Singapore is an international research hub, with an emphasis on translational clinical research. Despite growing evidence of the positive impact of public involvement (PPI) in research, it remains rare in Singapore.To investigate Singaporean public perspectives around the rationale, role and scope for being involved in health researchTo identify the potential, challenges, facilitators and strategies for implementing PPI in Singapore.Semi‐structured qualitative interviews with members of the public, analysed using thematic framework analysis.Twenty people participated. Four main themes emerged: potential benefits; challenges; facilitators; and strategies for implementation. Whilst initially unfamiliar with the concept, all interviewees recognized potential benefits for the research itself and those involved, including researchers. PPI was seen to offer opportunities for public empowerment and strengthening of relationships and understanding between the public, academics and health professionals, resulting in more impactful research. Challenges included a Singaporean culture of passive citizenship and an education system that inculcates deferential attitudes. Facilitators comprised demographic and cultural changes, including trends towards greater individual openness and community engagement. Implementation strategies included formal government policies promoting involvement and informal community‐based collaborative approaches.Given the socio‐political framework in Singapore, a community‐based approach has potential to address challenges to PPI and maximize impact. Careful consideration needs to be given to issues of resource and support to enable members of the public to engage in culturally sensitive and meaningful ways that will deliver research best placed to effectively address patient needs. A utilitarian argument has also been put forwardPPI can inform all aspects of research, from identifying and prioritizing questions through to design, data collection, analysis and dissemination. Patients have lived experiences of conditions and their treatments, and can comment on areas of uncertainty where research is needed. Patient input can thus help in asking patient‐focused questions and engaging other patients.1.2Shared ValuesFounded in 1965, Singapore has a culture that privileges the collective rather than the individual experience.Singapore is an international research hub,22.12.1.1Participants were identified in two ways: through (a) local community groups and (b) participants in a previous study,Out of 45 members of the public contacted by LLP, all of them replied and 20 agreed to be interviewed. Saturation was reached after 15 interviews, but we continued to 20 to ensure a solid representation of all age and demographic groups.2.1.2Data were collected through face‐to‐face semi‐structured interviews, designed to guide participants in reflecting on their experiences and views, and to enable them to produce their own narratives, privileging those issues most salient to them.The topic guide was informed by published literature on the scope and practice of PPI and was adapted iteratively to include emerging themes from the analysis. The initial version included participants’ personal background, their views on research and its relevance and impact, their own experiences of research and their understanding of PPI, including how it might be operationalized locally. These broad topic areas were expanded in subsequent topic guides to explore emerging themes, particularly the opportunities and challenges of PPI involvement within the context of Singaporean identity and education, how PPI could be operationalized at each of the different stages in the research cycle and supporting researchers wishing to include PPI in their research.Informed consent was obtained before the interview and confirmed again on completion. All interviews were audio‐recorded, transcribed verbatim, cleaned and anonymized before analysis. Data were stored securely in line with Nanyang Technological University's (NTU) requirements and the Personal Data Protection Act (2012).2.1.3A structured thematic analysisAnalysis started with familiarization with the data (Stage 1). An exploratory framework was adopted using applied thematic analysis, with coding occurring in distinct stages beginning with each case before moving to a cross‐case comparison and analysis (Stages 2‐3).To ensure reliability, a process of inter‐coder consensus was adopted (Stage 4), in which two of the authors (LLP and HES) independently coded a random selection of six transcripts before developing a coding framework which was applied to the remaining data by LLP. This codebook is a structured compendium of codes, providing the name of the code or theme, examples of source data and researchers' interpretive summary, providing an overview of how the codes are related to each other.’.Despite English being the language of education in Singapore, Singaporeans commonly use fractured, ungrammatical English, locally known as Singlish.Detailed reflexive notes, in the form of contact summaries,Analysis was iterative and concurrent with data collection,2.2At the time of this study, there were no frameworks for PPI in Singapore. This study was intended to engage with members of the public to explore their views as a first step in addressing that gap. It was itself an extended PPI consultation.33.1≥ 60, of whom four had been involved in designing a study to develop models of intergenerational support. Eleven people were Singaporean Chinese, four were Singaporean Indian, and three were Singaporean Malay. Four were retired, 15 were working, and one was a housewife  with an average age of 47 years (range 26‐71). Six people wereThe average interview lasted approximately one hour. The total amount of audio data was 19 hours. There was consistency in views between the perspectives of those who had previous experience of PPI (who shared their experiences) and those who had never been involved in research (who shared their expectations). The only difference between the two types of interviewees was that those with experience of involvement were able to give details of how that had operationalized in reality.3.2potential benefitschallengesfacilitatorsstrategies for implementation.Four main themes emerged from these interviews:Each of these themes is presented together with the sub‐themes that structure them using illustrative quotations. Unique identifiers include participant number, age, gender and ethnicity, with previous experience of involvement in health research indicated by yes or no (‘Y’/’N’).3.2.1All interviewees recognized the potential benefits of PPI. These were structured around three sub‐themes: positive impact on research, benefits for those involved and benefits for researchers. Whilst people identified a number of challenges around motivation to be involved, all described it as a worthwhile exercise.It will move us forward, because after all research is meant for everyone, and not just researchers’ (P17/56/M/Chinese/N).The first sub‐theme was rooted in a realization of the need for including the perspectives of those whom the research is intended to help, that is patients and the public: ‘You have to step into the community to do better research’ (P13/61/F/Chinese/Y). At a practical level, PPI was perceived as beneficial in all phases of research, from preparation of funding applications, through to data interpretation and implementation of evidence. Funding applications could be strengthened by ensuring that patient knowledge informed the questions and design: ‘If you have the inputs of the people on the ground, it will probably be beneficial to the funding application’ . It was anticipated that PPI could enrich the interpretation of data and help reduce bias attributable to seeing things only from the perspective of researchers, referred to as the ‘researcher's lens’ (P19/30/F/Indian/N). In terms of implementation, PPI was seen to have the potential to influence policy and service stakeholders who would be more responsive to recommendations from a study with public collaboration: ‘[The] general public, what they feel is very important for someone to implement something’ (P04/55/M/Chinese/N). In terms of meaningful public involvement, it was also considered that PPI had a role to play in ensuring the study design was such that participants felt valued and included, and thus would be more likely to engage fully: ‘I think people might give more instead of just being a passive participant’ .Linked to this was its potential to strengthen research through community engagement, as this participant with previous experience reflected: ‘(P08/29/M/Indian/N)Students, it's very clear cut. They [we] want credit. They want to be able to put it on their resume like; ‘I helped the researcher do that’. A bit of pocket money would definitely help. Linked to this more active participation, interviewees not only saw the potential for PPI to improve research, but also expected it to have an impact on themselves and others taking part. Within this theme, some generational differences emerged. Younger interviewees considered it an opportunity to improve professional prospects and gain extra income:[…] stimulate [your] mind, make [you] work and think. […] give you the opportunity to improve yourself […] more confident’ (P14/71/M/Chinese/Y). It could also provide experiential learning opportunities, developing new insights into the research process and the role of research in health: ‘A different way of looking at researchers [and through that] research can be very interesting’ (P11/60/F/Chinese/Y). However, the importance of providing practical resources to support involvement was also recognized, as highlighted by one interviewee, who was physically disabled:(P07/66/F/Indian/N)I [would] go with anybody, helping; talking about this, that, everything … If there was someone to bring me out, chitchat with me, [it] would make me happy also. The expectations on the part of older interviewees, however, centred more on self‐fulfilment and the hope that it would provide stimulation and opportunities to gain skills and knowledge, and increase self‐confidence: ‘(P08/29/M/Indian/N)It's easy to be caught up in your own circles, and it's not often that you see how what you do impacts the layperson. Beyond the more practical considerations of design and recruitment, participants also saw benefits of PPI for researchers, in its potential to enhance understanding of the impact of research on patients:(P06/32/F/Chinese/N)I don't know whether researchers have the luxury of the time to do it and even the skillset to do it [effective PPI]. There was also a recognition of the need for a change in attitudes amongst some researchers, with a sense that not all are prepared to involve the public in their work. This was seen to be linked to limited training and resources:[Researchers] do not know that these are the sorts of cultural issues […] involving people in the community helps […] being able to reach out to more people able to give you inputs that you do not have. However, they saw the development of such skills as having positive outcomes by enabling researchers to sensitively and appropriately work with diverse ethnic groups and with community members, to identify culturally specific issues and solutions:it may help to have a Singaporean around to help’ .This was seen as particularly important in the context of Singapore, which has a substantial number of non‐local researchers, for whom ‘3.2.2Despite the potential benefits of PPI identified, interviewees also mentioned potential challenges. However, no concerns were raised over potential individual harm or risk. The challenges consisted of three sub‐themes: pragmatic citizenship, the education system and deferential attitudes.They don't like to talk about things, they are more Asian culture. They just live their life’ (P03/32/M/Chinese/N).Interviewees described their compatriots as predominantly pragmatic and passive in terms of social and community engagement: ‘(P08/29/M/Indian/N)Singaporeans in general are apathetic about the issues of ethics, principles and conversations that go beyond bread‐and‐butter issues. This had broad implications in terms of how people engage with issues around individual and collective morality and social norms:For me, I’m quite pragmatic, so I’ll do it on a monetary [basis], unless I’m one of the patients’ (P03/32/M/Chinese/N), with a lack of time sometimes being used as an excuse: ‘I’m not sure if they are genuinely busy or if it's just an excuse’ (P19/30/F/Indian/N).Such pragmatism was rooted in practical issues that reflected attitudes to society and work which were felt to potentially deter people from PPI, particularly when there was no personal benefit: ‘Human to human interaction and relations are probably not as open as it would be in other countries’ .In terms of culture, it was considered that in Singapore, people are less open and transparent with each other than in other societies, with implications for meaningful involvement: ‘(P12/31/F/Chinese/N)Social circles tend to be very tight. It's very hard to get a Singaporean to open up [it is] the kiasu culture, then everyone is scared to lose face. This reserve was seen as a result of the need to avoid potential humiliation and thus an individual speaking out only when certain they are right. One participant expressed this in terms of a Chinese Hokkien term, ‘kiasu’, used colloquially in Singapore to refer to anxious, selfish behaviour characterized by a fear of ‘missing out’ or ‘losing out’.