Specific Behaviors Research Articles

Eating behaviors as pathways from early childhood adversity to adolescent cardiometabolic risk.

To identify specific eating behavior pathways that mediate associations between financial difficulties, negative life events, and maternal depressive symptoms from 0 to 5 years and cardiometabolic risk in adolescence. Hypotheses were tested with data from birth to age 15 years using the Avon Longitudinal Study of Parents and Children, a birth cohort in the United Kingdom (n = 3,887 for current analyses). Mothers reported on financial difficulties, negative life events, and maternal depressive symptoms at multiple points from 0 to 5 years and reported on worry about child overeating at 8 years. Youth self-reported restrained, emotional, and external eating at age 14. Youth completed a cardiometabolic health assessment at age 15 where waist circumference, triglycerides, high-density lipoprotein, and insulin resistance were measured. Longitudinal structural equation modeling with bootstrapping was used to test mediation models. Greater negative life events and maternal depressive symptoms predicted greater parental worry about child overeating at age 8, which directly predicted greater restrained and emotional eating at 14 and cardiometabolic risk at 15. Restrained and emotional eating at 14 directly predicted greater cardiometabolic risk at age 15. Negative life events and maternal depressive symptoms in infancy/early childhood are associated with cardiometabolic risk in adolescence through pathways of parental worry about child overeating in middle childhood and youth-reported restrained and emotional eating in adolescence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Source of information, knowledge, and sexual behaviour related to HIV/AIDS amongst university students in an inland territory of central Italy

Italian university students were investigated for: sources of information about HIV, knowledge of HIV risk behaviours, as well as sexual behaviours and condom use. A self completed anonymous questionnaire was administered to 430 university students in Campobasso, Italy (mean age 23,1; males 35,8%). Although TV, radio and the printed press were the most common sources of HIV information (>60% of respondents), most respondents preferred to receive information from physicians or resource centres (50 and 51%). Most students (>97%) were aware that specific sexual behaviours (unprotected vaginal or anal intercourse) and sharing of needles with illegal injecting drug users could transmit HIV. Most students (>50%) did not regularly use condoms (despite understanding their protective effect), and continued to engage in behaviours considered risky. Males were significantly more likely than females to engage in vaginal sex (84 vs. 67%) or anal sex (37 vs. 13%) with both regular and casual partners. Although knowledge of HIV in itself is not enough to produce behaviour change, increases in students’ levels of knowledge may be useful.

Peptide-conjugated Nanoparticle Platforms for Targeted Delivery, Imaging, and Biosensing Applications.

Peptides have become an indispensable tool in engineering of multifunctional nanostructure platforms for biomedical applications such as targeted drug and gene delivery, imaging and biosensing. They can be covalently incorporated into a variety of nanoparticles (NPs) including polymers, metallic nanoparticles, and others. Using different bioconjugation techniques, multifunctional peptide-modified NPs can be formulated to produce therapeutical and diagnostic platforms offering high specificity, lower toxicity, biocompatibility, and stimuli responsive behavior. Targeting peptides can direct the nanoparticles into specific tissues for targeted drug and gene delivery and imaging applications due to their specificity towards certain receptors. Furthermore, due to their stimuli-responsive features, they can offer controlled release of therapeutics into desired sites of disease. In addition, peptide-based biosensors and imaging agents can provide non-invasive detection and monitoring of diseases including cancer, infectious diseases, and neurological disorders. In this review, we covered the design and formulation of recent peptide-based NP platforms, as well as their utilization in in vitro and in vivo applications such as targeted drug and gene delivery, targeting, sensing, and imaging applications. In the end, we provided the future outlook to design new peptide conjugated nanomaterials for biomedical applications.

Associations between adolescent friends' responses during problem talk and depressive symptoms.

