Different Patterns Of Behavior Research Articles

Trait impulsivity influences behavioural and physiological responses to threat in a virtual environment

Trait impulsivity represents a tendency to take action without forethought or consideration of consequences. This trait is multifaceted and can be decomposed into attentional, motor and non-planning subtypes of impulsivity. The purpose of the current study was to investigate how subtypes of trait impulsivity responded to different degrees of threat within room-scale virtual reality (VR) with respect to behaviour and level of physiological activation. Thirty-four participants were required to negotiate a virtual environment (VE) where they walked at height with the continuous threat of a virtual ‘fall.’ Behavioural measures related to the speed of movement, interaction frequency and risk were collected. Participants also wore ambulatory sensors to collect data from electrocardiogram (ECG) and electrodermal activity (EDA). Our results indicated that participants who scored highly on non-planning impulsivity exhibited riskier behaviour and higher skin conductance level (SCL). Participants with higher motor impulsivity interacted with more objects in the VE when threat was high, they also exhibited contradictory indicators of physiological activation. Attentional impulsivity was associated with a greater number of falls across the VE. The results demonstrate that subtypes of trait impulsivity respond to threats via different patterns of behaviour and levels of physiological activation, reinforcing the multifaceted nature of the trait.

A personal social knowledge network (PSKN) facilitates learners’ wayfinding and its differences in behavior patterns between high and low performers in connectivist learning

Wayfinding, which is a part of learning in connectivist learning, involves consolidating a wide variety of resources and information and building connections among them. However, learners often encounter difficulties in wayfinding, and are lost without technological support in connectivist learning. This study examined the wayfinding processes occurring within a network of learners in a personal social knowledge network (PSKN), explored differences in behavior patterns between high and low performers in PSKN. The results reveal the diversity and complexity of wayfinding in a PSKN, including finding and connecting nodes, forming cognitive maps, finding and filtering information, and creating new nodes. Moreover, the characteristics of wayfinding in the PSKN differed across participants, and high- and low-performing participants demonstrated different and unique wayfinding behavioral patterns, which provided a basis for comprehensive analyses of wayfinding. These findings can be used to provide instructional support and network navigation in connectivist learning for learners at various performance levels. The proposed PSKN shows promise in facilitate wayfinding including finding nodes and connecting nodes, as well as relations between knowledge nodes and the course base demonstrated by PSKN, providing great convenience for learners to form cognitive maps based on the node sequence. Compared with current studies, this research focuses on diversified interaction data and resource behavior rather than teaching videos and quizzes or exercises as the main resources and considering that course and technological factors influence the ways in which learners access resources in connectivist learning.

The effects of the industrial transition on lower limb bone structure: A comparison of the inhabitants of Pecos Pueblo and present-day Indigenous peoples of New Mexico.

Comparisons between Indigenous peoples over time and within a particular geographic region can shed light on the impact of environmental transitions on the skeleton, including relative bone strength, sexual dimorphism, and age-related changes. Here we compare long bone structural properties of the inhabitants of the late prehistoric-early historic Pecos Pueblo with those of present-day Indigenous individuals from New Mexico. Femora and tibiae of 126 adults from Pecos Pueblo and 226 present-day adults were included in the study. Cross-sectional diaphyseal properties-areas and second moments of area-were obtained from past studies of the Pecos Pueblo skeletal sample, and from computed tomography scans of recently deceased individuals in the present-day sample. Femora and tibiae from Pecos individuals are stronger relative to body size than those of present-day Indigenous individuals. Present-day individuals are taller but not wider, and this body shape difference affects cross-sectional shape, more strongly proximally. The tibia shows anteroposterior strengthening among Pecos individuals, especially among males. Sexual dimorphism in midshaft bone shape is stronger within the Pecos Pueblo sample. With aging, Pecos individuals show more medullary expansion but also more subperiosteal expansion than present-day individuals, maintaining bone strength despite cortical thinning. Higher activity levels, carried out over rough terrain and throughout adult life, likely explain the relatively stronger lower limb bones of the Pecos individuals, as well as their greater subperiosteal expansion with aging. Greater sexual dimorphism in bone structure among Pecos individuals potentially reflects greater gender-based differences in behavioral patterns.

