Medication Adherence: To Have is to Hold

Nature of the problem: Medication non-adherence is consistently the most frequent cause of mental health decompensation, relapse of mental illness, and hospitalization. The solution to non-adherence remains quite elusive, despite it being relatively easy to identity as the most major obstacle to successful control of mental illness. Method: Eighteen documents published between years 2002-2012 were rated using the AACN’s evidence leveling system. The 18 studies were examined to better understand what is known and not known about the challenge we face in trying to effect recovery and to prevent relapse of mental illness in the United States. Results: Various study designs, diverse interventions and treatment strategies demonstrated limited success in effecting sustained adherence. However, to date, the literature does not show there to be a single, simple, intervention that is effective. The evidence strongly suggests an interdisciplinary approach, using various combinations of interventions is the best strategy, but not a guarantee. A Power Point presentation was used to share the findings of this project with 13 PMHNP students and 2 active, expert PhD, PMHNPs. Nursing implications: Adherence is a complex, multi-determinant, individualized process that is embedded in the core belief of the person. Nursing can use this knowledge to collaboratively work with patients, their families, and other health care team members to devise approaches to facilitate recovery and understanding of the role of medication adherence in recovery maintenance

Currents and finite elements as tools for shape space

The nonlinear spaces of shapes (unparameterized immersed curves or submanifolds) are of interest for many applications in image analysis, such as the identification of shapes that are similar modulo the action of some group. In this paper we study a general representation of shapes that is based on linear spaces and is suitable for numerical discretization, being robust to noise. We develop the theory of currents for shape spaces by considering both the analytic and numerical aspects of the problem. In particular, we study the analytical properties of the current map and the $H^{-s}$ norm that it induces on shapes. We determine the conditions under which the current determines the shape. We then provide a finite element discretization of the currents that is a practical computational tool for shapes. Finally, we demonstrate this approach on a variety of examples

The Role of Resilience in the STEM Identities of Post-Secondary Students: A Qualitative Metasynthesis

The purpose of this qualitative metasynthesis is to explore the relationship between science, technology, engineering, and mathematics (STEM) identity and resilience in racially and ethnically diverse post-secondary students. This study identifies experiences that impact STEM identity development in diverse undergraduate and graduate students. The results of a constant targeted comparison (an analytical technique not often used in educational studies) between STEM identity and student resilience suggests that STEM identity contributes to resilience in diverse students. Findings suggest that common adverse experiences that may impact racially and ethnically diverse students can be overcome in the presence of a well-developed STEM identity. This resilience in STEM appears to be impacted by factors such as group membership, race, gender, agency, internal and external supports, validation, and access. Diverse students may have access to a range of coping mechanisms including family and peer support systems, as well as a personal cache of innovative approaches to self-define their STEM identities and help them navigate the academic milieu. Additional research is needed to better understand the relationship between a strong STEM identity and resilience in diverse undergraduate and graduate students

Religious Studies 3UU3 Buddhism in East Asia McMaster University Winter 2019

Syllabus for my course 3UU3, Buddhism in East Asia planned for Winter term 201

Religious Studies 718 Topics in Buddhist Studies: Recent Scholarship McMaster University, Term II 2020–21

Course Description In this seminar we shall read and discuss a selection of recent important works on and around Buddhism and material culture (in English). In addition we shall survey trends in recent Buddhist Studies scholarship produced in other languages (Chinese, Japanese, French, German, etc.). Students will be required to write regular, short, critical responses to the readings in addition to a longer essay that reflects on the state of the field of material culture in Buddhist Studies

Religious Studies 726 Topics in Chinese Religions: Health, Healing, and Medicine in Chinese Religions McMaster University, Term II 2019–20

In this seminar we will examine representations of health and accounts of disease in a variety of Chinese religions. We will explore the various vectors of disease, including the so-called “winds” and various types of demonic infestation. We will identify modes of healing that employ therapies such as mineral, animal, and vegetable drugs, exorcism, talismans and spells, acupuncture, moxibustion, massage, breath control, and gymnastics. The course will focus primarily, but not exclusively, on the medieval period. All readings for this seminar are in English. Students will be introduced to the use of specialised research tools for the study of Chinese religions, such as dictionaries, concordances, indices and database

Principal subbundles for dimension reduction

In this paper we demonstrate how sub-Riemannian geometry can be used for manifold learning and surface reconstruction by combining local linear approximations of a point cloud to obtain lower dimensional bundles. Local approximations obtained by local PCAs are collected into a rank $k$ tangent subbundle on $\mathbb{R}^d$, $k<d$, which we call a principal subbundle. This determines a sub-Riemannian metric on $\mathbb{R}^d$. We show that sub-Riemannian geodesics with respect to this metric can successfully be applied to a number of important problems, such as: explicit construction of an approximating submanifold $M$, construction of a representation of the point-cloud in $\mathbb{R}^k$, and computation of distances between observations, taking the learned geometry into account. The reconstruction is guaranteed to equal the true submanifold in the limit case where tangent spaces are estimated exactly. Via simulations, we show that the framework is robust when applied to noisy data. Furthermore, the framework generalizes to observations on an a priori known Riemannian manifold