The present study examined how friends' responses to each other during problem talk predicted depressive symptoms over time. Participants included 271 adolescent friend dyads (69 female and 69 male early adolescent dyads; 72 female and 61 male middle adolescent dyads; 66.4% White and 26.6% Black). The adolescents were observed discussing a problem with the friend and reported on depressive symptoms at the time of observation and 9 months later. Friends' responses were coded into one of nine response type categories (i.e., four positive/engaged response types, one neutral response type, and four negative/disengaged response types). Actor-partner interdependence models revealed significant actor and partner effects for both positive and negative responses. Notably, receiving and/or producing positive/engaged responses, including saying something supportive, sharing related experiences, and asking questions, were associated with lower depressive symptoms over time. Receiving and/or producing negative/disengaged responses, including sharing one's own experience in a distracting way, changing the subject, saying something unsupportive or minimizing the problem, and saying nothing at all heightened risk for depressive symptoms. Additionally, significant Actor × Partner interactions revealed that greater differences between the friends in the degree to which they produced supportive responses were associated with increased depressive symptoms and that both friends saying nothing at all was associated with increased depressive symptoms. When gender and grade differences were found, the associations typically were particularly strong for middle-adolescent girls. These results highlight the importance of attending to friends' specific behaviors in social support contexts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Visual Exploratory Analysis for Designing Large-Scale Network-on-Chip Architectures: A Domain Expert-Led Design Study.

Visualization design studies bring together visualization researchers and domain experts to address yet unsolved data analysis challenges stemming from the needs of the domain experts. Typically, the visualization researchers lead the design study process and implementation of any visualization solutions. This setup leverages the visualization researchers' knowledge of methodology, design, and programming, but the availability to synchronize with the domain experts can hamper the design process. We consider an alternative setup where the domain experts take the lead in the design study, supported by the visualization experts. In this study, the domain experts are computer architecture experts who simulate and analyze novel computer chip designs. These chips rely on a Network-on-Chip (NOC) to connect components. The experts want to understand how the chip designs perform and what in the design led to their performance. To aid this analysis, we develop Vis4Mesh, a visualization system that provides spatial, temporal, and architectural context to simulated NOC behavior. Integration with an existing computer architecture visualization tool enables architects to perform deep-dives into specific architecture component behavior. We validate Vis4Mesh through a case study and a user study with computer architecture researchers. We reflect on our design and process, discussing advantages, disadvantages, and guidance for engaging in a domain expert-led design studies.

Examining associations between disordered eating and harmful substance use in a nationally representative sample of US veterans.

The association between eating disorders (EDs) and harmful substance use (substance use that causes psychosocial impairment) is well recognized in the literature, and military veterans may be at heightened risk for both issues due to deployment-related stressors. However, little is known about which ED-related symptoms are associated with harmful substance use in veterans, and whether gender plays a differential role in this relationship. Our aims were to: (1) examine gender differences in ED-related symptoms; and (2) examine whether ED-related symptoms differentially predict harmful substance use in US veteran men and women who had recently separated from service. This study was based on a nationally representative four-wave longitudinal sample of post-9/11 veterans (N = 835; 61.2% female). Longitudinal mixed modeling was used to test whether specific ED-related behaviors at baseline predicted harmful substance use at follow-ups. We replicated gendered patterns of ED-related symptoms observed in civilian populations, wherein men had higher weight-and-body-related concerns (including excessive exercise and muscle building) and negative attitude toward obesity, and women had higher bulimic and restricting symptoms. For women, alcohol, drug, and marijuana problems were predicted by higher bulimic symptoms, whereas for men, these problems were predicted by higher restricting symptoms. Gender played a differential role in the relationship between EDs and harmful substance use. Bulimic symptoms were the most robust predictor for harmful substance use among veteran women, whereas restricting was the most robust predictor for harmful substance use among veteran men. The current study found that veteran women had higher bulimic symptoms (characterized by binge eating and purging) and restricting than veteran men. In women, bulimic symptoms predicted future harmful use of alcohol, marijuana, and other drugs. In contrast, veteran men had higher weight-and-body-related concerns (characterized by excessive exercise and muscle building) than veteran women. In men, restricting symptoms predicted future harmful use of alcohol, marijuana, and other drugs.

