There is growing interest in the design of digital interventions to improve conditions for young people who engage in high-risk behaviors, like nonsuicidal self-injury (NSSI). However, few studies have focused on how young people self-manage NSSI, or their existing, and historic, use of technologies to support their goals related to NSSI behavior change. Such an understanding has the potential to inform the design of digital interventions that meet this population's unique needs.This study aims to (a) understand the self-management practices of young adults who engage in NSSI, (b) explore how they currently use technologies for self-injury self-management, and (c) identify the ways they can envision an app-based technology supporting their self-management.via thematic analysis.Twenty young adults (aged 18–24) with lived experience of NSSI, and who were not currently enrolled in therapy, were recruited from online venues. Participants completed baseline measures to assess mental health and NSSI characteristics, followed by a virtual 1-h semi-structured interview where they were invited to share their experience of self-management, their goals, and their thoughts on supportive technology. Interview scripts were transcribed and analyzed Themes and sub-themes are organized under two broad domain areas: (1) How young adults self-manage NSSI thoughts and behaviors and (2) Opportunities and challenges for digital interventions to assist young adults in their recovery process. We found that young adults had varied experiences with, and goals related to, NSSI. Participants reported a lack of effective strategies to reduce NSSI urges and a desire for an app-based technology to track patterns and deliver personalized suggestions for self-management. Participants reported existing use of technologies as part of self-management, as well as early information and support seeking for NSSI online.This study contributes a greater understanding of young people's experiences with self-injury, their self-management practices, and their desire to engage with technology. Our findings highlight the need for design flexibility in developing digital interventions that support individual goals, unique presentations of NSSI, and needs at different phases of recovery. Implications for the design of highly personalized and relevant digital interventions to address NSSI are discussed. Nonsuicidal self-injury (NSSI) is a growing public health concern, affecting 13% of young adults and 17% of adolescents worldwide . For manMany adolescents and young adults who engage in NSSI do not access professional treatment –10. ReseMost research at the intersection of technology and NSSI has focused on how young people exchange information and support around mental health and NSSI online, through forums and social media –23. CollResearch on digital interventions for NSSI is more limited but growing. Several apps and web-based treatments have been developed and undergone preliminary tests of their efficacy. For example, two apps designed as adjuncts to face-to-face treatment produced promising reductions in NSSI. DBT Coach, an app for adults with borderline personality disorder (BPD), promotes dialectical behavior therapy (DBT) skills generalization and practice in daily life. In a small pilot trial that introduced the app to 16 adults with BPD and self-harm after 6 months of standard DBT treatment, app use was associated with reductions in urges to self-harm, NSSI frequency, and subjective distress after 3 months use . AnotherIn addition to efficacy trials of digital interventions, several studies have focused on the types of digital tools young people would find helpful in their NSSI recovery –31. In aAnother study involved 6 young adults with lifetime suicidal ideation or self-harm in interviews to understand their experiences of NSSI urges and how a technology may be useful . FindingIn general, these studies point to several desired features for future digital interventions, including brief on demand coping skills, psychoeducation, social connection, and opportunities to gain self-knowledge about patterns and address common comorbidities or other life challenges. However, less is known about the specific ways these features should be instantiated within an app to best support young people's natural use of technology and their self-management patterns. Additionally, the generalizability of these findings to populations who are not currently treatment-engaged is unknown as both studies focused on young people who are actively in contact with mental health services. The current study was designed to address these gaps and detail the experiences and needs of young adults who are not currently engaged in treatment for NSSI, and the ways a digital tool may be able to better support them in their recovery.Designing technologies to fit within individuals' daily lives and habitual patterns requires a nuanced understanding of their current self-management practices, challenges, and technology-use. The present study aims to provide a nuanced examination of young adults' lived experience of NSSI and directly solicit feedback on their imagined use of technologies to support their goals. The broad aims are: (1) to understand the self-management practices of young adults who engage in NSSI, (2) explore their use of technologies to support their efforts toward NSSI and mental health management and (3) identify ways young adults could (or could not) envision using technology  to support them in managing their NSSI.Note: We use the term self-management deliberately as we did not want to convey any expectation or make assumptions about participants' desire to change their NSSI behavior. Given that many participants endorsed coping strategies as part of self-management practices, we use the two terms interchangeably to refer to shorter- and longer-term efforts to improve or maintain well-being. This includes but is not limited to management of NSSI. Similarly, when we discuss participant goals in the findings section this term was used to describe anything participants would like to work toward regarding their NSSI or mental health. In the interviews, participants were provided with this broad description and were able to offer alternatives if the term “goal” did not resonate with them.Participants were recruited from online venues between May and October of 2021. This included emailing individuals who were part of several research registries  and posting online study advertisements through social media platforms . All recruitment materials included a clickable link to a description of the study for interested individuals which included access to the online eligibility screener. For this study, inclusion criteria included: (1) engaging in NSSI on 2 or more days in past month, (2) between ages of 18–24 years old, (3) own a smartphone, and 4) US Citizen. Exclusion criteria were guided by our aim to design a digital self-management intervention and safety considerations. These included (1) severe mental health diagnoses , for which a standalone digital intervention would not likely be appropriate; (2) severe suicide risk, including suicidal ideation with a plan and intent to act; and (3) current engagement in psychotherapy, since we were interested in meeting the needs of a population currently uninterested or underserved in existing services. Eligible participants received an email to set up a remote interview time, which also contained a link to the online consent and baseline survey with additional items on mental health and NSSI history. Interviews were conducted by the first author over zoom, were under 1 h, and were audio recorded and transcribed prior to analysis. All recruitment and study procedures were approved by the university's Institutional Review Board.via the Alexian Brothers Assessment of Self-Injury – Short Form (ABASI-SF), a self-report measure that assesses the specific methods and frequency of NSSI, as well as medical severity, impulsivity, and experience of their NSSI behaviors , a self-report questionnaire focused on NSSI characteristics. Only the disclosure subscale was administered which contained items related to perceptions of others' awareness of their NSSI, as well as disclosure experiences  (The interview script was co-developed by the authors and contained questions related to (1) managing mental health and self-injury, (2) technology use in mental health self-management, and (3) imaged use of an app. For a full list of questions please see the ehaviors . NSSI dibout it) . All parbout it) , a nine via self-report measure containing nine common and/or exclusionary diagnoses  To assess experience with mental health treatment, participants additionally responded to two questions “Have you ever seen [Are you currently seeing] a therapist, counselor, psychologist for mental health treatment?”Mental health diagnoses were assessed at eligibility Thematic analysis, as described by Braun and Clarke , was useProcedures were developed to ensure participant safety throughout the study. During the baseline assessment, suicidality was assessed by self-report using item #9 of the PHQ-9. If participants score ≥1 on the PHQ-9 item 9, they received a suicide item (item 9) from Beck Depression Inventory (2nd edition). If they scored above a 1 on both they were called within 24 h and issued the Columbia Suicide Severity Rating scale. There was no formal assessment of severity of mental health symptoms or suicide during the interview. However, all participants were informed that their participation was voluntary and that they could pause or discontinue the interview at any time without consequences. They were also informed that they could skip questions if they felt uncomfortable.One participant scored at or above a “1” on the 9th item of the PHQ-9, was issued the BDI-II and scored above a 2 which indicates elevated risk. This participant was therefore administered the full Columbia Suicide Risk Assessment, followed by safety planning, prior to the interview. The participant was deemed to be at low risk based on clinical assessment, so we proceeded with the interview. Additionally, all participants were provided contact information, including phone numbers and links to crisis resources including the National Suicide Prevention Lifeline, the Crisis Text Line, and the Trevor Project.Mage = 20.7, SD = 2.2; Mode = 19). Most identified as female , 2 (10%) identified as male, 3 (15%) identified as non-binary or third gender, 1 (5%) identified as transgender, and 1 (5%) self-described as She/They. Most participants self-identified their race as White , 2 (10%) as Asian, 1 (5%) as more than one race, 1 (5%) as Black or African American.Participants were 20 young adults with recent (past month) engagement in NSSI. All participants were between the ages of 18 and 25  and having engaged in NSSI on around 5 days the past month . The most common forms of NSSI were cutting , scratching to the point of bruising or bleeding , hitting oneself , banging head or limbs against something , and preventing wounds from healing . Nine participants had made a prior suicide attempt (45%). Eighteen participants reported that they wanted to stop or decrease self-injury, while two disagreed. One of the two agreed that NSSI was a problem, and the other did not. While all participants were not currently engaged