Process-Based CBT: The Science And Core Clinica... Free

Edited by Steven C. Hayes and Stefan G. Hofmann, and based on the new training standards developed by the Inter-Organizational Task Force on Cognitive and Behavioral Psychology Doctoral Education, this groundbreaking textbook presents the core competencies of cognitive behavioral therapy (CBT) in an innovative, practically applicable way, with contributions from some of the luminaries in the field of behavioral science.

Process-Based CBT: The Science and Core Clinica...

As the discussion above indicates, some modifications may signify decreases in fidelity, while others may be consistent with the design of the intervention. The tension between modification and fidelity is a critical issue in implementation science [4, 54, 55]. Many recognize that modifications will occur throughout the course of an implementation effort, but the type and extent of modifications that can occur without compromising effectiveness or degrading fidelity to an unacceptable degree has not been sufficiently explored. In theory, it is possible to make some types of modifications without compromising effectiveness or removing the key elements of an intervention. However, for some interventions, the core elements have not yet been determined empirically, and very little is known about the impact of behaviors such as integrating other interventions or selectively implementing particular aspects of a treatment. Fidelity measures that emphasize competence or the spirit of an intervention over adherence may not adequately capture some potentially important types of modification, and those that emphasize adherence may not capture modifications such as tailoring. Thus, when observation or reliable self-report is possible, the use of a fidelity measure along with this modification framework can guide decisions regarding the extent to which a particular modification represents a departure from core elements of an intervention. Used alone or as a complement to fidelity measures, this measure may also be useful in determining whether particular elements can be removed, re-ordered, integrated or substituted without compromising effectiveness.

Introduction. Part 1. 1. The history and current Status of CBT as an evidence-based therapy. 2. the philosophy of science as it applies to clinical psychology. 3. Science in practice. 4. Information technology and the changing role of practice. 5. Ethical competence in behavioral and cognitive therapies. part 2. 6. Core behavioral processes 7. What is cognition? a functional-cognitive perspective. 8. Emotions and emotion regulation. 9. Neuroscience relevant to core processes in psychotherapy. 10. Evolutionary principles for applied psychology. part 3. 11. Contingency management. 12. Stimulus control. 13. Shaping. 14. Self-management. 15. Arousal reduction 16. Coping and emotion regulation. 17. Problem solving. 18. Exposure strategies. 19. Behavioral activation. 20. Interpersonal skills. 21. cognitive reappraisal. 22. Modifying core beliefs. 23. Cognitive defusion. 24. Cultivating psychological acceptance. 25. Values choice and clarification. 26. Mindfulness practice. 27. Enhancing motivation 28. Crisis management and treating suicidality from a behavioral perspective. 29. Future directions in CBT and evidence-based. Therapy. Index.

The position responsibilities include tasks related to research topics above, co-authoring papers, and mentoring students. AWE Lab members are expected to participate in lab meetings, retreats, field work and training activities as well as public engagement initiatives throughout the year. Public engagement and public science are fundamental to the AWE Lab, which seeks to inspire new generations of scientists and create opportunities for non-scientists to contribute in combatting the ecological and environmental challenges facing our planet. Diversity, equity, justice and inclusion are also core values in the AWE Lab and we are committed to ensuring the lab reflects those values and integrates them into our work. As such, we strongly encourage applications from researchers identifying as members of marginalized or underrepresented groups.

FDS launches in October of 2022, and will move into a newly renovated Kline Tower in the summer of 2023 along with the departments of Statistics & Data Science, Mathematics, and Astronomy. The institute was created to advance research in the mathematical, algorithmic, and statistical foundations of data science and their application to other disciplines. In addition to providing support to core foundational research, the institute hosts activities to help scholars across the university apply new methods of data science to their research. In turn, those scholars help us discover their unmet needs and thereby inspire the development of new methods and theories. Applying: Applicants should submit a cover letter, a curriculum vitae, and a research statement. The cover letter should list Yale faculty the applicant views as potential mentors. At least one of these should be a member of the institute. Applicants should arrange for the submission of three to five letters of recommendation. Creating a public Google Scholar page and an academic webpage is strongly encouraged. Timeline: Postdoctoral appointments typically begin in July or September. But, other arrangements are possible. We will review applications on a rolling basis. Those received before November 15, 2022, will be reviewed in the Fall. Those received later may have less of a chance of acceptance. The last review should conclude in May 2023. Funding: The yearly salary for the postdoctoral fellows is $95,000. They will also be supplied with a $10,000 / year fund to cover travel and research expenses. Yale University is an Affirmative Action/Equal Opportunity employer. Yale values diversity among its students, staff, and faculty and strongly welcomes applications from women, persons with disabilities, protected veterans, and underrepresented minorities. Please submit your application materials via this portal: . Questions may be sent to FDS Managing Director Tom Keegan at Thomas.keegan@yale.edu.

Qualifications for the position include a Ph.D. in geography, landscape ecology or a related field, experience in collecting and analyzing movement data, strong publication record, and exceptional research and communication skills. The candidate should have demonstrated competency using GIS, python, R, Google Earth Engine and remote sensing, Github as well as occupancy modeling, step selection, agent-based modeling, circuit theory and habitat selection. The position responsibilities include tasks related to these research topics, co-authoring papers, and mentoring students. AWE Lab members are expected to participate in lab meetings, retreats, and training activities, as well as public engagement initiatives. Public engagement and public science are core values of the AWE Lab, which seeks to inspire new generations of scientists and create opportunities for non-scientists to develop empathy for wildlife and a greater investment in the ecological and environmental challenges facing our planet. Diversity, equity, justice and inclusion are also core values in the AWE Lab and we are committed to ensuring the lab reflects those values. As such, we strongly encourage applications from researchers identifying as members of marginalized or underrepresented groups. 041b061a72