oURspace (Univ. of Regina)
Not a member yet
15455 research outputs found
Sort by
Exploring caregiver experiences and support needs in end-of-life care for people living with HIV: A scoping review protocol
No full textBackground and objectives
End-of-life care supports individuals in the last few weeks or months of their life and their caregivers, offering psychosocial support, symptom management and relief, and resources. While some of the first public end-of-life care facilities were established due to HIV/AIDS, the current needs of caregivers for people living with end-stage HIV are not well understood. Caregivers provide two-thirds of the care for people living with HIV, yet their specific support needs and experiences are under-researched. Existing strategies often use a “one-size-fits-all” approach, which may not address the unique challenges faced by these caregivers, such as stigma and lack of social support. This study aims to synthesize the literature on the end-of-life care experiences and needs of caregivers for individuals living with HIV.
Research design and methods
A scoping review, guided by Arksey and O’Malley’s framework and the Joanna Briggs Institute’s recommendations, will be conducted. An Information Specialist will assist in developing a search strategy to be applied across databases like Medline, Embase, PsycINFO, and PubMed. Search results from each database will be imported into Covidence software for duplicate removal and title and abstract screening. Two researchers will independently screen studies using the ‘Population–Concept–Context’ (PCC) framework, with screening conducted at two levels: title and abstract, and full-text. The inclusion criteria will be piloted on a random sample of articles to ensure inter-rater agreement (kappa statistic >0.61). Disagreements will be resolved through discussion or with the involvement of a content expert if needed. Final selections will be reported using the PRISMA flow diagram, and reasons for exclusion will be documented.
Discussion and implications
The findings from this scoping review will provide valuable insights into the end-of-life care experiences and support needs of caregivers for individuals living with HIV. By identifying common themes and challenges, such as caregiver fatigue, emotional strain, stigma, and lack of social support, this study will underscore the inadequacy of the current “one-size-fits-all” approach in addressing the unique needs of these caregivers. This research has the potential to influence both clinical practice and policy by advocating for more personalized support strategies within end-of-life care settings.Judith Friedland Fund; Department of
Occupational Science & Occupational Therapy,
University of Toronto
Baby-friendly initiatives to promote, protect and support breastfeeding practices of immigrant mothers: A qualitative study in Saskatchewan, Canada
No full textImmigrant mothers, who often experience separation from extended family and social disconnection in a new country, are at risk of experiencing reduced physical, mental and emotional well-being, especially during the perinatal phase of their lives. Saskatchewan has a noticeable increase in the immigrant population with young children, limited availability of healthcare settings with baby-friendly initiative (BFI) status, potential risks to the health of young immigrant children after breastfeeding discontinuation, and the limited number of empirical studies that intend to seek recommendations from immigrant mothers on need-based initiatives that can promote, protect and support their breastfeeding practices.
This qualitative study intended to seek recommendations from immigrant mothers belonging to diverse ethnic groups on need-based initiatives to promote, protect and support the breastfeeding practices of immigrant mothers in Saskatchewan, Canada. Using a critical ethnographic study design, this study was undertaken in Saskatchewan, Canada. After receiving ethics approval, in-depth interviews were undertaken with 30 immigrant mothers with young children of age 1 day to 24 months. Immigrant mothers were recruited from different cities through purposive and snowball sampling. Data was also gathered through observations of breastfeeding services in Saskatchewan.
Immigrant mothers recommended the need for support from people in their social network (healthcare provider, husband, community and government), baby-friendly initiatives in hospital and community-based settings (breastfeeding counselling facilities, breastfeeding education before and after childbirth, and follow-up care), culturally-sensitive care (interpretation services and culturally appropriate food in hospitals), breastfeeding helplines (offering services in multiple languages), breastfeeding acceptance in a variety of public places (workplace, airports, restaurants, parks and public transportation), and investment in immigrant programs (maternal and child programs) to promote the well-being of immigrant mothers with young children.