in mental health treatment, most participants had at one time seen a therapist, counselor, or psychologist for mental health treatment  and 60% indicated that someone knows about their self-injury. Self-reported comorbid conditions are reported in Most participants reported their first NSSI behavior around the age of 13 (Below we present themes and subthemes organized under two broad section headings focused on: (1) How young adults self-manage NSSI thoughts and behaviors and (2) Opportunities and challenges for digital interventions to assist young adults in their recovery process.Participants' reflections on their self-management of NSSI thoughts and behaviors, and related mental health symptoms, resulted in three themes: (1) differing goals and motivations, (2) strategies for self-management, and (3) technology as part of the self-management process.Participant goals and motivations varied in ways that reflected how they understood and related to their NSSI thoughts and behaviors. Some participants identified specific goals related to their experience of NSSI ranging from complete cessation of the behavior to reductions in the frequency and severity of injuries. Others described broader goals related to improved mental health and well-being, such as the desire to acquire new strategies to reduce NSSI as well as symptoms of comorbid mental health conditions like depression, anxiety, and disordered eating. Commonly participants endorsed more than one goal, identifying both short-term and long-term goals, that would help them to feel better in the short term and more confident in their ability to navigate difficult emotions or situations overtime.Stopping NSSI was the most common long-term goal reported by participants, with just two exceptions, while short-term goals were more personalized and varied across participants. Among those reporting intentions to work toward reductions in NSSI severity or frequency, harm-reduction techniques were often endorsed, including using different (less damaging) methods, replacement behaviors, and engaging in safer NSSI practices. Reflecting on both a long and short-term goal, one participant describes:Well, this is a general long-term one, but I would like to stop. It's not something I want to do my whole life. I view it as an addiction, and that's not a good mindset to have about anything. More current or short-term, I guess less frequently or less severely. There's some behaviors that are arguably worse than others. If I have to engage in some harmed behavior, I would rather it be something that doesn't leave a permanent mark vs. something that does” (P5).“alternatives that aren't as self-destructive” (P19) to reduce the physical impact of NSSI, without stopping the behavior entirely. Another participant described wanting to minimize the amount of harm done  saying: “obviously [I] wanna just stop completely. But more specifically, I would say reduce the severity of the cuts… Maybe just put it less deep, maybe surface level cuts, if anything” (P12).Many participants described using “The ice trick was not helpful. The rubber-band trick is tricky…you can leave marks and … welts if you try hard enough… the rubber band trick might be like a slippery slope kind of thing. I don't know if that's helpful or not.” Not all participants had positive experiences with harm reduction techniques. One participant described that she would tell herself that she “would only do just a little bit” but then found it “really hard to stop” once she started (P10). In sum, participants described varying degrees of success and comfort with cessation and harm-reduction as part of their personal histories.Though many participants described the use of less-severe methods or replacement behaviors as part of their NSSI self-management, they were not often seen as a viable solution long-term. On this, participant 16 commented “Importantly, even among those that described strong intentions to reduce NSSI over time, there was a great deal of ambivalence expressed. Many participants felt the behavior would be too difficult to stop, often because they had been injuring for a long time. One participant described: “I've been dealing with these thoughts since I was 13, so, it's about seven years now, you just kind of get tired… It doesn't get better, so why bother not doing it?” (P20) Vague intentions to stop were also common such as one participant who described wanting to “kick the habit” but having “no small specific goals at the moment… it's like biting your nails. It's like, ‘Well, I do want to stop. I just haven't put the stuff that tastes bad on my nails, or I haven't like worn the caps. I haven't done anything” (P11).I'm sort of cool with it. I think there's a bigger problem, and until I deal with the bigger problem, I don't feel like dealing with the symptoms would be beneficial” (P13). Embedded in many of these responses was the clear functionality of the behavior, and a fear, in some cases, of losing NSSI as a method to manage distress.Finally, NSSI was seen as a coping strategy for many participants reflecting the nuance of NSSI as part of a more complex mental health history. The idea that any change in NSSI was possible, or desired, did not resonate with these participants experiences. Rather, these participants felt they needed to resolve preexisting mental health symptoms, or to feel confident in using other effective strategies before they were willing to consider addressing NSSI. Reflecting this, one participant said: “keeping your hands occupied is important. That's why I like playing video games as opposed to watching TV because when you're playing video games you have to be holding a controller, or using a mouse, you don't have idle hands” (P5). For others more vigorous physical activity like boxing or running were perceived to be a helpful way to discharge overwhelming emotions or energy and made them tired, and therefore, less likely to act on urges.Most participants endorsed several strategies they had used, or tried, to achieve their mental health or NSSI goals. Outside of harm reduction techniques, participants described avoidance strategies reporting mixed success. Activities aimed at distracting participants from intense NSSI urges or thoughts, including reaching out to friends to talk about something unrelated, watching TV, or doing “mundane tasks” like organizing their room were common. Others qualified that they needed to engage in activities that fully occupied their mind or hands, often citing video games as an example of an activity that did both: “Though distraction was a go-to strategy for participants who characterized NSSI thoughts and urges as momentary, some participants described their thoughts and urges as too intense and persistent to manage with acute in-the-moment activities. For these participants staying “constantly busy” and actively avoiding down-time when they may be able to act on those thoughts, felt necessary.I start listing off reasons why I shouldn't do it” P20) or the use of distress tolerance skills from DBT, like TIP  or STOP . Those who endorsed approach strategies often described being introduced to them through past therapy or through searching for skills online.While less common, several participants mentioned cognitive and behavioral approach strategies like talking back to, or challenging, negative thoughts, engaging in pro and con exercises .“This desire for more effective coping strategies that resolve both short-term distress and provide longer-term relief in the form of self-efficacy was pervasive.Technology was embedded within participants' self-management practices and a means to engage in coping strategies, to access information, and to connect with community. Participants reached for their phone, tablet, or computer to connect with others for support, distract in moments of distress, or seek content that could shift their mood. Activities like boxing or running were often done while listening to evocative music through headphones. In fact, several participants described curating playlists to match the intensity of their emotions, or to invoke safe mental states.when I was a teenager, and I was first struggling with it…. I didn't understand why I was doing this and what I was going through” so she went online to get “more general knowledge about it” (P15). Another participant described searching for NSSI alternatives on social media: “I would go through the tag and read what people would do as an alternative. That used to be a big, big thing where these posts would go around that would be like, ‘Instead of doing this, put an ice cube on your arm, or drawn on yourself with marker”’ (P7). Such information-seeking often led participants to connect with peers with shared experiences through online communities.In addition to technology being part of specific self-management practices, internet-based technologies were also used by participants to seek information about self-injury. For example, one participant described: “when I was younger, I'd use Tumblr a lot to post and reach out to people with similar situations and see – I think, maybe, they wouldn't give advice, but knowing I'm not alone was helpful, having a sense of community” (P19). Rather than discontinuing use, some participants noted that their use patterns changed as their needs shifted over time: “I do use them now but not really in the same way” (P2).While some participants described current use of online communities to connect, most participants reflected on the benefits of these spaces when they were younger, with their utility declining with time. For example, one participant described “When I was younger. I know I did in middle school quite a bit. But the more that I was able to kind of work through … on my own, and make strong, deep bonds with people, I found that actually having the person-to-person connection has been more beneficial to me” (P18). By contrast, for others, it was less about a shift in their needs and more an increased awareness of the harmful qualities of online communities that prompted them to disengage or use them less as they entered young adulthood. Indeed, many participants commented on the potential for negative experiences in these online spaces. For example, one participant notes:Some participants identified that their needs shifted as they developed a greater capacity to manage their mental health. For example, one participant describes “I think eventually I realized that it was just very triggering. Reading about people's sort of own struggle with self-harm just backfired and made me think about it all the more frequently and also gave me new ideas of things to try and that kind of stuff. So, eventually, I was like, I can't. I can't do that anymore” (P5).