Individualized instruction is a type of educational principle. On the one hand, it necessitates the creation of individualized teaching resources, courses, and methods. Students, on the other hand, require a high level of autonomy and the ability to make personalized plans based on their own cognitive characteristics and needs. The big data (BD) era opens up new possibilities for IE  work in universities, but it also poses some challenges. IE development will be greatly aided by recognizing opportunities to meet challenges and optimizing and integrating PL  resources. The LNN  model has been established. The simulation results show that the LNN network can converge to the optimal solution quickly and effectively and then reconstruct sparse signals. Individualized college PL instruction using LNN and BD technology helps students communicate more effectively and improves the pertinence, immediacy, and positivity of IE. Massive data provide great value for people. Contemporary young students can be said to grow up together with the Internet , 2, so cMany large-capacity data sets are obtained from many large-scale data sets through intelligent statistical measures , and BD The construction of teaching systems in research universities has given the teaching quality standard a new meaning and orientation. We should not only reflect the teaching quality standards of research universities in the index system of teaching evaluation but also reflect the teaching ideas of research education through the corresponding evaluation models, methods, and operating mechanisms when assessing classroom teaching quality. Finding new ways to do things has become a top priority. This paper examines the challenges faced by ideological network teaching resources and proposes optimization and integration methods to improve the teaching effect of ideological network teaching, based on the connotation and characteristics of BD.Literature  pointed In literature , a singlTo summarize, online learning is attracting an increasing number of students due to its time and space flexibility as well as significant cost savings. With the rise of fragmented learning, customized and personalized online teaching based on BD has become the online teaching platform's development trend, providing a large number of potential users for BD in the development of online teaching, and the combination of BD and online teaching also has promising practices and research prospects.Personalized teaching is becoming a hot topic in China's educational circles as they try to reform the curriculum and change teaching methods. Because students differ in cognitive ability, cognitive level, and personality, educators should integrate students' personalities and teaching activities, put people first, begin teaching with students' needs, respect students' personalities, and use personalized teaching. Personalized teaching is a type of teaching idea that has three meanings: first, personalized teaching emphasizes the diversification of teaching, and teaching materials, teaching resources, teaching forms, and teaching methods should be rich and colorful; second, personalized teaching is learner-centered, values learners' subjectivity, respects students' individual differences, and meets students' diverse needs; and third, personalized teaching is learner-centered, attaches importance to learners' subjectivity, respects students' individual differences, and meets students' diverse needs.The data of a learner's entire learning process can be recorded using BD technology. Knowledge points are assigned to every topic and data collected in tests, assignments, and exams. Encourage students to study more effectively and improve the quality of their learning. Various text and video resources can also be pushed to learners to help them internalize and absorb knowledge points. Students' learning motivation and interest are stimulated, and students' innovative, problem-solving, and practical abilities are developed. The implementation process is shown in Through digital analysis to build a data model and use this resource to get students' psychological feelings during this period. For students who behave abnormally, find the source of the problem through data analysis and guide the wrong ideas in time.At the same time, abundant IE resources and various forms of IE models provide students with a comprehensive platform for learning, which can satisfy students' personality styles and learning initiatives. Therefore, study in an online classroom or use WeChat to brainstorm and learn. In short, college PL teachers should comply with the development requirements of the BD era, further use BD to find favorable resources and information to master the IE initiative, and enrich and adjust teaching content with dynamic data. Before entering the course, connect and arrange the learning contents according to the key points and subkey points; at the same time, arrange your own learning time, which time period to learn what content, and when to conduct self-evaluation; and constantly revise your personal plan in combination with teachers' teaching.On the one hand, independent assessment has no bearing on the teaching process. Only in an environment where teaching quality is highly valued and pursued can the evaluation result information be considered an integral part of school decision-making, and it is this information that the school administrators use. On the other hand, schools' value choice in using teaching evaluation results should be based on improving teachers' teaching ability, promoting teachers' development, then promoting students' development, fully mobilizing teachers' enthusiasm, and stimulating teachers' potential so that both teachers and students can benefit from teaching evaluation and so that teaching evaluation can be widely recognized and continuously promote the improvement of both teachers and students.The penalty coefficient of LNN is variable, and the neural network can still converge to the optimal solution of the optimization problem without calculating the initial value of the penalty term in advance. A neural network model of differential inclusion is established to solve the optimization problem. The similarity calculation formula of the two nodes isPi represents the similarity between node U and CN U′ and wj represents the weight value of this attribute in the i-th attribute.where simMAXL represents the length of the longest path in the tree and P represents the distance between nodes. Therefore, the similarity calculation formula is:Teachers can assign different difficulty problems to students at different levels in class, which meets the individualized needs of students at each level, increases teaching efficiency, and truly realizes individualized teaching. Teachers can also gather students with problems in the same knowledge point based on the correct or incorrect situation of knowledge points and provide targeted explanations and training to help students improve and progress quickly. To help students master the content related to knowledge points, focus on synchronous or asynchronous explanations of common problems. Students can have individualized communication for personality issues. The explanation methods for students vary according to different knowledge points, which can promote the development of students' personalities and allow questions to be solved and answered at any time.Personalized teaching based on BD can collect all of the students' data automatically; manage all types of learning materials digitally, such as students' homework, pictures, grades, and teachers' comments; track and record students' learning behaviors with BD technology; provide adaptive learning feedback; and provide students with personalized learning guidance. It is more convenient for students to think and reflect, objectively promote students' progress, and make students more active in self-evaluation by collecting and managing their entire process data.Introducing the thinking mode of planning into college IE teaching based on BD is to break through the fixed thinking mode, with new eyes, new viewpoints, and new methods, from the establishment of the thinking mode of college IE planning to the implementation of the plan and the realization of the target requirements. Under the influence of BD, the way of IE in traditional mode has undergone great changes.One is to accurately judge the resources of ideological network teaching, that is, the selected teaching resources can be authentic, effective, and reliable enough. The second is to find the best resources from massive IE resources, so as to ensure the best teaching effect. Of course, on the basis of the principle of scientific construction, should reach a certain degree of adaptability, specifically, the selected materials can adapt to students' physical and mental characteristics and knowledge structure characteristics. This work should also pay attention to two points: one is to choose the teaching resources that fit the students' actual network, and the other is to seriously explore the students' concerns and interests and find out the places where students have insufficient knowledge to enhance the pertinence of the teaching process.The goal of this paper is to design a neural network so that its equilibrium point can meet the optimal conditions. In order to explain the neural network model, firstly, a Lagrangian-like function is defined as follows:λ > 0.in which Lagrange multiplier L1-square x-guide number of the Lagrange function:Find the According to the gradient descent, the following neural network can be constructed:0 is not differentiable, the function f(xi) ≈ xi2/xi2+σ is considered to approximate ‖x‖0. The smaller σ is, the more accurate the approximation effect is, that is:Because the operator ‖·‖Differentiated assessment is possible thanks to the teaching cloud platform's ability to personalize curriculum assessment strategies for different classes. Most students who major in art or sports, for example, are outgoing and good communicators, but they dislike reading. College PL teachers can focus on content material learning and knowledge consolidation exercises and strive to help students lay a strong theoretical foundation and develop a practical learning attitude, depending on their characteristics. Create more personalized practice plans and improve the methods and forms of practice. Personalized practice schemes can effectively stimulate students' interest in learning, arouse participation in practical activities, and improve their overall creative ability in the relatively relaxed, happy, and free practice process.Evaluate and judge the similarity between the given user portrait model and the user portrait model in the user portrait database. The user's current learning user portrait is called the main learning user portrait. The user portrait similarity calculation obtains the user portrait similarity by constructing a decision tree and performing node operation. Taking the user attribute elements as an example, the user portrait model tree is constructed, as shown in Teachers' personalized teaching system is used to watch the completion and accuracy of students' preview self-test questions. Because each test question has different knowledge points, the students' mastery degree is analyzed to understand the overall preview of students. According to the real-time updated ranking of students' preview scores, this paper analyzes the changes in students' grades and the wrong questions of each student, so as to teach students in accordance with their aptitude in the process of teaching.Cloud engine in BD infrastructure module realizes the management of distributed Hadoop nodes through task scheduling function. Considering that other modules in the system, such as database management module of user portrait, also need to manage the database by task scheduling, asynchronous task transfer is adopted, which also ensures the