Knowledge translation (KT) is an effective strategy that uses the best available research evidence to bring stakeholders together to develop solutions and improve public health policy-making. Despite progress, the process of deinstitutionalization in Brazil is still undergoing consolidation, and the changes and challenges that are involved in this process are complex and necessitate evidence-informed decision-making. Accordingly, this study used KT tools to support efforts that aim to improve the care that is available to deinstitutionalized people with severe mental disorders in Brazil.We used the Supporting Policy Relevant Reviews and Trials tools for evidence-informed health policymaking and followed eight steps: 1) capacity building; 2) identification of a priority policy issue within a Brazilian public health system; 3) meetings with policy-makers, researchers and stakeholders; 4) development of an evidence brief (EB) that addresses the problem of deinstitutionalization; 5) facilitating policy dialogue (PD); 6) the evaluation of the EB and PD; 7) post-dialogue mini-interviews; and 8) dissemination of the findings.Capacity building and meetings with key informants promoted awareness about the gap between research and practice. Local findings were used to define the problem and develop the EB. Twenty-four individuals  participated in the PD. They received the EB to subsidise their deliberations during the PD, which in turn were used to validate and improve the EB. The PD achieved the objective of promoting an exhaustive discussion about the problem and proposed options and improved communication and interaction among those who are involved in mental health care. The features of both the EB and PD were considered to be favorable and helpful.The KT strategy helped participants understand different perspectives and values, the interpersonal tensions that exist among those who are involved in the field of mental health, and the strategies that can bridge the gap between research and policy-making. The present findings suggest that PDs can influence practice by promoting greater engagement among stakeholders who formulate or revise mental health policies. Knowledge translation (KT) is a dynamic and interactive process that uses evidence to make decisions and take actions that can improve health outcomes and reduce health inequities, particularly in low- and middle-income countries (LMICs) .Overall, there are different complexities and barriers that impede the application of KT for public health action in LMICs: deficits in knowledge production, the application of the available knowledge, and the use of strategies that are based on the best available evidence . When reIn order to promote the appropriate use of scientific evidence in the development and implementation of public health policies, KT platforms such as the Evidence-informed Policy Network (EVIPNet), which is supported by the World Health Organization (WHO), have been established to support health policy-making in Africa, Asia, and the Americas . The maiKT platforms are change agents that have a positive impact on policy decisions, interest group interactions, and health systems . The useEvidence briefs should rely on the best available systematic reviews to delineate the important aspects of the issue in question. It must integrate global evidences and local knowledge to inform deliberations about health policies among policy-makers and stakeholders . Policy Since its inception in Brazil in 2007, EVIPINet has been focusing on promoting the use of scientific knowledge in the decision-making processes of the Brazilian Health System, the development of innovative strategies in health management, and the facilitation of technical cooperation regarding KT among the participant countries . The BraSeriema .Accordingly, in response to the need for and challenges in the promotion of evidence-informed health policy-making in the largest city in the state of São Paulo (Sorocaba), a working group was constituted at the University of Sorocaba in 2016. This team, which consisted of researchers, doctoral students, and health professionals, was denominated as The Seriema group aims to suggest and contribute to health initiatives and formulate evidence-based public policies. This group works collaboratively with the Health Department of Sorocaba, which oversees 48 additional cities in São Paulo that are together inhabited by more than three million individuals .This group seeks to design research studies in accordance with the needs of Brazilian policy-makers specially supporting deinstitutionalization in Brazil (mainly in region of Sorocaba).In the 1980s, the history of Brazilian mental health was marked by serious denunciations of mistreatment, lack of hygiene and care for patients with mental disorders who lived in psychiatric hospitals, mainly in the region of Sorocaba (São Paulo), Rio de Janeiro (Rio de Janeiro), and Barbacena (Minas Gerais) . Social Sorocaba has a population of approximately 671,186 inhabitants and a high human development index (0.8), and its economy is based on industries and commerce . The citThe Sorocaba region housed the largest mental asylum in the country (i.e. high number of psychiatric beds) . The sevDuring the second half of the 1990s, there were 72,514 psychiatric beds in the Brazilian public health sector. In Brazil, the number of beds had reduced to 52,962 in 2001; in 2014, there were 25,988 psychiatric beds across the 167 psychiatric hospitals that were located in the 116 municipalities of the 23 states . In 2014On the basis of the aforementioned census data, the federal, state, and municipal bodies signed an agreement that they would ensure the gradual deinstitutionalization of patients with mental disorders and the closure of the seven asylums in the region . HoweverIn October 2016, the Seriema organised the first workshop on evidence-based health policy during which the deinstitutionalization of patients with mental disorders was ascribed the highest priority among all other health policy-related issues. Subsequently, the State Health Department of the Sorocaba region contacted the Seriema group with the objective of signing a partnership and helping them formulate public policies that are related to deinstitutionalization. This represented an important opportunity to subsidise the policy and collaborate with the State Health Department. This allowed them to adapt their actions and strategies to improve the care of deinstitutionalized individuals with mental disorders in Sorocaba and the neighboring regions.Since the use of KT is one of the challenges that is currently faced by the health systems in LMICs, the present study investigated the means by which the care of deinstitutionalized individuals with severe mental disorders can be enhanced using KT tools.We used the SUPPORT Tools  for evidCapacity buildingThere was a need to conduct capacity building workshops that addressed evidence-informed policy-making and provided technical training on the use of SUPPORT tools for relevant stakeholders. Therefore, in 2016 and 2017, three workshops were conducted to provide training and raise awareness. In addition, there was the possibility of addressing topics of interest.Prioritizing and supporting evidence-informed policy-makingThe first step was to prioritise policy-related issues. The Seriema group provided a set of criteria that were to be used to select important topics, and it included questions about public perceptions and the impact of the problem  