‘Our school system kind of teaches people the mechanics of education but discourages people to think independently’ (P17/56/M/Chinese/N), resulting in what a number of participants described as the ‘Asian mindset’ (P02/34/M/Chinese/N).Underpinning such a culture is the education system which participants considered generates high levels of literacy whilst producing students who are required to show respect and not challenge their teachers. Consequently, critical thinking is often poorly developed: ‘We have some kind of programme which allows the students to research, but […] it doesn't give them a real sense of what research is’ .Linked to this, the education system was not considered to give students an understanding of research: ‘The individual researcher's piece of work. It doesn't involve public. It's very personal. There's nothing public about it’ (P11/60/F/Chinese/Y), with the role of the public confined to passive participation and a means to an end: ‘[…] ‘the white mouse’. For what? They do a test. It's like guinea pig’ (P14/71/M/Chinese/Y).It was considered that this contributed to research being seen as the domain of researchers: A lot of Singaporeans think research is for people who are way up there. They have to have a very high pay; they have to be super smart and stuff like that. Linked to this notion of research being the domain of researchers only, the culture of deference embedded within the education system was seen to lead to assumptions and beliefs around the status of researchers that positioned them high in the social order:(P10/37/F/Caucasian/N)Sometimes they [participants] see researchers as, ‘oh, he is so educated, right? How can I share with him because I feel very small?’ […] they might not want to share with them because they don't want to lose face. The implications of such hierarchical positioning were intensified by the character trait of ‘saving face’ discussed above and were seen as a barrier to laypeople's genuine engagement with the research process:(P07/66/F/Indian/N)Because their qualification is very [high]… They study about it. So, we don't know about it, which is wrong, and which is right. What he [researcher] says, we follow. Such deference could result in an unquestioning position, which would limit the impact of involvement:3.2.3Despite these challenges, interviewees also highlighted characteristics of Singapore society that could facilitate involvement locally. These consisted of two sub‐themes: the ageing population and cultural change.Youngster just come out, so they know less than what the old people know’ (P07/66/F/Indian/N).Firstly, the rapidly ageing population was perceived as a potential catalyst for PPI adoption, particularly as the associated health‐care demands necessitate research focusing on innovations and interventions tailored to the needs of older people. The life‐experiences of older people were seen to provide an added dimension which could enrich research: ‘‘[PPI] is a way I can use to help myself. I find it useful, so I can use it to help others’ (P11/60/F/Chinese/Y).Interviewees considered the wish to help others as a strong motivation for older people. This was thought to be rooted in the ‘kampung spirit’,(P08/29/M/Indian/N)[Authorities] are making moves towards doing that [giving people a voice], but they should be more radical in it. Secondly, despite the cultural challenges, interviewees recognized Singaporean society is changing in ways that will create more opportunities for PPI, with people becoming less closed and wanting to contribute more at a community and societal level. They described increasing interactions amongst people from differing ethnic communities, and across age groups, and saw ways in which PPI could both be nurtured and further nurture these new relationships. This move to diversity and inclusion was observed amongst individuals and government:(P10/37/F/Caucasian/N)Because Singaporeans are very structured. People could [do] research a little bit better because they like to follow rules. Although hierarchical attitudes reinforced by the education system were seen as challenges, on the other hand the increasingly high level of education could mean people were better able to contribute to research. Furthermore, the emphasis on discipline and respect for authority was considered consistent with the systematic requirements of best research practice and thus facilitators for involvement:3.2.4During the interviews, participants drew on their past experiences of campaigns driving changes in health care to suggest both formal and informal strategies to realize PPI in Singapore. A frequently cited example was the recent government‐led initiative to address diabetes by involving communities and voluntary organizations‘That would make a whole world of difference and should be implemented right away’ (P17/56/M/Chinese/N). Such potentially ready engagement by the public was seen as a benefit of a style of government that emphasizes the collective rather than the individual: ‘Just one of the perks of being semi‐authoritarian in Singapore, because it works’ (P08/29/M/Indian/N).Interviewees discussed the potential to introduce policies to promote PPI which, given the culture of deference, most interviewees considered could be achieved by making it mandatory: (P17/56/M/Chinese/N)Sure, there are certain things that are purely medical that do not have huge political or social implication. Those are usually allowed, and the moment they have some level of social political impact, then they are very controlled. However, linked to this there was some concern that a top‐down approach would defeat the principle of empowerment inherent within PPI, particularly undermining the potential to identify research priorities, resulting in research questions that did not challenge existing policies and practices:(P15/64/F/Chinese/Y)[Study name], they are very good. They know the need, between the young people and the old people, and they use a very attractive way, a creative way of bringing us together. The young girl that partnered me, we are still in touch. She called me. I went out to lunch with her. At first, I talked one hour, [then] we talked for four hours. […] So, for me […] you're creative in helping the elderly to feel more confident to want to participate. Secondly, interviewees suggested various informal strategies to support PPI implementation, beginning with raising awareness. The role of the community was highlighted, with those with PPI experience recalling researchers effectively engaging and collaborating with community members, building trusting relationships to foster confidence amongst those involved:People who are interested to learn [could] sit down with researchers and whatever, and then they can volunteer’ (P06/32/F/Chinese/N).Personal contact with researchers in familiar environments, with opportunities to informally ask questions, was considered important ahead of making a decision as to whether or not to engage: ‘(P19/30/F/Indian/N)It sounds like a very scary thing. Rocket science. But, if you can break down to them, really, what research really is about, and how they can involve themselves…. As part of this rapport building, the importance of using lay terminology and avoiding highly technical explanations was highlighted, including being clear about the research aims, and the role and purpose of PPI in particular projects:(P17/56/M/Chinese/N)You have to start from the bottom up […] we are still Asian […] still quite collective at a certain level, even though we try to be individualistic. Interviewees identified the importance of emphasizing PPI as a shared collaboration between people, research communities and the government:should be a joint effort between the community, the research institutes and the government’ (P08/29/M/Indian/N).Indeed, most interviewees thought that promoting PPI ‘(P17/56/M/Chinese/N)If you are talking about lay people, then you should try everybody. You can start with [community] organisations. Finally, it was suggested that researchers could learn from community organizations that are already using bottom‐up strategies and inclusion to develop their understanding of community participation:(P10/37/F/Caucasian/N)You need to find the leaders. You need to go to communities that you see that are very active in their monthly gatherings. Those are the people that might be willing to help you do this. Such community groups were seen as an obvious means of identifying research advocates:(P15/64/F/Chinese/Y)This desire of getting to know each other […] Last time [before now] we just kept quiet, but now we interact here and there. So, there is this effort of wanting to know, to continue to maintain this harmony that we have. A community‐focused approach was also seen to be reflected in recent shifts to emphasize a shared identity, encouraged by government policy and supported by community initiatives:(P19/30/F/Indian/N)If an app could be created, social media is being used, like a cool, attractive one, or something, then you'd probably get the younger generation. Finally, it was considered important to develop a range of communication strategies to engage different populations and lifestyles. Such strategies should include social media and mobile applications:44.1Asian mindset’, because of social norms emphasizing a high degree of deference, an educational system resulting in high literacy and numeracy but low critical appraisal skills, and a society with a heavy emphasis on long‐working hours to the detriment of community involvement. Nonetheless, interviewees noted current cultural shifts which could facilitate PPI adoption, including the revival of a ‘kampung spirit’ with its emphasis on community support and inclusion. Participants identified formal and informal implementation strategies, including government policies and incentives and awareness‐raising campaigns at a community level.Findings from this study suggest that although laypeople in Singapore may be unfamiliar with the concept of PPI, once it was explained they recognized its potential benefits at both an individual and a societal level. PPI was thought to offer the potential to generate individual and collective empowerment and to build new relationships and trust between laypeople, academics and health professionals. Proposed challenges were seen as culturally rooted in the ‘However, PPI has been criticized for being dominated by top‐down and expert‐driven models4.2Nation before community and society above self’) and communities .Previous studies suggest that it is the structure of engagement that determines who gets involved, and to what outcome.Underpinning such a model is the need to educate researchers on the role and importance of PPI,4.3This is the first study to explore the perspectives of the Singaporean public on PPI, drawing on a range of views, from diverse ages and ethnic backgrounds. It identifies promising opportunities for PPI in an Asian setting, whilst also highlighting a number of challenges that are culturally specific. The findings from this study, including the supported group model, can be extrapolated internationally to multicultural societies where engaging ethnically diverse groups in research remains an ongoing challenge.A further strength of the study was the contribution of researcher reflexivity. The use of the contact summary forms, memo writing and discussions with the other authors encouraged further reflection. This process informed both data collection (refining the topic guide) and analysis. The study was undertaken as part of a doctoral research project by LLP, a non‐Singaporean. Initially, this led to concern that the public would be reluctant to share their views with someone perceived as an outsider. In fact, participants shared generously, often commenting that they felt less constrained talking to an outsider who might be better positioned to critically evaluate the situation in a way that a Singaporean might not. Consequently, being an outsider generated potentially richer data than might otherwise have been the case.In terms of limitations, this was a small exploratory study which showed no differences in attitudes across the ethnic groups included. More in‐depth exploration of attitudes across a diverse range of ethnic populations is needed in order to fully understand the potential for PPI in Asia.5Our study concludes that whilst unaware of the concept of PPI, participants recognized its potential to increase impact and improve implementation of research findings into health care, as well as having direct personal benefits for engaged individuals. Interviewees noted challenges specific to the local context, particularly hierarchical power relationships between professionals and the public. Facilitators included current demographics, cultural shifts and a tendency to comply with centralized initiatives, leaving room for both formal and informal PPI implementation strategies.Findings suggest the need for a ‘supported group model’ of involvement. Such a model offers opportunities for partnership and collaboration framed within the socio‐political context of Singapore, within which the principles of PPI resonate deeply with current community‐based initiatives from diverse stakeholders, including the government. However, given the lack of familiarity amongst the public of research generally, and PPI specifically, a combination of formal and informal strategies will be required to raise awareness of the unique contribution such involvement makes to research. More research is needed to understand the motivators and barriers to involvement amongst diverse ethnic populations in Singapore and in Asia, and to identify culturally sensitive solutions. Finally, careful consideration needs to be given to issues of resource and support, both educationally and practically, so as to enable members of the public to engage with researchers in meaningful ways that will deliver research best placed to improve patient outcomes.There was no financial support or other benefits from commercial sources for the work reported on in the manuscript, or any other financial interests that any of the authors may have, which could create a potential conflict of interest or the appearance of a conflict of interest with regard to the work.The study was reviewed and approved by the University's Internal Review Board, April 2018.