Distinguishing between Low- and High-Cost Pro-Environmental Behavior: Empirical Evidence from Two Complementary Studies

To reach sustainability goals, researchers and policymakers must focus on addressing changes toward more pro-environmental behavior (PEB). Therefore, this study shows evidence-based perceptions of low- and high-cost behaviors and deduces recommendations for PEB interventions. We applied a multi-step mixed-method approach: First, a representative online survey was conducted to collect a general quantitative overview and classify low- and high-cost behavior based on past behavior and behavioral intentions. Second, a gamification intervention that aimed to gain quantitative data about certain behaviors and perceived low- and high-costs was conducted with university students. The results of the two studies showed that PEB can easily be categorized into high-, rather-high-, rather-low-, and low-cost behavior. However, this classification is not based on emission sectors, e.g., mobility, but on the specific behavior. Interventions can be recommended according to subjective costs: For example, low-cost behavior does not need additional interventions in most cases but must be maintained as is. According to the empirical findings, high-cost behavior needs top-down interventions, while rather-high- and rather-low-cost behavior requires bottom-up interventions to achieve behavior changes. In summary, managing interventions using this classification and focusing on high-impact behavior can lead to successful behavior changes and emission reductions.

Injury Pattern Analysis to Optimize Burn Injury Prevention in the Unhoused Community.

Unhoused patients are an overrepresented group in burn injury, and are a uniquely vulnerable population. Current research focuses on the consequences of homelessness on burn outcomes, with little known about the specific circumstances and behaviors leading to burn injury that may represent specific targets for injury prevention efforts. The burn registry at an urban regional burn center was queried for burn admissions in unhoused adults from 2019 to 2022. Registry data pulled included demographics, urine toxicology, mechanism of injury, and injury subjective history. Subjective injury history was reviewed to determine more specific injury circumstances and activities during which accidental burns occurred. Demographic and mechanistic trends in burn admissions were explored via descriptive statistics. Among 254 admissions for burns from the unhoused community, 58.1% of patients were positive for stimulants on admission. Among accidental injuries (69.7%), common circumstances included preparing food or beverages, cooking or using methamphetamine, smoking cannabis or tobacco, bonfires, and candles. A specific common circumstance was lighting a cigarette while handling accelerants (6.7%). Interventions for stimulant abuse, as well as outreach efforts to educate unhoused patients about situational awareness, safe handling of accelerants, safe smoking practices, and safe cooking practices, may be effective tools in reducing burn admissions in this vulnerable population.

Three-dimensional analysis of steel beam-column bolted connections

Abstract The design of steel beam-column end-plate bolted connections is becoming increasingly popular owing to its simplicity of production. This requires knowledge of the full nonlinear resisting moment–rotation (M–Φ) behavior of the joint. To investigate the impact of various geometrical factors on the overall behavior of the connection, this work provides a three-dimensional finite element model (FEM) utilizing ABAQUS software. The suggested model accounts for the pretension force on the bolts, material and geometrical deviations from linearity, and the proximity of surfaces that are adjacent. The numerical model’s ability to simulate and process both the total and specific behavior of varieties of end-plate steel riveted connections is confirmed by calibrating the finite element findings with experimentally disclosed outcomes, which are reviewed in this study. The ultimate behavior was then investigated through a parametric study using the verified FEM with variations in the bolt pretension load, yield strength of the sections, and yield stress of the bolt considering the M–Φ curve. The results of the parametric study showed that as the bolt pretension load and yield stress of the column, beam, and plate materials increased, so did the connection’s moment ability. The yield tension of the bolts, however, had only a minor effect on the connection’s moment capacity.

Predicting individuals’ behaviors during a pandemic: why we might have acted as we did during the COVID-19 pandemic

BackgroundThis study examined individual differences in how people behave in response to a pandemic – more specifically, the current coronavirus pandemic.Participants and procedureA sample of 420 participants was recruited through the online data collection platform MTurk. Participants were directed via an online link to a Qualtrics survey. This survey was composed of several demographic questions and self-report personality and belief scales, followed by a set of outcome measures designed to measure specific behaviors relating to avoidant behavior, protective behavior, and impulsive buying which the participants might, or might not, have engaged in during the COVID-19 pandemic.ResultsThe results showed that locus of control was the best personality-related predictor of peoples’ pandemic-relevant behavior, such that externally oriented people were more likely to report both protective behavior and impulsive buying behavior. In addition, perceived threat was significantly associated with all three types of pandemic-relevant behaviors (avoidant, protective, and impulsive buying).ConclusionsIndividuals’ personality traits and beliefs clearly play a major role in determining their behavior during health crises. In the case of the current COVID-19 crisis, some people adopt behaviors that ensure their safety and the safety of others, whereas other people display careless behaviors that contribute to spreading the infection. Because individual differences in this situation matter, it is important to determine which variables accurately predict which behaviors.