asylums provided inadequate services to their patients with mental disorders; (ii) there was immense pressure to shut down the seven psychiatric hospitals in the region; and (iii) important changes have been made to Brazilian mental health policies.Meetings with policy-makers researchers and stakeholdersA number of meetings were organised with policy-makers and stakeholders to clarify and define the problem, gather information about the status quo that could promote dialogue, and identify other key informants who could provide further insights.The development of a policy brief that addresses the problem of deinstitutionalizationOnce the issue of deinstitutionalization was prioritised, the focus was geared towards gathering a wide range of evidence on the various aspects of the issue. Therefore, a systematic review of literature was undertaken. First, a well-defined search strategy was used to retrieve relevant research articles from research databases. The search focused elements for policies that were related to the care of deinstitutionalized patients with mental disorders , equity, key implementation considerations, and role distribution.The evaluation of the evidence brief and policy dialogueThe evaluation of the evidence brief and the policy dialogue was based on an adapted version of Lavis (2009) . SpecifiPost-dialogue mini-interviewsDuring the policy dialogue, the stakeholders were invited to participate in a video-recorded interview. In this interview, they were required to describe the insights that they gained from the dialogue. For this purpose, we posed the following two questions: a) How did the policy dialogue change your perspective about the problem in question? and b) What actions should be taken to address the problem in question?Dissemination of the findingshttp://brasil.evipnet.org/), where it is currently available for free download by all who are interested. A summary of the evidence brief and the policy dialogue will also be made available. Further, the federal government will order 100 prints of the evidence brief.The evidence brief was uploaded to the EVIPNet-Brazil secretariat webpage  insufficient and fragile community care services to meet patient needs; (ii) unequal access to community care across the different regions of Brazil; (iii) insufficient funding and a lack of political resources; (iv) qualitative and quantitative human resource deficiencies; (v) a lack of intensive follow-up care; and (vi) the absence of integration and communication between services.All the participants agreed that it is necessary to expand and strengthen community care services for all Brazilians. Indeed, the process of deinstitutionalization did not progress in the same manner across different Brazilian regions. In some of them, such as region of Sorocaba , where the number of patients admitted to hospital beds was very high, the deinstitutionalization process exceeded the capacity of assimilation of services offered in community.Some participants observed that, despite progress, community care services are still precarious with regard to a wide range of issues . They noted that many professionals still retain an “asylum mentality,” and that there is insufficient communication among mental health professionals and services, and between the municipal, state, and federal governmental bodies. The participants contended that the lack of communication and continued education adversely affects the follow-up care and rehabilitation of patients with mental disorders.The participants expressed their concerns about the process of deinstitutionalization  and trans-institutionalization (i.e. the transfer of patients from asylums to other inappropriate institutions). Indeed, these can lead to social neglect and have profound repercussions for the community, such as increased rates of homelessness, incarceration, drug addiction , depression, suicide, and an overloading of emergency services. All participants agreed that deinstitutionalization requires efforts that extend beyond deinstitutionalization and trans-institutionalization. They also agreed that the “Ministry of Health must have a serious commitment to those patients who leave the psychiatric hospitals.”The participants contended that the issue of deinstitutionalization is also complicated by financial conflicts of interests that pertain to psychiatric hospitalizations. This suggests that there is a “mercantilization of life of an especially vulnerable population.” Finally, the participants also recognised that the health care that is available to deinstitutionalized individuals has significantly advanced across the years; however, the socio-cultural treatment of these individuals remains problematic.The five mutually non-exclusive options to address the problem of deinstitutionalization that was articulated in the evidence brief are presented in The deliberations that pertained to the options are summarised in the following sections.something that did not work in the past, which isolates and excludes.” At the same time that the policy dialogue was conducted, the national policy on mental health was being reformulated with a strong aim to reopen the psychiatric hospitals; evidently, many of the participants were aware of this. However, other participants understood this option more accurately and were in favor of such an approach because it entails the early discharge policy of psychiatric day hospitals. However, they suggested that the name of the option be changed to “Strengthening interventions for acute psychiatric episodes” in order to convey that this option endorses institutions that provide humane treatment to individuals who present with acute psychiatric episodes, and hospitalize briefly such individuals only when necessary.This option caused much polemic and controversy among the participants of the policy dialogue, possibly because of a misunderstanding of the option. A majority of the participants opposed this option because they considered traditional psychiatric hospitals to be regressive: “This option was wholeheartedly supported and endorsed by the participants. Further, a majority of the studies that were reviewed supported the effectiveness of this option. The Brazilian Health System does not offer psychoeducational programs. According to some of the participants, this may have been attributable to the preconceived notions that managers hold about mental health professionals. They also recommended the implementation of a few psychoeducational techniques.Only one of the systematic reviews  addresseModel that is similar to those of intensive case management are practiced in some communities in Brazil. Every participant considered this model to be extremely important to all Brazilian cities. However, several small towns do not comply with this model. Therefore, the participants highlighted the importance of expanding and strengthening this model.The participants underscored the importance of and challenges that are involved in implementing assisted living in such a manner that it does not result in trans-institutionalization.Two participants observed issues that pertained to the inadequacy of housing, infrastructure, and food, and the absence of leisure-time activities.Many participants agreed that cohabitating a space with individuals who differ in age, diagnosis, and the severity of the diagnosis facilitates social reintegration: “caring and helping each other are positive factors observed in their daily lives.”Eight and nine individuals out of the 24 