rapid development and debugging of submodules as shown in The script is developed in python, which mainly includes two parts, task and task fragment. The task is initialized in the management server by reading the policy file, and the task script and shell script are packaged according to the corresponding configuration in the policy file. After the packaging is completed, it is sent to the proxy service module of the Hadoop node through socket. The proxy service module decompresses the task and shell script, executes the task fragment script, calls the corresponding shell script, completes the task scheduling, and returns the execution result to the cloud engine.Individualized teaching creates a democratic and harmonious atmosphere for teachers and students and allows students to have their own thoughts and answers, thus fully expressing their individuality. Personalized teaching is personalized in curriculum, teacher's teaching, and students' learning. Mind mapping also reflects personalization. Deal with the problem according to the way you handle the information, which obviously has a strong personal color. When thinking or solving problems and combine multidimensional information into a dynamic structure diagram, what is completed is a personalized mind map.Under BD background, IE personalized teaching needs the comprehensive strength of teachers and technical teams. Specifically, the construction of a personalized teaching team can improve BD development literacy through the optimization and potential stimulation of the internal staff of the teaching team and strengthen the screening and optimization of massive teaching data. It can focus on future development education and fully absorb data professionals from all aspects to strengthen personalized teaching. This innovative personalized teaching method can gradually transform the traditional IE work from the extensive passive response mode to the active intervention and active guidance mode and create a new personalized teaching mode of college IE.x of order k, without losing generality, the positions of these k nonzero elements are randomly generated and meet the uniform distribution of , and the sizes of the corresponding nonzero elements are randomly generated and meet the uniform distribution among . The generation of random signals is shown in Using MATLAB to generate sparse signal Students' intuitive and comprehensive qualitative evaluation of teachers and courses is referred to as aspect evaluation. The individual evaluation reflects the quantitative requirements for teaching based on subject characteristics or course nature. Teachers' personal styles and preferences, as well as the school's current reform focus, are reflected in the selective evaluation. Subjective evaluation captures characteristics of teaching quality that aren't captured by standardized indicators. Teachers can also use a specific knowledge point or piece of content as a theme for each group to investigate and promote. Teachers can allow students to create their own personalized mind map during the evaluation stage, which includes not only the relationships between knowledge points but also their own learning methods and cognitive strategies. Students can use this map to learn about their learning situation and provide timely feedback, making it easier for them to identify and correct their own flaws, humanize the evaluation, and make the cognitive and thinking processes operable.Virtual practice teaching alleviates the difficulties of traditional practice teaching, such as students' lack of subjectivity, limited teaching time and space, shortage of teaching resources, and so on; highlights students' dominant position; expands the field of teaching virtual space; and enriches teaching resources. In the course system construction of personalized teaching, the setting of emotion and belief courses cannot be ignored. A complete personalized teaching course system should be the integration of three courses. Therefore, on the basis of the main courses, emotion and belief courses should be properly arranged, and at the same time, emotion courses should be refined into the specific teaching of the first two courses. Teachers can link the first two courses with the third related part in teaching; for example, they are often combined with corresponding emotions in the teaching of psychology, and the beliefs and thoughts of historical figures are linked with them in the teaching of anthropology so that the three courses are harmonious and unified.m and the correct reconstruction probability under different sparsity, take different sparsity k= and perform 1,000 random experiments on each group of .In order to test the relationship between the observation times k, when the number of observation points m is greater than or equal to 110, the probability that LNN method can correctly recover sparse signals is extremely high.It can be seen from The integration of BD and teaching is conducive to strengthening the supervision and management of college students' ideological fields. Through the digital analysis of students' ideological status, to control the operating mechanism of ideological education in colleges and universities, introduce new thinking ways and teaching methods, integrate the working resources of college IE, give full play to the advantages of digital technology, and cultivate the ability of college ideological educators to use data. Enhance the scientificity and modernity of college IE.BD should be introduced into practice teaching, and more space for students to choose independently should be reserved in the PL teaching practice theme design. This can effectively stimulate students' initiative of independent innovation in the process of stimulating students' personal development potential. In the BD development environment, it can provide differentiated teaching ideas for college PL teaching and realize individualized education development. In personalized education, pay attention to actively listening to students' opinions and suggestions, praising students' personal strengths, which can safeguard students' personal dignity and interest.m= with different observation points, when the sparsity k is less than or equal to 20, the LNN method has a very high probability of correctly recovering sparse signals.As can be seen from Provide training, expert guidance, and technical support for teachers to help them improve their teaching level. Establish a website for the purpose of “serving teachers' teaching” to provide teachers with places for learning and communication. Organize a series of discussion lectures and classroom observations to help young teachers learn from other teachers' advanced teaching experiences and form their own teaching style and characteristics. Hire experienced old teachers as teaching consultants, listen to young teachers' classes regularly, and give guidance. Carry out a series of educational technology training to improve teachers' ability to master modern technologies such as multimedia.The visualization of a mind map can help students understand the solutions and methods adopted by teachers and classmates when solving the same problem. At the same time, continuous reflection and regulation can promote the formation and transfer of their own cognitive strategies and cultivate their metacognitive ability. The explicit way of mind map opens tacit knowledge, realizes information exchange, connects more information to expand the breadth and depth of thinking, inadvertently exercises thinking, and lays the foundation for the emergence of new inspiration and the stimulation of creativity, thus promoting the innovation and perfection of knowledge.x1, x2. x1. Therefore, this is consistent with the minimum point set in problem analysis.Use MATLAB software programming to simulate the behavior of the neural network. Learning objectives have a specific order, and they do not exist in parallel. Similarly, knowledge points follow a logical order: before learning a specific knowledge point, you must first learn its lower knowledge points, which serves as a necessary prelude to learning the upper knowledge points and improving the upper knowledge points. Students will be pushed to master the basic knowledge points, then the writing knowledge points of chemical equations, and finally the knowledge points related to the simple calculation of chemical equations. Students will master knowledge content ranging from easy to difficult, and personalized learning will be realized. There are two types of personalized teaching resources: static and dynamic. Words, pictures, animations, courseware, and material conditions are examples of static resources, whereas dynamic resources refer to dynamic information and active human resources. The construction of static resources is currently mostly in the stage of low-level repeated construction in the resource creation process, and the lack of individuality cannot meet the needs of students. Furthermore, it frequently overlooks the discovery of dynamic resources hidden in teaching activities, such as creativity and intellectual resources. However, mind maps can assist in the resolution of these issues.x1=1, x2=0.5) inside the feasible region finally converges to the minimum point. It can be seen from x1=0, x2=5) outside the feasible region enters the feasible region after a period of operation and finally converges to the minimum point .It can be seen from In order to facilitate code maintenance and subsequent expansion of functions, Python and Shell scripts that can explain execution are selected. When running on the system line, the code can be modified. The task dispatching room executes in sequence through queues, and the cloud engine executes corresponding tasks according to the priority of the queues. So the elements that make up the user portrait must be able to be automatically identified by the computer, or the user can provide explicit information about the elements of the user portrait. When building a user portrait model, the finer the entity elements that make up the model, the more accurate the description of the model is. However, in the actual application process, many and fine user portrait elements will be dull. Therefore, the scope and accuracy of the user portrait model must meet the actual needs.The platform will continuously collect user information and apply it to the current user portrait and constantly improve the user's portrait features through the current user portrait's use of data, so as to realize the continuous enrichment and perfection of data and portrait and ensure that the model has good adaptability. According to the difference of data dimensions, starting from multidimensions, the data is finally aggregated into a cluster set with the least differentiation in a certain dimension. There are often great differences between different clusters, so cluster analysis has become a commonly used data processing method in the field of machine learning.Students have more autonomy with personalized instruction. They will not get the corresponding effect if they are too free, so educators, particularly front-line teachers, must grasp and control it properly. Furthermore, no idea or tool can be flawless. We can make them work by constantly exploring and tapping their useful value. When incorporating the LNN development concept into university PL personalized teaching, it is important to keep in mind that students' personalized development differs. Encourage students to actively change their learning styles, pique their curiosity about learning, and develop their practical skills and creative spirit. Establish and improve the incentive and restraint mechanisms in the classroom, as well as stimulate teachers' awareness of the need to continually improve teaching and their level of expertise. The outcome of classroom evaluation is useful for postappointment teaching, professional and technical postappointment, and various awards.