Real-Time Heterogeneous Road-Agents Trajectory Prediction Using Hierarchical Convolutional Networks and Multi-Task Learning

Trajectory prediction of heterogeneous road agents such as vehicles, cyclists, and pedestrians in dense traffic plays an essential role in self-driving. Despite breakthroughs in trajectory prediction technology in recent years, challenges remain in world state representation, social interaction modeling, real-time computing, and road agent heterogeneity. To address these challenges, we propose a new model that employs hierarchical convolutional networks and multi-task learning to predict agents' trajectories. The model first achieves effective and unified representation of agent and scene context by rendering heterogeneous world states in a top-down multi-channel raster map. Based on this representation, we propose hierarchical convolutional networks to extract global interaction and local features of all agents simultaneously, enabling the model to predict multiple agents' trajectories in real-time in a single forward inference. In addition, we specifically design multi-task learning branches with dynamic adaptive anchors to capture differences in behavioral patterns of heterogeneous agents, allowing a single model to accurately predict multimodal trajectories of multi-class agents. Extensive experiments on public nuScenes and Lyft datasets demonstrate top model performance. Importantly, our model is faster (2.2x) and more computationally stable than state-of-the-art models, making it well-suited for mass-produced self-driving systems that require both performance and computational efficiency.

Knowledge and engagement of the sustainable development goals among undergraduate business students

This paper analyses the level of knowledge and engagement of the students of the Bachelor's Degree in Business Administration and Management (GADE) of the Faculty of Economics and Business (Gipuzkoa Section) of the University of the Basque Country (UPV/EHU) on the SDGs using Multiple Correspondence Analysis and Cluster Analysis. This analysis makes it possible to identify different patterns or profiles of student behavior in relation to sustainability. The results show the coexistence of four different patterns of behavior in relation to knowledge, perception, and commitment to the Sustainable Development Goals (SDGs) and sustainability among students. We identify a first group comprising 23.4% of students with low knowledge and high commitment to the SDGs; a second group that includes 30.4% of students with high knowledge of and commitment to the SDGs; a third group comprising 30% of students with low knowledge of and commitment to the SDGs; and finally, a fourth group comprising 16.2% of students with high knowledge of and low commitment to the SDGs. This scenario suggests the necessity to make further progress in the incorporation of the sustainable development dimension in the teaching-learning processes.

Value systems of representatives of different generations in the process of decision-making on choosing a university and educational program

Purpose: is to propose the methodological approach to modeling the behavior of the representatives of generations Y and Z in the process of making decisions about choosing a university and educational program based on differences in their value systems.Methods: the theoretical and methodological basis for studying the value systems of potential and actual university students is the theory of generations. The findings of the study are based on the methods of analysis of secondary and primary data collected through an online survey of students belonging to generations Y and Z on representative samples of 380 (Y) and 788 (Z) observations in 20 large universities in Russia, as well as the methods of analysis of statistically significant differences in value systems of two generations using T-test for independent samples.Results: the authors proposed the methodological approach to modeling the behavior of consumers of generations Y and Z in the process of making decisions on choosing a university and educational program. Based on the results of desk and field (empirical) research, at each stage of the decision-making process on selecting an educational institution and program, differences were identified in the value systems of students of generations Y and Z, which determine their behavior: statistically significant differences were identified in 19 out of 65 variables. The study provides description of the behavior patterns of students of the two generations at each stage of the decision-making process which formed the basis for dividing students into target groups. The guidelines for differentiating marketing interactions with target groups of representatives of two generations in the process of educational interactions while making decisions are proposed.Conclusions and Relevance: differences in the value systems of representatives of generations Y and Z cause differences in behavioral patterns at each stage of the decision-making process. Understanding these differences enables us to model the behavior of the two target groups, differentiate marketing approaches to interaction with them at the stages of the decision-making process while choosing a university and educational program as well as increase the effectiveness of educational interactions in the process of education.

Hey student, are you sharing your knowledge? A cluster typology of knowledge sharing behaviours among students

Knowledge Sharing (KS) is crucial for all organisations to better face current and future challenges. It is justifiable to assume that after graduation, students will have to face the coming challenges at societal and business levels, and that they will need the adequate KS skills to do so. Though the importance of KS is established, the understanding of how students pass on their knowledge is still fragmented and underdeveloped. Therefore, a deeper understanding of students’ KS behaviour is crucial to identify and promote better actions. As different patterns of behaviour are very probable among students, this study aims to identify patterns that can be used to group students according to their KS behaviour. Drawing from a dataset of 124 Business and Management students, this paper empirically conceptualises a typology of KS behaviours among this group. The typology consists of three different types of student groups that emerged from a cluster analysis: new entrants with neutral KS behaviour, undergraduate students with strong KS behaviour facilitated by social ties, and mature students who share knowledge based on the perceived self-concept. By acknowledging the heterogeneity found among Business and Management students, this paper departs from viewing students as a homogeneous group.