The World Health Organization’s International Classification of Functioning Disability and Health (ICF) conceptualizes disability not solely as a problem that resides in the individual, but as a health experience that occurs in a context. Word embeddings build on the idea that words that occur in similar contexts tend to have similar meanings. In spite of both sharing “context” as a key component, word embeddings have been scarcely applied in disability. In this work, we propose social media  to link them.The objective of our study is to train a model for generating word associations using a small dataset (a subreddit on disability) able to retrieve meaningful content. This content will be formally validated and applied to the discovery of related terms in the corpus of the disability subreddit that represent the physical, social, and attitudinal environment  of people with disabilities.Reddit data were collected from pushshift.io with the pushshiftr R package as a wrapper. A word2vec model was trained with the wordVectors R package using the disability subreddit comments, and a preliminary validation was performed using a subset of Mikolov analogies. We used Van Overschelde’s updated and expanded version of the Battig and Montague norms to perform a semantic categories test. Silhouette coefficients were calculated using cosine distance from the wordVectors R package. For each of the 5 ICF environmental factors (EF), we selected representative subcategories addressing different aspects of daily living (ADLs); then, for each subcategory, we identified specific terms extracted from their formal ICF definition and ran the word2vec model to generate their nearest semantic terms, validating the obtained nearest semantic terms using public evidence. Finally, we applied the model to a specific subcategory of an EF involved in a relevant use case in the field of rehabilitation.We analyzed 96,314 comments posted between February 2009 and December 2019, by 10,411 Redditors. We trained word2vec and identified more than 30 analogies . The semantic categorization test showed promising results over 60 categories; for example, s(A relative)=0.562, s(A sport)=0.475 provided remarkable explanations for low s values. We mapped the representative subcategories of all EF chapters and obtained the closest terms for each, which we confirmed with publications. This allowed immediate access (≤ 2 seconds) to the terms related to ADLs, ranging from apps “to know accessibility before you go” to adapted sports (boccia). For example, for the support and relationships EF subcategory, the closest term discovered by our model was “resilience,” recently regarded as a key feature of rehabilitation, not yet having one unified definition. Our model discovered 10 closest terms, which we validated with publications, contributing to the “resilience” definition.This study opens up interesting opportunities for the exploration and discovery of the use of a word2vec model that has been trained with a small disability dataset, leading to immediate, accurate, and often unknown  terms related to ADLs within the ICF framework. Natural Language Processing (NLP) is increasingly being integrated into several application domains. Google AI recently introduced BERT   to matchWords that occur in similar contexts tend to have similar meanings. This was likely first formulated in 1954 by Harris . But theOne of the strongest trends in NLP at the moment is the use of word embeddings, which are vectors whose relative similarities correlate with semantic similarity, building on the ideas of Harris and Firth.context  because it is obtained for category “38. A non-alcoholic beverage.” This is because water is the first term in category 38 and is included in the mean distance calculation for b(i), (distance=0), but it is not included in the calculation of a(i) because the term i is not included in any calculation of a(i)  . The sams(i)=-0.645, for i=tuna in the “52. A fish” category (b(i) is remarkably lower because the distances to category “43. A vegetable” are lower for all words in the category. This means that our model finds a closer relation between, for example, broccoli or lettuce with tuna  than between tuna and shark, bass, beta, or cod, which are very difficult to relate only to fish names.It is important to note the lowest silhouette we obtained, category . In thisIn spite of obtaining some low silhouette codes, the detailed analysis led to promising results. The first terms for e1100, fruits and vegetables (veggie), have been extensively reported to be related to LDL (low-density lipoprotein) cholesterol , as wellgluten as the closest result, followed by mitochondrial , increases nearly twofold in patients with CD, as reported by Gajulapalli et al ; we obtained ca et al ). The prli et al .Ungprasert et al  demonstrIn relation to e1101 (drugs) cannabis, there is an increasing interest in the medical use of it  .In relation to assistive products , several state-of-the-art solutions were retrieved, such as Speechify, Zoomtext, Voiceover, Siri, Dragon, and Alexa.lightest or reclining, as well as top product providers . For indoor transportation, the closest terms were hoist, stow, and hoyer, as opposed to powerchair, which was retrieved for outdoors.In relation to e120, mobility transportation, desirable properties for outdoor transportation were retrieved, such as uber, lyft, and paratransit. It is important to remark that Uber [We then explored transportation services (taxi+wheelchair), and the closest terms were hat Uber  and Lyfthat Uber .kayaking or archery. Another close term was boccia, which is another (but perhaps less popular) Paralympic sport [In relation to e140, culture recreation and sport, several paralympic well-known ports emerged, such as ableroad [wheelmap [Finally, in relation to e1501, outdoor wayfinding, the wheelchair+app operation retrieved ableroad  and wheewheelmap  as closeresilience. Resilience has been recently regarded as a key feature of rehabilitation and living life well following a disability [As shown in sability . Evidencsability .It is unclear how well resilience or strategies to cultivate resilience are currently promoted as a component of rehabilitation programs. Furthermore, it does not yet have one unified definition, and research scholars have not decided on one specific understanding of what resilience means. Understanding resilience is an important component of building resilience .Maturity, compassion, anger, resentment, grief, insecurity, contentment, and resenting were identified by our model as the closest terms to resilience. Resilience and maturity have been extensively reported on . The pres et al . As repoes et al , the inaes et al .As noted by Howard and Meichenbaum , resentmAs was presented in the EU Social Insecurities and Resilience Report , people In this paper, we proposed social media as the link between word embeddings and the ICF’s environmental factors in a General Public License (GPL) framework (R-3.5.1). We applied a set of publicly available R libraries for collecting, model training, and analyzing Reddit public data. We trained a word2vec model using a small dataset and obtained encouraging results in king-queen–type analogies. Further, we obtained remarkable results in a standardized semantic categorization test. When mapping the discovered closest terms to representative subcategories of all ICF environmental factors, we verified them with scientific publications.resilience) and how expansive we want the explored space to be.The obtained results open up interesting opportunities for exploration. Similarity isn’t just a way of finding the nearest words; it is also a way of extracting items of a single class in every environmental factor that makes up the physical, social, and attitudinal environment in which people live and conduct their lives, ranging from apps ”to know accessibility before you go“ to adapted sports (boccia). Therefore, it can be thought of as a form of topic modeling; however, rather than letting the algorithm choose a fixed number of topics, it gives us the option of choosing the specific term  because, in this study, we follow the approach of studying disability in general (instead of any specific group or etiology), an approach also adopted in other recent literature reviews . In addFurthermore, including only 93,614 comments allowed us to verify our hypotheses.We did not include submissions in our analysis; we collected them , but we did not use them for model training because only 2745 of them were labeled as “questions” while 1256 were labeled “articles and news,” 438 of them were labeled “videos,” and 13,570 were not labeled.As presented in Other relevant limitations to our study are related to the geographic location, spatial trajectory, or the time of day on which a comment was posted. As noted by Padilla et al  and GoreIn medical applications, word2vec has recently been applied to larger datasets, such as 641,279 French health-related documents produced in a professional context , 880,16Reddit has recently been used as a data source for studies in chronic diseases, such as Foufi et al’s  analysisIn a small corpus  using a semantic categorization test, word2vec was applied in analyzing and disambiguating the content of dreams ; this reFacebook groups, discussion forums, and chat rooms were recently analyzed  to explohear+association+kid, we obtained depaul as one of the closest results. The DePaul School for Hearing and Speech teaches children who are deaf or hard of hearing to listen and speak without sign language [saskatoon, a new early learning pilot program in Saskatoon that impacts preschoolers who are deaf or hard of hearing by breaking down communication barriers [Our approach is completely different in that we provide a tool for discovering terms of interest . For example, regarding e5 services and associations, in using the 3 terms language . Anotherbarriers .Therefore, it can be addressed to a wide variety of involved stakeholders besides people with disabilities themselves, such as informal caregivers, health care professionals, and private or public associations.This study explored the ability of word2vec to extract the main factors affecting the lives of people with disabilities within the ICF framework from a small dataset, showing promising results.Our results open up interesting opportunities for exploration and discovery. Similarity is revealed as not only a way of finding the nearest words but also a way of extracting out items related to specific elements. Therefore, it can be thought of as a form of topic modeling, where users can focus on a particular term in-breath or in-depth.