“In sum, while technology was part of participants' self-management process, our participants described use for information and support in the early phases of their NSSI, with a change in use as their needs evolved.Findings up to this point provide critical context for understanding how to support young adults in managing NSSI and mental health. In the remaining sections, we shift focus to participants' ideation on the use of technology to help them work toward their NSSI goals. Below we report on two major themes with multiple sub-themes: (1) What participants would like to receive through the technology, and (2) How they would like to engage with the technology, including perceived facilitators and barriers to engagement and usefulness.Here, we describe three desired components of a digital intervention for young adults who self-injure, including: (1) safe connection to social support, (2) tracking patterns for improved self-knowledge and personalized recommendations, and (3) varied support for mental health and NSSI-specific needs.Participants expressed a desire to connect with others who have shared experiences with NSSI, but in a way that differed from prior experiences in online communities or support forums. While connecting with peers online helped address issues of loneliness and validated their struggles, they reported trouble leveraging this beneficial support to make concrete changes in their self-management in daily life.help[s] a lot, especially when they struggle, they not only struggle with self-injury, but other things like, certain trauma or something like that. But it really feels like you can connect with the other person even though you're not talking to them” (P20). For this participant part of the value of hearing from peers was in recognizing her story and struggles in theirs. Knowing that peers shared common demographics, or mental health histories  made their advice more credible. On this, one participant described his connection to peer stories like this:The usefulness of hearing peer stories, particularly strategies or activities peers engaged in to meet their goals, was unanimously supported. For instance, a participant described that hearing peer stories “if we have a lot of similar characteristics, I tend to listen to their stories more closely. And I tend to find a lot of their solutions are very personal to them. And I assume that if we share a lot of the same characteristics, maybe they could be personal for me, too. So, I try to see some very specific things that people have done… something that [is] smart and intuitive and knew what's gonna work on a 19-year-old is not gonna work on a 40-year-old and vice versa” (P12).“If you had them, the people with similar experiences, input their suggestions into the app, and then have those suggestions be reviewed, and then go through a process where they can be spit back out at people who need suggestions. To better manage the stuff that they have going on” (P15). Building on a similar idea described another participant that a network of users could generate a bank of content for on-demand suggestions or support.Participants imagined that social support could be delivered in an app format to capitalize on the benefits of peer support , while also promoting a sense of autonomy in their efforts toward better health and protecting against the harms. One participant described a suggestion feature where they could share and learn about different strategies that have worked for peers with similar characteristics: “In general, participants felt it was important for any future digital intervention to incorporate the benefits of peer support in a format that could reduce the harms associated with open online forums, and enable autonomous interaction with the app.via online sources, one participant described the promise of an app with tracking functionalities like this:Participants hoped that the app could help them understand and track patterns, which could increase self-knowledge and be used for self-diagnostics. Participants who did not have a clear understanding of why they engaged in NSSI, thought it would be useful for the app to track (passively and actively) emotions, behaviors and contexts uniquely associated with their self-injury in order to receive personalized insights or recommendations. When comparing his experience receiving generic solutions offered If there would be a complex step-by-step process on what you can do, I would actually appreciate it a lot. Because I find these solutions, like the ones I mentioned before, they don't really solve the root of the problem. They're temporary fixes. And if you actually wanna defeat something like this, you have to really get to the root of the problem and work on very specific solutions. I don't know what they are at the moment. I can't really help myself, of course. But if there was something that could help me do that, I would appreciate it.” (P12)“Different coping skills where you'd have to do them over time to see if they would be effective for you. So, then, it would help a person keep track to see if it worked for them” (P14). Participants were also willing to put in effort to get good insights if they could help them navigate distressing future situations:As reflected in the above quote, many participants expressed a desire to respond proactively to urges and a need to identify “root problems,” which we understood to mean things that made individuals vulnerable to NSSI in the first place. There was an expectation that such tracking would lead to more specific and personalized strategies, that they could then use and gather additional data on. On this, one participant that the app could both teach, and log the use of, new strategies: “If it had the option of putting more things in, you get to, obviously, learn more, like if it had a option of, briefly, what you did that day. If there was just certain things you could click like stayed home, went to work – things like that – I feel like it would more, too, to realize how your moods are affected by the activities you do throughout the day because then you'd realize like, “Oh, when I go to work, I tend to be more on the angry side.” (P19)“Sometimes I try and write down what I'm feeling. I guess it's in the place of just telling it all to somebody and really just getting all my feelings out somewhere.” These participants imagined an augmented app feature that allowed them to record notes in the service of detecting patterns and improving insights. Importantly, though most participants recognized the value of being able to track patterns significant to their own goals and recovery, there is a need to be careful with this feature as some participants reported that self-competition, disappointment or shame could result from seeing declines in progress over time. This is discussed in more detail later.Several participants mentioned using the “notes” feature on their phone to keep track of things that helped them when they experienced urges and saving ideas for future use. For example, participant 7 said: “You could have some sort of activity within the app that takes 10, 15, 20 minutes, however long, because I think for a lot of people… oftentimes the urge will pass within 20, 30 minutes, an hour, so if they get over that hump, then they're fine” (P5). She goes on to clarify “that doesn't work for everyone, but for some people, I think it does. So, having some sort of engaging activity that you can do easily, just laying in bed or sitting at your desk, for however long you need, I guess, until you're done, would be helpful” (P5).Finally, participants wanted the app to have on-demand activities that could help them de-escalate the intensity of their thoughts, emotions, or urges. One participant described: “As the quote highlights, activities need to be varied in length and easily completed. For others it was more important that the app could connect them to activities that would generate or shift specific emotional states.sadness app where I go when I'm sad. It could also just be somewhere that I also associate when going when I'm in a good place” (P13). The inclusion of resources related to other mental health symptoms, was particularly compelling for those participants who understood their NSSI behaviors to be a symptom of a broader problem. Participant 7 describes,Nonsuicidal self-injury is often cyclical and long gaps can exist between episodes of NSSI behavior. This fact was reflected in participants' desire for the app to contain content and strategies for periods of more frequent and intense NSSI, as well as content and strategies that could help them with a broader range of mental health outcomes and goals. As one participant described that it should not be a “I would like to probably engage with it every day including days when I'm not feeling negative. I think in that case, that would be when it would be the most effective. Because sometimes, it feels really, really silly to be in such an awful, terrible mood, and downloading an app. A lot of times … they'll be like, “Hey, we haven't seen you for a week. How you doing?” And it's like, “I'm doing awful.” And then in that case, when I'm feeling very bad, I think I'm more resistant to help and reframing my thoughts and thinking positively. So, I think if it was something more like a routine, if I did it when I felt very good as well as when I felt very bad, then it would probably be more effective for me.”“: “Usually, if I have the urge, then I will engage in self-injury. I try to avoid having the urge because once I do, it doesn't feel like there's much I can do to get rid of the urge without actually acting on it” (P5). Similar reflections were noted by other participants who identified their goal as not having the urge to self-injure in the first place.In addition to diversifying content based on mental health needs, participants desired for the app to support them in meeting shorter- and longer-term goals which meant it should have resources for imminent distress as well as maintenance. One participant notes the need for features aimed at maintenance like thisFinally, in addition to describing what would be helpful in an app to support NSSI self-management, participants provided insight on specific features or interactions that would either encourage or dissuade them from app use. We report on two key sub-themes related to: (1) facilitators and (2) barriers to use of an app in the following sections.I think definitely talking to a robot or something along those lines would help me feel a lot more confident expressing myself because I don't have to worry about how it's gonna be received. I could just get the solutions, be very honest to myself and to the person behind it, and move forward from there” (P12). Another participant similarly commented:Common facilitators to app use included interactions that respected and reinforced autonomy and features that provided incentives and positive reinforcement. Participants consistently described the need to feel autonomy when interacting with the app, and in their mental health management. While they appreciated the idea of the app making suggestions for how to manage NSSI, they needed to feel like the decision to engage in new strategies was ultimately theirs. Indeed, participants described the imagined app as assisting in self-regulation, and that a fully automated app would allow them to express themselves more honestly and freely: “I feel on an app it's more personal. It's yourself making you do it kind of thing, but if it's not on the app and like someone else is telling you, ‘Hey, maybe you should…’ for me, it gives me more of like, why? Now I really don't want to, because someone's saying like, ‘Hey, go do this thing’ But like, in my own head, like, Hey, maybe you should, or being pushed by the app to make me think positively” (P4).