This article addresses a gap in the work psychology literature regarding psychosocial working conditions and bullying among staff in academic organizations. We examine the influences, institutional demands, and resources attached to given academic positions, such as how the level of social support and cooperation influence the level of experienced negative acts at work and bullying in different work groups in an academic work environment. We also examine whether some professions or positions in an academic organization are more vulnerable due to organizational structure, perceived and experienced resources, and demands to bullying or experiencing more negative acts at work. A common division of different employees in the university sector is between administrative/technical staff and scientific personnel. Our hypothesis in this study is that there are significant differences among these two groups regarding levels of experienced social support and cooperation, as well as levels of experienced negative acts at work. We postulate that differences in job demands and resources lead to significantly different levels of self-reported bullying for the two main groups of personnel. We expect scientific personnel to be more exposed to negative acts at work and bullying due to differences in the demands and resources associated with these positions. This article addresses a gap in the work psychology literature regarding the psychosocial working conditions and bullying among personnel in higher education organizations in the Nordic context. Academic organizations and universities all over the world have a bad reputation for offering their employees a rough work environment, with high levels of competition among employees and prolonged and unsolved conflicts in combination with low levels of social support and cooperation among employees, leading to high levels of workplace bullying ,2,3.survival of the fittest type of work environment [The relatively high incidence of bullying in the university sector has been attributed to specific social and work features of the academic profession . Academiironment , and onlA university can almost be compared to a micro-society in that it contains a wide range of different professions and positions with a range of different backgrounds and educations. This paper studies the employees charged with the day-to-day operations of a university—from human resource professionals, financial operators, and IT professionals to the more traditional scientific positions such as professors.Conflicts are a natural part of everyday life in organizations. Interpersonal conflicts in the work environment are a common problem in most sectors, and conflicts are also one of the main reasons for reduced psychosocial work conditions. In a study on living conditions in Norway, 30% of the respondents reported being in a conflict with their manager or department head, and 20% reported being in a conflict with a colleague . ConflicThe phenomenon of workplace bullying refers to a prolonged and repeated negative behaviour at work directed against employees who are unable to defend themselves , leadingSelf-reported workplace bullying in Norway is normally reported to be around 5%, depending on the sector . In a naScandinavian leadership has historically been characterized by three central features, namely a high level of employee involvement in the decision-making process, a short distance between managers and employees, and “freedom with responsibility”, which means that the employee has ample space in which to take initiative and work independently . This wiIn the Nordic academic work sector, scientific personnel, especially professors, have had considerable amounts of autonomy . This auAccording to the Job Demand Resources theory , also caOne central assumption of the JD-R model is that every occupation may have its own specific work characteristics associated with both job engagement and job exhaustion. It is, according to the JD-R model, possible to model these characteristics into two broad categories, job demands and job resources .The JD-R model defines job demands as physical, psychological, social, or organizational aspects of the job that require sustained physical and/or psychological  effort and are therefore associated with physiological and/or psychological cost. Examples can be a poor psychosocial work environment, high workload, or conflicting roles. Job resources however are defined as the physical, psychological, social, or organizational aspects of the job that function in achieving work goals, reducing job demands associated with high physiological and psychological costs, and stimulating personal growth and development.In academic organizations, resources can be related to external or internal research funding possibilities, administrative support, and access to Ph.D. candidates. Resources may also be found in interpersonal and social relations in the work setting such as support from leaders or co-workers and a good psychosocial work environment in general. The organization may also provide resources by offering high degrees of job clarity and good leadership competence and by allowing employees to participate in important decisions regarding their work situation.Job demands in an academic organization can be both positive and negative. Positive demands are closely related to meeting difficult goals . AccordiAccording to the JD-R model, job demands will normally require the use of resources. If, as an example, a researcher works in a department with a high level of interpersonal conflicts and low social support, this will normally preclude the mobilization of job resources . If emplThe JD-R model assumes that high job demands such as a high workload and a high level of role conflict and low levels of resources such as task autonomy and social support increase bullying over time. An empirical study including 177 employees from various establishments in Belgium supported this hypothesis . The resIn this article, we focus on how job resources and demands, such as high levels of reported social support (resources) and low levels of cooperation among employees (demands), affect the level of reported negative acts and bullying among two different groups of employees. We tested the relationship between job demands and job resources and how it affects the types and extent of negative acts in an academic organization. We measured job demands in terms of quantitative demands, lack of feedback and cooperation, and institutional stress, and we measured job resources by self-reported social support and cooperation, meaningful job tasks, and autonomy.We distinguished between scientific and administrative personnel because the JD-R model focuses on the importance of awareness that every profession and work climate may have their own unique pattern of typical expected demands and available resources built into the organizational structure. Administrative and technical personnel in our sample include both employees working in different departments at the faculties, and employees located in centralized departments such as HR, the communication department, the economy department and the IT department. Administrative and technical personnel is therefore a term for all employees who do not have a scientific position at the university.Another proposition of the JD-R model is that several different job resources can play a buffering role for several different job demands, making a simple model more complex. Not only will a work environment have its unique pattern of demands and resources built into the job design, but so will the different professions and occupations and every individual employee. Consistent with this view, local and thorough information is needed to design healthy and productive work environments. Therefore, it is also meaningful to explore what type of job demands and resources can act as a buffer or a risk for bullying in different work environments and for different types of positions.This study also provides data to test an empirical model of organizational and structural factors leading to higher risks of bullying in an academic work setting.We were interested in examining if any of the different positions at a university—due to the type of work tasks they perform, how the work processes are structured and organized, or the type of cooperation and dependability on other professions they have at work—are more at risk of experiencing higher degrees of negative acts or bullying due to the patterns of job demands and resources offered by their organization.H1. Structural organizational resources and demands predict the level of workplace bullying among university personnel.H2a. Scientific staff as a group experience different effects of demands and resources on bullying than administrative staff.H2b. The effect of demands on bullying is stronger for the scientific staff than for the administrative staff.H2c. The effect of resources to prevent bullying is stronger in the administrative group than in the scientific group.The data used in this study were collected using a work environment questionnaire survey that was sent to all employees at a university on the west coast of Norway in the spring of 2019. The survey included a range of validated questionnaires on themes relevant to the above issues. In total, 1600 employees received the questionnaire, and the overall response rate was 84% for the total sample of employees.To eliminate the respondents that were returning a large proportion of missing values, only the returned surveys in which more than 50% of the questions were answered were kept. This criterion led to 922 answered surveys. Of those, 450 were administrative/technical staff working in support positions, 311 were scientific personnel with both research and teaching duties at diverse career stages, and 161 covered other types of positions and were not specifically considered in this study.Quantitative demands were measured using QPS-Nordic [Lack of feedback was measured by a questionnaire from a Nordic research group [Lack of cooperation was measured by the cooperation scale from QPS-Nordic and Census work environment questionnaire [Institutional stress was measured using Cooper’s Job Stress Questionnaire (CJSQ) [In this study, job demand variables included quantitative demands, lack of feedback and cooperation, and institutional stress. Accordingly, S-Nordic ,27 with ch group  with theionnaire ,27 by the (CJSQ)  with 5 ie (CJSQ) . The CJSJob resources include autonomy, self-reported social support, and meaningful job tasks. Autonomy was measured using the autonomy scale from the Organization Assessment Survey [Social support was measured by a scale