participants completed the evaluation surveys for the evidence brief and policy dialogue, respectively. The response rate was low despite repeated attempts to administer the survey, and it can be attributed to time limitations and the busy lives that the participants led.Despite the low response rate, the average item scores were positive, and they ranged from 5.0 to 7.0 for the evidence brief evaluation survey. The features that received the highest ranking (i.e. very helpful) were as follows: employ a graded-entry format and use systematic and transparent methods to identify, select, and assess synthesized research evidence , and none of them were conducted in Brazil. This demonstrated a knowledge gap regarding mental health care in Brazil . This leFurthermore, our findings corroborate the gap between research and practice that has been observed in LMICs, as well as the difficulties and complexities that mental health care entails. Despite the global burden of mental disorders (e.g. disability and lower disability-adjusted life years), mental health is not a policy priority in LMICs . Mental Provide psychoeducational programs) was strongly supported by findings as well as the participants. On the other hand, option 1  was strongly opposed by a majority of the participants due to local findings; further, there were differences of opinion between international and local researches. Many of the participants were aware of the grave and inhumane treatment that patients with mental disorders had been subjected to in psychiatric hospitals in this region; they were also cognisant of the struggles that were required to shut down all the hospitals. The regulation of care with regard to crisis management and the treatment of acute episodes appear to be the most unclear albeit critical aspects of mental health care in Brazil  conceptualized the problem based on their rich practical experience, and they echoed a majority of the challenges that were already presented in the evidence brief. In other words, the policy dialogue deliberations validate the evidence brief . Thus, in Brazil .There is no KT strategy that is singularly effective across all contexts. Therefore, it is important to report about the context-specific utility of each strategy, so that they can be modified and utilised by other interested decision makers . In thisEvidence briefs and summaries of policy dialogues (i.e. products of KT) can be used in public health policy-making only if the local and federal authorities are receptive to such efforts; unfortunately, often not the case .Although the application of KT in public health policy-making is relatively new in LMCIs, the situation is changing. There is an increased use of evidence-informed policy frameworks  and an iThe present study was the first attempt to use KT tools to improve some aspects of mental health care in Brazil , which is a priority topic of regional and national importance. The policy dialogue brought together stakeholders who are involved in the process of deinstitutionalization , which enriched the deliberations and provided the participants with an opportunity to acquire new knowledge and learn from each other.The present study has a few limitations. A large part of the KT framework and the best evidence available were developed in high-income countries  that’s can bring indirectness evidence. Further, we could not examine budgetary impact because the studies did not present cost analyses. Additionally, some of the options that were identified were difficult to understand because they were articulated using obscure terminologies. The variability in the quality of the reviewed studies and the lack of information about the options that can be implemented are a few other limitations. The low response rate that was evidenced for the evidence brief and policy dialogue evaluation surveys was attributed to time limitations and the busy lives that our participants led; therefore, some of our results may be underestimated. Although we have conducted an exhaustive and in-depth discussion, some topics that pertained to implementation were not discussed due to the paucity of time. However, since some aspects of implementation vary across communities, they should be discussed in accordance with the conditions of each municipality.The KT process that was adopted was considered to be a useful means to discuss important policy issues, bring together policy-makers, health care providers, researchers, and representatives of civil society and public defense, enhance interaction and partnerships between evidence-producers and evidence-users, and promote the dissemination and application of global and local evidence in practice.The present study did not seek to examine causal relationships. Nevertheless, a longer study period will allow future researchers to capture the positive changes in mental health care that result from KT. Future investigations are required to understand whether and how evidence briefs and policy dialogue can be used to improve the care of deinstitutionalized people with severe mental disorders and their contributions to Brazilian mental health policy.Researchers and other stakeholders who are interested in using KT tools should consider the lessons that were learnt during the course of our study.LL conceptualized the study. IF, JB, LL designed the study. IF, SB, MC and LL led data collection, carried out the analysis and drafted the initial manuscript. All authors read  provided critical revision and approved the final manuscript.This article was funded by FAPESP grants 2017/20668-7 and EVIPNet Brazil/Ministry of Health SCON2017-02502.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The availability of both digital and traditional mental well-being interventions is rising, but these interventions typically do not consider people with intellectual disabilities as potential users.The study aimed to explore the acceptability and feasibility of a new digital intervention, developed with and for people with intellectual disabilities, to improve their subjective well-being.Using a single-group pre-post design, participants with intellectual disabilities and their caregivers completed the 4-week intervention. Mixed methods questionnaires assessed the acceptability of the intervention, in addition to self-report and proxy-report measures of subjective well-being and behavioral problems.P=.17) and for behavioral problems .A total of 12 men with mild to moderate intellectual disabilities enrolled in and completed the study alongside 8 caregivers. Participant acceptability of the intervention was high, and feedback covered multiple aspects of the intervention, including (1) program concept and design, (2) program content, and (3) intervention usage. Self-rated mood barometers indicated mood improvements for 5 participants, deteriorations for 2 participants, and no observed changes for the remaining participants. Statistical analyses yielded no difference from pretest  to posttest  for subjective well-being in people with intellectual disabilities (W=10.5; People with intellectual disabilities and their caregivers are receptive to using digital well-being interventions, and this research shows such interventions to be feasible in routine practice. Given the acceptability of the intervention, its potential efficacy can now be evaluated in people with intellectual disabilities and symptoms of reduced mental well-being. People with intellectual disabilities have an increased vulnerability for developing mental