“I can imagine maybe it to be nice to have a mental health professional accessible. I can't really think of what I would use it for, but I can imagine it being probably helpful. But I don't think I'd like to have other people involved in my thing” (P13).The idea of an app utilizing data that participants input themselves , made receiving suggestions more palatable than if they would have received that information from another person who did not have their exact set of experiences. Though many participants recognized the value in having peers or professionals involved, they overwhelmingly expressed a desire to use this app on their own and described concerns about privacy and safety that might make them disengage. One participant said “I always like things that monitor your progress and sort of celebrate whenever like…you know, it'd be cool to have an app … that celebrated every day you were clean, and sort of kept track and that didn't make you feel guilty when you relapsed or whatever. Like, something to encourage you to feel proud of yourself for not self-harming” (P20). However, others were skeptical about the effects of positive reinforcement, saying that this type of feedback could come across as silly or patronizing if not designed with a clear attention to detail. Indeed, participant comments were highly varied on the types of messages they would like to receive as incentives or reinforcements when interacting with the app.Incentives were also mentioned as a way to motivate users and encourage app use. Participants described that the app's benefit needed to be apparent in the initial interactions to prevent early disengagement. As a solution, participants recommended an incentive structure where they would be provided with positive reinforcement when engaging in activities that were aligned with their goals . One participant described, “Despite general interest in using an app that could help them to achieve their personal goals, participants reflected on common barriers to app use as a result of their prior use of other apps, and anticipated use of a new app with a new app. Consistent with the facilitators participants described the failure of the app to bring new insights and patronizing comments or features as barriers to use. Participants noted three additional barriers including a carry over-effect, , notifications without proper context or personalization, and preferences for in person support.Many participants described a carry-over effect that involved negative bias toward apps based on past experiences with ineffective digital tools. Further these biases would need to be disconfirmed in early interactions, since participants would have little tolerance for the use of resources that were not helping. On this several participants expressed concerns that an app would provide them with ineffective or generic, recommendations that they had already received elsewhere. For example, one participant described:Well, it's really like the social media stuff that I was talking about earlier … and I have kind of put that, well it's always going to be like that or going onto Google, it's giving only things that don't really help. In my mind, I'm just kind of – I am assuming like every app and everything like that is going to be oh, just write down your stuff or oh, do a little color sheet or something” (P4).“I just kept seeing a lot of the same information and suggestions for a long time. And I think, at that point I had known that they didn't work or apply to me very well, and they worked for other people. I think I was kind of like, “Well, I've seen all there is” (P7). This failure of apps to bring new insight was the most commonly referenced barrier and cause for past disengagement.Similarly, another participant described prior use of an app that supplied stale suggestions, “In addition to fears of an app bringing more of the same , a common anticipated barrier was that app-based communication  could be belittling or patronizing. Participants were particularly concerned that an app could make them feel childish if it congratulated them on certain things or was too “cutesy” in its presentation of material. On this, one participant described:I don't use any of the tracking apps or anything like that. I know a lot of people I do. I never got – it felt too self-congratulatory for me to get myself to use one. –It's like, “Good job. You didn't do this, or this, or that for three days. Good job.” It's like I'm not a baby. I don't need to be congratulated for doing something that like nobody else here is doing.” (P11)“While this participant describes these types of encouragements as a cause for disengagement, others saw them as potentially incentivizing. There were similarly mixed feelings on whether the digital tool should include notifications, or “pull elements” that would initiate interactions in moments when participants were not directly engaged with the app. Though most participants understood the utility of notifications to keep them engaged, motivate them toward their personal goals, and increase self-awareness, they also cautioned that this type of feature could become annoying, burdensome, or exacerbate feelings of guilt for not achieving their goals. As an example of the complicated nature of participant feelings around notifications, one participant described:So, My first Instinct Is to say, “No Notifications,” but Then My Other Feeling Is, if I'm not Regularly Using It or Regularly Thinking About It, I'd say I'd Go six Months Without Self-Harming and Completely Forget About the app on My Phone and Then Experience an Urge, Chances Are I'm not Going to Think to use the app Because I Haven't Used It in so Long or Thought About It and It Hasn't Reminded Me to Check in. So, That's a Really Tough Question. I'm not sure” (P5)“This participant's comment additionally reflects the perceived benefit that could be derived from the app serving a purpose in periods of more frequent NSSI episodes as well as periods when NSSI was not at the forefront of their concerns.My first instinct is to say, if I'm getting messages or notifications, I'm more likely to start thinking, and I'm not thinking about self-harm at all, and then I get a notification from an app that has to do with self-harm, I'm going to start thinking about self-harm” (P5). Though research has shown that studies utilizing such prompts on suicide and self-harm through ecological momentary assessment do not increase likelihood of harm  or tied to an “app for self-injury” might increase thoughts of NSSI. On this one participant said: “ of harm –43, thisIt'd definitely be other people in my life and not a technology thing or anything related to that” (P2). However, even in these cases participants recognized this as a deeply personal preference and noted the potential usefulness of an app for others who did not have access to such supports or were disinterested in in-person support.Finally, in a small number of cases participants expressed a preference for in person support and did not feel that an app would be a good solution for them at this point in time. For example, one participant felt interpersonal relationships were key to her recovery. She described that if something was going to help her with self-management, “The current study contributes to the literature a more nuanced understanding of the self-management practices of young adults with lived experiences of self-injury, as well as their current and desired use of technology to support these practices. While at a high-level many of these findings are consistent with existing literature on the NSSI recovery, they also extend our understanding of young adults' needs and contribute new insights on how they would like for their needs to be addressed within the design of technologies to support them.We found that technology use was implicit in many of the activities participants endorsed to reduce NSSI thoughts and urges. Participants commonly accessed NSSI information and support through the internet, even if the usefulness of such online engagement shifted with time. Our findings both highlight young adults' interest in, and willingness to try, a digital intervention (like an app) to support them in reaching their mental health goals and call attention to factors that could enhance or impinge upon the utility of such a tool. In the sections that follow we describe findings with implications to guide the design of digital interventions for this population.Despite interest in trying a digital tool to support NSSI self-management, many participants described that they would approach the app with biases from prior experiences with digital resources. This finding underscores the importance of designing to enhance early engagement and satisfaction, prioritizing user needs and goals early on, and making sure that users receive feedback that is personally relevant.design flexibility, which can enable digital interventions to be reconfigured to meet the needs of the user via a person-centered approach.While personalization, attuning to a clients' needs and motivations, is an inherent part the therapeutic process, it is challenging to accomplish within fully  automated digital tools. The variability participants' expressed in terms of goals and their experiences of NSSI aligns with a shift toward a person-centered understanding of recovery from NSSI –47, and Historically flexibility was discussed in the field of engineering in terms of the ability of a system or product to change and adapt to a range of conditions , and accApproach flexibility refers to the ability of the tool to frame and present content in a way that is appropriate and acceptable to users. This includes a consideration of user needs, goals, and motivation, and is necessary to mitigate early discouragement and disengagement with the tool. While the psychotherapeutic approach that informs the digital tool  should remain consistent across tool instantiations (so as to not jeopardize the integrity of the intervention model) the way content is delivered should be flexible to account for individual needs. This may include tailored sequencing of materials to prioritize areas for personal growth. For example, during onboarding an app could collect information on participant's NSSI history, and use of strategies to provide a sequence of strategies that build upon their strengths, and fit with their unique profile.Individual experiences of NSSI recovery are nuanced and often include other facets of well-being such as healthy relationships, daily functioning, and acceptance . ConsistInteractive flexibility refers to how a user would like to interact with the app, including frequency of contact and language use if there is a dyadic component. Such flexibility can be accomplished by allowing users to adjust the frequency of use by choosing notification timelines that feel appropriate for their unique threshold of contact. Additionally, though all participants reported some desire to shift away from self-injury over time, albeit with expressed ambivalence, the language participants used to talk about their goals reflected different orientations toward NSSI as a target of intervention. As in prior work , 47, somIn addition to approach and interactive flexibility, apps must be responsive to shifting needs within an individual's own recovery. This refers to temporal flexibility, which may include allowing users to set multiple short- and longer-term goals that can be adjusted as their