developed by Van der Heijden [Meaningful job tasks were measured with the “positive challenges at work” scale from the QPS-Nordic instrument [t Survey  with the Heijden  with thestrument . The iteBullying. Exposure to workplace bullying was measured using a 12-item trimmed version of the Negative Acts Questionnaire—Revised (NAQ-R) [ (NAQ-R) . All iteSelf-reported bullying was measured by the item “Have you been exposed to bullying at your workplace during the last six month?” [ month?” .We first ran a principal component regression (PCR) on the pre-bullying variables to predict self-reported bullying, in order to test whether negative acts in the workplace give strong indications about actual bullying and whether previous validations of the NAQ-R, as a two-factor measurement of work-related and person-related bullying , are conTo understand whether the administrative and scientific staff have a different perception of negative acts, we first considered the number of employees in the two groups who reported having been exposed to some negative acts at the workplace . We then tested whether the percentage of employees stating so was significantly different The dimensionality underlying the NAQ-R questions was also investigated through a factor analysis, the extraction method being a principal component analysis with varimax rotation. This compresses the variability into new few factors that are non-correlated and are thus linear combinations of the original variables. The same was performed on the measurements for job demands and resources. The new factors could thus be used in modelling methods such as structural equation modelling (SEM) (explained below).SEM was used to uncover possible causal effects on negative acts, thus allowing the estimation of a theoretical network of relationships linking latent complex concepts , each measured by means of observable indicators . The chosen SEM methodology is component-based so as to maximize the amount of variance explained and is referred to as a Partial Least Squares Path Model (PLS-PM) . In addiOur model specification  aimed atThe model specification was applied to the whole survey sample as well as to the scientific staff and to the administrative staff separately. This was useful for validation purposes in terms of robustness of the results and for testing differences between the two groups of employees.2 = 0.42). Our results  also suggested keeping the second factor because the slope of the curve was levelling off after it and because it was an important factor according to interpretation. These two factors explained a sufficient percentage of the total variability (59%) and were thus kept for further analysis. The eigenvectors  indicated that the first factor explained the size effect of the NAQ-R. The second factor was instead discriminating between undesirable actions at the workplace that were either at the personal level or were work-related see , in geneWhen considering the SEM structural model for the whole sample of employees , both reThese results indicated that the latent variable for demand was mainly constituted by the observed variables for institutional stress and lack of cooperation in terms of both weight and correlation. Resources were mainly formed by social support and secondly by autonomy. Additional SEM models for the whole sample of employees, as well as for the administrative and scientific staff separately, were tested by discarding the size-effect factor for the NAQ-R and by focusing only on either work-related or person-related factors . The results from these six different models, not shown here, were quite robust and did not highlight the different weights or constructs in the measurement models for resources and demands. They confirmed the patterns that we detected from the SEM models described in this paper.The assumption of the JD-R model was thus confirmed, and high job demands, such as a high workload and lack of cooperation, and low levels of resources, such as low task autonomy and lack of social support, increased negative acts and bullying in the workplace. Therefore, these results support hypothesis H1: structural organizational resources and demands predict the level of workplace bullying among university personnel.The quality of a PLS-PM depends on the GoF of both the measurement and structural models. For the measurement model, the test for potential multicollinearity between items was satisfied because the maximum variance inflation factor value was 1.833. The discriminant validity was also satisfied .2 (measuring the predictive performance) was satisfactory, being equal to 0.447  and that those effects are different between the two groups (H2a). The assessment of the GoF for both the measurement and reflective models and on the models for administrative and the scientific employees, respectively, was satisfied.2, which was 3:1 for the administrative staff and about 7:1 for the scientific staff.The structural model for the administrative staff showed that the latent variable of demands gave an effect on negative acts that was about 2.5 times stronger than the effect of resources, but even so, both effects were highly significant . The gapThe effect of demands on bullying were therefore stronger for the scientific staff than for the administrative staff, while the effect of resources to prevent bullying was stronger in the administrative group than in the scientific group, thus confirming H2b and H2c.When it comes to the measurement model, we also observed that demands were mainly constituted by institutional stress and lack of cooperation in terms of both weight and correlation. This was true for both the administrative and the scientific personnel, as well as for the general model. The patterns varied for the resources latent variable. In the model for the scientific staff, this was mainly formed by social support and secondly by autonomy, which was also observed for the model for the university employees as a whole. Instead, the results for the administrative staff indicated that meaningful job tasks were also weighted similarly to the other two observed variables , thus playing a relevant role in both the measurement and structural models. The added role of meaningful job tasks explained the stronger effect that resources had on negative acts for the administrative personnel.In this study, we aimed to determine the risk factors for being exposed to negative acts or bullying in different groups of personnel in the university sector. A main goal with examining specific risk factors for different positions is that it is possible to develop better initiatives aimed at preventing and reducing bullying for the different types of personnel and positions, thereby also offering employees in the university sector a healthier and safer work environment. There have been many suggestions for the potential risk factors for why the rates of self-reported bullying in universities are higher than in other work sectors, ranging from personal traits and high levels of competition among employees, lack of professional support, and poor leadership structures to neoliberalism taking over the university sector, thus depriving scientific personnel of important autonomy and influence and creating frustration and conflicts .The results from the descriptive analyses for both scientific and administrative staff showed that these two groups of personnel experience significantly different levels of negative acts and self-reported bullying. The findings therefore support our hypothesis that there is a different risk of being exposed to bullying and negative acts at work depending on the type of profession, the job position, and the work task that employees are responsible for at the university. When considering the percentage of employees in both groups confirming being exposed to negative acts at the workplace or self-reported bullying in the last six months, we found that the scientific personnel had consistently higher values than the administrative personnel at 6.4% in the scientific group and 2.6% in the administrative group. The self-reported bullying rate was comparatively lower than the national average of 13%. A possible explanation for this is that the surveyed university has worked constructively over the past decade to counter workplace bullying and negative acts, thus reducing self-reported bullying from 11% at the highest measurement in 2009 down to 4.8% at the lowest in 2017.Our results shows that the values were also significantly different between the two groups of personnel for 5 of the 12 negative acts questions. The scientific personnel reported significantly higher scores than administrative personnel on the following negative acts at work: hostility or silence in response to questions or attempts at conversation, having your opinions ignored, having gossip and rumours spread about you, having insulting or offensive remarks made about your person, attitudes, or your private life, and being ignored or excluded from the social community at work. All these negative acts are mainly person-related types of negative acts at work.One interesting question one may ask here is why scientific personnel are more at risk of being exposed to bullying and negative acts in the workplace. The universities in Norway have a management culture where especially managers of scientific staff have a responsibility for many employees, and in our dataset, having between 50 to over 100 employees reporting to one leader is not uncommon, making it hard for these leaders to follow individual problems and conflicts on a day-to-day basis. Administrative leaders in universities, however, normally have considerably fewer employees per leader, and having over 20 employees is regarded as a big group for administrative leaders. In Norway, managers of scientific personnel are given a fixed-term position for 4 years, with the possibility to apply for two more periods. They must have a relevant PhD to obtain a leader position, but unfortunately, previous management experience is not always a job demand and can vary. Therefore, one may have leaders with a large span of employees and limited leadership experience. This in combination with more rotation in the leadership positions for scientific personnel than for administrative personnel might explain some of the differences found between the groups in our study.In scientific positions, there are also some potential stressful demands such as uncertainty regarding receiving a permanent job position from Ph.D. positions to tenure tracks, high requirements regarding students’ feedback and evaluations, and measurements of research production. There is also a high degree of competition to