Breastfeeding support in hospitals, public places, workplaces and society at large is essential to promote, protect and support the breastfeeding practices of immigrant mothers in Saskatchewan, Canada. The role of healthcare professionals, family members, workplace supervisors and colleagues, policymakers, and governmental/non-governmental organizations is crucial in supporting the breastfeeding practices of immigrant mothers.This work was supported by the Saskatchewan Health Research Foundation's Establishment Grant [grant number 5251]
Animacy & movement
No full textA Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science (Honours) in Psychology, University of Regina. 20 p.In the past, monitoring for human and non-human animals was crucial for survival. Accordingly, despite limited competitive engagement with animals today, the Animate Monitoring Hypothesis (AMH) purports that cognitive adaptations evolved to direct quicker and more accurate attention towards animate beings as opposed to inanimates. Minimal information regarding this phenomenon in children drives a need for further insights, especially in the context of motion as an alternative mechanism for this bias. As such, in the present study I aimed to measure the extent to which recall of an action sequence is impacted by differences in animacy and degree of motion for children 4- to 5.5-years-old. Using a deferred imitation task children (N = 50) were told that an object was either a mobile animate, an incapacitated animate, or a mobile robot. This object was then used in an action sequence which children observed and then replicated themselves. In line with predictions, recall in the animate conditions was superior to the robot condition, providing support for the AMH, but recall was only significantly higher in the mobile animate condition. Thus, there is a need for future research to further delineate the role of motion and animacy in memory.Studentn
Credit card fraud detection using incremental feature learning
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science, University of Regina. xiii, 125 p.Detecting credit card fraud is essential and it is one of the most popular payment methods. Credit card fraud can cause huge losses for cardholders. Therefore, so many studies have focused on proposing different standard machine learning methods and limited use of incremental learning to create a robust detective system. None of these studies can solve all the credit card fraud challenges together. The reason is the complicated real-world scenario and data we have in our hands. Some of these challenges are rapid data arrival rate, concept drift which causes model performance to decline over time and data sensitivity which causes a limited amount of instances in hand for training a model. We have proposed a chunk-based credit card fraud detection model which is based on incremental feature learning and transfer learning. Our proposed approach gives our model the capability to adjust its topology to find the near-optimal solution for the problem at hand. Our approach creates submodels per chunk and for the predictive model creation. We use the most relevant sub-models to the current data distribution we have. By doing so, we do not need to store all the transactions and we can avoid the model infinite growth by setting a limit on the number of used sub-models. There are a limited number of datasets for credit card fraud detection available due to the data sensitivity issue. So, we have evaluated our approach using two of the existing datasets: A mid-scale dataset consisting of two days of European cardholders’ transactions in September 2013 and A large-scale dataset consisting of 6 months of transactions in 2019. We have separated each dataset into a different number of chunks to be able to test and train our approach incrementally. We have compared our approach with a static model based on the initial chunk and re-trained on each chunk. Moreover, we have changed the number of sub-models to evaluate its impact on the performance.Studentye
Determination of evaporative flux from water and soil surfaces
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Environmental Systems Engineering, University of Regina. xvi, 247 p.The Canadian Prairies has the highest water demand-to-availability ratio in Canada. The region is characterized by a scarcity of water resources because evaporation generally exceed precipitation. Evaporation is a complex phenomenon based on interactions between meteorological and physiological factors. The purpose of this research was to accurately determine evaporative flux from water and soil surfaces. The main research contributions of this research are summarized as follows: (i) a Bench-scale Atmospheric Simulator (BAS/BAS2) was developed to control artificially generated parameters for short time periods; (ii) a Controlled Photogrammetry System (CPS) using Structure-from-Motion (SfM) technology was developed for accurate and non-destructive measurement of dimensional changes during evaporation; (iii) high-quality evaporation datasets were developed for calibration of devices, validation of prediction equations and evaluation of theoretical frameworks; (iv) predictive models for evaporation from water were evaluated to select appropriate empirical equations for predicting potential evaporative flux from water; and (v) a theoretical framework for evaporation from soils was developed to correlate with soil behavior (water retention and soil shrinkage) for both fresh water and saline water. The findings of this research are useful for developing methods to minimize evaporation and for helping with devising water use policy.Studentye
Crystallography of Pharmaceuticals: Ways to improve efficiency and assessing the fragment-based approach for enhanced polymorph discrimination
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Chemistry, University of Regina. xvii, A29 p.Nuclear magnetic resonance (NMR) crystallography is an emerging method that
combines experimental and computational data to perform various characterization tasks,
such as structure determination, validation, and refinement. NMR crystallography can be
used to determine the crystal structures of chemicals even when other experimental
methods, such as X-ray diffraction, cannot. Here, we discuss aspects of computational
modeling at the Density Functional Theory (DFT) level. Specifically, we calculated NMR
parameters such as magnetic shielding values. Most often, we will be looking at 1H
magnetic shielding values, as they are associated with the hydrogen atoms that are
regularly involved in the intermolecular interactions needed to form crystalline structures.