Work, travel, or leisure: comparing domain-specific physical activity patterns based on rural–urban location in Canada

BackgroundPhysical activity occurs across various domains including leisure/recreation, for transportation, or for work or household reasons. Rural and urban active living environments are characterized by different opportunities for physical activity within each domain which may translate into different patterns of behavior. The aim of this study was to compare rural–urban differences in physical activity across different domains, and explore interactions between sociodemographic factors, physical activity domains, and rurality.MethodsWe used self-reported data collected across three physical activity domains (active transportation, recreation, occupational/household) and relevant sociodemographic variables from the Canadian Community Health Survey. Adjusting for sociodemographic factors, we did two separate cross-sectional analyses: 1) binary logistic regression to determine the odds of reporting any activity in each domain, and 2) ordinary least squares regression using the sub-samples reporting > 0 min per week of activity to compare how much activity was reported in each domain.ResultsOur final survey weighted sample of Canadian adults (mean age 47.4 years) was n = 25,669,018 (unweighted n = 47,266). Rural residents were less likely to report any active transportation (OR = 0.59, 95% CI [0.51, 0.67], p < .0001). For recreational physical activity, rural males had lower odds (OR = 0.75, 95% CI [0.67, 0.83], p < .0001) and rural females had higher odds (OR = 1.19, 95% CI [1.08, 1.30], p = .0002) of reporting any participation compared to urban residents. Rural males (OR = 1.90, 95% CI [1.74, 2.07], p < .0001) and females (OR = 1.33, 95% CI [1.21, 1.46], p < .0001) had higher odds of reporting any occupational or household physical activity.ConclusionsUrban residents tend to participate in more active transportation, while rural residents participate in more occupational or household physical activity. Location-based differences in physical activity are best understood by examining multiple domains and must include appropriate sociodemographic interactions, such as income and sex/gender.

A Crowd–AI Collaborative Approach to Address Demographic Bias for Student Performance Prediction in Online Education

Recent advances in artificial intelligence (AI) and crowdsourcing have shown success in enhancing learning experiences and outcomes in online education. This paper studies a student performance prediction problem where the objective is to predict students' outcomes in online courses based on their behavioral data. In particular, we focus on addressing the limitation of current student performance prediction solutions that often make inaccurate predictions for students from underrepresented demographic groups due to the lack of training data and differences in behavioral patterns across groups. We develop DebiasEdu, a crowd–AI collaborative debias framework that melds the AI and crowd intelligence through 1) a novel gradient-based bias identification mechanism and 2) a bias-aware crowdsourcing interface and bias calibration design to achieve an accurate and fair student performance prediction. Evaluation results on two online courses demonstrate that DebiasEdu consistently outperforms state-of-the-art AI, fair AI, and crowd–AI baselines by achieving an optimized student performance prediction in terms of both accuracy and fairness.

(Mis)align: a simple dynamic framework for modeling interpersonal coordination

As people coordinate in daily interactions, they engage in different patterns of behavior to achieve successful outcomes. This includes both synchrony—the temporal coordination of the same behaviors at the same time—and complementarity—the coordination of the same or different behaviors that may occur at different relative times. Using computational methods, we develop a simple framework to describe the interpersonal dynamics of behavioral synchrony and complementarity over time, and explore their task-dependence. A key feature of this framework is the inclusion of a task context that mediates interactions, and consists of active, inactive, and inhibitory constraints on communication. Initial simulation results show that these task constraints can be a robust predictor of simulated agents’ behaviors over time. We also show that the framework can reproduce some general patterns observed in human interaction data. We describe preliminary theoretical implications from these results, and relate them to broader proposals of synergistic self-organization in communication.