obtain Ph.D. students and external funding, with much effort placed on applications despite the often-limited chance of their success. All of this may lead to a higher stress level in general among individual employees in scientific positions. Administrative staff can also have stressful work demands, but as a rule, there seems to be less competition among them for the same resources, and they are often in regular positions and experience more cooperation towards common goals, thus reducing the risk of being exposed to bullying and negative acts at work.Universities have also been described as large and hierarchical organizations with an unequal distribution of power across positions , giving One interesting finding in our results is the big difference in the models measuring how job demands and resources influence bullying among administrative personnel compared to scientific personnel. In both groups, job demands had a much stronger effect on bullying than job resources. Job demands in our study were represented by quantitative job demands, institutional stress, lack of cooperation, and lack of feedback. In our model, demands had a 2.5-fold stronger effect on the level of perceived negative acts than resources among administrative personnel.When it comes to the results for the scientific personnel, the effect of resources was not as significant as the effect of demands on bullying, which was about five times greater. We argue that such a difference between the two groups of personnel can be explained by the differences in demands and resources in the job tasks and roles of the different positions, and thus, we claim that to reduce bullying, one must be aware of what types of demands and resources one needs to minimize or maximize for different types of employees. Our results also show that resources were not significantly related to bullying in the group of scientific personnel. This is a surprising finding considering the importance that resource factors including meaningful job tasks, autonomy, and social support have shown in theories on work motivation and well-being . The resAnother interesting finding in our study is that the variable of institutional stress seems to be an important job demand that predicts bullying among scientific personnel. Institutional stress is related to disagreeing with the organization’s policy, with the amount of power and influence one has as an employee, having conflicting values with those of the organization, and feeling that the organization uses the wrong parameters to measure the quality of one’s work . A move Institutional stress may lead to a conflict between different worldviews in the academic sector, typically observed between those who manage, plan, and propose and those who are expected to follow and respond based on their views regarding different rationalities. For example, at a university, it is an important value and goal for most researchers that their research be free from leaders’ influence and be based on the interests, competence, profession, and knowledge of the researchers’ themselves. However, to finance one’s research, one is dependent on external funds, applications, and leadership steering the direction of research towards certain goals, values, and outcomes. In this landscape, organizational changes such as quality reforms in teaching and new rules and regulations regarding research time and funding can lead to a changing role of scientific positions, and scientific professionals can perceive demands coming from top management and political levels as a threat to the principle of academic freedom and independence in scientific positions. Some scholars have claimed that radical governmental changes have undermined important professions such as professors and doctors in public organizations . The chaIn some organizations, bullying and other forms of harassment seem to be more or less “allowed” because such events are met with higher levels of tolerance than in other work environments. In universities, there can sometimes be a fine line between critical thinking that is important in academia and personal harassment.Our findings indicate that structural organizational resources and demands predict a level of workplace bullying among university personnel and that scientific staff as a group experience different effects of demands and resources on bullying than administrative staff. There is also a significantly higher risk of experiencing both negative acts at work and self-reported bullying in a scientific position. Our findings also show that the effect of demands on bullying is stronger for the scientific staff than for the administrative staff.Although management has little control over individual personality traits and characteristics, except in recruitment and promotion decisions, work environment factors are to a greater degree under the control of management, who may exert considerable influence on organizational structures, workflow, information flow, reward systems, job design, leadership training, conflict resolutions, and ensuring negative consequences for negative behaviours .Future research based on our results should focus on how improved resources and increased demands for different professions in the university sector can decrease levels of bullying and negative acts. Our results indicate that an open, inclusive, and transparent management style when it comes to organizational changes and new requirements that affect employees’ everyday work can reduce institutional stress. A focus on how to create healthy, challenging, and supportive networks and groups where one can reduce individual competition and increase reward collaboration in research and teaching can be a good measure for both administrative and scientific staff.A goal to reduce bullying and harassment must be central to all organizations because an average of 13% of employees report being bullied at work in general in the Norwegian university sector , and thi


Although smart speaker technology is poised to help improve the health and well-being of older adults by offering services such as music, medication reminders, and connection to others, more research is needed to determine how older adults from lower socioeconomic position (SEP) accept and use this technology.This study aimed to investigate the feasibility of using smart speakers to improve the health and well-being of low-SEP older adults.A total of 39 adults aged between 65 and 85 years who lived in a subsidized housing community were recruited to participate in a 3-month study. The participants had a smart speaker at their home and were given a brief orientation on its use. Over the course of the study, participants were given weekly check-in calls to help assist with any problems and newsletters with tips on how to use the speaker. Participants received a pretest and posttest to gauge comfort with technology, well-being, and perceptions and use of the speaker. The study staff also maintained detailed process notes of interactions with the participants over the course of the study, including a log of all issues reported.At the end of the study period, 38% (15/39) of the participants indicated using the speaker daily, and 38% (15/39) of the participants reported using it several times per week. In addition, 72% (28/39) of the participants indicated that they wanted to continue using the speaker after the end of the study. Most participants  indicated that the speaker was useful, and approximately half of the participants felt that the speaker gave them another voice to talk to  and connected them with the outside world . Although common uses were using the speaker for weather, music, and news, fewer participants reported using it for health-related questions. Despite the initial challenges participants experienced with framing questions to the speaker, additional explanations by the study staff addressed these issues in the early weeks of the study.The results of this study indicate that there is promise for smart speaker technology for low-SEP older adults, particularly to connect them to music, news, and reminders. Future studies will need to provide more upfront training on query formation as well as develop and promote more specific options for older adults, particularly in the area of health and well-being. As the global population ages, new solutions that address multiple dimensions of health and well-being are needed to ensure healthy aging. In addition to promoting physical health, a range of factors may contribute to emotional and social well-being, which are key pillars for healthy aging and the ability of older adults to lead rich, independent lives . Those fFactors that may help low-SEP older adults compensate for limitations or lack of resources or may help them leverage their positive capabilities and interests may be vital to promoting and maintaining well-being . InformaPrevious research has indicated that there is an association between technology use and well-being among older adults, with internet use reducing loneliness, predicting better mental health, increasing life satisfaction, and improving communication ,5.Technology offers the opportunity to increase connections with friends and family and connect to the necessary resources and knowledge (such as providing links to news sources or services) to remain engaged with the society at large without in-person interactions with others . In addiHowever, several challenges have historically impacted the ability of older adults to fully engage with technology . For exaskills, which are voice-based apps (similar to voice-based versions of apps that appear on smartphones). Commonly used skills include the ability to play music, find recipes, check the news, and ask health-related questions.A key component of this interface is the feature of voice-activated personal assistants, which use artificial intelligence to create tailored, personal interactions through adaptive learning systems that may converse directly with the user in a back-and-forth discussion . In addiAlthough there is promise in enhancing well-being through these devices, research involving smart speakers and older adults is still in its early stages. Often, research involving smart speakers is conducted using one-time quantitative or qualitative surveys that gauge potential interest or initial reactions. A feasibility study conducted in a California retirement community deployed smart speaker devices in residents’ homes, conducting focus groups and training workshops . FeedbacHowever, it is vital to replicate and expand these studies with more groups of older adults to truly gauge their acceptance and relevance for this age group. Although the features of