Behaviour Modification Model Research Articles

Mastering minds: Unleashing the power of Neuro-Linguistic Programming in workplaces and schools

Neuro-Linguistic Programming (NLP) intricately examines the visual, auditory, and kinesthetic representation systems, traversing the transformative trajectory from superficial to profound linguistic structures. This comprehensive paradigm elucidates the sophisticated cognitive processes through which the brain interprets events, molding emotions and behaviors through filters such as values, beliefs, memories, decisions, and meta-programs. As a potent catalyst for excellence and success, NLP empowers individuals and organizations to realize their aspirational objectives, nurturing flexibility, creativity, and autonomous behaviors. In educational contexts, practitioners adeptly employ NLP techniques to navigate conflicts, enhance leadership acumen, and inspire personnel toward organizational goals. NLP assumes a crucial role as a foundational element for ongoing learning, development, and the cultivation of dynamic capabilities within professional environments. Its applications extend beyond conventional business domains, seamlessly integrating with behavior modification models employed in psychotherapeutic settings. In the realm of child psychiatry, NLP addresses neurodevelopmental disorders, such as oppositional defiant disorder, with the potential to mitigate triggers in educational milieus. The Behavior Modification Model, anchored in the ABC (antecedents, behavior, and consequences) framework, meticulously shapes behaviors through positive and negative reinforcement and punishment. NLP is a versatile professional instrument applicable across personal development, therapeutic interventions, and diverse organizational landscapes. It is pivotal in elevating communication effectiveness, facilitating conflict resolution, and propelling individual and collective success to new heights. Applying NLP in schools proves invaluable by elevating teaching methodologies, cultivating effective communication, and nurturing essential skills for conflict resolution and leadership. Integrating NLP in educational settings can offer a holistic approach to learning, providing support for educators and students alike in navigating intricate situations and fostering an environment of continuous improvement. Implementing NLP should be approached with a balanced understanding of both its potential benefits and the need for empirical validation and ethical considerations.

IMPROVING COGNITIVE SOCIAL-SKILLS BY BEHAVIOR MODIFICATION TECHNIQUES: A STUDY ON ISLAMIC PRIMARY SCHOOL STUDENTS IN INDONESIA

Student behaviour, in general, is still a problem. Many students still need to be responsible for school assignments and do not do homework or other assignments. Concern for the environment is still very low. Like they were throwing trash in its place. Therefore, the ability of the teacher to intervene in modifying student behaviour is essential. This research was carried out to provide Behavior Modification Models for improving children's social skills. It was divided into four parts: (1) a preliminary study, (2) a workshop on behaviour modification, (3) a field test on the behaviour modification models and (4) improvement to the models following the test results. The participants consisted of 225 Islamic elementary school students in Indonesia. The data were examined by SEM (Structural Equation Modeling). The students' skills were developed using behaviour modification techniques, namely modelling, reinforcement, token economy, punishment, prompt, relaxation and shaping. The result suggested the importance of cognitive process (awareness) and learning contracts through class discussion for improving children's social skills. An interesting finding is that there is a significant increase in the application of behaviour modification techniques when students are involved in thinking and being involved in determining activities or actions that disturb the class and the consequences that will be given if students commit several violations in class through contract learning or agreement techniques, modelling, reinforcement, token economy, punishment, time out, relaxation and awareness of cognition.

Learning Models: A Literature Review

In education, learning models are a topic that should be investigated because it is both relevant and intriguing. This research aims to conduct a literature review on learning models that have been created and implemented in various educational settings. A literature review is a process that is used, comprised of collecting related articles from the available database. According to the findings of this research project, numerous learning models have been established over time. Some examples of these models include social interaction models, information processing models, personal models, behavior modification models, problem-based models, and component display theory models. The findings of this research point to the conclusion that these learning models are adaptable and may be utilized in various educational settings. This adaptability is contingent on the learning goals as well as the characteristics of the learners. The contribution of this research is to offer guidance to educators and researchers about selecting the appropriate learning model which should be implemented in various learning environments.

Effectiveness of Behavior Modification Models on Reducing of Non-Adaptive Behavior in Children with Intellectual Disability

Effectiveness of Behavior Modification Models on Reducing of Non-Adaptive Behavior in Children with Intellectual Disability

2460 Qualitative study of obesity risk perception, knowledge, and behavior among Hispanic taxi drivers in New York

2460 Qualitative study of obesity risk perception, knowledge, and behavior among Hispanic taxi drivers in New York

Why Big Data Won't Cure Us.