needs shift. Designing digital tools with logic patterns and inputs that allow individuals to adjust criteria about their goals, their readiness to change their behavior, and their need/desire for contact  over time, is one way to protect against an app feeling generic. Another option may be to use automated methods to detect shifts in language  to adapt recommendations over time.In sum, design flexibility both in terms of individual goals and where individuals are at in their NSSI recovery trajectory were desired.There was unanimous support for the value of an app connecting users with coping strategies tailored to their unique presentation of NSSI. This is not unsurprising as enhanced self-knowledge and tailored recommendations may increase the likelihood that an individual is able to use a coping strategy that works for them in moments of distress, and subsequently improve self-efficacy. Participants described many functions for their NSSI behavior, as well as different triggers, and activities they tried to reduce or manage these triggers. As such, generic advice was not generally thought to be useful. Many participants were excited about the possibility of an app that could improve upon traditional recommendations found in online forums or from other informational resources . There was interest in the use of tracking patterns and use of coping skills either through self-report monitoring or passive sensing to detect patterns and provide feedback that could increase self-knowledge and capacity to regulate over time. This desire for tracking is consistent with recommended therapeutic techniques like chain analysis from DBT , as wellDespite the perceived value of tracking, participants expressed reservations on the tracking of self-injury behaviors, as in other work . ParticiIn addition to better understanding their behavior, participants wanted to act on these new insights, especially in moments of acute distress. This finding aligns with past work , 33, andFinally, most participants relied on avoidance-based coping strategies , which had some short-term efficacy but did not work reliably and left them feeling unsatisfied. While features that could help users distract were desired, a digital tool may be help users acquire and practice strategies with longer-term efficacy. For example, approach strategies, like problem-solving, have been empirically linked to less NSSI risk . Thus, dOur findings also provide new insights on how and why peer support was helpful for participants, and how their desire for peer support shifted over time. For many participants online peer support was especially helpful when they were younger or earlier in their recovery process. However, most participants felt that after a period of using social media or peer support forums the advice they received became stale or they noticed ways the content shared was harmful, or not conducive to their recovery. Despite noting that this format of peer support lost some benefit over time, participants still reflected on the value of knowing that they were not alone, the validation they received, and increased understanding of their own struggles through shared stories. One solution participants described to circumvent potential harms of an interactive interface with other individuals who struggle with NSSI, could be through sharing content and peer stories.+) and experiences . That is, participants felt that peer stories could be used to inform algorithms within the app to tailor recommendations based on the likelihood of a certain strategy or recommendation being relevant to a user. One way to do this may be to crowdsource peer stories and infer distinct user profiles. While there are limits to this approach, future work may wish to consider whether there are distinct profiles of individuals that may benefit from specific skills.Notably, peer stories were imagined as a means to combat feelings of loneliness and provide participants with validation, but they were also cited as a data source that could be of use to improve that app-based suggestions would resonate with individual users with similar characteristics .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Then, we conducted hotspot and trend analysis with LDAPR and carried out further studies, including annual hot topic extraction, a 10-year keyword evolution trend analysis, topic map construction, hot region discovery and fine-grained correlation analysis of interdisciplinary research topic trends. These analyses revealed valuable information that can guide epidemic prevention work: (1) the research enthusiasm over a certain infectious disease not only is related to its epidemic characteristics but also is affected by the progress of research on other diseases, and (2) infectious diseases are not only strongly related to their corresponding microorganisms but also potentially related to other specific microorganisms. The detailed experimental results and our code are available at https://github.com/KEAML-JLU/Biosafety-analysis.Coronavirus disease 2019 (COVID-19) has infected hundreds of millions of people and killed millions of them. As an RNA virus, COVID-19 is more susceptible to variation than other viruses. Many problems involved in this epidemic have made biosafety and biosecurity (hereafter collectively referred to as ‘biosafety’) a popular and timely topic globally. Biosafety research covers a broad and diverse range of topics, and it is important to quickly identify hotspots and trends in biosafety research through big data analysis. However, the data-driven literature on biosafety research discovery is quite scant. We developed a novel topic model based on  Related2000 Cartagena Protocol of Biosafety [With the development of biotechnology and the advancement of globalization , 30, theiosafety , many coiosafety  and biosiosafety  have alsinfectious diseases , 66 758 biosafety-related papers have been published in the last 10 years. For researchers, it has become a great challenge to quickly and effectively identify the latest research progress and results from among the tens of thousands of publications. Additionally, extracting the research hotspots and predicting trends are difficult problems.With the development of biosafety research, related papers and data have been produced at a speedy rate. In PubMed , the affinity propagation (AP) algorithm and the hierarchical PageRank algorithm) to extract the topics of these abstracts. Figure In response to these issues, we collected the abstracts of biosafety-related papers released in the past 10 years from PubMed and designed a novel topic model called LDAPR ’, ‘Crimean-Congo hemorrhagic fever virus’, ‘Ebola virus’, ‘enterovirus’, ‘hepatitis A virus’, ‘human adenovirus’, ‘Middle East respiratory syndrome coronavirus (MERS-CoV)’, ‘rabbit hemorrhagic disease virus (RHDV)’, ‘Zika virus’, ‘aureus’, ‘Bacillus subtilis’, ‘Brucella’, ‘Campylobacter’, ‘Clostridium’, ‘cyanobacteria’, ‘Escherichia coli’, ‘Klebsiella’, ‘Lactobacillus’, ‘Lactococcus’, ‘Listeria monocytogenes’, ‘meningococcus’, ‘Salmonella’, ‘Serratia marcescens’, ‘Streptococcus pneumonia’, ‘Candida’, ‘Cryptococcus neoformans’ and ‘Pichia pastoris’. These can be divided into three categories: bacteria, viruses and fungi. For example, To learn more regarding the research relevance of various microorganisms, we used the microorganisms obtained from the data as keywords to search PubMed, processed the data with LDAPR and then searched for other microorganism keywords in the results. Finally, we used the chord diagram in Figure Listeria monocytogenes and Salmonella are food-borne pathogens that cause diarrhea and other symptoms [We found that the co-occurrence of microorganism-related keywords is closely related to the similarity of the microorganisms’ characteristics. For example, symptoms .Biosecurity accidents are often accompanied by outbreaks of epidemic diseases, so we studied disease-related keywords and derived statistics on the results. Figure ‘Listeriosis’ and ‘paratyphoid’ appear in all years. These are two common serious diseases caused by food safety problems. ‘Influenza’ appears eight times in 10 years. The prevention and control of influenza is thus an important topic in biosafety research .By comparing the annual occurrence of microorganisms, it can be found that there is a strong correlation between diseases and microorganisms. For example, ‘meningococcus’ appears in the 2019 keywords, and ‘epidemic cerebrospinal meningitis’, which is caused by it, appears in the same year . In addiIn addition to diseases directly caused by pathogenic microorganisms, the frequency of the co-occurrence of certain diseases and other microorganisms is very high. For example, influenza and some infectious viruses often appear simultaneously. Viral infections usually cause influenza or are similar to influenza. The flu season is also when viruses spread most rapidly. On the disease side, the appearance of Listeria infection and paratyphoid are very similar. We can speculate that there is a close relationship between these two diseases. Trichinella and tularemia also have similar distributions, but the frequency of Trichinella infection is significantly higher than that of tularemia. Based on this, we conclude that tularemia is more likely to occur in groups at high risk for Trichinella infection, which has been confirmed by related studies . On the It is widely acknowledged that biosafety research involves a variety of disciplines. From the results, we select each year’s disciplinary keywords for analysis; these are displayed in Figure We found publications from 2013 and 2020 corresponding to six disciplines, with the results in each year involving a variety of disciplines. Among them, publications from 2019 cover only two disciplines. ‘Biochemistry’ is associated with publications from 7 years , ‘microbiology’ with publications from 7 years  and ‘pathology’ with publications in 2018 only.Biosafety issues and related studies have strong regional characteristics. In Figure Biosafety research is developing continuously, with many new research results appearing every year. To identify development trends, we collected keywords for each year separately. If we take 2017 as an example, the topic results are shown in the first subtable in Table Nature in October 2016 studied the impact of self-organized ecological factors (pollen flow) on biosafety [From the results over the 10 years, we can observe the following: (1) ‘Cell’ always appears as a central keyword. It can be inferred that most of the research on biosafety is centered on cytology. (2) Words related to diseases, microorganisms, chemistry and disciplines appear in high proportions every year, indicating that these are long-term themes of biosafety research. (3) Biosafety is a discipline closely related to events. In addition to long-term research topics, there are some keywords related to public health emergencies, such as the keywords ‘coronavirus’, ‘pneumoniae’ and ‘vaccine’, which appear in 2020 and are closely related to the outbreak of COVID-19. (4) New research findings also bring about changes in research trends. For example, we found the term ‘pollen’ in the results for 2016 and 2017, indicating that research on pollen in the field of biosecurity may have delivered new findings. We then found evidence to support this speculation: the