Despite the body of evidence on heterosexual men’s inequitable access to HIV prevention, testing and antiretroviral therapy (ART) , 2, and problem (i.e. transmitting HIV), and the health outcomes of women and children have been prioritized [The gendered nature of health services in SSA has been well described , 4, 6, 7oritized . Consequoritized , 3, 10. A successful HIV response requires a shift from portraying men as the “problem” to acknowledging that, like women, men are vulnerable to HIV infection due to individual, social and structural drivers. We recently undertook a study in a peri‐urban region of KwaZulu‐Natal province of South Africa, an area where high levels of poverty, unemployment and alcohol consumption co‐exist alongside high HIV prevalence rates. A total of 6993 men participated in male‐focused community‐based HIV and non‐communicable diseases screening from August 2017 to June 2019. In contrast to widely cited generalizations about men’s poorer health‐seeking behaviour, we found that men were concerned about their own and their families’ health. Out of 6988 men who consented to HIV screening, 6740 (97%) gave consent for an HIV test [Our work confirms that men, like women, are not a homogenous group. The 2017 South African National HIV Prevalence, Incidence, Behaviour and Communication Survey found that age, race, education, employment and locality type were all significant predictors of new HIV infection among men aged 15 years and older . Thus, lThe news is not all bleak, however. Recently, there is some sense that the narrative has shifted. International agencies such as UNAIDS, the World Health Organization and PEPFAR have an increased focus on men and HIV. Some countries have developed, or are formulating, national strategic plans on men and HIV . Using DThe landmark IAS Forum on Men and HIV prior to the 10th IAS Conference in Mexico represented a turning point in challenging the prevailing discourse on men. Building on the momentum created by the Forum, it is time to reframe the approach to heterosexual men in the HIV epidemic. Men and women should not be seen as competing populations. Like women, men have the right to health, HIV care and treatment, and their poorer access to HIV care cannot be reduced to individual behaviour. HIV interventions for both men and women must be guided by evidence. We need to watch our language: no more “men as a problem” or “men as the vectors”. HIV interventions should improve heterosexual men’s health for their own sake, not only to improve outcomes for women and children. Future HIV/AIDS conferences must include heterosexual men as a vulnerable population. In getting the frame right in the way we view men, we have the chance to address the biggest gap in the response to HIV in SSA.The authors declare that they have no competing interests.TM conceptualized and drafted the paper, HvR provided comments and edits, MC provided guidance on the key messages and edited drafts. All authors approved the final version.AIDS, Acquired immunodeficiency syndrome; ART, Antiretroviral therapy; HIV, Human immunodeficiency virus; SSA, sub‐Saharan Africa.


Mental health Step-up, Step-down services (SUSD), also known as subacute services or Prevention and Recovery Services, have emerged to fill an identified gap between hospital-based inpatient care and clinical community-based mental health support. Evidence for the effectiveness of the SUSD service model is limited but growing. Accordingly, this study looked to add to the extant body of knowledge, by (i) assessing change outcomes in mental health and wellbeing, and predictors of these changes, for patients who accessed Western Australia’s first SUSD service; and (ii) evaluating patients’ satisfaction with service, and what patients value from their stay.This was a mixed-method retrospective cohort study. Participants comprised 382 patients who accessed a 22-bed Mental Health SUSD facility and incurred 551 episodes of care during the 01/07/2014–30/06/2016 period. Patients’ change outcomes in psychological distress, general self-efficacy, and work and social adjustment from service entry to service exit were analyzed using generalized linear modeling. Simple Pearson’s correlation coefficients were calculated for preliminary assessment of the associations between patients’ service satisfaction and their change outcomes. Qualitative outcomes that patients valued from their stay were analyzed thematically according to a semi-grounded theoretical approach.p < 0.0001). A strong and persistent baseline effect existed across the three measures. Older age, female gender, and having a dependent child in the same household were protective/enhancing factors for the patients’ recovery. Satisfaction with service was high. Patients valued having the time and space to recuperate, gain insight, focus, and create changes in their lives.Significant improvements were observed in patients’ self-reported psychological distress, self-efficacy, and work and social adjustment (all The encouraging findings, regarding both patients’ change outcomes and satisfaction with service, support the value of the SUSD service model for patients with mental illnesses. Strengths and limitations were discussed; ensued recommendations were offered to both service providers and researchers to enhance the robustness of future research findings, to help inform more effective policy and funding decisions related to mental health care. Mental health policy in Australia is undergoing reform to deliver a stepped care approach, to ultimately see people receiving supports matched to their level of need; that is, the right level of the right type of clinical care is received at the right time . This reThe Australian literature on the SUSD model is currently limited but growing. Existing studies have described aspects of the model as applied in different service settings such as location, capacity, goals and parameters, service usage demographics and service approach and program activities –9. In adIn the historic and international context, the SUSD model can be said to have evolved from the movement of ‘deinstutionalization’ beginning several decades ago in countries such as the United Kingdom (UK) and the United States (US) . In the At the more fundamental level, outcomes for the service users, referred to as patients henceforth, which purportedly are a key driver for the birth of this type of models, have been variably assessed using different measures, with mixed rationales. Examples of the measures used in relevant studies thus far include: the Mental Health Recovery Star , HealtThis lack of clarity in choice and rationale of outcome measures used in evaluating the SUSD service model is understandable, given the relatively new and unique position of this type of model, compared with the more traditional, or more established care models in the acute hospital setting, or the day-visit community setting , 19. ThaThere is also a case for pitching service outcome goals and measurement instrument design to ‘what is wanted’ in terms of quality of life and wellbeing outcomes that go beyond the absence of illness –25. ExplTaken together, while there is a small and growing volume of early research suggesting the value of the SUSD model, it is clear that substantial further research is needed to shed more light on the diverse facets of its effectiveness. Meaningful assessment of the model’s effectiveness can be realized via the adoption and/or development of measures of change or recovery that are relevant or salient to the patients, as well as informative to both the service providers and the health system collectively. In this light, the current study is set out to primarily assess change outcomes in mental health and wellbeing for a cohort of patients who accessed Western Australia’s Joondalup SUSD service, which is the first of its kind in this Australian state. At set-up, the service administrators conceptualized the Joondalup SUSD as being a setting where people make recovery gains that are assisted by the development of skills and confidence to self-manage upon return to home.Recovery in this SUSD context is defined by “a deeply personal, unique process of changing one’s attitudes, values, feelings, goals, skills and/or roles” , and “thThis was a retrospective cohort study, with mixed methods for data collection and analysis. The main part of the study, on patients’ change outcomes, utilized a simple pre-post design (with data collected at both service entry and exit) and quantitative data analysis. The secondary component of the study has a cross-sectional design, where data on patients’ satisfaction with, and perception of, the service, were collected only at service exit. This secondary component involved both quantitative and qualitative data analyses.The 22-bed facility, Neami Joondalup Mental Health Step-Up Step-Down service (JMHSS), is run by Neami National, a not-for-profit community mental health service supporting people with mental illness “to improve their wellbeing, live independently and pursue a fulfilling life” . Neami aParticipants were patients with mental health issues who accessed JMHSS service any time during the period from 1 July 2014 to 30 June 2016 inclusive. Patients’ data were routinely collected by the service provider JMHSS  at service entry and exit. Patients may choose, or refuse, to provide the data in question. Patients are aware that Neami National may use the data for research and/or service evaluation and improvement purposes, provided that the data are anonymized in reporting and dissemination. In the specific context of this study, relevant patients’ data were made available in de-identified format to the first author, an independent researcher external to Neami National, for analysis.Patients accessing the JMHSS service were requested, but not obligated, to complete self-report measures of their state of health and functioning , in addition to providing their contact and demographic details. The K-10 consists of 10 questions, with each rated from 1 to 5 in order of increasing frequency of a particular (negative) feeling; thus a person may score as low as 10  or as high as 50 (most distress). The GSES also has 10 items, with each rated from 1 to 4; hence total scores may range from 10 to 40, with higher scores indicating high self-efficacy. The WSAS has 5 items, with each rated from 0  to 8 (severe impairment), yielding a maximal possible range of 0 to 40 for total scores. All three scales K-10, GSES, and WSAS have been validated widely in other mental health service settings –34). In . In 34])Outcome measures were score changes in K-10, GSES, and WSAS – from service entry to service exit, and patients’ satisfaction with service upon exit. Score changes were defined as “score at exit minus score at entry”. It is noted that scales K-10 and WSAS measure ‘undesired’ constructs, namely psychological distress and work and social impairments. As such, a negative score change on K-10 or WSAS  is desired. The GSES, on the other hand, measures self-efficacy, a ‘desired’ construct. Therefore, a positive score change on GSES  is desired.First, the study cohort was described using descriptive statistics: mean and standard deviation for continuous measures, and frequency and percentage for categorical measures. Descriptions involved demographic, clinical, and systemic characteristics. Demographic characteristics included age, gender, socio-economic indexes for areas , countSecond, for the primary aim, among those who had ‘paired’ data , change outcome measures were tested for statistical significance using paired t-test. Magnitude of change was also expressed as percentage of change relative to baseline for added context. Statistical predictivity of patients’ characteristics in change outcomes was assessed using generalized linear modelling, given the response variable being continuous. For the secondary aim, among patients who completed an Exit Questionnaire, their satisfaction with service was profiled using descriptive statistics and column charts. Simple Pearson’s correlation coefficients were also calculated for preliminary assessment of the associations between patients’ service satisfaction and their change outcomes. Where relevant, these associations were investigated further using generalized linear modelling.As the outcome measures were available and relevant at the episode level, all the main analyses were conducted at the episode level accordingly. The only exception was the profiling/ characterization of the patient cohort  which was carried out at the (unique) patient level; this was consistent with Neami National’s data management practice where the patient’s characteristics at the most recent service episode were allowed to override those recorded for their earlier episode(s), should they have incurred multiple episodes. Quantitative data analyses were conducted in SAS , version 9.3. Statistical significance was set at α = 0.05; hence 95% Confidence Intervals (CIs) were presented in conjunction with estimates where appropriate.Qualitative data on what patients valued about their JMHSS stays – used interchangeably ‘valued outcomes’ henceforth – were analyzed thematically according to a semi-grounded theoretical process as illustrated by Braun and Clarke (2006). The qualitative analysis process involved firstly a collective familiarity with all the response statements to the question ‘what was valuable to your stay?’ at service exit. This informed the nature of the enquiry which was to understand the type of personally valued outcomes that patients experienced as a result of their stay at the JMHSS, and to understand how these outcomes were facilitated. Secondly, the response statements were broken into smaller response units. For example the response “I learnt a lot about myself and seem to have got my medications right, as well the staff have been so caring and helpful through this tough time” was broken into 4 smaller units as follows: 1) learnt about self, 2) medications working, 3) caring staff, and 4) helpful staff. Each response unit was deemed equivalent to a unique idea within a statement. Response units were then coded and grouped into themes according to either A) valued personal process outcomes , or B) facilitators of valued outcomes .This study was approved by The University of Western Australia’s Human Research Ethics Committee (RA/4/1/8805).A total of 551 service episodes, corresponding to 382 unique patients, between 1 July 2014 and 30 June 2016 were included for analysis. Patients’ characteristics are described in Table Significant improvements were seen in all three self-reported outcome measures at service exit, compared to at service entry Table . The mosTable For GSES scores, baseline measure was also a strong statistical predictor of change at service exit, in that patients with higher GSE score  at baseline improved less than those with lower efficacy at baseline, by 0.6 (CI 0.4–0.7) point in score change for every 1-point increment in GSES at baseline Table . Older aOf the 13 factors assessed, only the WSAS baseline scores were predictive of the WSAS score change at service exit. Specifically, patients with higher WSAS score (ie higher impairment) at baseline improved more than those with lower impairment at baseline, by 0.3 (CI 0.2–0.5) point in score change for every 1-point increment in WSAS at baseline. No other factor was significant in predicting WSAS score changes.Up to 251 episodes  had data on patients’ satisfaction reported via the Exit Questionnaire, hence analyzed. Potential biases, or differences, were checked for Exit Questionnaire completers versus non-completers. Additional file As seen in Fig. All seven indexes of patients’ satisfaction with service positively and significantly correlated with the patients’ reduction in psychological distress Table . Improvep = 0.0022), relative to those who were less confident (ratings 1–4). Similarly, patients with highest confidence with their health plan also reported a greater reduction in work and social impairment by a further 5.3 points . For general self-efficacy, however, there was only a marginally significant effect of confidence with health plan (p = 0.0538).Given that Question 6 taps on the core focus of Neami’s service model, and that it is most consistently associated with the three outcome measures (score changes), we assessed its effect further with generalized linear modelling. Patients who were most confident (rating 5) with their health plan on average observed a further reduction in psychological distress level  contributing qualitative responses to the question ‘what was valuable to your stay?’ via the Exit Questionnaire. The 235 responses were broken into 531 smaller response units, which were subsequently categorized into two broad themes of (A): Valued outcomes, and (B): Outcome facilitators. As seen in Table This study provides evidence that receipt of service at the JMHSS was strongly associated with significant improvement in patients’ psychological wellbeing , general sense of self-efficacy, and work and social adjustment. There was a strong and persistent baseline effect present across the three measures , which showed that the less well patients benefited more from the service. This makes sense, as the further one is from the ‘ideal’ position, the more ‘room’, or potential, one has to improve, or to get there. Older patients and female patients benefited more from the services, compared to their younger or male counterparts, respectively. Further analyses (data not shown) confirmed the underlying baseline effect, which stipulated that older or female patients had reported poorer health status  at baseline than their respective younger or male peers. Parenting responsibility and role model expectation appeared to serve as a protective factor for the patient’s psychological wellbeing and general self-efficacy during their recovery journey with JMHSS. There was some mild indication that repeated patients  might have benefited more, via slightly greater reduction in psychological distress scores and increase in self-efficacy scores, than their single-episode peers. If true, this would not be a surprising finding, as anecdotally in focus groups run by Neami, patients did share that they appreciated using the JMHSS as a way of ‘top-up’ for improving their mental health.Patients’ satisfaction with the service, as reported via the Exit Questionnaire, in general was high, with higher satisfaction generally correlating with greater improvements in the three outcome measures . Features that patients valued most from their stays with JMHSS include being afforded with the time and space to recuperate, gain perspectives, focus, and create changes in their lives. Facilitating these valued features were: aspects of the environment , staff attributes, program activities, and interactions with other residents and staff. Thematically and conceptually, the patients’ qualitative feedback concurs with the three quantitative outcome measures. For example, reduction in psychological distress (measured via K-10) would be expected to be ‘linked’ to the patients having the time and space to recuperate. Similarly, gaining insight, focus, direction, and the ability to create change  should foster one’s sense of self-efficacy (measured by GSES) as well as enhance one’s work and social functioning (measured by WSAS). Notably, patients who completed the Exit Questionnaire on average stayed three days longer than those who did not complete the questionnaire. This may be because longer stays afforded more opportunities for patients to be contacted to complete the Exit Questionnaire, although longer stays were not associated with more beneficial change outcomes, as already seen in the Results.Findings from this study build on recent Australian literature for the value of the SUSD setting to patients, or service users, in terms of a) change outcomes identified by routinely administered assessment tools and b) qualitative feedback obtained from consumers who have accessed this type of service , 5, 8, 9The added qualitative component to assess the patient’s satisfaction with the service, particularly the valued aspects of their stay, has taken one step further in the direction towards ‘recovery-orientation’ , and awaOn many counts, this study has several strengths compared to previous research in the field. Specifically, our study has a much larger sample, in contrast to several previous studies employing an effective sample size of up to 40–50 participants . Assessment of relationships between patients’ satisfaction with service and their outcome measures has added another level of insight not only into the patients’ reception and perception of the service, but also the potential areas that need focusing to help enhance their recovery. Further, nuanced qualitative feedback from patients have afforded the researchers, service providers, and stakeholders alike with an expanded understanding of what matters most to them along their ‘recovery’ or change process, which in turn will help develop outcome measures that are more meaningful to the patients, for whom the services are designed.There are limitations to our study. First, this is a retrospective cohort study with only ‘cases’ and no ‘controls’ to act as an appropriate comparator. One therefore is not able to ascertain if the observed positive changes would have also occurred  in non-SUSD patients. Second, a belated inclusion of an independent research collaborator precluded applications of stringent research principles, such as the absence of express, informed, and written consent from patients regarding the use of their data for research purposes, and more robust data collection methods, as noted next,Third, Neami’s current system of data recording and storage allows for the patient’s last record and associated details to override all previous records, if the patient has had more than one service episode. This inadvertently removes an amount of potentially valuable longitudinal data, especially those on more ‘dynamic’ characteristics of the patient (such as employment status). This data removal also prohibits the potential examination of associations between these dynamic characteristics and the patient’s recovery outcomes at each episode.Fourth, the outcome measure WSAS may have not been the most optimal in measuring the patient’s change in work and social adjustment. Although there was strong evidence for improvement in levels of functioning (or reduced impairment) in the patient’s work and social activities post-JMHSS, there was no significant predictor of this, other than its baseline level. Coupled with this is the observation . Nevertheless, as alluded to earlier, the qualitative component has provided a supplementary first-person narrative about the value of the SUSD model to those who access it. Furthermore, the qualitative data come from the same population as the rest of the study, thus allowing the opportunity to compare these two sets of data, quantitative and qualitative.Overall, this