The biggest challenge for the use of “big data” in health care is social, not technical. Data-intensive approaches to medicine based on predictive modeling hold enormous potential for solving some of the biggest and most intractable problems of health care. The challenge now is figuring out how people, both patients and providers, will actually use data in practice. To understand how data-intensive solutions could have an impact on health care, our research team talked to frontline providers in impoverished and rural areas, technology enthusiasts in mobile health and health IT startups, clinicians and researchers in major research hospitals, Quantified Self members at data-driven meetup presentations of massive amounts of tracking data, and attendees at the growing number of conferences for health technology and innovation up and down both coasts. I found the buzz as feverishly loud around health information innovation as it was during my research on the first dot-com boom. One of our findings from this research seems at first blush so obvious that it is hard to believe it has been overlooked in the design and implementation of health-care innovation technologies. Namely, people imagine data in very different ways. Understanding this key fact about data helps us understand why so-called “big data” solutions to health care are so difficult to implement in practice. Doctors, patients, and health-care entrepreneurs all value data in very different ways. One physician simply said, “I don't need more data; I need more resources.”* Saying this in Silicon Valley or at TedMed would be tantamount to heresy. Ditto for those of us who work in research and spend our careers collecting, massaging, managing, analyzing, and interpreting data. From the doctor's perspective, though, data require (and do not save) extra interpretive, clerical, and managerial labor. This perspective on “data,” at least with regard to current clinical practice, is that data use up more resources than the benefits they provide. In other words, most doctors think data innovation means more work for them, not less, and takes away time from what they see as their key priorities in providing quality care. In another setting, we observed nurse-practitioner case managers in a Medicare demonstration project working with a simple algorithm parsing patient-entered health data. Combined with case management, these data provided a look into the daily health of chronically ill elderly patients and a pathway for the care when it was needed. The data in that project were tightly tied to medical expertise within an existing clinic where a trusted person could initiate a chain of care responses. Although widely recognized as a clinical success, Medicare pulled the plug on the project for financial reasons—expertise is expensive. These two reactions to data-intensive pilot projects highlight the dilemmas of data-analytic approaches to health care. Businesses are in the thrall of the possibilities of ever-increasing predictive analysis on expanding troves of generated data. While the business and technology sectors see data as valuable, doctors often see data as costs, risks, and liabilities. And for many in health care, data are not seen as a source of value, but of additional work. Without the work needed to make data valuable and useful in particular settings in particular contexts in health care, big data will never solve problems. To turn a technology truism on its head, data in health care will never be free. And yet, the ways in which health technology innovators have talked about the power of data neglects key aspects of the social interoperability or integration of data into health solutions. How will such data be integrated into care providers' work practices; through the complex routines of clinics and hospitals; and into existing legal, social, political, and economic frameworks? These questions are enormous. Until we solve these questions of social interoperability, the risks presented by “big data” in health will outweigh the benefits to any particular individual, regardless of whether we're talking about terabyte-scale analytics or the “small-data” of n=1 individuals. What follows is an outline of how to tackle these questions based upon what our team has seen throughout our research.

The Downside of Preclusion: Some Behavioural and Economic Effects of Cause of Action Estoppel in Civil Actions

The primary objective of the present article is to draw attention to the drawbacks of preclusion, especially of the rules of cause of action estoppel. The article challenges the traditional assumption that the rule of cause of action estoppel increases efficiency by introducing some economic and behavioural effects of the rule, especially the effects of the rule against splitting a single claim or cause of action. Analysis of the effects of cause of action estoppel has three major methodological goals: (a) to re-examine the rule in light of the behaviour modification model, (b) to evaluate the economic efficiency of the rule and its effect on the cost of litigation, and (c) to consider the influence of the rule on the chances of reaching a settlement. The article discusses the problematic incentives of litigating parties under the current Anglo-American rule of cause of action estoppel, and some of its harmful effects on the conduct and cost of litigation as well as on the chances of reaching a settlement. The article shows that, in many cases, the cause of action estoppel rules have undesirable effects on the conduct of litigation, including stimulating overlitigation in the initial action. Furthermore, the rule against splitting a single cause of action does not always contribute to an economically efficient legal system, and reduces the chances of reaching a settlement, which has a harmful effect on both the economic and behavioural aspects of litigation. By contrast, allowing the splitting of a single cause of action can significantly increase the litigants’ incentives to settle, providing the parties with opportunities for employing useful settlement strategies.