article ‘Pollen-mediated gene flow and seed exchange in small-scale Zambian maize farming, implications for biosafety assessment’ published in the journal To study the distribution of topics over the decade, we used LDAPR to process all the data and obtained 12 central topics. Then, we sorted these topics with their PageRank values. The results are shown in Figure Each word cloud represents a topic, and each topic corresponds to one or more of the topics in Figure important topic in biosafety research . With thTo validate the ability of our model to reflect emergency biosafety incidents, we performed an analysis of COVID-19-related research publications.We align the results with the COVID-19 knowledge graph from  and showhttps://biopython.org/) as an input. First, we use LDA to obtain preliminary topic results [As shown in Figure  results , train a results , 41 and  results . Third, LDA, a well-known unsupervised probability model for text topic extraction based on the Bayesian model, was proposed by Blei et al. in 2003 . Its maiLDA divides the text content into three levels, namely, documents, topics and words, and expresses each document as a distribution of topics: To obtain the final topic results, we chose the Gibbs sampling method based on Markov chain Monte Carlo (MCMC) to estimate the LDA model .PageRank is a webpage ranking algorithm proposed by Page et al. in 1998 . It usesyperlink , 71. TheIn general, the PageRank algorithm uses more practical matrix operations to achieve the same effect. It can be expressed as Through the above formula, the PageRank value AP is a graph-clustering algorithm proposed in 2007 , 37, 73.There are four main parameter matrices in the AP algorithm: similarity After the iterative update, we calculate the sum of each pair of We obtained the abstracts of 66 758 related papers published during the past 10 years from the biomedical database PubMed. The keywords included ‘biosafety’, ‘bio-safety’, ‘biosecurity’, ‘bio-security’, ‘biological safety’ and ‘biohazard’.The statistical results show that with the development of biotechnology and increased social attention to biosafety-related fields, related research is also increasing. Figure The original data obtained from PubMed are natural language text and contain a great deal of noisy information. To achieve better results for subsequent work, we preprocess the data with natural language processing tools .Next, we introduce the main part of the model. The structure and flow of this part are shown in Figure We connect all topics in pairs and use the cosine similarity between their topic vectors as the weights of the edges to construct an undirected weighted graph. The formula is as follows: https://www.keaml.cn/Biosafety/) .Then, we use the AP algorithm to cluster the remaining topics and select the central topics of each category as the representatives. Subsequently, we redecouple each central topic as a set of topic words and construct word networks with weighted edges from Equation We tune the hyperparameters of the model based on perplexity , 15)\do\do(15)\dRandom, LDA and PLSA as the baseline models to compare with LDAPR. The results of perplexity and clut[K-means, 67; we To discover more information, we expand the numbers of topics and words. Specifically, we use the selected keywords to filter the results and calculate the weight Taking bioinformatics frameworks and tools as an example, we use relevant keywords to search, and the results are presented in Figure In this paper, we proposed a novel LDAPR framework based on LDA, AP and the hierarchical PageRank algorithm to summarize and analyze trends in biosafety research over the past decade. We processed 66 758 papers in related fields and visualized and fully analyzed the results. Studies in related fields support our results, which proves the comprehensiveness and accuracy of our method. The research objects of this experiment covered many areas. Among them, we focused on the microorganisms, diseases and disciplines associated with biosafety research. We discovered many implicit connections among these categories and extracted valuable information that is expected to be useful for research. We believe that the LDAPR model can play a guiding role in trend analysis for bodies of biosafety literature and can shed light on the future directions of biosafety research. For example, it can be seen from the results that research on microorganisms, especially infectious disease viruses, has gradually become an important research hotspot. Genes and vaccines are increasingly becoming the topics of greatest concern in biosafety research.With the outbreak and spread of COVID-19, biosafety has become a global hot topic, and a large number of related studies have emerged.Compared with other research domains, biosafety research covers more fields and more disciplines. Therefore, it is difficult to systematically organize and summarize the enormous number of related research papers.We developed a novel topic model: LDAPR. We utilized this model to process biosafety-related papers in the past 10 years and to discover and analyze trends and hotspots.We discovered a large number of implicit relationships in the data and demonstrated their authenticity and accuracy via relevant studies.The proposed model can also be applied to many research fields and can provide valuable information for future research.


Pregnant women are at greater risk of adverse outcomes from SARS-CoV-2 infection. There are several factors which can influence the ways in which pregnant women perceive COVID-19 disease and behaviorally respond to the pandemic. This study seeks to understand how three key audiences—pregnant and lactating women (PLW), male community members, and health workers—in Kenya conceptualize COVID-19 to better understand determinants of COVID-19 related behaviors. This study used qualitative methods to conduct 84 in-depth interviews in three counties in Kenya. Data were analyzed using a grounded theory approach. Emerging themes were organized based on common behavioral constructs thought to influence COVID-19 related behaviors and included myths, risk perception, economic implications, stigma, and self-efficacy. Results suggest that risk perception and behavioral attitudes substantially influence the experiences of PLW, male community members, and health workers in Kenya during the COVID-19 pandemic. Public health prevention and communication responses targeting these groups should address potential barriers to preventive health behaviors, such as the spread of misinformation, financial constraints, and fear of social ostracization. SARS-CoV-2 has impacted every corner of the world. In Kenya, the first case of SARS-CoV-2 infection was reported on 13 March 2020  because I am a human being and I breathe and I have a future…They say that it is an airborne disease and I breathe that same air. You can be any person, you will still get infected”.Pregnant women and lactating mothers spoke to their unique susceptibility to the disease for various reasons. For one, pregnant women and lactating mothers perceived a risk of transmission from mother to fetus or child. As these lactating mothers put it: “If [COVID-19] infects a breastfeeding mother like me, the baby will definitely be affected” (Nairobi) and “If I get Corona, my child will also get it… And also the expectant mother. If she gets [Corona], even the baby inside will get Corona” (urban Kakamega). Additionally, pregnant women and lactating mothers both perceived themselves and were perceived by others as having greater susceptibility to COVID-19. This pregnant woman from rural Kakamega describes the risks of socializing for PLW: “[Pregnant women and breastfeeding mothers] are in danger because when they congregate somewhere and they do not observe social distancing, they can be infected”. A family member from urban Kakamega reinforced this notion: “The reason as to why I say that [pregnant women] are at a bigger risk of contracting Corona is because when they walk around and meet other people, you know women like talking and sitting together, laughing, and touching each other”.Health workers perceived a high degree of susceptibility due to the nature of their work. Although most health workers “try to do self-care” by wearing proper PPE while working, “there are so many things that can make us get it” . Despite these findings, there remained several participants who perceived little risk of contracting COVID-19. For example, this family member from Nairobi shares: “I am not thinking that I will get Corona. First of all, the protocols and guidelines that have been put in place by the health workers is that each one of us should take personal responsibility. You should always wear a mask, keep on washing your hands. So if you take care of yourself, your chances of getting Corona are minimal”.Perceptions of severity were fairly consistent across target audiences. To nearly all who believed in COVID-19, it was seen as a “deadly” disease. As one lactating mother from urban Kakamega put it: “COVID is deadly. You can suffer for 3 days or even just a day and then you succumb to it… It causes death and it leaves other people behind who are so helpless”. Health workers echoed this notion, as one from Garissa shared: “[COVID-19] can kill you instantly if you joke with it. So, I think it is very severe. It is a killer disease”. For this gatekeeper in Nairobi, the lethality of COVID-19 is readily apparent: “It is now said that COVID-19 has taken center stage because we no longer have a hearse which is not booked”.Some participants elaborated on the severity of the disease, noting how severity can be exacerbated by co-occurring conditions. For instance, this family member from Nairobi shared this belief: “People say that if you have other underlying illnesses, it will kill you”. A neighbor from rural Kakamega echoed this fear: “You know, we have different diseases. You may get a heart attack or cancer, so if you are infected and you have an underlying condition, you may not make it. That is the fear we have at the moment”.Aside from the health implications of the COVID-19 pandemic, participants described several non-health related challenges that have emerged. Economic downturn and financial hardship resulting from the pandemic was a recurring theme across all participants. As one family member from Nairobi summarized: “Before Corona came, business was good, life was good, even traveling was good. Everything was OK. But when it came, it destroyed everything. The economy has crumbled, people have lost their lives, they have left their families, and you cannot interact with your family well”.When asked how COVID-19 has affected their community, participants most commonly reflected on employment. This lactating mother from urban Kakamega describes her personal experience with economic hardship resulting from the pandemic: “The impact of COVID-19 on my daily responsibilities as a young woman, I have to close down my business… If I am a working-class lady, I will have to at least miss going to work. I will be given compulsory leave and when you come back you find that you have already been replaced at the job. You find you are back to stage one… So with COVID, you will not even be able to protect your job, to protect your daily income, to protect the people you love, and also your