Epigenome-wide association study of long-term psychosocial stress in older adults

ABSTRACT Long-term psychosocial stress is strongly associated with negative physical and mental health outcomes, as well as adverse health behaviours; however, little is known about the role that stress plays on the epigenome. One proposed mechanism by which stress affects DNA methylation is through health behaviours. We conducted an epigenome-wide association study (EWAS) of cumulative psychosocial stress (n = 2,689) from the Health and Retirement Study (mean age = 70.4 years), assessing DNA methylation (Illumina Infinium HumanMethylationEPIC Beadchip) at 789,656 CpG sites. For identified CpG sites, we conducted a formal mediation analysis to examine whether smoking, alcohol use, physical activity, and body mass index (BMI) mediate the relationship between stress and DNA methylation. Nine CpG sites were associated with psychosocial stress (all p < 9E–07; FDR q < 0.10). Additionally, health behaviours and/or BMI mediated 9.4% to 21.8% of the relationship between stress and methylation at eight of the nine CpGs. Several of the identified CpGs were in or near genes associated with cardiometabolic traits, psychosocial disorders, inflammation, and smoking. These findings support our hypothesis that psychosocial stress is associated with DNA methylation across the epigenome. Furthermore, specific health behaviours mediate only a modest percentage of this relationship, providing evidence that other mechanisms may link stress and DNA methylation.

Towards discovering human urban activity—tactics of human spatial behavior

ABSTRACT The study of human spatial behavior primarily focuses on recognizing their spatial diversification and indicating their distribution, which is well described in the literature. In addition to exploring the phenomenon and its description, the essence of human geography is also to explain it. In this context, it is valuable to learn about the practices carried out by users of urban spaces and the tactics they adopt that result in specific spatial behaviors. To date, most research has been concerted on identifying the determinants, needs, and perceptions of space by its users and, in recent years, on psychophysical responses to the surrounding environment. This research investigates how people strive to realize their needs in urban public open spaces. The study was conducted among users of the Liberty Square in Poznań, Poland. Two methods were used during the qualitative field research: observation and individual in-depth interviews of a casual nature. The obtained data were subjected to qualitative analysis using CAQDAS software. The results of the study identified three human spatial behavioral tactics (SBTs) oriented toward (1) space, (2) people, and (3) needs. SBTs mark the course of human activity and determine where it occurs, its duration and intensity. A person chooses one dominant tactic, while the others influence their spatial behavior but play a complementary role. A person determines the proportions between tactics each time, which affects a great deal of flexibility in the course of their spatial behavior.

Simulation-Assisted Tool Design for Pulsed Electrochemical Machining of Magnetic Shape-Memory Alloys

Shape-memory alloys set high demands on the production technologies being used. During cutting, continuous heat input and mechanical stress have an undesirable influence on the shape-memory effect. Pulsed electrochemical machining (PECM), which is based on anodic dissolution, enables force-free machining without thermomechanical influence on the edge-zone properties of the workpiece. Depending on the desired geometry, the development of a customized PECM fixture is necessary. The design of the fixtures is often based on the experiences of the designers and manufacturers, which often results in an estimation of the functionally critical dimensions. For this reason, the study focuses on a methodical approach for evaluating crucial fixture dimensions using knowledge of the specific material dissolution behavior linked with a numerical simulation model. It has been shown that the shape-memory alloy NiMnGa has a non-linear dissolution behavior in sodium nitrate. A reduction of stray currents up to 20% resulting from a lateral gap between the cathode and electrical insulation was demonstrated using numerical simulation. The study shows that a low cathode shaping height has the strongest influence on precise processing. Varying the process parameters allowed for the lateral gap to be adjusted between 0.15 and 0.25 mm.

Customer Segmentation in IT Sector using Datamining Techniques

Due to its large client base, the IT industry generates enormous amounts of data every day. Business experts and decision-makers stressed that keeping current clients is less expensive than acquiring new ones. Business analysts and customer relationship management (CRM) analysts must understand the causes of customer attrition as well as the patterns of behavior found in the data of these clients. This research is a comprehensive study about churn prediction in IT industry it also suggests a churn prediction model to identify consumer churn and provide the reasons behind customer churn in the IT industry by employing clustering and classification algorithms. Information gain and correlation attribute ranking filters are used in feature selection. One of the CRM's most important tasks is to create retention strategies that work to keep customers from leaving. The study intends to create a model that can effectively identify the primary reasons behind customer churn. This model is likely to use various techniques, such as analyzing customer behavior, preferences, or other relevant data, to identify patterns or characteristics associated with churn and segment the churning customers based on groups in order to retain the customers based on the specific characteristics or behaviors they share within their respective groups. The main aspect of the study is to identify the challenges in the existing methods that are used in churn prediction and suggest a model to improve churn prediction and elude churn effectively.