study has showcased compelling, albeit preliminary, evidence for the need for more transitional/ community services like the JMHSS program, with a strong focus on both prevention and recovery. The program has shown very promising outcomes for patients, both in terms of their change measures and their satisfaction with several aspects of the service. Findings in this study build on the emerging evidence base for the value of the SUSD setting in terms of positive outcomes for consumers, and contribute knowledge that may advance program logic modelling and evaluation practices for mental health SUSD settings.From a service viewpoint, the following aspects, among others, may require further attention. First, procedures and systems need to be in place such that the individual patient’s needs can be continually monitored and effectively met. For example, this may require a delicate balance in the provision of clinical and psychosocial care, depending on the patient’s journey or progress. Second, patient intake needs to be reasonably balanced such that SUSD services do not become overflow wards for acute cases, as anecdotally noted. In the current study of the JMHSS, this was not the case, with almost 60% of admission episodes coming from the ‘intervention/preventative’ Step-up stream (instead of Step-down). Third, services need to ensure equity in access and accessibility to patients of Indigenous and/or other disadvantaged ethnic backgrounds. In our study, 2.6% of the patients self-identified as Indigenous, which is approximately in line with the 2.1% estimate from the 2016 census for Greater Perth . NeverthIn terms of research enhancement, further conceptualizations and/or assessments of patient outcomes in alignment with the expectations of both the patients, the service providers and funders, particularly with the aid of more rigorous qualitative research methods, would be beneficial and recommended. Lastly, extensions of similar studies, with the inclusion of an appropriate control group, would help elucidate the robustness of the findings.Additional file 1. Sub-acute consumer exit questionnaireAdditional file 2. Comparing baseline profiles of Exit Questionnaire completers (n=251) versus non-completers (n=300)


Hype surrounds the promotions, aspirations, and notions of “artificial intelligence (AI) for social good” and its related permutations. These terms, as used in data science and particularly in public discourse, are vague. Far from being irrelevant to data scientists or practitioners of AI, the terms create the public notion of the systems built. Through a critical reflection, I explore how notions of AI for social good are vague, offer insufficient criteria for judgement, and elide the externalities and structural interdependence of AI systems. Instead, the field known as “AI for social good” is best understood and referred to as “AI for not bad.” We have begun to apply artificial intelligence (AI) to areas that claim to interact with “social good.” New academic centers and initiatives label themselves as such. Cornell and Berkeley work on human-compatible AIThese efforts carry over into conferences. At the prestigious AI conferences NeurIPS, ICML, and ICLR this past year, one group led workshops on “AI for social good.”The world outside of universities has not been quiet. Google, Facebook, IBM, and Intel have pages on “AI for social good”“Social good” shifts between social responsibility, societal impacts, society, common good, the good, development, and ethics. Its proposals come in similar forms: calls for more data, better data, broader application, more diverse voices, reflexivity, transparency, changes to funding priorities, more education, more regulation—more.The meaning of artificial intelligence shifts as well. It may mean “algorithmic systems,” or “automated decision making”   has aimed to define best principles and practices for AI systems. Like Greene et al. . We are meant to accept that because a project works on health, with not-for-profit organizations, in the space of climate change, on poverty-reduction, etc., that it is “for social good.” In this section, my argument is as follows:When working for “the good” we must ask capability approach and social justice.I provide an alternative definition of good according to the Following 1, there are projects that are good, but that are not labeled as such.Following 1, AI technologies carry inherently bad externalities.Following 3, in order to consider net goods, “AI for social good” must engage with and balance out these bads.this definition as to advocate for discussion of which definition is most appropriate just as Green, Patton, and D'Ignazio do. Such a frame will then allow us to analyze claims of “social good.” Suffice to say, a “good” intervention should be empowering (particularly of basic human functioning), address structural conditions of oppression, and perform at least as well as interventions using similar amounts of resources.First, I offer a functional definition of “good” for an AI system using the capability approach and social justice. Green , p. 4 ciFor example, imagine a project designed in partnership with a community in a specific West-African country with little access to health care. The project uses a computer vision application on a smartphone to screen babies for birth defects. This project might be viewed of as “good” given that it specifically works with a marginalized community and increases their capability to access health care. Further, the community might not have achieved the same access to care with a similarly-resource-intensive effort to train more medical professionals.Second, using the definition of good from 1, there are projects which do not use the label “AI for the good” that might be classified as such. For example, consider recent efforts in federated learning to decentralize and distribute the computations constituent in the training of a model . Recall the USC AI for Social Good project on policing which Green named as oppressive. Indeed, according to the definition of good from 1, the USC project would be bad—it does privilege community voices and reinforces forms of oppressive policing (which restrict peoples” capabilities).“Furthermore, non-profit organizations, which at least some AI practitioners associate with their use of “social good,”Fourth, this all suggests that to be considered “good,” projects must commit to a definition of social good and then show that, even after considering negative externalities, on the balance they still achieve good. On the whole, then, projects might better consider the degree to which they are “not bad.”In this section, I consider four critiques of my argument.First, detractors might chafe at a focus on the words of AI. They might argue that focusing on words ignores the substance of technologies which would actually bring about “good.” Of course the substance of the technologies is important, but in this paper I focus on the use of language, which, as I make the case for in the introduction, is also important.Second, one might posit that even if “AI for the good” is vague, the use of such terms does no harm. While the claim of vagueness has been used to decry the difficulty of regulating AI technologies Scherer, , we use Third, a reader might say that “social good” is just marketing speak—not what practitioners say. That may be so, but the term appears from research to implementation: in governments, in funding agencies, in research papers, at conferences, in companies, and in public discourse. Even if the majority of the use of “AI for good” occurs externally to AI practitioners, it is through these routes that the notions of AI manifest. That is, practitioners must care about how their work is used and not just what it is.Still, one might argue that, fourth, despite its flaws, “social good” is a relevant distinction. Even in the absence of a more robust criteria, there is a difference between machine learning researchers choosing to work on credit card companies being defrauded vs. those working on disease modeling. I suggest that there is a better approach than to ignore the ambiguity, the insufficient criteria, and the externalities of AI. Instead of banishing “AI for good,” we might rather rename the field.In this critique of the use of language, I also offer a suggestion. Namely, we should stop labeling projects as “for social good” and instead use the term “for not bad.” The latter more accurately evokes the need to avoid the inherent bad traits of AI technologies without falling into the traps involved with vague claims to “social good.”Information Technology and International Development focuses on the background theory of such workPractitioners who would still like to use terms like “AI for the good” should read literature that studies the criteria for evaluation of social change projects and then apply those criteria. This includes work in the health sciences, social sciences, development studies, economics, and more. In the scope of technological changes for implementing theories of a just society, the literature in Information and Communication Technologies for Development provides some examples. Conferences in this space include the ACM Conference on Computing and Sustainable Societies (COMPASS) and the Workshop on Computing Within LimitsWith such a background, practitioners may be better prepared to define and measure criteria of “good” to expand on my attempt above. More work to quantify the externalities of AI projects [building on examples like Maxmen  and StruSustained interaction with those in communities that are to be “innovated” will further concretize what constitutes “good.” Tambe and Rice  and Patt“AI for not bad” avoids some of the problems of “AI for good.” It more honestly describes the current vagueness and centers the externalities. Practitioners unwilling or unable to commit to explicit notions of good should consider adopting it.“AI for the good” is vague, lacks sufficient criteria, omits the externalities of AI, and elides the structural interdependence of AI projects. “AI for the good” may really be AI for flashy slide decks, AI for difficult-to-maintain and highly interdependent computational systems, AI for new statistical methods, or (at best) AI for public health analyses that may end up saving lives. In this paper, I raise concerns about the presentation of the “AI frontier” as beneficent. Following Green, I ask that the field “AI for the good” recognize that, as it is now, it really constitutes “AI for not bad.” Practitioners would more honestly embrace this label or else do the work necessary to legitimately claim good.In this work, I advocate for a more honest discipline. I ask those out there who interact with AI at any level—the new student wondering where to put her time, the executive of a company—to consider what their use of language ignores.“AI for social good” speaks to the desire of many of practitioners to share what opportunities they have. It sounds nice. It imagines a world of lucrative careers optimized to better humanity. The world is not so simple. Perhaps it is enough that society, as bolstered by science, has tended toward longer lives, more food, and less violence Pinker, , but extJM contributed everything to this paper and is accountable for the content of the work.The author declares 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 handling editor and reviewer HL declared their involvement as co-editors in the Research Topic, and confirm the absence of any other collaboration.


