, contains conditional control statements. Using sequences of binary divisions (dichotomy approach) drives the assignation of products and services (available for the study) to each user, depending on their clinical and social requirements.First, information, education, and communication are recommended to all. This premise of the algorithm consists in providing advice and interventions to increase trust and awareness about everyday risks indiscriminately to the whole target elderly population. Patients can be informed about the environmental and health risks of falls and the behaviours that should be adopted to prevent them. Moreover, this advice concerns cardiovascular prevention, nutritional and lifestyle habits, and, thus, periodic screening.Digital devices, with different functionalities and technological impacts depending on the particular ability of the patient;Social and healthcare services offered and suggested to the elderly to improve their well-being and quality of life in the specific needed area.Additionally, the algorithm contains different investigation areas that manage and integrate patient information, elaborate it, and produce a proper output for each patient. Conditions are tested, and other results are proposed to the patient depending on the response. As extensively described in In addition to input and output variables, boundary conditions are set in the decisional analysis to make the process more efficient. The patients are classified into two categories based on their predisposition and inclination to the technology. Suppose they are part of the “active” group, named class (A). In that case, they may be associated with high technological impact devices. In contrast, if they belong to the “passive” group, named class (B), they may be assigned to the low-technology, easy-to-use devices. Additionally, specific function features of the devices  are taken into account in the decision-support logic.A flowchart, a simple and intuitive graphical representation, has been employed to explain the decisional process at the base of the algorithm. The entire algorithm flowchart is available as ® cannot be provided, then the presence of PMK/DFB and prostheses in the hands is assessed. If they are absent, then the smartwatch or the wearable pendant is suggested based on the patient’s aptitude for technology (class (A) or (B)). Otherwise, the wearable pendant is provided in both cases . Then, the cardiological investigation area receives input from the fall risk evaluation data. In this way, if the patient has already been recommended a smartwatch for fall monitoring, it is confirmed whether cardiological monitoring is required (avoiding the assignation of another device).In this excerpt, the algorithm evaluates the fall risk. If the fall risk is low , the presence of eventual previous falls is investigated. If the patient has fallen, a follow-up visit is recommended. Otherwise, it is suggested that they perform volunteering activities to keep them healthy and active. A fall monitoring system is indicated if the fall risk is high. Other patient characteristics are investigated to define the best device fitting their need. The ambient fall sensor is indicated if the patient lives alone and does not have pets at home. Instead, if the patient lives with someone and the VayyarThe algorithm was implemented with Visual Basic for Applications, an event-driven programming language to record, create, and edit subroutines. VBA uses functions and objects to perform an automated set of operations. VBA was employed to exploit the advantages of simplicity and immediacy of being integrated into Microsoft Office Excel. Indeed, the MOSAICO software platform provides the patients’ database in Excel. Through VBA, the decisional workflow was converted into code interacting with the patients’ database through specific iterated logic. The decision-support logic was composed to be cautiously conservative in case of a lack of information. In this manner, the algorithm avoids the eventual dangerous lack of devices or services assignment. The programme keeps the patients’ data from an Excel sheet. It presents, as output, the assignment for each patient of the needed devices and services. A macro allows automatically running the code for each patient.The algorithm’s reliability concerning the user device/service matching was tested by statistical analysis in terms of sensitivity and specificity. These mathematical parameters describe, in general, the accuracy of a test in reporting the presence or absence of a determined condition. Additionally, they are standard methods to assess a diagnostic test’s accuracy, validity, and ability to accurately measure what it is meant to ,23.The test allows discriminating between four categories: (i) true positive (TP), (ii) false positive (FP), (iii) true negative (TN), and (iv) false negative (FN).The sensitivity (S) (true positive rate) and specificity (Sp) (true negative rate) can be calculated as respectively reported in Equations (1) and (2):In this work, the test is represented by the proposed algorithm. The condition assessed was the patient’s candidature (or not) for a fall or cardiac monitoring device and the neurological medical examination. This condition was tested against the clinical assessment to evaluate and validate the algorithm’s performance. The sensitivity indicates the probability of the algorithm correctly assigning a patient as eligible for a fall/cardiac monitoring device or the neurological visit if they require them, based on the clinician’s opinion. The specificity represents the probability of the algorithm assigning a candidate for a fall/cardiac device or neurological visit when the patient does not need any monitoring or a medical examination. False positives and negatives are computed to evaluate the algorithm misassignments .To validate the automatic decision-support algorithm, a sub-sample of fifty elderly patients from the study by  were enrThe target population, coming from twelve municipalities of the seismic crater areas of Central Italy, meets two inclusion criteria: having an age over 75 and being a grade I, II, or III according to the Rankin modified scale, which means a good-to-moderate level of autonomy. Additionally, it should be mentioned that comorbidities and pathologies to organs and systems  and joint prostheses or implanted cardiac devices are not exclusion criteria. The only exclusion criteria consist of the survival diagnosis of less than one year and severe cognitive impairment that would not guarantee adequate and reliable participation in