Balancing the harms and benefits of early detection of prostate cancer

van Leeuwen et al fail to explain why the prostate-specific antigen (PSA) by itself is misleading and how physicians can gather better data to achieve better outcomes with fewer side effects.1 A person may have a high prostate-specific antigen (PSA) level due to an enlarged prostate gland (which is quite common), irritation, inflammation, infection, or other changes of the prostate gland. Thus, a PSA level of 10 ng/mL may not necessarily require biopsies or aggressive therapy. I illustrate with 1 example so physicians will have a better view of likely noncancer variability (a subject that in my opinion is poorly understood and omitted in most studies). For over 5 years, patient PP had a PSA level between 9 and 11 ng/mL. He had a negative biopsy the first time his PSA level was found to be elevated. His prostate gland was substantially enlarged (but no exact measures were available), with the usual consequences. One day his PSA level was 21 ng/mL. The patient changed his diet and behavior drastically (losing weight, exercising more, eating healthier foods, and other behaviors). Within a few weeks, the PSA level declined to 15 and then 11 ng/mL. For the past 3 years, the patient's PSA level has remained between 9 and 11 ng/mL. When the PSA level was highly elevated, 1 of the top prostate cancer experts in the United States insisted that a biopsy be performed immediately, without waiting for repeated testing or the effects of the drastic diet and behavior changes proposed by the patient. The patient refused a biopsy. Physical examination of the prostate for the past 3 years has found no nodules. After having a PSA level of 10 ng/mL for >10 years, and 3 years after having a PSA level > 20 ng/mL, no cancer has been detected to date. PSA values of approximately 10 ng/mL are not necessarily indicative of a high probability of cancer, nor deserve biopsies. Although the relevant factors are not known, it is possible for a 10-point variation in PSA to be the result of factors other than cancer, which are correctable via diet, behavior modification, antibiotics (for infections), and other treatment models (different from cancer treatment). We need far better data regarding the probability of cancer given PSA level, prostate size, body size, prostate status (inflamed, infected, irritated, etc), types of diet, and other factors. We also need a probability distribution of the variability of PSA values over relatively short time periods (measured in months). In the interim, physicians should carefully evaluate the patient and consider alternative treatments (such as substantial weight loss and a healthier diet) before proceeding with a biopsy. Biopsies do have undesirable side effects, and could lead to unnecessary treatment, again with undesirable side effects. Eduardo Siguel MD, PhD*, * Gaithersburg, Maryland.

Childhood Obesity Prevention (CHOP) programme: a conceptual framework for nutrition intervention

The prevalence and severity of people suffering from obesity has increased markedly worldwide. The WHO declared obesity a 'crisis of epidemic proportion'. This article outlines a conceptual framework for an intervention programme over three year period that can be easily adapted to prevent childhood obesity. The presented approach is based on behaviour modification model without giving foods. Family, school and children are essential counterparts to achieve meaningful improvement. Advocated by policies makers and embraced with favourite environmental factors, CHOP programme could be the conceptual framework for nutrition intervention that can be effectively integrated within the national health framework to attain public health goals.

Social Learning Interventions in a Developmental Disabilities Partial Hospital Program

Social learning interventions have been widely applied to the treatment of psychiatric symptoms. However, treatments for individuals with developmental disabilities and coexisting mental illness have routinely emphasized reinforcement-based contingency strategies rather than cognitive approaches. The slower rate of integrating cognitive strategies may be due to several factors including adherence to widely accepted behavior modification models, failure to acknowledge the coexistence of mental illness with mental retardation, and the difficulty of adapting social learning strategies for the developmentally delayed. Treatment outcomes following the application of social learning interventions were observed in a psychiatric partial hospital program for persons with developmental disabilities and mental illness. Three cases are presented to illustrate the application of social learning interventions and highlight specific adaptations of treatment strategies to the cognitive functioning level and developmental...

Social phenomena and the planning of a nutrition education programme

The purpose of nutrition education is to promote better food habits in a community. In other words: behavioral change is the goal of nutrition education. On the basis of a Behaviour Modification Model by Van Beugen and data from case-studies on food habits proposals are formulated for the use of social data in planning a nutrition education programme.

Effects of the Use of Four Types of Teaching Models on Student Self-Concept of Academic Ability and Attitude Toward the Teacher

This study developed and used a multidimensional observation instrument to compare various “families” of teaching models: behavior modification models, information processing models, social interaction models, and person models. Classes of students whose teachers utilized various families of teaching models in differing proportions differed on Specific Self-Concept of Academic Ability but not on Attitude Toward the Teacher. Teachers who used positive reinforcers abundantly and/or information processing models were associated with higher student Specific Self-Concept of Academic Ability scores.

Effects of the Use of Four Types of Teaching Models on Student Self-Concept of Academic Ability and Attitude toward the Teacher

This study developed and used a multidimensional observation instrument to compare various “families” of teaching models: behavior modification models, information processing models, social interaction models, and person models. Classes of students whose teachers utilized various families of teaching models in differing proportions differed on Specific Self-Concept of Academic Ability but not on Attitude Toward the Teacher. Teachers who used positive reinforcers abundantly and/or information processing models were associated with higher student Specific Self-Concept of Academic Ability scores.