Development and validation of the Trans- and Nonbinary-Affirming Parental Practices (TAPP) measure.

Parental support is instrumental in protecting the mental health of trans and nonbinary youth (TNB). Yet minimal measures exist that measure parental support, and current measures typically measure parental attitudes or general perceptions of supportiveness rather than measuring specific TNB-affirming behaviors. This study aimed to fill this gap by developing and validating the Trans- and Nonbinary-Affirming Parental Practices scale. The scale items were developed based on existing psychological literature on TNB-affirming parenting behaviors as well as adapting existing measures. The sample consisted of 570 parents or caregivers of TNB youth ages 5-27 (M = 15). The vast majority of participants were White (90%) and cisgender women (92%). The sample was randomly split to conduct both exploratory factor analysis and confirmatory factor analysis. Factor analysis found good fit for a four-factor structure with 14 items. Each subscale represented a type of TNB-affirming parental behavior: communicating support, affirming language, advocating for their TNB child, and seeking affirming resources. The measure demonstrated invariance with both heterosexual participants and participants with minoritized sexual identities and demonstrated convergent and discriminant validity. The Trans- and Nonbinary-Affirming Parental Practices measure can be useful in intervention research aimed at increasing TNB-affirming behaviors among parents and caregivers of TNB youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Machine learning-based approach to predict thermal comfort in mixed-mode buildings: Incorporating adaptive behaviors

Mixed-mode (MM) buildings are designed to provide mechanical air conditioning and natural passive cooling as regulated by occupants. This would enable the potential of shifting the narrow comfort range in HVAC (heating, ventilation and air conditioning) buildings to a wider range similar to NV (naturally ventilated) buildings. Recent studies have provided evidence of higher degrees of thermal adaptation among occupants in MM buildings. However, limited attention has been given to understanding the linkages between these expanded ranges and the specific adaptive behaviors or contextual factors that influence them. This paper aims to investigate the influence of occupants’ adaptive behaviors on thermal comfort in MM buildings. A one-year field study in two MM office buildings with 5096 valid questionnaires was conducted in Chongqing, China, under hot summer and cold winter climatic characteristics by developing machine learning algorithms compared with classic thermal comfort models. Results show that incorporating adaptive behaviors as input variables enhances the performance of machine learning algorithms, leading to improved overall model performance, while the classic thermal comfort index PMV (predictive mean vote) presents the limited accuracy but the best recall in most cases. This paper also demonstrates that some energy-inefficient thermal adaptations were found in MM buildings during the HVAC mode, such as using air conditioning in mild spring and autumn, and frequent window openings during cooling periods of summer. It is therefore valuable for future research to further focus on how MM buildings both incorporate positive features and reduce negative features during the HVAC and NV modes.

The origin of {113}&lt;361&gt; grains and their impact on secondary recrystallization in producing ultra-thin grain-oriented electrical steel

Abstract Ultra-thin grain-oriented electrical steel with a thickness of 80 µm is produced by one-step-rolling with industrial grain-oriented electrical steel. The research employs electron back-scattering texture analysis technique to investigate the evolution of deformation and recrystallization textures in this specific steel. Emphasis is placed on examining the origin of {113}&lt;361&gt; grains and their consequential impact on secondary recrystallization. It is revealed that primary, secondary, and tertiary recrystallization phases are integral during the annealing process. The origin of surface {113}&lt;361&gt; grains were result of initial deviated Goss grains with specific shear deformation behavior in cold rolled ultra-thin strips. Additionally, the influence of these grains on texture evolution is predominantly evident during secondary recrystallization. These grains potentially undergo abnormal growth in secondary recrystallization, exploiting high-energy grain boundaries among Goss grains. This phenomenon consequently leads to the diminution of the sharp Goss texture formed during primary recrystallization. Given the magnetic properties and predominant applications of ultra-thin grain-oriented electrical steel in medium-frequency fields, it is recommended to prepare ultra-thin grain-oriented steel during primary recrystallization phase.