voice technology are poised to remove barriers to traditional technology use, more research is needed on the exact features of the technology that are perceived as most beneficial for older adults and the areas in which they require additional learning to use the speaker successfully. Furthermore, research should focus on low-SEP individuals, particularly given the previous findings of challenges with other forms of technology, to ensure that using these smart speakers does not further propagate communication inequalities. Measuring the potential barriers and facilitators of speaker use can determine whether these speakers will resonate with older adults in ways that can foster health and well-being.This study aimed to investigate the feasibility of using voice interface technology in group of low-SEP older adults living in a subsidized residence for older adults. Our specific aims included (1) documenting the frequency of use of technology and the ways in which the technology was used; (2) assessing the acceptability and usability of the technology, as measured through process data and survey assessment; and (3) measuring the interest in and the use of the speaker for health information seeking.Older adults were recruited from a residence facility for older adults subsidized by the United States Department of Housing and Urban Development (HUD) in South Georgia to participate in a 3-month feasibility study. This study was reviewed and approved by the Harvard T.H. Chan Institutional Review Board (19-0304).The eligibility criteria for the study included being in the age range of 62-85 years, living alone, and not having a smart speaker currently at their residence. The upper bound of 85 years was determined because of the increased risk of cognitive concerns such as memory loss or dementia past this age. The site principal investigator made an initial presentation to a group of 52 residents. In the presentation, she presented the features of the smart speaker and the details of the study through a Microsoft PowerPoint presentation. At the end of the presentation, interested residents were invited to fill out a screening form for consideration for joining the project. The names of those who appeared eligible were discussed with the center staff to determine if they were cognitively able to participate. There were 24 individuals who filled out the screening form after the presentation; however, only 15 individuals were eligible. There were 11 individuals who filled out the screening form but were ineligible: 3 individuals were excluded because of cognitive concerns, 5 individuals were excluded because of age >85 years, 2 individuals were excluded because of living with others, and 1 individual was excluded because of already owning a smart speaker .Although many participants expressed hesitance to adopting a new technology, there were several factors that helped to overcome this hesitance. The first was the partnership with and advocacy of the management staff at the residence in helping to recruit and reassure residents. Throughout the study, they served as champions for the project and helped to encourage residents to participate. They also kept a speaker unit in their office to learn about the speaker and to demonstrate its use to the residents. Second, as the first participants were connected to their speakers, other residents became interested after seeing the participants demonstrate the speaker’s capabilities. Once the first residents provided positive reports on their speaker use, more residents agreed to participate. Therefore, we created a rolling enrollment process that spanned 2.5 weeks to recruit and enroll the remaining participants, reaching a final number of 39 participants . During Screened, eligible participants were then walked through the consent process by the study team. Before signing the consent form, each participant reviewed the terms of use of the smart speaker with the site principal investigator and then discussed a set of comprehension questions to ensure that participants understood the basics of the smart speaker (such as data tracking and privacy) before signing. After signing the terms of use of the speaker, the site principal investigator reviewed all study details with the participant and then had them sign the study consent form.Before installing the smart speaker, the research team verified that each resident had internet access in their apartment. Overall, 56% (22/39) of the participants had internet access in their apartment before the study. Those without internet connection were provided connection through either a 3-month account setup and paid for by the study staff or assistance to obtain a low-cost internet connection offered for HUD housing–based residents in their own name. Most participants  elected to set up their own internet accounts.Once internet connectivity was established or verified, the study staff visited the participant’s residence to install the smart speaker in the home. Each participant’s speaker was connected using their unique study account ID and study-generated email address. After the speaker was connected and activated, the staff provided the participant with a brief orientation to the speaker, including how to ask questions to the unit, adjust the volume, play music, and set reminders and alarms. In addition to the brief introduction, each participant received an introductory sheet on the smart speaker that provided instructions on how to make simple queries or give commands.The participants were then involved in the study for a 3-month period. During the study, participants received weekly check-ins with study staff in the form of phone calls and help desk hours. All issues were documented by the study staff and addressed as needed. The site principal investigator held 3 workshops throughout the study period in which participants’ questions were answered and additional tips were shared on how to use the speaker. Periodic newsletters introduced other ways to use the device, providing wording to request that the speaker perform actions such as reading Bible verses, tracking calories, and playing games. Emphasis was placed on activities that increased health  or mental well-being (learning to have conversations with the speaker and connecting to podcasts or games).At the end of the study, if the participant desired to continue with the speaker, the study staff assisted them in connecting the speaker to their personal accounts. If the participant did not want to continue using the speaker, the study staff assisted them with deregistering the speaker and canceling internet accounts, if needed.Once participants consented to participate in the study, they received a paper-based pretest survey that asked them about their mental well-being, loneliness, social well-being, demographics, prior technology use, comfort with technology, and social networks.During the 3-month study period, participants’ speaker use data were recorded through their study account; each query made to the speaker was documented in the speaker’s records. As a user operates the smart speaker, each interaction with the speaker is recorded in the user’s personal account. One key component of the study was the use of back-end data to record the interactions with the device. To do so, the study staff created study-related email accounts and study-related accounts with the speaker’s parent company. These accounts were created so as not to use participants’ real names in any recording; the study accounts only contained links to the participant’s ID number. Process data were also tracked through a spreadsheet in which the study staff recorded each weekly check-in call with the participants, including any specific comments that were made.At the end of each participant’s 3-month study period, the participant was given a paper-based posttest that asked for repeated measures on health and well-being as well as asked questions on usability and perceptions of the speaker.Responses from the paper-based pre- and posttest survey, along with the process data gathered throughout the survey, were included in this study.The participants were asked about their age, sex, income, and highest level of education. Food security was measured by providing the statement, “in the past 12 months, the food we bought ran out and we did not have money to get more,” with response options being never, sometimes, or often true. Income security was measured by asking participants to select a phrase that described their household income, with options being living comfortably, getting by, finding it difficult, or finding it very difficult on present income.We asked participants if they had ever used the internet, how often they used it, and if they had internet access at their residence. Participants were asked to select the devices they currently owned and used, with response options including smartphone, tablet, computer, and smart television. Participants were also asked to indicate their level of comfort with technology, with response options including not comfortable at all, somewhat comfortable, comfortable, and very comfortable using technology.In the posttest, participants were first asked how often they used the speaker during the 3-month study period. They were then asked to rate whether the speaker was easy to use, if it seemed easier to use over time, and if they understood how to ask the speaker a question, with response options ranging from totally disagree to totally agree. Participants then rated how often the speaker correctly understood their questions, with response options ranging from all the time to never.On the basis of the feedback gathered throughout the study, we created an index of reactions to the speaker content, including how connected the speaker made them feel to the world, if it helped them keep track of appointments, if the speaker helped them keep track of the day or time and appointments, and if it made them feel less lonely.A spreadsheet was created that tracked each interaction with the participants, including phone calls and in-person interactions. For each interaction, the study staff listed the topic of the call, including any issues or positive statements about the speaker. Resolutions for these issues were also noted.Responses to the pretest and posttest were analyzed. Frequencies and percentages were gathered from all pretest and posttest variables. Process notes were analyzed for counts of certain types of issues or interests expressed by the participants.The final sample comprised 39 participants . Most . The most frequently owned device was a smartphone .Before the study, 56% (22/39) of the participants were using the internet (on a computer