Investigating the Effects of Dry Needling on Hamstring Muscles Flexibility: A Randomized Controlled Trial

Introduction: Flexibility or the ability of a muscle to increase in length is an integral part of musculoskeletal characteristics and is essential in preventing musculoskeletal injuries and increasing functional levels. Hamstring muscles rupture is a common injury. One of the important factors in the occurrence of this injury is poor hamstring muscle flexibility, which because of its stiffened structure, has less ability to quickly increase in length. Some researchers have recently suggested that the dry needling technique could reduce the number of treatment sessions for hamstring muscle tightness and bring faster and more effective results. Accordingly, this study aims to investigate the effect of the application of dry needling through an acupuncture technique on hamstring muscle flexibility.&#x0D; Materials and Methods: The present study is a single-blinded randomized controlled trial in which 16 individuals with bilateral hamstring muscle shortness were randomly allocated into dry-needling and sham-needling groups. The sampling method was non-probability convenience. The outcome measures were the right and left active knee extension range of motion, assessed before and after the first, third, and fifth sessions of intervention. A 2-factor mixed analysis of variance was applied to determine the differences between and within the two groups.&#x0D; Results: Except for the group main effect, time main effect and interaction effect were statistically significant for the right and left active knee extension range of motion (P&lt;0.001). There were differences in behavioral patterns in groups; accordingly, in the real dry-needling group, a significant difference was detected across times. However, in the sham dry-needling group, no significant difference was observed.&#x0D; Conclusion: The application of dry needling into motor points of hamstring muscles in individuals with bilateral hamstring muscles shortness could improve flexibility and increase the range of knee extension after 3 and 5 sessions of intervention because of the therapeutic effects of the dry needling technique in improving the muscle flexibility.

Differential behavioral aging trajectories according to body size, expected lifespan, and head shape in dogs.

The twofold life expectancy difference between dog breeds predicts differential behavioral and cognitive aging patterns between short- and long-lived dogs. To investigate this prediction, we conducted a cross-sectional analysis using survey data from over 15,000 dogs. We examined the effect of expected lifespan and three related factors (body size, head shape, and purebred status) on the age trajectory of various behavioral characteristics and the prevalence of canine cognitive dysfunction (CCD). Our findings reveal that, although age-related decline in most behavioral characteristics began around 10.5years of age, the proportion of dogs considered "old" by their owners began to increase uniformly around 6years of age. From the investigated factors, only body size had a systematic, although not gradual, impact on the aging trajectories of all behavioral characteristics. Dogs weighing over 30kg exhibited an earlier onset of decline by 2-3years and a slower rate of decline compared to smaller dogs, probably as a byproduct of their faster age-related physical decline. Larger sized dogs also showed a lower prevalence of CCD risk in their oldest age group, whereas smaller-sized dogs, dolichocephalic breeds, and purebreds had a higher CCD risk prevalence. The identification of differential behavioral and cognitive aging trajectories across dog groups, and the observed associations between body size and the onset, rate, and degree of cognitive decline in dogs have significant translational implications for human aging research, providing valuable insights into the interplay between morphology, physiological ageing, and cognitive decline, and unravelling the trade-off between longevity and relative healthspan.

Russian-Speaking Families and Public Preschools in Luxembourg: Cultural Encounters, Challenges, and Possibilities

Abstract In the twenty-first century, multicultural encounters have become an experience that is familiar even to the youngest. In superdiverse trilingual Luxembourg, over 50% of the population are foreigners, and many of them do not speak the titular language of the country. Multicultural classrooms are studied very closely, but Russian-speaking students, a new but exponentially growing addition to the cultural mix, have not been studied yet in their journey of school integration. There is a gap between the parents and the teachers regarding perception of the content of the studies and family aspirations. Instruction in the Luxembourgish language, usually unfamiliar to Russian families, is not the only obstacle for a child to make good progress at school. The Slavic family group and the Cyrillic alphabet, different holiday calendar and traditions, as well as differences in behavioural patterns and educational models complicate the perception of implicit school rules both for the children and their parents. In this short ethnographic study, based on five in-depth semi-structured interviews with parents, qualitative data were analysed in order to single out the main challenges that Russian-speaking families face while adapting to the public Luxembourgish preschool, the first contact with Luxembourgish language and community life.