daily life. It will all be affected”. Similar stories of job loss and business closures were widespread across the data.Although many participants attributed these challenges to self-isolation from a positive test result, others pointed to certain aspects of the community-level pandemic response. In particular, several participants suggested the nation-wide curfew, negatively impacting local businesses. This lactating mother from rural Kakamega describes her experience: “COVID has negatively impacted our economy. Recently, there has been a curfew and many people survive from hand-to-mouth. They need to go out to work and you realize that people are told to stay at home. There are those people who work at night, but they are told that the curfew begins at 7:00 P.M. There are those who sell vegetables who come to the market at 6:00 P.M. and they expect to be selling up until 8:00 P.M., yet curfew begins at 7:00 P.M. That has really impacted our economy”.In addition, pregnant women, lactating mothers, and health providers reported experiencing or observing others struggle with medical care costs. As this lactating mother from Nairobi put it: “Yes, [COVID-19] is a problem because if you contract it, there are expenses. The expenses of taking care of a COVID-positive person is so expensive”. A health worker in Garissa elaborated on this dilemma, explaining that: “People are spending a lot of money. Some have traveled to hospitals in Nairobi, some are spending many days in the wards in our referral center, and some are dying. So, it is impacting the community in many ways”.Participants described a societal inclination to avoid and, in some cases, completely ostracize individuals who contract COVID-19 to avoid transmission. Societal stigma against COVID-positive people was a prominent theme that appeared across all target audiences and geographies. As this family member from Nairobi summarized: “[A COVID-positive person] is viewed as someone who is no more. You are isolated. There is no one who will come near you”. This lactating mother from Garissa shared the extent to which her community fears even the objects touched by a COVID-positive person: “[The community] cannot accept him. Even now as we speak, they are scared of the cup he used to drink from… just like the disease itself”.In many cases, this stigma permeated families to the point that, even following recovery, spouses and other family members were afraid to re-integrate them into the home. As this health worker from rural Kakamega described: “[Families] normally abandon [relatives with COVID-19]. They won’t want to associate with them. There was one case when the patient was discharged, the relatives told us they don’t want that client to go back home because she will infect them. So, we had to arrange for a facility-based care at another facility until the patient recovered”.For several participants, the tendency to stigmatize COVID patients was compared to former stigmatization of HIV-positive people in their communities. As this lactating mother from Garissa put it: “In the past, there was stigmatization of HIV, but nowadays, it is Corona. If you hear that someone in your family has died or recovered from Corona, people will not even come to greet you”. One gatekeeper from Nairobi expanded on this, explaining how comparing COVID-19 to HIV can have a stigmatizing effect on the entire family: “Initially there were a lot of myths… Just as somebody with HIV was taken as a burden by the community, so is the person with COVID-19, because the moment COVID-19 is prone in a family or household, that would be the start of the end to the family. In terms of the care and support that these people require financially, physically, emotionally, spiritually, it is not easy. It would be seen as a draining of resources to this particular family… So people are like, ‘Can we leave them for dead?’ and so on”.Stigmatization of COVID-positive people as a form of prevention was noted as having harmful, lasting implications for those stigmatized. Participants expressed that the marked manners in which their communities are responding to COVID patients and survivors is causing degradation of their mental health to such an extent that, “when we isolate [COVID-positive people], we kill them” . This family member from urban Kakamega shared how he imagines stigma from COVID-19 evolves: “One feels that there is no hope to live. Their self-esteem goes low. Some will feel like they don’t have the immune system to fight Corona, so he pulls himself down and maybe it was not time for him to die, but depending on how that person’s mentality is, it may kill him because he will feel he does not have hope and he panics”.In terms of one’s perceived control over protecting oneself and others from contracting SARS-CoV-2, participants had differing perspectives. In some cases, PLW and male community members described feelings of powerlessness and inevitability which stemmed from religious beliefs. As one male family member succinctly put it: “[COVID-19] is something that only God can prevent… COVID-19 here in Garissa is very high, so we just pray to God for help”. A lactating mother in Nairobi agreed, stating: “[COVID-19] is a problem because when it’s in the community, it’s only God who helps. Others will get well while others will die”. In other cases, participants reported structural barriers which prevented them from adhering to risk-reducing activities. For some, the costs of necessary products like soap and sanitizer were unaffordable: “You will find that somebody can easily lose his or her life just because of Ksh.10” . For others, the task of maintaining social distancing was unrealistic given their community’s living conditions. As one community member in Nairobi stated: “In these one-roomed houses with children and parents, it is a very big challenge. You maybe share toilets, bathrooms, shops. Basically, you do things together, so it is very easy for the disease to spread in the community”.Health workers also described a lack of control when it came to preventing transmission in their health facilities. Despite providing protective and hygienic resources such as masks, soap, and hand sanitizer to patients and other visitors, health workers reported low use of these resources among the general public. One health worker from Garissa described their frustrations with trying to curb transmission in their facility: “Even at the hospital, those who come do not put on masks. So, it is left up to us  to tell them to put on masks… We have washing stations for hand wash, and they do not wash their hands. We have sanitizers and yet, we are the ones to tell them what to do”.Despite these instances of lower self-efficacy, many participants described how they take control of their risk by adapting their behaviors. PLW often reported that they “don’t go to places where there are sick persons”  and “always have masks on especially when you are in a public place” . One family member in Nairobi explained how taking ownership of one’s own preventive behaviors can encourage others to act similarly: “First of all, you are the one who is supposed to be safe… You have to protect yourself before you tell the others. So, if you are wearing a mask, that is when you can tell your neighbor that Corona is real, that they should wear a mask, sanitize, keep their home environment clean. That is when they will heed”.This study presents the various ways in which COVID-19 is conceptualized among PLW, male community members, and healthcare workers in three Kenyan counties through myths, perceived risk, financial implications of the pandemic, stigma, and self-efficacy.Myths related to COVID-19 were prominent among pregnant and lactating participants and the communities in which they reside. This finding supports prior research which has identified common misconceptions relating to the existence, spread, and weaponized use of COVID-19 in Kenya and the Sub-Saharan African region, suggesting misinformation and misconceptions about COVID-19 are not uncommon in Kenya ,35. ReseParticipants perceived PLW as well as healthcare workers to be highly susceptible to SARS-CoV-2 infection. Similarly, studies across the Sub-Saharan Africa region have shown high risk perception of COVID-19 among healthcare workers ,47,48. IProgram implementers and health communicators should consider leveraging risk perceptions among target audiences in this study to promote compliance with behavioral prevention. Several strategies could be used to do so, such as providing factual information about the burden of COVID-19, using empathy to connect with and express concern for an audience, and communicating a direct and clear connection between behavioral prevention and reduced risk of disease ,52. HoweEconomic hardship resulting from both individual experiences with COVID-19 and community-wide preventive measures was widely experienced across this sample. Namely, participants spoke about the impact of the pandemic on job loss and restrictions to local businesses, causing families to struggle to make ends meet. According to participants, job insecurity was a result of both contracting the disease and the recovery process as well as local prevention measures which restricted business hours and consumer travel. The pandemic’s impact on the economy has not only been felt in Kenya, but across the region ,55,56,57Participants also described pronounced stigma against those who test positive for COVID-19, often compared to the ostracization once experienced by HIV-positive people in their communities. According to our data, Kenyan COVID-19 survivors may experience detrimental effects on their mental health and their social support networks as a result of stigma within their families and broader communities. This stigma has the potential to discourage preventive behaviors critical for controlling the spread of the pandemic, such as screening, social distancing, using proper hygiene, and seeking treatment for positive cases ,60. MoreSelf-efficacy varied among participants, with some describing an inability to adhere to behavioral prevention due to religious beliefs and structural barriers, while others described instances in which they have taken control of their risk of transmission by complying with recommendations. Little research has been done in Kenya to identify structural barriers to nonpharmaceutical prevention strategies. However, one study (preprint) of more than 2000 participants in informal settlements in Nairobi found that despite high awareness of their risk of transmission (83%), 37% and 53% of participants reported access to water and costs as barriers to hand washing and sanitizing, respectively . Across This study is not without limitations. This cross-sectional qualitative study was not designed to be generalizable, and so findings cannot be attributed to settings outside the three counties studied in Kenya and conclusions related to residence  cannot be made. Given the self-reported nature of the study design and the somewhat divisive topic of COVID-19, social desirability bias is likely. Due to the recruitment strategy in which participants were identified through health and family networks, sampling bias is possible. The study was collected during a particular point in time (August–September 2021) of the SARS-CoV-2 pandemic, when knowledge about the disease