health problems, in part owing to the frequency of negative life events and experiences that are common in this population, for example, experiencing stigma, isolation, dependency on caregivers, and experiences of abuse -3. AlthoThere is comparably little research and clinical attention for this population, in spite of their vulnerability and the resulting high prevalence of mental disorders. In terms of treatment or intervention options, pharmacological therapies are available, but also frequently prescribed in the absence of diagnosed mental disorders . PsycholNew technologies present a range of applications that people with intellectual disabilities can benefit from, from mobile apps to improve problem-solving skills to virtual and augmented reality applications for social, vocational and self-determination skills -18. The A key challenge in delivering internet interventions to people with intellectual disabilities is the accessibility of such interventions. Barriers include economic factors related to the cost of computers and difficulties associated with potential cognitive and physical limitations . TurningTaking together the vulnerability of people with intellectual disabilities to experience mental health problems and the potential of digital interventions as an addition to traditional treatment interventions, this study presents an initiative to provide an accessible digital intervention to promote the mental well-being of people with mild to moderate intellectual disabilities. The driving objective is that successful mental health promotion might present an alternative and preventative strategy to improve the mental well-being of people with intellectual disabilities, in addition to or before the treatment of mental health problems through established pharmacological or psychotherapeutic interventions. To this extent, we set out to develop an intervention that fulfilled the following criteria:Including people with intellectual disabilities in the development and design phases of the intervention to ensure its accessibility and its acceptance by people with intellectual disabilities.Incorporating cognitive-behavioral components from evidence-based interventions.Adopting a resource-oriented approach which involves the caregivers and support workers to assist with the implementation of the intervention in daily life.Offering content that is personally relevant or can be customized.In this paper, we briefly described the development of the intervention and presented a small pilot study to explore its potential feasibility and practicality as well as gave a first indication of its potential efficacy.The intervention was intended to provide tips to improve the users’ psychological well-being. Program content was derived from existing empirically tested programs and included both psychoeducational, behavioral activation and cognitive restructuring components. An advisory group of people with and without intellectual disabilities was established to provide feedback during the development process.The intervention comprised 8 modules which covered the following topics: (1) participation, (2) being active, (3) friendships, (4) relaxation, (5) self-acceptance, (6) communication, (7) self-actualization, and (8) cognitive restructuring  was used to develop the intervention. The intervention was designed for use with 11.6-inch Odys Primo Win 12 2-in-1 tablet computers, which would be lent to the participants in the study. The images used within the intervention were either self-generated or license-free materials.Wohl, which references a German wordplay involving well-being. This poodle avatar explains how to navigate through the slides using the on-screen arrows and what users can expect from the program. This includes explaining symbols used throughout the program that introduce quizzes and discussions. Some quizzes prompt users to evaluate statements as helpful or unhelpful or good or bad, whereas in other quizzes users are given multiple-choice questions using drag-and-drop selection methods. Discussion slides present a question or statement that the user is encouraged to respond to or discuss together with their support worker. The main poodle avatar also provides an overview of his 8 animal friends, represented by 8 different animal avatars, that are associated with each module.The intervention was introduced and led by an animal avatar: a poodle named Overall, we aimed to minimize visual distractions by refraining from presenting a table of contents or navigation menu. To enhance user engagement, slides were animated where possible and were provided both on-screen text and a voice-over.An advisory group was established in collaboration with a local information technology workshop for people with and without disabilities or mental disorders. Flyers were distributed at the workshop to inform their users about our study. Workshop staff confirmed the time and date of the 4 planned consultations with users who expressed an interest. The consultations were held at 2-week intervals, with attendance varying between 4 and 7 participants, of which at least 3 presented with intellectual and developmental disabilities. We did not employ specific inclusion or exclusion criteria for people to attend the consultations. As these attendees were not participants in a research study, we did not routinely collect information regarding their sociodemographic characteristics, but all advisory group members were adults, with more men than women attending the consultations. During each session, the researchers presented drafts of the program modules and requested feedback regarding module content, design, accessibility, interactivity, and delivery. Changes, as a result of this feedback process, were presented at consecutive meetings for further evaluation and included changing font sizes, simplifying language, increasing and simplifying program interactivity, changes to program navigation options and page layout, and the use of supportive instead of corrective feedback in exercises. Feedback that was not incorporated for the pilot study because of limited resources included the provision of male and female voice-overs, more animations, and mutable background music.A more detailed description of the co-development process for the intervention is given by Vereenooghe and Westermann .People with intellectual disabilities and their support workers from 2 residential facilities in North Rhine-Westphalia, Germany, took part in the study. Both facilities provide services for children and young adults with intellectual and developmental disabilities. Support staff were informed about the study objectives and procedures and were asked to identify potential participants with intellectual disabilities among the residents whom they supported.We aimed for minimal exclusion criteria to reflect the heterogeneity found within the population of people with intellectual disabilities and only excluded participants who (1) had a diagnosis of autism spectrum disorders without intellectual disabilities and (2) people with severe or profound intellectual disabilities who might not be able to operate the tablets and engage with the program content. Details regarding participants’ level of intellectual disabilities was obtained by the participating support workers from the service users’ records.The sole inclusion criterion for support workers was the requirement of a minimum of 2 contact hours per week with the participant with intellectual disabilities to ensure both