On occasion, we will also consider 13C magnetic shielding values.
With this in mind, we focussed on how we can efficiently determine the crystal
structures of small molecule organics at the DFT level but using less computational time
and resources. We have considered four organic systems: cocaine, flutamide, AZD8329,
and flufenamic acid. After, we will briefly discuss the fragment-based approach for
calculating NMR parameters and how this approach allows us to include relativistic effects
at the spin-orbit level of theory, which we hope can enhance our ability to distinguish
between different polymorphs of a chemical. In this portion of the thesis, we studied three
organics: sulfanilamide, theophylline, and cocaine.Studentye
Infographics to bridge misconceptions surrounding a neurodevelopmental
No full textA Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Bachelor of Arts (Honours) in Psychology, University of Regina. 43 p.The public continues to hold many misconceptions around Attention Deficit Hyperactive Disorder (ADHD). The objective of the present research was to determine if those misconceptions might be reduced through the presentation of correct information via infographics compared to the presentation of text-only material. Infographics are a popular method of displaying scientific findings on social media in a simple-to-process manner containing visual, content, and knowledge elements about a specific topic. Delivery of information to participants was manipulated through use of an infographic or a text-only paragraph that contained the same information addressing popular misconceptions of ADHD. Ninety-nine undergraduate students from the University of Regina Participant Pool were asked to self-report their mental health knowledge then were randomly assigned to either an infographic paragraph, a text-only paragraph, or no paragraph. Participants were asked about the effectiveness of the material at conveying information and then completed a 33-statement quiz assessing their knowledge and perceptions of ADHD. Infographic participants scored higher on the quiz compared to control participants, with text-only participants filling between the infographic and control participants. Students majoring in psychology self-reported higher knowledge of mental health and scored higher on the 33-statement quiz compared to students in other majors. The results from the present study suggest that the discrepancy between ADHD and public perceptions and clinical research may be addressed through use of infographics, especially to counter misinformation online.Studentn
Policy issue networks: Social network analysis case studies
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Public Policy, University of Regina. xi, 227 p.This research demonstrates that Social Network Analysis (SNA) can be a
powerful, proactive tool for policy makers to understand the online policy networks in
which they operate. It does so by undertaking SNA at two points in time to quantify the
actor nodes of three Canadian public policy networks, comparing the network evolution
over time, and visualizing their structure and relationships with related policy issues.
The three Canadian policy case study subjects are cannabis legalization, nuclear
energy development, and the Trans Mountain Pipeline expansion project (TMX). The
cases were selected for their current social importance and national concern, and
complexity as socio-technical systems. Cannabis legalization represents a social policy
shift, while the other two policy issues involve highly technical infrastructure projects to
provide the energy that drives modern society at a time when energy solutions and needs
are shifting. The research was undertaken to answer three main questions: Does a
network structure consist of multiple clusters of subnetworks primarily concerned with
tangential issues but bridged together to form a network for this policy issue? Is there
any evidence of network effects that affect the network’s evolution over time? Finally, is
there evidence that regional or international networks are present?