These methods are revolutionary but require an understanding of both (bio)chemistry and computer science to be exploited to best advantage. We give a high-level  background to the deep learning revolution, and set out the crucial issue for chemical biology and informatics as a two-way mapping from the discrete nature of individual molecules to the continuous but high-dimensional latent representation that may best reflect chemical space. A variety of architectures can do this; we focus on a particular type known as variational autoencoders. We then provide some examples of recent successes of these kinds of approach, and a look towards the future.The number of ‘small’ molecules that may be of interest to chemical biologists — chemical space — is enormous, but the fraction that have ever been made is tiny. Most strategies are discriminative, i.e. have involved ‘forward’ problems . However, we normally wish to solve the much harder generative or inverse problem . ‘Deep’ (machine) learning based on large-scale neural networks underpins technologies such as computer vision, natural language processing, driverless cars, and world-leading performance in games such as Go; it can also be applied to the solution of inverse problems in chemical biology. In particular, recent developments in deep learning admit the  Mycobacterium tuberculosis) and it either worked (here to kill the bacteria) or it did not. No mechanistic understanding was required (though could later be sought). A major advantage was, after all, that the drug worked. Beyond the thought of trying a variety of molecules, no specific hypothesis was required. In a more modern version, a target  is sought, on the basis of a hypothesis, usually about the desirability of inhibiting said target, and typically on a purified protein in vitro. Following a terminology from genetics, the former is referred to as ‘forward’ chemical genomics, the latter as ‘reverse’ . Thus,  in vivo , it is a in vivo .Recently, there has been much excitement about the use of methods referred to as ‘Machine Learning’, ‘Artificial Intelligence’, or simply ML or AI. These too can serve to relate the world of ideas to the world of data. Perhaps surprisingly, their relationship to classical (Neyman-Pearson or frequentist) statistics  Figure , is simi60 ..89–91]. o’ e.g. ,92–107),,de novo’o’ , they also trained a standard MLP to use values of the latent vector as inputs and the calculated properties as outputs. In principle, any kind of deep network might be used for the encoding, and the same or any other kind for the decoding )With regard to chemical biology, the original motivation of the ‘robot scientist’ project  was in fFrom a scientific point of view, the empirical success of deep learning comes at a major cost. That cost, as mentioned, is the cost of knowing precisely how the ‘knowledge’ is actually stored in a deep network, and thus exactly how inputs map to outputs . It is also assumed that such knowledge will help avoid costly and dangerous errors as we begin to trust these methods more. Thus, ‘explainable AI’ will continue to be an important area for the future.This has been a purposely high-level overview of some of the possibilities in cheminformatics and chemical biology that have been engendered by the development of deep learning methods in general and of generative methods in particular. Our main aim has been to draw attention to these developments, and to some of the means by which readers who are only loosely acquainted with them can incorporate these methods into their own work. Its success will be judged by the rapidity with which this happens.Discriminative model. A type of ‘supervised’ machine learning model used for classification or regression problems, based on the learning of relationships between pairs of inputs X and outputs Y. Such models serve to create decision boundaries in high-dimensional space, that allow the prediction of new outputs given new inputs of comparable type. They allow modelling of the probability of Y given a value of X (P (Y|X = x)). In chemical biology they are familiar as QSAR models. Most classical ML methods involve discriminative modelling.Generative model. A much more powerful (and difficult) approach to modelling that also relates inputs X to outputs Y but that allows the de novo prediction of X given Y. They can do so because they capture the joint probability distribution p over the training data, and effectively permit the prediction of candidate inputs X given a desired output Y (i.e. P(X|Y = y)). Generative models have also been used to great effect in a very particular way in deep learning to create ‘fake’ or ‘decoy’ inputs, whose avoidance can assist deep networks in learning to generalise better [Generative Adversarial Networks (GANs).e better ,124. TheGenerative Adversarial Networks (GANs). It was recognised by Ian Goodfellow [odfellow ,124 thatHyperparameters. The training of neural networks can be affected greatly by many control variables including the size, number and connectedness of layers, means of weight initialisation, learning rate, momentum, weight decay, transfer function, and so on. These hyperparameters still tend (and need) to be adjusted empirically for specific problems. Tuning hyperparameters is itself an optimisation problem, best addressed via intelligent search.Overtraining. Equivalent to overfitting a function by adding too many terms, this is equivalent to learning a model that fits the training data perfectly but is less good at fitting the validation or test data. It is the greatest danger of ANNs of all stripes. Indeed, almost every strategy for improving training is ultimately designed to decrease the overfitting of the training set.Radial basis function networks. These networks have a broadly similar architecture to MLPs . This uses paired inputs X and outputs Y to learn a nonlinear mapping from one to the other. In unsupervised learning the class membership of the outputs Y is not given, so only clustering is possible, while in semi-supervised learning some  of the class memberships (outputs) are known and may be used to guide the learning. In reinforcement learning, a software agent takes actions in an environment, which is interpreted into both a reward and a representation of the state; these are fed back to the agent and may be used iteratively in a decision-making process. Reinforcement learning underpins many of the great successes of Google DeepMind, such as in Go playing [ playing ,166.Universal approximation. A very powerful theorem that shows that any feedforward network with just a single hidden layer (of unstated and hence arbitrary size) and a suitable, nonlinear transfer function can effectively approximate anything from a continuous distribution. Although perhaps a little overblown, it does provide the conceptual underpinnings for much of the power of ANNs.


Ageism is defined as stereotypes, prejudice, and discrimination toward people because of their age (Ayalon and Tesch-Römer, et al., From the get-go, the COVID-19 outbreak has been portrayed as “the problem of older adults” and a clear age division, separating young from old has been promoted (Zhou In other countries, the division between young and old resulted in somewhat different manifestations, depending on the sociocultural background of the country and its ability to address the pandemic. In Israel, the Ministry of Defense had issued a statement that “the single most important insight… is to separate old people from young people. The single most lethal combination cocktail is when grandma meets her grandchild and hugs him” (Gross and TOI Staff, et al., et al., et al., et al., These messages are ageist, as they take chronological age as a sole criterion, and automatically equate older age with vulnerability, dependency, and limited contribution. This ignores the diversity that is present especially in old age and regards all people over a certain age as a homogenous group (Lowsky The division between young and old and the portrayal of older adults as the main at-risk group have resulted in younger people feeling invincible, thinking “this is not their illness.” In the USA, Germany, and other countries, younger people have celebrated the COVID-19 outbreak in “Corona parties,” thinking they are immune Casey, . The hasThe transition from seeing older and younger people as two separate groups to sacrificing older adults for the greater good of society has been quick. In Israel, the former CEO of the Ministry of Health had stated that “for very few people, whose expected lifespan is not very high, you do not ruin a country.” He further said that the state should “sacrifice these people” Magen, . Similaret al., et al., Realistic threats, which represent disputes over material assets, occur when resources become scarce (Stephan and Stephan, During the COVID-19 outbreak, intergenerational solidarity has been brutally negated and social distancing Mahase, , rather et al., Chronological age should not be used for the allocation of goods and services and should not be a sole criterion for determining people’s vulnerabilities, prognosis, or treatment options. There is a high variability in old age, which in fact becomes even greater as people grow older (Lowsky The divisive language of “us” vs. “them” or young vs. old splits societies and has a malicious impact not only on older adults, but also on younger adults and on our already fragile social fabric (Ayalon and Tesch-Römer, Finally, the most vulnerable members of our society, including older adults in long-term care facilities and those with severe physical and cognitive impairments, face substantial threats to their autonomy, unrelated to the current outbreak. It is our duty to ensure that the autonomy of the most vulnerable members of society is not hampered and that their voices are heard. Older people’s rights should not be compromised, and human rights should not be differentially allocated based on chronological age (United Nations Human rights – Office of the High Commissioner,