Exploring Education for Children with 22q11.2 Deletion Syndrome: A Qualitative Study of Mothers Perspectives

22q11.2 deletion syndrome (22q11.2DS) is a complex and widely variable genetic syndrome involving multisystem physical health problems, significant cognitive and psychosocial challenges, all of which may impact upon learning and academic achievement. In the current study, we explored mothers’ perceptions of their child’s learning within early and primary educational contexts. We conducted 3 online focus groups and 1 online semi-structured interview with a total of 9 mothers of children diagnosed with 22q11.2DS. Mothers were included if their child had a genetic diagnosis of 22q11.2DS and was aged from 3 to 12 years old. The mothers were asked a series of open-ended questions to explore the educational experiences of their child. We adopted an inductive approach to our data analysis and conducted a reflexive thematic analysis resulting in the emergence of 4 major themes (1.) The impact of 22q11.2DS on a child’s learning; (2.) The impact of adaptive behaviour skills on their child’s learning; (3.) The level of support available within the educational setting and; (4.) Mothers’ perceptions about their child’s learning. From these themes, the following 12 sub themes were identified: absences affecting learning; the development of specific learning behaviours; the impact of a 22q11.2 DS diagnosis on their child’s self-perception; toileting, motor issues; communication; sleep; school and teacher support and the presence (or absence) of therapists. Finally, the mothers’ confidence about their child’s learning; mothers’ concerns and comparisons of their child; and mothers’ apprehension about their child’s future were all identified as sub-themes. Children with 22q11.2DS require increased and specific psychosocial support to allow them greater opportunities to fully participate in their learning environments. Mothers perceived the level of support their child received was greater during pre-school compared to that received at primary school. It was clear that a greater understanding of the needs of children with 22q11.2DS, by educators, was needed. Implications for tailored support for school-based learning and educational transitions for young children with 22q11.2DS are discussed.

Family Caregivers' Management of Behavioral Expressions of Dementia.

Behavioral expressions of dementia are often stressful for family caregivers to manage as they strive to ensure their relative's needs are met. Guided by Lazarus and Folkman's Transactional Model of Stress and Coping, we identified specific behaviors that disrupt daily routines and challenge the achievement of caregiving goals, and the approaches and strategies caregivers employ to address them. We conducted semistructured interviews with 30 family caregivers in rural Appalachia caring for a relative living with dementia. Analysis involved use of open and focused coding processes to identify the ways caregivers managed behaviors and bar graphs to examine management approaches relative to categories of behaviors and caregiver demographic and emotional well-being variables. Analyses revealed 10 types of behavioral expressions of dementia associated with confusion, irritability, and resistance to engaging in necessary activities of daily living. Caregiver approaches to managing behaviors included gentle persuasion, being harsh by yelling or threatening, being persistent in expecting the person with dementia to complete the tasks at hand, disengaging by postponing the activity, and employing a combination of strategies. Approaches differed across types of behavior and caregiver demographics and had varying effects on caregiver well-being. Uncovering specific behaviors family caregivers of persons living with dementia found bothersome, caregivers' adaptive strategies for managing behaviors, and the impact of those approaches provides new information to inform training on effective dementia caregiving practices and development of targeted intervention programs for dementia care.

Visual Biosensing with Specific Liquid-Based Interface Behaviors.

Liquid-based interface behaviors at micro/nano or even smaller scales induced by biomolecules take us into a fascinating realm, fostering a deeper understanding and innovation in visual biosensing. This biosensing technology, grounded in specific liquid-based interface behaviors, redefines how diseases can be detected, monitored, and diagnosed in resource-limited settings, providing rapid, cost-effective, and self-testing solutions to the current healthcare landscape. To date, the technology has witnessed significant advancements in visual sensing, driven by diverse liquid-based materials, advanced nanomanufacturing techniques, and a profound understanding of interface-material interactions. In this Perspective, we discuss and elucidate the interface biosensing mechanisms arising from three types, including liquid-solid, liquid-liquid, and liquid-gas interfaces, and we provide insights into the challenges and future development of visual biosensing applications.