The study’s findings provide significant evidence that addresses these questions.
For example, for question one, the cannabis legalization network shows an isolated
online community primarily interested in the research and use of cannabis as a medical
treatment, an issue tangential to the primary policy focus but connected to the policy
issues. For question two, Canada’s stated nuclear policy shift toward small modular
reactors reveals an online issue network dominated by industry rather than government
actors. Finally, regarding question three, the study found that regional clusters were
especially apparent in the cannabis legalization and TMX networks.
This research provides insight into the policy networks of the specific cases,
which contributes to the literature on these policy topics and network analysis in terms
of network structure and evolution. It also validates the use of SNA in a policy analysis
toolkit. Where existing literature has examined Internet-age government, it has found
that governments often replicate routine procedures and processes in new, virtual forms
rather than innovate or reimagine their capabilities. Government actors have improved
their responsiveness, but they also need to fundamentally change their behaviour,
particularly in engaging stakeholders in meaningful public policy analysis. SNA is a
novel use afforded by technology that has gone unexplored to innovate government
performance.
This dissertation adds to the lengthy body of research in SNA by experimenting
with a practical application of its theories and methods. The critical conceptual approach
underpinning this thesis is complexity theory, which provides the framework to situate
the dynamic environment of policy making and stakeholder engagement.
It is hoped that this research will help policy makers by providing a toolkit that
enables visualizing how issue patterns emerge in real-time, patterns that can represent
the “unknown unknowns” — the voices not yet heard, the unanticipated concerns, and
the opportunities not yet discovered to reach out to broader or underrepresented
communities in the policy arena.Studentye
Systems Biology of Host-Pathogen Protein-Protein Interactions
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biochemistry, University of Regina. xvi , 200 p.Despite undeniable therapeutic developments in infectiology, emerging infectious
diseases continue to be a growing threat to public health, as seen by the current COVID-
19 pandemic caused by the novel virus severe acute respiratory syndrome coronavirus
(SARS-CoV-2). This virus is classified as an obligate intracellular parasite that co-opts
host cellular proteins, often through protein-protein interactions (PPIs), to ensure its
replication. Therefore, this thesis aims to integrate high-throughput proteomic approaches
with computational modelling to systematically characterize SARS-CoV-2-human
networks for a detailed understanding of SARS-CoV-2 pathogenesis.
The angiotensin-converting enzyme (ACE2) receptor of SARS-CoV-2 is displayed
on many human cells, including the lungs and other organs. However, despite considerable
knowledge explaining the SARS-CoV-2 infection mechanism, organ-specific SARS-CoV-
2-host protein interactions remain understudied. In Chapter 2, we carried out an
organ/tissue-unbiased proteomic profiling approach of mapping SARS-CoV-2-human
protein interactions using high-throughput mass spectrometry (MS)-based proteomic
approaches. First, automated machine learning (ML)-based computational workflows with
different algorithmic strategies were devised to generate high-quality tissue-specific and
tissue-common SARS-CoV-2-human PPIs. Subsequent clustering of highly conserved
networks using an optimized complex-based analysis framework uncovered several virally
targeted protein complexes (VTCs), reflecting conserved mechanisms of replication.
Finally, organ/tissue-specific interaction revealed that NSP3 protein evades host antiviral
innate immune signaling by targeting IFIT5 for de-isgylation.