Sex-based differences in the distribution of Aujeszky’s disease-seropositive Japanese wild boar

BackgroundAujeszky’s disease virus (ADV) primarily infects domestic pigs and wild boars, causing the abortion and death of young piglets due to central nervous system disorders. In Japan, the national eradication program for ADV in domestic pigs has been successful in most prefectures; however, concern has been raised regarding ADV-infected wild boars as a source of transmission to domestic pigs.ResultsWe assessed the nationwide seroprevalence of ADV among wild boars (Sus scrofa) in Japan. Moreover, we determined the sex-based differences in the spatial clustering of seropositive animals. Serum samples were obtained from a total of 1383 wild boars acquired by hunting in 41 prefectures in three fiscal years (April–March in 2014, 2015, and 2017). Seropositivity tests for ADV using enzyme-linked immunosorbent assay, the latex agglutination and neutralization tests showed 29 boars seropositive for ADV (29/1383, 2.1% [95% confidence interval, CI: 1.4–3.0%]), with 28 of these boars originating from three prefectures in the Kii Peninsula (28/121, 23.1% [95% CI: 16.0–31.7%]). The degree of spatial clustering of these ADV-seropositive adult boars in the Kii Peninsula was evaluated using the K-function and data from sera samples of 46 (14 seropositive) male and 54 (12 seropositive) female boars. The degree of clustering among females was significantly higher in seropositive animals than in tested animals; however, such a difference was not observed for seropositive males.ConclusionsThe spatial dynamics of ADV among adult wild boars may be characterized based on sex, and is likely due to sex-based differences in behavioral patterns including dispersal among wild boars.

Coping Mechanism for Street-Level Bureaucrats in the Implementation of Policies for Handling Coronavirus Disease 19 (Covid-19) in Gorontalo City

In interacting with the community, street level bureaucrats (SLB) have many different patterns of behavior in providing services to the community, both between agencies and between individuals in making policies given to the community. Lower-level executive officials (street-level bureaucrats) often face a dilemma situation, where they are required to provide services according to the rules, while on the other hand, the rules that are applied are often not always in accordance with the situation of the community members who are the target group (target group). In response to this situation, street-level bureaucrats (SLB) developed coping mechanisms, in which they simplified the nature of their work or implemented routine activities. The results showed that in the implementation of the Covid 19 policy, lower-level implementers (street -level bureaucrats) sometimes take coping measures because lower-level implementers are not matched by the provision of adequate service facilities and resources, so that in implementation many different decisions are taken by lower-level implementers (street-level bureaucrats), giving rise to separate problems for top-level implementers. down because it is not clear which standard operating procedures should be used as a guideline.

Undergraduate Students' Profiles of Cognitive Load in Augmented Reality-Assisted Science Learning and Their Relation to Science Learning Self-efficacy and Behavior Patterns.

Research evidence indicated that a specific type of augmented reality-assisted (AR-assisted) science learning design or support might not suit or be effective for all students because students' cognitive load might differ according to their experiences and individual characteristics. Thus, this study aimed to identify undergraduate students' profiles of cognitive load in AR-assisted science learning and to examine the role of their distinct profiles in self-efficacy together with associated behavior patterns in science learning. After ensuring the validity and reliability of each measure, a latent profile analysis confirmed that 365 Chinese undergraduates carried diverse dimensions of cognitive load simultaneously. The latent profile analysis findings revealed four fundamental profiles: Low Engagement, Immersive, Dabbling, and Organized, characterized as carrying various respective cognitive loads. The multivariate analysis of variance findings revealed different levels of the six AR science learning self-efficacy dimensions across profiles. Low Engagement students displayed the lowest self-efficacy among all dimensions. Organized students recorded better conceptual understanding and higher-order cognitive skills than Dabbling ones. Students with the Immersive profile had the highest science learning self-efficacy. The lag sequential analysis results showed significant differences in behavior patterns among profiles. Among them, profiles with social interaction, test, and reviewing feedback behavior had a significantly higher score for self-efficacy than those patterns mainly based on test learning and resource visits. This finding provides a unified consideration of students' diverse profiles and can inform interventions for effective design of AR-assisted science learning to match appropriate strategies to facilitate the science learning effect.

GENDER-BASED ARITHMETICAL ANALYSIS OF RELATIVE BEHAVIOR ON LIFE SATISFACTION, SELF-ESTEEM, AND MENTAL HEALTH

This article presents a gender-based arithmetical analysis of relative behavior and its impact on life satisfaction, self-esteem, and mental health. The study aims to explore gender differences in behavior patterns and their associations with psychological well-being. The research employs quantitative methods to analyze data collected from a diverse sample. The results provide insights into gender-specific behaviors that influence life satisfaction, self-esteem, and mental health outcomes. Understanding these gender-based differences can inform interventions and strategies to enhance psychological well-being for both men and women.