participants had sufficient time together to implement the intervention.A single-group pre-post design was used, with no control condition. Outcomes of mental well-being were assessed at pretest and posttest, in addition to mood barometers completed before each session. No follow-up data were obtained for this pilot study, for which recruitment took place from March 2018 to June 2018.Program evaluation questionnaires were completed at posttest to assess the acceptability of the intervention. Questions were derived from the Client Change Interview Schedule  as impleQuestions for participants with intellectual disabilities included “what in particular do you still remember about the intervention?” and “which aspects did you like?” Support workers’ questionnaires asked whether they had noticed any change in the well-being of the person with an intellectual disability. Their version also asked more explicitly to identify specific content they considered to be helpful or not and what negative and positive aspects they have kept in mind.The Personal Well-Being Index—Intellectual Disability (PWI-ID)  was tranParticipants also completed mood barometers before each session, using the same picture-based Likert scale as used with the PWI-ID. To this extent, they received assistance from their support worker.The Aberrant Behavior Checklist—Community (ABC-C) ,30 was uParticipants were instructed to complete 1 session per week, with a maximum of 2 sessions per week. Tablets containing the program were lent to the participating organizations so people had instant access to the devices. The intervention was implemented in the regular working time of the support workers. Support workers had a facilitating role, and the intervention was intended to be used by the person with an intellectual disability as its primary user. Support workers could provide both practical and content support, for example, regarding the use of the tablet computers , clarifying the content , and assisting with program demands .Ethical approval for this study was obtained from the Bielefeld University Ethics Committee. All participants received information about the study in easy-to-read language and provided written informed consent. Participants without the capacity to provide informed consent were not enrolled in the study.Responses from the feedback questionnaires regarding the acceptability of the intervention were analyzed using quantitative content analysis of qualitative data . First, Differences in pretest and posttest scores were analyzed in SPSS  using nonparametric 1-tailed Wilcoxon signed rank tests.Following eligibility checks and informed consent procedures, 12 pairs of participants completed baseline assessments . A totalNone of the enrolled participants, either people with intellectual disabilities or their support workers, dropped out during the study or withdrew their consent. The overall recruitment success (completed/informed) rates were 26% (12/46) for support workers and 80% (12/15) for people with intellectual disabilities . Owing tContent analysis of the program evaluation questionnaires was classified into 3 main areas: (1) program concept and design, (2) program content, and (3) intervention usage. Analysis of the positive and negative feedback, as shown in the quantitative content analysis in The use of animal avatars was liked by the majority of people with intellectual disabilities and support workers. The interactive design, with quizzes, and use of both images and videos were also positives of the program. Support workers valued the program as a user-appropriate concept based on its audiovisual approach, the use of repetition, encouragement and supportive feedback, and session length. Given the heterogeneity of people with intellectual disabilities in terms of cognitive and communicative abilities, some support workers also rated the intervention as either too childish or difficult with regard to language. By contrast, none of the participants with intellectual disabilities mentioned the program to be childish and instead were explicitly positive about the design of the intervention.The friendships, self-acceptance, and self-actualization modules were particularly well received by people with intellectual disabilities, as were specific tips to improve your well-being. Support workers approved the wide range of topics and the information regarding local service providers included in specific modules and also highlighted the need to provide more concrete and less abstract tips in the self-actualization module. They considered the content of the modules concerning maintaining friendships, being active, and relaxation as most helpful to the people they were supporting. Both user groups considered the communication module too difficult, which is likely because of the metaphor used to explain the different roles and aspects of good communication .Technical errors in the use of the program were a main hindrance for both people with intellectual disabilities and their support workers. This applied to navigation arrows that were considered too small and buttons or interactions which were inactive. Session length was appropriate, according to support workers, and implementation should be limited to 1 session per week.Overall satisfaction rates for the 4-week intervention were high. Participants with intellectual disabilities and support workers gave the program approval rates of 92% and 86%, respectively.The picture-based mood barometers for participants with intellectual disabilities administered before each session were converted to a 5-point Likert scale ranging from 0 to 4, with higher scores indicative of a better mood. Descriptive analysis showed improved moods for 5 participants and deteriorations for 2 participants . A totalP=.17). There was also a nonsignificant reduction in behavioral problems  as reported by support workers at pretest  and posttest .Finally, data from the program evaluation questionnaires showed that half of the support workers did not observe any changes in the behavior or well-being of the participants with intellectual disabilities. Other support workers did report an improved relationship with the participant with intellectual disabilities, as well as increased interests in daily activities associated with the program content .This pilot study shows that it is feasible to develop a digital psychoeducational intervention—with multiple brief sessions of interactive content—for use in routine practice. We also observed initial improvements in subjective well-being and reduced behavioral problems in some participants. Participants’ interest in the study and the absence of any dropouts further indicate that an evaluation of the intervention’s efficacy in a larger sample would be feasible.The participatory approach in developing the intervention together with people with and without intellectual disabilities or mental health problems was both necessary and valuable in the changes that were made to the program. User-driven changes sometimes contradicted universal design recommendations that were otherwise expected to improve the accessibility of digital materials . Their iKey limitations of this study are the lack of randomization procedures and follow-up measures as well as the small sample size. These were deliberate decisions as the main objective was not to statistically evaluate the intervention’s efficacy but to investigate, using a naturalistic study design, whether it would be acceptable and feasible to implement the