or smartphone) at least once per day, and 33% (13/39) of the participants rarely or never used the internet, with those who had in-unit internet access significantly more likely to use the internet frequently  of the participants said that they had used their speaker once per day, and 38% (15/39) of the participants had used it several times per week. There were no significant differences between having internet access before the study and use or usability ratings of the smart speaker.After the study, 72% (28/39) of the participants kept the speaker, with 53% (9/17) of the participants who did not have prior access keeping the speaker and retaining their internet access to continue use. Of the 11 participants who did not keep their speaker , 3 had tReason given by participantsRelied on a study-based internet connection and were not able to maintain internet connection. (3 participants)Had increased privacy concerns and did not want to use the speaker (1 participant)Felt that other newly purchased devices (tablet) provided more value (1 participant)Had trouble hearing the speaker and lost interest (1 participant)Had difficulty with the internet provider and lost interest (1 participant)Did not have any other devices; did not want to maintain the internet connection (1 participant)Liked the device but did not want to continue using it (1 participant)Did not use the device often and did not want to maintain the internet connection (1 participant)No reason given (1 participant)good morning and good night to the unit.Common uses of the speaker that were quantified in the posttest are reported in More than half of the participants agreed or strongly agreed that the speaker was useful , helped them obtain the required information , and helped them keep track of the day and time  of the participants commented in their check-in calls about the difficulties with asking questions to the unit. Owing to frequent comments about this issue, a workshop was held to provide assistance. Within this workshop, it was revealed that there were the following concerns: (1) participants felt that the device was giving inconsistent answers to the same question, (2) participants felt that the device was not acknowledging them, and (3) participants were often asking questions that were too long or complex (such as multipart questions). Many participants were asking multipart questions that the speaker could not process, were pausing too long between the wake word and their request, or were spending time trying to frame their request in a polite manner (during which time the speaker determined that the request was not relevant). Within this trial session and workshop, it was also determined that there were some options that required skills (particular apps that are saved within the speaker preferences only once the user activates them) to provide reliable answers to particular questions. For example, if the participant wanted the speaker to read Bible verses, a particular skill could be enabled that would provide the desired results of requesting a particular verse. However, without requesting to open this skill, the speaker may pull from various other sources (or interpret their request as asking the speaker to recite the whole Bible from the beginning), thus the answer discrepancy. Owing to these issues, the research team offered suggestions and created a newsletter that addressed common ways of wording  and simple directions to enable commonly desired skills.Another issue discovered through process notes was that 5 participants had volume issues. Volume issues were often exacerbated by loud air conditioner units that were in the same room as the speaker, as most participants preferred that the speaker be placed in their living room. Each participant who noted a volume issue was provided with an additional Bluetooth speaker that could increase volume.Within the process notes, several direct quotations noted also speak of the positive reaction to the speaker .Quotes from participants about their speaker interactions“it is nice to have someone to talk to.”“it’s like [the speaker] is a little friend.”“I enjoy the company.”“The speaker has ‘become part of the family’.”“at least I have somebody to talk to.”This feasibility study indicates promise for the use of smart speaker technology in a group of low-SEP older adults. By providing the speaker and related support to older adults, the research team was able to observe the barriers and facilitators of initial speaker use in this population. Overall, the speaker was well received by most of the sample, with 38% (15/39) reporting daily speaker use and 38% (15/39) reporting using it several times per week. Participants perceived the speaker as useful and assisting them in finding the information they needed. Although there were initial barriers to uptake in using the speaker, frequent monitoring and check-ins with study staff alerted the study staff to these issues; once addressed, the perceived ease of use of the speakers appeared to increase.Notably, most of the participants  opted to continue using the speaker after the study period ended. This illustrates the journey of many participants from being technology hesitant to routinizing technology use in their day-to-day lives. Although there was a learning curve for understanding how to frame questions to the speaker, it was embraced by many respondents. At the end of the study, 53% (9/17) of the participants who did not have internet access before the study elected to maintain internet access and continue using the speaker. This echoes the patterns observed by the Pew Research Center that once older adults are on the web, the technology becomes a daily fixture; among internet users aged ≥65 years, 75% use the internet on a typical day at least daily, with 51% saying they go on the web several times per day and 8% say they use the internet almost constantly . This peParticipants found many sources of value of the speaker, including connecting to the world, accessing information, and using the device for reminders. Process data notes taken during check-ins reflect the interest in using the speaker for reminders of doctors’ appointments and social engagements, particularly to remember events happening within the residence. Participants indicated the value of the speaker to help them keep track of the day and time, a feature that was deemed useful for keeping track not only of appointments but also to anchor them to the present. The frequency and enthusiasm with which participants used the speaker for this purpose and for connecting to music and other interests suggests the potential for this technology to be an asset to this population, particularly in overcoming some of the additional challenges to mobility, dexterity, and resource access by low-SEP older adults . For exaThis study identifies some potential strengths and weaknesses of smart speakers in this population. Despite the initial hesitance with the speaker, most participants found value in the speaker, using it several times per week, with many even reaching daily use. Future analyses of our back-end data will further explore how this has been integrated into their lives.This study also points to potential issues that should be addressed when designing a smart speaker study within this population. First, initial hesitance to technology use may be noted, particularly because of privacy concerns. Within this project, the buy-in and assistance of the staff at the residence were critical to project success, as they provided space for residents to convene for speaker-related activities and served as champions for our process. Second, this study points to the need for targeted training on using the device once it is installed, with emphasis placed on how to properly craft questions and how to activate certain skills of interest. Of note is the lower percentage of participants  who felt that the speaker helped them with their health or nutrition. Within the study, the newsletters that were provided to participants emphasized different health-related activities for participants to try, such as asking for calorie information in certain foods but process findings suggest that these queries did not always yield useful information. These frustrations with correctly framing questions have also been cited in a previous qualitative study, in which groups of older adults were invited to test out the speaker . StudiesThis study had some limitations. As we created study accounts, we were not able to sign participants up for some of the specific older adults–focused skills that required passwords and personal details; therefore, we were unable to study the use of these targeted apps. Our recruitment also occurred within one senior housing unit in which participants would often share tips and experiences with other participants in the study. It is unknown whether we would have had the same success if we had conducted this study with home-dwelling older adults.Despite these challenges, smart speakers are still poised to alleviate some of the main barriers to technology use in this population once these factors are addressed. Many functions that were of value to the participants were integrated quickly into routines upon brief demonstration  and showed immediate value at a low cost. Several participants reported gaining confidence in technology because of the ease of the speaker for basic functions, and they were eager to learn how to explore more uses. Speaker manufacturers may consider building in features that can aid in understanding additional speech patterns and have easier-to-navigate menus of information options built into basic features. Although some of these features may appear in certain skills geared toward older adults, these functions would assist a larger section of the population that has low literacy and low health literacy use the unit to find the required information. Future research may explore in greater detail the value of other aspects of the speaker, such as the aforementioned specific skills designed for older adults as well as other smart devices that can be linked to the speaker to assist further with daily life, such as smart switches and thermostats, that may assist low-SEP adults in living independently.Smart speakers show great promise for providing low-SEP older adults with an opportunity to increase their connection with music, news, and the weather as well as providing a way to anchor them to the date and time. As research using this speaker in this population progresses, special attention should be paid to the design of health-related skills and services to determine the best way to engage older adults with relevant, useful health content.