Driving Forces: Generational Differences on the Purchasing Behavior of Investment Assets among Gen Y and Gen Z

With the rising numbers and interest in the financial literacy of Filipinos, more and more people are delving into investment assets. In this case, investment firms in the Philippines must discover new methods to address the current demand for investment assets better and plan effective strategies. This study aims to identify the purchasing behavior and factors influencing investment intention among Gen Y and Z investors. In order to assess the generational differences in behavioral patterns, the researchers used a quantitative approach using the convenience sampling technique for data collection. The data was analyzed using Partial Least Square-Structural Equation Modeling (PLS-SEM). The data collected in this research will help the firms know the behavior of their target market. Thus, acquiring the right strategies would increase sales of the said investment firms and help them determine the appropriate target market. This research shows that only financial literacy has a significant relationship with the investment purchasing behavior of both Gen Y and Gen Z investors, and there is no significant difference between their investment intentions. In order to influence both generations, marketing promotions of investment firms must appeal to the investors' prior investment knowledge. The results of this study will help the firms know the behavior of their target market, and thus, acquiring the right strategies would lead to the increase of sales of the said investment firms and would help them determine the appropriate target market.

Growth and behaviour of juvenile European eel (Anguilla anguilla) in sandy and stony bottom substrates

AbstractUnderstanding how the physical habitat influences growth and behaviour is essential for developing effective habitat restoration programmes of threatened and endangered fish species. In our study, we compared the growth and behaviour of juvenile European eel during 13 weeks in aquaria with either sand (0.8–2 mm) or pebbles (25–40 mm) as bottom substrate. In aquaria with the pebble substrate, eel grew significantly faster than in aquaria with sand (specific growth rate 0.15 vs. 0.11% day−1). Moreover, growth rates varied more for individuals inhabiting aquaria with sand than in those with pebbles (coefficient of variation 1.26 vs. 0.67). Habitat‐dependent growth rates may partly be explained by the observed differences in behavioural patterns. In aquaria with sand, eel left the substrate more often and moved close to the bottom or freely in water column. In aquaria with pebbles, eel remained hidden in the substrate to a high degree, also during feeding. These results may be important for prioritising connectivity‐ and habitat‐restoring measures and for optimization of restocking programmes.

MULTIOBJECTIVE OPTIMIZATION OF THE INTERGENERATIONAL RESIDENTIAL SPACE WITH THE GOAL OF DAYLIGHTING AND THERMAL COMFORT

ABSTRACT (1) Background: An ageing population and two-child policy have led to the transformation of China’s family structure, and multigenerational residences account for an increasing proportion of mainstream family residences. Different generations of residents have great differences in behaviour patterns and health requirements, but existing residential buildings are not especially designed for health needs. (2) Methods: First, based on relevant codes and a questionnaire survey, the spatial needs and behaviour patterns of different generations of residents are obtained, and the benchmark model is established based on the Grasshopper (GH) parametric platform. Then, based on the GH platform and the building simulation plug-in, which are Ladybug Tools and a multiobjective optimization tool named Wallacei, daylight autonomy (DA), useful daylight illuminance (UDI), and the proportion of thermal discomfort hours (PDH) are taken as daylighting and thermal comfort indicators, and the bedroom location, orientation, bay size, depth to bay ratio, window form, window-to-wall ratio, and horizontal shading width are optimized. Finally, the Pareto front is analysed by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) comprehensive evaluation method, and the optimal solution is compared with existing multigenerational residences in Tianjin. (3) Results: First, the middle room, oriented south or south by east, large bay, small window-to-wall ratio, and bay window can effectively be improved for indoor thermal comfort, while rooms that are oriented south or south by east, small depth bay ratio, large window-to-wall ratio and balcony can effectively be improved for daylighting quality. Second, compared with existing buildings in Tianjin, the DA, UDI, and PDH of the adult bedroom with the ideal solution are increased by 33.7%, 3.5%, and 10.8%, respectively; the DA, UDI, and PDH of the child bedroom with the ideal solution are increased by 15.5%, 4.2%, and 4.9%, respectively; and the DA, UDI, and PDH of the elderly individual bedroom with the ideal solution are increased by 42.7%, 4.9%, and 1.7%, respectively. (4) Conclusions: The optimization scheme is substantially improved for the health of the indoor daylight and thermal environment of existing housing, and it provides a scientific and quantitative decision-making basis for the healthy design of multigenerational residences.