proposed intervention in the weekly routine of people with intellectual disabilities, and whether the recruitment of people with intellectual disabilities for an interventions study would be feasible.The absence of any statistical effects of improved mood and behavior is also not surprising as we did not employ a threshold score on either of the outcome measures to select a sample where improvements in the mental well-being and behavioral problems were most desirable.We also noted that the 4-week duration of the study is likely to have been too short for participants to implement meaningful changes and to record their potential impact. Meanwhile, the quick succession of very brief modules on distinct topics did not allow for a comprehensive or thorough work-through for each module. Hence, participants may not have had sufficient time to explore and master the attitudes, knowledge, and skills related to each module. Although from a clinical perspective that would have been more useful, this study focused primarily on exploring whether such content could be delivered using a digital format. The brief modules in combination with the qualitative feedback, therefore, enabled us to identify which modules in particular could be considered more useful for expansion in the intervention’s further development.In spite of our efforts to recruit a representative sample, the final sample of people with intellectual disabilities was all male. It is not clear whether this reflected a bias by the support workers in identifying potentially interested participants, or an actual gender difference in interest to participate. Previous studies indicate, however, that technology use among people with intellectual disabilities is generally higher for adolescents and young adults aged below 30 years of age and for men ,33.The technical errors, as mentioned by the participants, were an additional negative aspect of the intervention. In spite of this, the overall approval ratings were nevertheless high.Finally, although no participants dropped out during the study, it is unclear to what extent they adhered to the intervention contents and completed the homework tasks as we did not collect any data on actual use of the intervention. Given that usage characteristics may not be the ideal means of assessing adherence for electronic health technologies , future The Pudelwohl intervention, in its content and design, most closely approaches a combination of the 2 intervention arms of the Beat It trial, behavioral activation and guided self-help, both of which led to patient improvement . Direct .Focusing on the digital components of our intervention, we found similar levels of acceptability to that of a website aimed at informing people with intellectual disabilities about good mental health .In terms of customizability and tailoring the intervention to individual participant needs, our intervention offers a compromise between a more rigid design of a website and the flexibility that can be offered in a face-to-face therapy, for example, by presenting options for local activities, giving participants the option to choose those tasks that are more relevant to them, and by involving support workers who could ensure program content was discussed in a way that was meaningful to the participant. However, it is not yet clear whether the acceptability and efficacy of individually tailored digital interventions is higher than that of standard packages .Self-acceptance, where participants were prompted to both say what they are good at and to reflect on questions such as my weaknesses are not failures, you can laugh about some mistakes, I should feel bad about my weaknesses, and my weaknesses are a part of me.Contributing to the intervention’s overall acceptability is our purposeful attempt to adapt all aspects of the intervention to the variable needs of people with intellectual disabilities. This includes incorporating all but one of the suggested adaptations to psychological therapies for people with intellectual disabilities, as put forward by Hurley et al . Use of Involving support workers is generally viewed favorably when planning or delivering psychological interventions to people with intellectual disabilities ,39,40. WWhen a decision is made to include support workers, either as active participants or in a supporting role, attention should also be directed to any potential effects of the intervention on the support worker and their relationship with the person with an intellectual disability. This could include changes in attitudes, knowledge, or skills, as well as the quality of the relationship, which was reported to have improved by some of the support workers in this study.Overall, and in spite of the methodological shortcomings of this pilot study, this study clearly shows that internet interventions to improve the mental well-being of people with intellectual disabilities are worth further exploring as an additional intervention or prevention strategy, alongside more traditional psychopharmacological and psychotherapeutic approaches. Involving people with intellectual disabilities in the design of the intervention and ensuring the involvement of support workers and personal relevance of the intervention contents were major contributors toward the acceptance and feasibility of this intervention. The higher interest and usage rates of digital technologies in young people with intellectual disabilities identify them as the likely initial target group for such interventions.


Alzheimer’s disease (AD) is a complex neurodegenerative disease involving a variety of pathogenic factors, and the etiology detection of this disease has been a major concern of researchers. Neuroimaging is a basic and important means to explore the problem. It is the main current scientific research direction for combining neuroimaging with other modal data to dig deep into the potential information of AD through the complementarities among multiple data points. Machine learning methods possess great potentiality and have reached some achievements in this research area. A few studies have proposed some solutions to the effects of multimodal data fusion, however, the overall analytical framework for data fusion and fusion result analysis has thus far been ignored. In this paper, we first put forward a novel multimodal data fusion method, and further present a new machine learning framework of data fusion, classification, feature selection, and disease-causing factor extraction. The real dataset of 37 AD patients and 35 normal controls (NC) with functional magnetic resonance imaging (fMRI) and genetic data was used to verify the effectiveness of the framework, which was more accurate in classification and optimal feature extraction than other methods. Furthermore, we revealed disease-causing brain regions and genes, such as the olfactory cortex, insula, posterior cingulate gyrus, lingual gyrus, CNTNAP2, LRP1B, FRMD4A, and DAB1. The results show that the machine learning framework could effectively perform multimodal data fusion analysis, providing new insights and perspectives for the diagnosis of Alzheimer’s disease. Alzheimer’s disease (AD) is an irreversible neuropsychiatric disorder, which often occurs in elderly and manifests clinically as memory deterioration, aphasia, social difficulties, and other symptoms . The morWith the rapid development of neuroimaging technology, MRI technology has provided powerful support in AD research and has become an indispensable tool . Since aMoreover, owing