In those theories or empirical-evident model of sexual offending, they all recognized which major life event would cause the sex offense in some conditions, therefore the onset crime of sexual offenders were not only a mark of personal history, but also could reflect the heterogeneity of sexual offenders. Our purpose is to study the onset crime typology of sexual offender and their difference in specialization, problem of psychology marks, and negative developmental experiences. We analyzed the pre-conviction data from 3,750 sexual offenders and their risk assessment data. The research results found that onset typology of sex crime would persist their criminal career into sexual offending, and through the group comparisons, the study pointed out differences in risk factors domain and adverse development experiences. We also discussed those research results and their meaning of risk management. The severe and long-term physical and mental health issues caused by sexual assaults should be a major public concern . Many ofBoth descriptive and etiological models of sexual offending and the characteristics of cognitive structures and operations indicate that aspects of previous experiences in the lives of sexual offenders have an impact on the trajectory and shaping of sexual assault, which cannot be ignored, particularly aspects that open them up to violence or offenses. For instance, Using the criminal records of over 3,000 sexual offenders, Past studies on sexual offending have mostly focused on the fact that a significant correlation exists between the age at which sexual violence is committed and the subsequent sexual recidivism of the sexual offender . HoweverThus, the objective of this study was to group sexual offenders by their onset typologies and compare their criminal characteristics. Because there is no consensus used crime categories, our study tried to referenced the research strategies from different studies to choose this four type of onset crime, and it was also convention in criminology e.g., . We refeUnder the legal procedure of Taiwan, all sexual offenders should get into community treatment in order to monitoring and make sure public safety. Therefore, first step of community treatment is to do risk assessment, all information is imported into a special database system, which is called “National Domestic Violence, Sexual Assault, and Children-Juvenile Protection Information System,” it belongs to Ministry of Health and Welfare of Taiwan. This study was a research project commissioned by same unit (project case no. M04B3252). All risk assessment done by trained therapist.Research data were delinked export from this database system, and then, in accordance with the regulations of the Personal Data Protection Act, a case handler anonymized all of the required data before providing the data over to our research team, such that the file for each sample was only marked with a case number. The procedures and methods employed in this study were reviewed and approved by the Institutional Review Board of Fu Jen Catholic University .In order to analysis onset group typology, our research team looked for the Offense Determination Table and transcribed the criminal record data by age at the time of offense and by the type of offense. Then we also extracted the Static-99, acute dynamic risk factors, stable dynamic risk factors, and the four items of developmental history  from the assessment data as group comparison variables and used them to retrospective the potential influence of the onset offense typology.All obtained data regarding 8,370 sexual offenders from 2007 to June of 2015 from the database system. Inspecting the completeness of the data and removing any samples lacking criminal record data for onset typology analysis resulted in data from 3,750 sexual offenders. Furthermore, we removed samples with overly incomplete data, that is when lack of any one of index sexual offense information, criminal records, and risk scales, research team would define them as overly incomplete data and excluded for data analysis. Followed this procedure, which resulted in complete risk assessment data from 819 sexual offenders for group comparison analysis. As shown in n = 488, 59.6%), violence , property , and addiction . We listed in The official criminal record data provided by the Offense Determination Table  of the “National Domestic Violence, Sexual Assault, and Children-Juvenile Protection Information System” included length of sentences, the criminal charge, and the personal criminal history of the sexual offenders. We focused on four types of offenses: sexual offenses, violent offenses, property offenses, and addiction, as categorized by However, our research found significant differences in onset group comparison of number of sexual offenses, age of first offense, and intervals of any offense. For further analysis, research results pointed out the sex onset offending group was higher than addiction onset offending group in “number of sexual offenses.” But both of “age of first offense” and “intervals of any offense” were significant higher in violence and property onset offending groups than the other onset groups. When we analyzed the victim type differences of different onset groups, the research found that sex onset offending group had more than 50% of adolescence type of victim, but in the addiction onset offending group was adult female type of victim.This scale makes assessments based on information in official documents and records from arrests of sexual offenders . The scale contains ten items, and a higher score represents a higher risk of recidivism . Harris The dynamic risk factors are psychological markers that may related to recidivism. Those items also included the database system, they included two risk assessments: stable dynamic risk factors and acute dynamic risk factors. These scales were developed by In this database system, they also included four items of developmental variables that related to risk of future re-offense, the trained therapist evaluated personal history of sexual offender throughout risk assessment. Items of developmental adversity included: Any childhood sexual victimization (under 12 years old), poor family relationship, maladaptive in school, and any conduct problems under 18. All items rated as yes (1) / no (0).To understand whether the criminal careers of sexual offenders converge or change, we referred to the method proposed by Researchers interested in essential difference in onset typology of sexual offenders, therefore we use one-way ANOVA to do group comparison with offense-related variables, include prior any offense records, index offense information, sexual specialization, four areas of psychological markers, and developmental adversities.Based on the criminal charge of the first offenses in the official criminal records, we divided the first offenses of the sexual offenders into four different onset typologies and then conducted one-way ANOVAs and chi-square tests using SPSS. The results are displayed in The selected data in this study mainly originated from sexual offenses. As shown in The analysis of specialization in sexual offending in the various onset typologies in In the analysis above, we observed variations in the criminal careers of sexual offenders with different onset typologies. We further explored whether specialization and versatility can also reflect differences in four common psychological markers among sexual offenders. These psychological markers include the following: sexual self-regulation, offense supportive cognitions, the level of interpersonal functioning, and general self-regulation problems. Using the data in The theoretical models discussed by This study attempted to determine whether the onset typology of sexual offenders reflects differences in the nature of sexual offending using the perspectives of For the four risk factors, we only used Static-99 and a stable dynamic risk factor scale to analyze the differences among the sexual offenders with different onset typologies, and these methods were enough to elucidate some issues with proportional distribution. For instance, though weak, only one observed variable for offense-supportive cognitions could be analyzed, and consequently, the results could not show differences among the different onset typologies. This is a limitation of using samples from a database because the results can only be analyzed with a limited amount of information. Future studies involving psychological markers may improve on this by strengthening measured content. Those results of developmental adversity presented by the results above, it is worth considering that regarding the sexual onset offending group, the key influence was the onset offense and the certain degree of fixation that it created in the learning experience of the offender. For instance, the experience and feelings of committing a sexual assault influenced the evolution of future criminal behavior, and although only a little more than 20% of offenders specialized in sexual offending, their tendency to fixate on sexual offending is still a concern for society at large. In another aspect, the analysis above indicates that offenders with violent offenses, property offenses, and addiction presented the same specialization tendencies. From another perspective though, only 20 to 30% of these offenders will specialize in their respective offenses. In other words, no matter what the onset offense is, about two-thirds of offenders’ progress toward a versatile criminal career in the future. Thus, the results of this study indicate that to a certain degree, the onset typology of offenders will determine the development trajectories of their future criminal careers and leads them to specialize in a certain type of crime. However, criminal versatility is still an issue that requires attention. Based on these study results, it is worth deliberating how current correction and treatment policies can make arrangements for prison inmates who will return to society.This study explored two criminal career characteristics: the onset typology and criminal specialization. Those results of developmental adversity support the views of The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Institutional Review Board of Fu Jen Catholic University . Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.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. 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