Adolescence is marked by significant life stress. Recently, school refusal and dropouts as well as suicide among Japanese adolescents have increased. Sense of coherence (SOC) is recognized as a competency that helps people deal with stress. The purpose of this study was to examine the factors influencing SOC in male and female high school students. We conducted a survey with 203 pairs of high school students and their mothers, in Tokyo, to explore their SOC, family relationships, school belonging, and autistic traits. Analysis of the data revealed a weak relationship between female students’ SOC and that of their mothers, and no relationship between male students’ SOC and their mothers’ SOC. Feelings of acceptance and recognition from teachers improved students’ SOC, irrespective of gender. Low SOC in mothers had a negative impact on female students’ SOC, and children’s lack of imagination (an autism spectrum tendency) had a negative impact on male students’ SOC. This study revealed the importance of support at home and school according to the needs of both genders. In the early 20th century, American psychologist G.S. Hall described late adolescence as a period of “storm and stress” . It is aIn light of this background, the Ministry of Education, Culture, Sports, Science and Technology-Japan (MEXT) states that it is important to promote education that helps students learn how to deal with stress and provides an overview of common suicide prevention strategies. Young people can be at the mercy of unsolved and unprecedented problems such as globalization, changes in social conditions, and weakened family relationships. Under such stressful situations, the ability to utilize various coping resources effectively and transform a stressful experience into growth is required. MEXT has named this ability the “power to live” .In recent years, sense of coherence (SOC) has gained attention as a means to cope with stress and has been the subject of extensive research, mainly in Europe, Asia, and the United States. SOC is described by Antonovsky  as a comAdolescent SOC is very fragile; it is developed by the experience of building trust and having affectionate relationships . In otheAdolescents spend most of their day at school; thus, much of their life experiences take place there. Feldt  stated tStudies have reported that undiscovered and undiagnosed Autism Spectrum Disorder (ASD) is often behind school refusal and suicide ,18. Few The purpose of this study was to understand whether student/mother SOC, school environment, family relationships, and ASD personality traits are related to students’ SOC.In 2016, we provided a self-administered questionnaire to 671 students attending a Tokyo metropolitan high school and their mothers. The questionnaire was assigned a common ID number for parents and children so that they could be matched. Students’ responses were collected in a school collection box, and mothers’ responses were collected by mail. There were 629 responses from students (response rate = 93.7%) and 203 responses from mothers (response rate = 30.2%). Our analysis was conducted on the 203 pairs of mothers and students. This study focused on mothers specifically because in Japan, mothers are the main caregivers for children . As inclTakakura et al.  stated tThis study complied with the rules of the Declaration of Helsinki, revised in 2013, and was conducted with the approval of the Toho University Faculty of Nursing research ethics review committee . Since high school students formed the target group, we provided written explanations to each parent about their children’s participation in the survey, in accordance with the Japanese Ministry of Health, Labor, and Welfare ethical guidelines. We explained in the document that participation in the survey was voluntary and those who refused to take part would not be penalized. We guaranteed in writing that they could opt out of the study at any point using email, telephone, fax, letter, interview, or other means. There were no refusals from parents. We included a check box in both the parent and child questionnaires for informed consent to participate and analyzed the responses of those parents and their children who provided consent. A common number was assigned to the parent and child; the numbers did not match the student name or student ID number, and it was explained in writing that individuals could not be identified. All methods were carried out in accordance with the relevant rules, guidelines, and regulations.Students’ gender and year of study were recorded. The students’ mothers were asked to provide their own age, educational background, financial status, occupation, and marital status.The original SOC scale is a 29-item instrument scored on a 7-point Likert scale . In thisThe FRI was developed based on one of the three structures of the Family Environmental Scale developed by Moos and Moos . The FRIWe used the Japanese short version of the school membership scale , which mThe Autism-Spectrum Quotient (AQ), developed by Baron-Cohen, Wheelwright, Skinner, Martin, and Clubley , is a 50t-test was performed on the average values by gender for both mothers and children. Cronbach’s alpha was calculated for each scale. Spearman’s correlation coefficients were then computed for parents and adolescents (split by gender) between the total SOC, FRI, and the subscales and other variables. We examined the correlation coefficients for each variable in order to investigate factors related to the SOC of students. Specifically, the correlation coefficients were calculated with data from the family relation scale, sense of belonging to school scores, and AQ-J-16 scores.The matched parent/child data were analyzed. First, a simple tabulation of demographic attributes and characteristics of the participants was conducted. Since normality of the distribution was found in the SOC total score, a SPSS AMOS was used for path analysis by gender. In constructing the structural equation model, we first referred to the model of Yamazaki and Togari , accordiWe used RMSEA (Root Mean Square Error of Approximation) and CFI (Comparative Fit Index) for the model fit and examined the model with CFI set to 0.9 and RMSEA set to 0.1 or less. SPSS Statistics and AMOS 25 for Windows were used for the other analyses.Nearly 90% of the mothers indicated that they were married and 42.9% stated that they were economically poor or very poor compared to 23.6% economically wealthy or very wealthy. Of the respondents, 52.7% were females, while 35.8% were first-year students—the highest number in the first to third grades. The students’ average SOC score was 37.3 ± 6.8 and the mothers’ average SOC score was 42.7 ± 7.6 .p = 0.004).r = 0.226, p = 0.023).r = −0.200, p = 0.033) between conflicts in family relationships felt by mothers and female students’ SOC scores.There was no significant relationship between male students’ SOC scores and their mothers’ response variables. There was a small significant negative correlation . Regarding the AQ-J-16, a significant negative correlation was observed between SOC scores for both male and female students and their reduced ability to switch attention and poor communication abilities . Male students also showed a negative correlation between their SOC scores and poor imagination skills .There was a positive correlation between SOC and the school membership scale scores for both male and female students  but did not affect their SOC. Acceptance by teachers  had a positive impact on students’ SOC. On the other hand, lack of imagination skills as measured by the AQ-J-16 had a negative effect on students’ SOC . For female students, the mothers’ SOC affected children’s SOC  through the family conflict that the child felt . On the other hand, unlike the male students, the lack of imagination did not affect females’ SOC. Just as in male students, acceptance by teachers had a positive influence on the females’ SOC . In addition, the cohesiveness and expression of the family relationships in students and mothers, student acceptance and sense of belonging to school, AQ-J-16 communication skills, attention switching, and so forth, were examined, but a good model fit was not obtained.For male students, the mothers’ SOC significantly affected children’s conflicting feelings about their family (In this study, we investigated whether factors such as ASD tendencies, family relationships, and school life influenced SOC among Japanese high school students. Although SOC is said to be affected by the environment in which one grows up, so far there has been little research on the relationship between parent and child SOC. This study revealed that the factors that affect SOC were different for male and female high school students, indicating the need for gender-specific interventions to develop SOC.Among the participants, mothers’ SOC was higher than children’s SOC. This is in line with Antonovsky’s work indicating that SOC will rise slowly over time with age . The ageMale high school students’ SOC scores were significantly higher than females’, which is consistent with previous research. A study with college students in Japan showed that males had higher SOC scores than females . In a coThe female students’ total SOC scores were slightly positively correlated with their mothers’ total SOC score. Daughters are said to be closer to the mothers psychologically compared to sons . In addiIn Togari et al.’s research targeting high school students and their mothers , about 8In fact, our results show that school-related variables were more strongly associated with SOC than with family relationships . AccordiRegarding the formation of SOC, putting oneself in a predictable situation fosters a sense of comprehension, and participation in decision-making and problem-solving fosters a sense of meaningfulness . In highAt the same time, some studies have shown that members of families with alcoholism and high levels of domestic violence and abuse also have low SOC . TherefoAdolescent females perceived that the mothers’ SOC affected family conflict, thereby impacting the daughter’s SOC. This study used structural equation modelling, but it is also possible that the daughters’ own SOC caused stress, anxiety, and domestic conflict that affected the mothers’ SOC. Previous studies have revealed that irritable temperament is negatively associated with SOC , and adoFor male students, similar to female students, our results suggested that if the mother’s SOC was low, the son felt a high degree of family conflict. However, for male students, this did not affect their own SOC. In contrast, the lack of imagination as an ASD tendency had a negative impact on male students’ SOC. Examples of items measuring lack of imagination include “It is difficult for me to understand the intentions of the characters when reading the story” and “I am not good at imagining what other people would feel when encountering an event.” High scores on these items revealed difficulties male students had in building good relationships in club activities and classrooms. According to previous studies, not only are relationships between peers very important for males, but making good friendships in class and club activities has a positive effect on mental health, while lack of friendships may have a negative effect on their SOC . Males’ In this study, we also examined the relationship between SOC and ASD and found a negative effect only on high school boys . With reThis study has several limitations. First, parents’ response rate was low, while high school students had a high response rate, which may indicate that only parents who understood their children responded. Second, only mothers and not fathers were asked to participate. In the future, it will be necessary to invite both parents to participate. Finally, our study only examined students and mothers from one high school. In order to generalize findings, it will be necessary to conduct research in diverse schools representing people from various backgrounds.Through our study, we gained knowledge about the relationship between mother and child SOC, which has received little attention to date. Female students’ SOC was slightly related to their mothers’, but male students’ SOC was not. This may be due to psychological closeness between daughters and mothers. The mothers’ SOC affected family conflicts as perceived by the daughters, which may in turn have impacted the daughters’ SOC. However, when children reach high school, their worlds expand; outside influences, such as school, become stronger than parental influences. Both male and female students’ SOC is positively impacted if they feel they are recognized by their schoolteachers. Lack of imagination in males had a negative impact on their SOC. Schools are the best place for providing intervention and support for students to develop a healthy SOC. Being sensitive to gender differences, providing information to families, and encouraging positive relationships with teachers at school may improve students’ SOC.