to the various reasons, there are a few credible public databases for Alzheimer’s disease with multiple modal data such as neuroimaging, genes, proteins, and others, resulting in a small amount of available data . In addiTo better address the above problems, this paper will study multimodal data of neuroimaging and gene data of Alzheimer’s disease, and design a complete framework to realize classification, feature extraction and disease-causing factor extraction. Specifically, we first designed the fusion scheme of neuroimaging and genetic data to construct fusion features, then proposed a multimodal random forest (MRF) method to distinguish AD from NC to extract optimal fusion features. We further extracted abnormal brain regions and genes based on the optimal features. Compared to other methods, our framework was able to extract fusion features with higher differentiation ability and obtained higher classification accuracy, providing good insight into the causes of Alzheimer’s disease and a new solution for the early diagnosis of this disease. The Materials and Methods describes the experimental data and the framework for data fusion, classification, feature extraction, and pathogenic factor extraction. The Results shows the results of the experiment and performance comparison. The Discussion discusses the experimental results and the Conclusion summarizes this study.http://adni.loni.usc.edu/) to appraise our presented framework, including 37 AD and 35 NC. The ADNI contains a variety of fMRI, structural MRI (sMRI), genetic data, etc. We selected the fMRI and genetic data of AD and NC, respectively, to implement our study. p > 0.05). This research was supported by multiple governmental organizations and each participant provided written informed consent.In this paper, we collected a total of 72 participants from the ADNI database  in a chip. In order to extract genetic data, we need to further process the SNPs that have been done for quality control. First, these SNPs are grouped in genes and the gene groups with SNPs above the threshold are kept to ensure experimental accuracy. To integrate with fMRI data, we segment the SNPs in each gene, which keeps the length of all gene sequences consistent. Then these gene sequences are digitally encoded, converting A to 1, T to 2, C to 3, and G to 4. For the fMRI data of each participant, we divide the brain image obtained by pre-processing into 90 brain regions using the AAL template. To match the genetic data, we cut the length of the time series for each brain region to equal the length of the gene sequence. After the two types of data are both processed, we use the Pearson correlation analysis to estimate the correlation between each brain region and each gene and regard the calculated correlation coefficients as fusion features. The data fusion method of each participant is the same as above, and we eventually obtain the fusion features of all participants.N samples and M fusion features in this study, then all samples are represented as {, , ,}, where yn is the classification label. The N samples and M fusion features are seen as the input of the MRF. In order to better train the MRF model, the sample set is divided into a training set and a testing set according to the partition ratio of 6:4, before constructing the MRF model. The detailed construction procedure is shown below. Initiatively, n samples and m fusion features are randomly selected to form a decision tree which is constructed using the classification and the regression tree (CART) algorithm. Subsequently, we set the number of decision trees in the MRF model to a. Finally, a decision trees are integrated to complete the construction of MRF.The multimodal random forest model is the core of the multimodal fusion analysis framework, which is aimed at analyzing multimodal data. Suppose there are Since the performance of the MRF model underlying different number of decision trees may be discrepant, we set the number to different values and selected the most suitable number to build the MRF model, ensuring optimal performance.Classification and feature extraction are two important applications of the MRF model. In this study, the MRF model is adopted for AD classification to validate the effect of multimodal data fusion. Because there are two groups of samples including AD and CN, we set the labels to “–1” and “+1”. The optimal MRF model is constructed by the above methods. We used the majority voting method to predict the sample label of the test set. When the test sample is used to assess the model, each base classifier will give a classification result. If the results of most base classifiers are “–1”, the prediction label is AD, otherwise, it is CN.m fusion features in each base classifier and sort the frequency of each fusion feature in descending order to select the first b fusion features for further analysis. The b fusion features are divided into several subsets with the number of features increased in turn, and the discrimination ability of each subset is evaluated by the MRF model. Eventually, the most discriminatory fusion feature subset is selected as the optimal fusion feature subset.When the optimal MRF model is built, the test set is reclassified to achieve the highest value of the classification accuracy. We count the Identifying abnormal brain regions and disease-causing genes is the ultimate goal of designing the multimodal data fusion analysis framework. The chosen optimal fusion features include two parts of the brain region and genes. More importantly, we extracted and analyzed the two parts separately. We counted the frequencies of the corresponding brain regions in the optimal fusion features. The higher the frequency is, the more influential the brain region is on the disease. Similarly, we also calculated the frequencies of genes. The higher the frequency is, the more strongly the gene is associated with the disease.With the aim of evaluating the performance of the MRF model, the classification accuracy is used as an evaluation index to determine whether the model can carry out accurate classification for multimodal data, as shown in formula (1).C represents the accuracy of MRF and T represents the total of the testing set. When the thi participant is predicted precisely, the value of is is 1, otherwise, it is 0.where Additionally, we further employed other conventional correlation analysis methods such as canonical correlation analysis (CCA) and correlation distance (CD) to calculate the correlation between the brain region and genes and combined these correlation analyses with other classification or feature extraction methods to form several frameworks. These frameworks are compared to the proposed multimodal fusion analysis framework and the comparison results are shown in part 4 of Section 3.Methods and Materials section, and the fusion feature matrix of 36×90 was formed. These fusion features were the initial input features used to construct the multimodal random forest.After data preprocessing, fMRI images of each sample were segmented into 90 brain regions, and 82400 SNPs were preserved in the genetic data. We grouped the remaining SNPs according to their corresponding gene and selected 36 groups with SNPs counts of more than 30. Next, the Pearson correlation coefficients between the 36 gene groups and 90 brain regions were calculated according to the feature construction approach mentioned in the The input features’ number of each decision tree in the random forest was 57, and these