and governmental vaccination policies were still evolving. During data collection, for example, the Kenyan Ministry of Health issued a press statement that stated that PLW could choose to receive COVID vaccines after counseling, which differed substantially from the previous recommendation which stated that PLW were not eligible for COVID vaccination (February 2021). Additionally, data were collected when COVID-19 cases and deaths were starting to decline in Kenya.Despite these limitations, this study has several strengths. This is one of the few studies that has examined COVID-19 related behaviors specific to PLW and provides additional insight about community members and health workers. Moreover, this study contributes to a growing body of literature exploring social, emotional, and behavioral experiences and outcomes during the COVID-19 pandemic. Findings from this study can and should be used to inform the design and development of tailored communication programs and policies relating to PLW, healthcare workers, and the general public in Kenya.Pregnant women are at high risk of adverse outcomes following SARS-CoV-2 infection, and uptake of preventive behaviors are essential to their and their babies’ health and well-being during the pandemic. To facilitate health prevention among this group, we must first understand how PLW and key stakeholders in their decision-making processes experience and conceptualize COVID-19. This study sought to understand how three key audiences–PLW, male community members, and health workers–in Kenya have come to conceptualize COVID-19 to better understand determinants of COVID-19 related behaviors. Results indicate that risk perception and behavioral attitudes are largely influential in their experiences of the pandemic. The spread of misinformation is contributing to the continued presence of myths which are lessening the public’s perceptions of risk to COVID-19 and adherence to preventive behaviors. Moreover, fear of stigma and economic instability were commonly reported as barriers to testing, treatment-seeking, and social distancing. Addressing potential barriers to preventive health behaviors, such as the spread of misinformation, financial constraints, and fear of social ostracization, will be essential for future public health prevention and communication responses targeting these groups.


There is an increasing demand for multi-agent systems in which each mobile agent, such as a robot in a warehouse or a flying drone, moves toward its destination while avoiding other agents. Although several control schemes for collision avoidance have been proposed, they cannot achieve quick and safe movement with minimal acceleration and deceleration. To address this, we developed a decentralized control scheme that involves modifying the social force model, a model of pedestrian dynamics, and successfully realized quick, smooth, and safe movement. However, each agent had to observe many nearby agents and predict their future motion; that is, unnecessary sensing and calculations were required for each agent. In this study, we addressed this issue by introducing active sensing. In this control scheme, an index referred to as the “collision risk level” is defined, and the observation range of each agent is actively controlled on this basis. Through simulations, we demonstrated that the proposed control scheme works reasonably while reducing unnecessary sensing and calculations. Recently, labor shortages in the transportation industry have become a serious problem because of declining birth rates and an aging population. Although the transportation industry is an important economic sector, workers experience physical fatigue caused by long working hours. Moreover, recent developments in information and communication technology have increased the workload. Therefore, the development of control schemes for autonomous mobile systems such as automated transport robots in logistics warehouses and flying drones is necessary. In these systems, each mobile agent must reach its destination while avoiding other agents. Thus, safe collision avoidance must be considered in the design of control schemes. In addition to safety, other factors can further improve the utility of these systems. Specifically, if the speed of each agent is maintained at a maximum with minimal acceleration and deceleration, that is, if quick and smooth movement is achieved, agents can reach their destinations quickly with low energy consumption.Multi-robot systems have been studied from various aspects, such as formation control , collective transport , and task allocation . Collision avoidance in multi-robot systems has also been extensively studied, and several methods such as path planning using centralized  and deceTo address this issue, we previously developed a simple decentralized control scheme for multiple mobile agents by modifying the social force model , which iThis paper proposes a control scheme for mobile agents capable of enabling quick, smooth, and safe movement with limited sensing capability for each agent. For this purpose, we drew inspiration from the active sensing of living organisms, such as the echo location of bats . Active The remainder of this paper is organized as follows. In N agents are on a two-dimensional (2D) plane with a periodic boundary condition. The position of the agent i is denoted by ri. Although the unit vector ei, which represents the direction in which agent i intends to move, can be varied temporally in a real scenario, it was kept constant in this study for simplicity. The direction of ei is determined randomly, that is, each agent aims to move in a different direction. The target speed v0, that is, the speed in the absence of other agents, is common to all agents. Here, we do not consider the cases in which obstacles exist in the plane.We assume that T denotes the total time of the simulation experiment and i and j collide , is inevitable. However, we attempted to reduce this deterioration to the maximum possible extent.In our previous study , we succIn this section, we briefly review our previous model  Section and propR from itself at every constant time interval.Step (i): Each agent detects the relative position and velocity of agents within a distance T by numerically solving a differential equation in which the social force term is omitted from the social force model, with the initial position and velocity of the agents set to be the same as those obtained in Step (i) (Step (ii): Each agent predicts the future motion of nearby agents for duration Step (i) .i and j has a minimum value or until they collide, τij, is derived : Based on the numerical calculation performed in Step (ii), the expected time until the distance between agents  derived . Furtherτij and τij and Step (iv): The control input is calculated using the values of ce model . It consWe previously modified the social force model , a modelR from itself by solving a differential equation [Step (ii)]. A reduction in the calculation cost is required to consider the hardware implementation.In our previous study , we demoHerein, we propose a mathematical model that incorporates a decentralized control scheme for autonomous mobile agents to achieve quick, smooth, and safe movement with low sensing and calculation costs. For this purpose, an index referred to as the “collision risk level” is introduced for each pair of agents, and each agent is controlled such that it ignores agents whose collision risk level is low. The observation range of each agent is constrained to a fan shape, and its direction is actively controlled to focus on agents whose collision risk is high . Active r and can move omnidirectionally on a 2D plane. Agents have their own destinations, and their task is to reach these destinations without losing velocity or smoothness, while avoiding other agents. It is assumed that each agent can detect the relative position and velocity of other agents within its fan-shaped observation range.Each agent has a circular shape with radius Step 1: An agent detects other agents within its observation range and calculates the collision risk level.Step 2: The agent controls the direction of the fan-shaped observation range to focus on agents whose collision risk is high, that is, it performs active sensing.Step 3: The agent predicts the future motion of agents whose collision risk is high and calculates the avoidance force.Step 4: The agent moves based on the calculated avoidance force.The control algorithm for each agent consists of the following four steps .Step 1: In the following section, each step is described in detail.i calculates the collision risk level between agents i and j, defined as Kij, according to the following equation:α is a positive constant, β is a constant that satisfies 0 < β < 1, i observes agent j, and φij is the range of vision of agent j as viewed from agent i  , which is given by.ɛ, γ, w1, and w2 are positive constants and θi,goal denotes the direction of the destination with respect to the moving direction of agent i. j with respect to the direction of movement of agent i, which is described asri denotes the position of agent i and j with respect to agent i at time t. The derivation of The direction of the fan-shaped observation range with respect to the direction of the movement of agent i < π) . Angle θp is the normalized function of f and f consists of three terms /|rj − ri|, tij is a unit vector perpendicular to nij, dij = |rj − ri|, and θ(x) = x for x > 0 and θ(x) = 0 for x ≤ 0.By modifying the social force model  and usince model  asfijphA and B are positive constants, j. However, when agent j was not within the observation range, a repulsive force was generated using the estimated relative position  and accelerations ai(k) are given by vi(k) = (ri(k + 1) − ri(k))/δt and ai(k) = (vi(k + 1) − vi(k))/δt, respectively.The performance indices In N = 2. The video and snapshots are shown in First, we perform a simulation with N = 20 . Furthermore, because each agent focuses only on agents whose collision risk is above threshold Kth, the calculation cost decreases as Kth increases. Another advantage of the proposed control scheme is that each agent does not need to know the directions in which nearby agents intend to move, . In our previous control scheme, however, it was necessary for each agent to know this information.An advantage of the proposed control scheme is that its calculation cost is considerably lower than that of our previous scheme . Althoug• Limitation of the control scheme: We found that the proposed control algorithm did not perform well when the density of the agents was large. This is likely because the prediction of the agents’ motions was oversimplified. We intend to further improve the control scheme such that its performance is improved without increasing the calculation cost.• Technical problem: It is technically difficult to instantly change the direction of the fan-shaped observation range because mobile robots usually have a lidar sensor that is statically linked to the robot. Thus, the proposed model remains somewhat unrealistic. These problems should be addressed in future hardware realizations.• Further extensions: We intend to extend the proposed control scheme to the three-dimensional case and the case where obstacles exist.However, several problems remain unresolved.