the experimentation.The sample resulted in 16 males and 34 females, with a mean age of about 83. The data employed for the algorithm validation were collected during various sessions of multidimensional assessment by a multidisciplinary team of social and healthcare specialists within the MOSAICO project.Concerning the physical conditions, mean values show high performance in walking 3 m (TUG), low risk of falling (BBS), minimal dependence (MBI), and most-limited community (WHS). Regarding the psychological domain, participants had mild–moderate depression (GDS) and mild anxiety levels (Zung). Indeed, while anxiety prevails in the younger population, depression is predominant in the elderly. The mean values of the cognitive functional test were barely low (low performance for the corrected MMSE ≤ 24). The muscle mass was over the cutoff values both in males and females. The handgrip strength was over the cutoffs only for females, indicating that the overall muscle strength in men is reduced. Concerning the nutritional assessment, participants had a normal nutritional status (MNA).The algorithm validation results are presented in n = 50) requires fall monitoring, compared to the 50% proposed by the clinical evaluation. Matching assignation, which results when the algorithm’s output coincides with the clinician’s output, is reported in 78% of the cases. Non-matching assignations refer to two situations: the patients addressed to a fall monitoring device by the algorithm but not by the clinician (FP) and those who were not assigned candidates by the algorithm but assigned candidates by the clinician (FN).According to the algorithm definition, 68% of the target population , which means it does not miss needy patients. Medium specificity (60%) means that the algorithm is not highly performant in ruling out people who are not needy. Therefore, this second aspect should be improved.Regarding the cardiac assessment, 84% of the target population requires cardiac monitoring per the algorithm method. In comparison, the clinician proposed a 56% percentage. This corresponds to a matching assignation in 64% of the cases. Again, considering the rate of FN that contributes to the non-matching assignation, the number of people who would require cardiac monitoring but instead are ignored by the algorithm can be evaluated. The value is 4%, slightly higher for the fall monitoring assessment. Regardless, a meagre percentage indicates that the algorithm incorrectly classified only two patients.In this case, the sensitivity is again high (93%), which means the algorithm correctly identifies patients needing cardiac monitoring. However, the specificity is very low (27%) because many patients were addressed to cardiac tracking even if they did not need it.To take stock of these results, high sensitivity and low specificity values support the conclusion that the present algorithm adopts a more preventive and protective approach. It led to a higher percentages of patients assigned to fall or cardiac monitoring than that identified by the clinical evaluation. This conservative strategy, however, does not exclude and correctly permanently recognises needy patients, apart from very low percentages.Moreover, The assignation percentages referring to each specific device are reported in The wearable pendant  was given to 40% of the 68% of falls monitored. The smartwatch for cardiac monitoring was given to 68% of the cases out of the 84% of cardiac candidates observed. This finding is understandable since 80% of the patients belong to the passive class, which means a low predisposition to technology. In comparison, just 20% fall into the active category, indicating a greater inclination toward technology.Finally, significant percentages emerge from the smart scale (74%) and the smartphone assignations (76%). The latter means that patients would require an internet connection to use the assigned devices, but they do not have it (lack of Wi-fi and need for a smartphone as a hotspot).Significant percentage values  were recThe most needed visits  were carThis paper proposes a decision-support automatic algorithm to help clinicians find the best products and services tailored to elders’ social and clinical needs. Its multidimensional nature investigates multiple aspects of the elders’ health, not limited to the functional and mobility domain, for more accurate identification of their deficits. The product/service user matching aims to encourage elders to use digital devices to monitor their health status in a preventive way while taking advantage of social inclusion activities.Promoting proactive behaviour focused on preventing acute events rather than their treatment provides multiple benefits. Indeed, it can encourage awareness of the elders’ health status to preserve independent living or to improve their well-being. The National Health System could spare financial resources to promote reduced hospitalisation and better service quality. Finally, it is a step towards the digitalisation of society since using such technological devices involves elders, caregivers, and general practitioners.The algorithm presented in the paper was conceived as a decision tree. It drives the assignation of products and services to each user, depending on their clinical and social requirements. The products refer to digital devices with different functionalities and technological impacts depending on the particular ability of the patient. Social and healthcare services aim to improve elders’ well-being and quality of life in the specific needed area.The algorithm’s reliability concerning the user device/service matching was statistically evaluated over a sample of 50 users in terms of sensitivity and specificity. Its output was compared to clinicians’ decisions during the multidimensional evaluation to validate the algorithm. The algorithm reported a high sensitivity  and a lower specificity .This result highlights the preventive and protective behaviour of the algorithm. However, it misclassified a high percentage of patients as needy, contrasting with the clinicians’ assessment. Thus, to improve the algorithm’s reliability, a larger sample size should be considered. Moreover, 1-year monitoring of the study participants could validate the algorithm’s development procedure by assessing its efficacy in terms of non-worsening health status, early diagnosis of disease, and improved life quality. Future research could be devoted to developing an automatic software tool with enhanced accessibility, availability (based on a mobile app for Android/IOS smartphones), and usability .