input features were randomly extracted from all the 3,240 fusion features. In the experiment, we found that the quantity of decision trees had a significant impact on the performance of the multimodal random forest. If the number of decision trees is too small, it is difficult to reflect the advantages of ensemble learning. If the number is too large, it will lead to greater similarity and redundancy between decision trees, which will also decrease the accuracy of the ensemble learner. Specifically, by testing different numbers of decision trees, the search interval of the optimal number was initially determined . We then took 10 as the search step, and the performances of multimodal random forests with different numbers of decision trees were evaluated. The result is exhibited in It is widely accepted that high classification accuracy is closely related to the validity of input features. A decision tree with high accuracy in a multimodal random forest provides a reference for extracting the most recognizable fusion features. More precisely, the top 100 decision trees with the best classification performance in the optimal multimodal random forest were retained, and the input features of these decision trees were counted. Next, with frequency as the criterion, we retained 400 high-frequency input features. Therefore, the search range of the most recognizable fusion feature was reduced from 3240 to 400 dimensions.Based on these 400 high-frequency features, we further searched the most effective feature subset. Initially, 400 high-frequency features were divided into 67 subsets according to frequency. The number of features in the subset increased gradually with the step size of 5, and the minimum number and the maximum number of features in subset were 70 and 400. Subsequently, we constructed a multimodal random forest to test the classification performances of different feature subsets using the methods mentioned above, and the results are shown in To verify the validity of the most recognizable fusion features, the multimodal random forest was compared with several other typical methods, and the specific results are shown in Additionally, we also compared the multimodal method with the unimodal method to verify the effectiveness of fusion features in classification see Figure 5After the above comparative experiments, we were confident that the most recognizable feature set extracted by our method was more reasonable. We split these fusion features and isolated specific brain regions and genes. If the brain region or gene appeared repeatedly in the most recognizable feature set, it means that the brain region or gene is closely related to AD. The abnormal brain regions and genes found in this study are shown in Exploring the etiologies of AD is a long-term challenge in brain science. Our work provides a scalable framework for this field. Unlike most previous studies on multimodal data fusion, most of them are limited to neuroimaging data , such asIn this study, a framework for multimodal data fusion analysis was constructed. As an important part of the framework, we evaluated various correlation analysis methods, including CCA and CD . The expOn the other hand, the multimodal random forest, based on fusion features, has more obvious advantages than the traditional single-modal method . For insMoreover, all participants are partitioned into the training set and the test set according to the partition ratio of 6:4. The training set is utilized to construct the multimodal random forest. The test set is utilized to measure the classification performance of the multimodal random forest. In the process of the MRF construction and measurement, the samples and features are randomly selected, which avoids over-optimization to a certain extent. In addition, the experimental results reveal that the multimodal random forest accomplishes well on the real dataset, therefore, there is no possibility of an over-optimized model.In this study, we extract brain regions and genes related to AD based on the most discriminative fusion features. These factors are validated from various perspectives in the following paragraphs.First, in the detection of abnormal brain areas, we found that the frequencies of some brain areas were significantly higher, such as olfactory cortex, insula, posterior cingulate gyrus and lingual gyrus, which meant that these brain areas played an important role in the progression of AD. Specifically, the olfactory cortex participates in the encoding of episodic memory in the brain .The olfaThe detection and analysis of AD risk genes are significant contributions of our paper. We found that some potential risk genes for AD included CNTNAP2, LRP1B, FRMD4A, and DAB1. The polymorphism in the CNTNAP2 gene has been found to take part in many aging diseases . The resThis study has made some progress in the multimodal fusion of brain science, but some limitations should be mentioned. We proposed the MRF model to classify AD and CN using the correlations between brain regions and genes and achieved satisfactory results. However, because the Pearson correlation analysis still possibly neglects subtle correlations, we will design a more appropriate correlation analysis method to construct fusion features in a follow-up study. On the other hand, although we detected the most discriminative fusion features, and proved that there is a certain correlation between brain region and gene, we still want to determine the specific pathways of different genes affecting the brain regions, and therefore still need to continue to invest a lot of energy in this research.Unlike previous classical unimodal brain science research, this paper attempts to carry out multimodal fusion research on AD based on fMRI and gene data. Our work first validates the potential of the associations between brain regions and genes in the accurate recognition of AD and proposes the fusion features of brain regions and genes. We then constructed a multimodal random forest according to the fusion features. The multimodal random forest and feature construction method are integrated into a comprehensive framework based on machine learning. With this framework, we have realized the efficient detection of AD patients, and located the pathological brain regions and potential risk genes of AD. Our research can provide references for precision medicine in AD.http://adni.loni.usc.edu/) database with no accession number(s).All data files are available from the ADNI  workgroup guidelines, Institutional Review Board (IRB). The study was approved by IRB of each participating site, including the Banner Alzheimer’s Institute, and was conducted in accordance with Federal Regulations, the Internal Conference on Harmonization (ICH), and Good Clinical Practices (GCP). Written informed consent was obtained from the individual(s), and minor(s)’ legal guardian/next of kin, for the publication of any potentially identifiable images or data included in this article.X-AB proposed the design of the work and revised it critically for important intellectual content. YL carried out the experiment for the work and drafted part of the work. RC and YW collected, interpreted the data and drafted part of the work. All the authors approved the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.This work was supported by the Hunan Provincial Science and Technology Project Foundation (2018TP1018), the National Science Foundation of China (No. 61502167).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.