Although host interactome is indirectly affected during viral infection, earlier
studies have only focused on characterizing the properties of the viral proteins within the
host-viral interactions. However, systematically exploring the host-viral interactions from
the perspective of the host interactome is essential and should be included in PPI network
for a better understanding of viral pathogenesis. In Chapter 3, we combined cofractionation
mass spectrometry (CF-MS) with a novel deep learning-based framework,
DeepiCE, to map physiologically relevant viral-host and host interactome. First, through
comprehensive statistical validations, we demonstrated the remarkable performance of
DeepiCE over the state-of-the-art method for network construction. DeepiCE was then
applied to co-elution data from salivary samples of individuals infected with SARS-CoV-
2, which led to the generation of high-quality viral-host and host interactome maps highly
relevant to SARS-CoV-2 infection. Subsequent clustering of resulting networks using a
sophisticated two-stage clustering framework generated high-quality SARS-CoV-2
affected protein complexes, many of which were enriched for diverse cellular processes
related to viral pathogenesis and provided new insights into SARS-CoV-2 infection from
both the host and pathogen perspective.
Despite arduous and time-consuming experimental efforts, PPIs for many
pathogenic microbes with their human host are still unknown, limiting our understanding
of the intricate interactions during infection and the identification of therapeutic targets.
Since computational tools offer a promising alternative, in Chapter 4, we developed a
R/Bioconductor package, HPiP software with a series of amino acid sequence property
descriptors and an ensemble machine learning classifiers to predict the yet unmapped
interactions between pathogen and host proteins. Using SARS-CoV-1 or the novel SARSCoV-
2 coronavirus-human PPI training sets as a case study, we show that HPiP achieves
good performance with PPI predictions between SARS-CoV-2 and human proteins, which
we confirmed experimentally using several quality control metrics. HPiP also exhibited
strong performance in accurately predicting the previously reported PPIs when tested
against the sequences of pathogenic bacteria, Mycobacterium tuberculosis and human
proteins. Collectively, our fully documented HPiP software will hasten the exploration of
PPIs for a systems-level understanding of many understudied pathogens and uncover
molecular targets for repurposing existing drugs.Studentye
Evaluation of anxiety treatment for children through online education (ACE)
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Clinical Psychology, University of Regina. ix, 140 p.Child anxiety is very common and can potentially have lasting, harmful effects.
Cognitive behavioural therapy (CBT) is an effective treatment for child anxiety, but
access to traditionally delivered (i.e., face-to-face) CBT is limited. Low-intensity
interventions are more accessible to families and less time-consuming for therapists,
allowing for therapists to help more families. Anxiety Treatment for Children Through
Online Education (ACE) is a low-intensity, therapist-guided, parent-directed, Internetdelivered
cognitive behavioural therapy (ICBT) intervention for child anxiety. The
implementation of ACE has yet to be comprehensively evaluated. This intervention is
relatively unique within the field. Past research on ACE has aimed to investigate
participant engagement with the ACE program (Mazenc, 2021). While this past research
is important, little is known at this time about parental experiences with the program and
the extent to which the program has been effectively implemented. The Updated DeLone
and McLean Model of Information Systems Success (D&M Model; DeLone et al., 2003)
offers a model for examining implementation of the program, and involves measuring
various aspects of online information systems (e.g., information quality, system quality,
service quality, intention to use/use, user satisfaction, net benefits). The purpose of the
current study was to conduct a process evaluation exploring parents’ experiences with
the ACE program, while at the same time assessing the utility of the model. Ninety-one
parents of 7-12 year old children with anxiety participated in the ACE program, with 47
completing the program. Descriptive statistics for information quality, service quality,
system quality, intention to use/use, user satisfaction, and net benefits were computed.
Parents were satisfied with ACE’s content, online platform, e-therapist, and overall
experience. Paired sample t-tests revealed significant improvements throughout the
intervention in terms of therapeutic alliance, child anxiety symptoms, negative parental
beliefs about anxiety, and parenting confidence. High ratings of content satisfaction were
positively significantly correlated with perceived credibility, expectancy, and overall
satisfaction of ACE. Participants who were satisfied with the website’s visual aesthetics
reported significantly more overall satisfaction, and those who reported a good working
alliance with their e-therapist perceived ACE to be significantly more credible and
overall satisfactory. Further, improvements in parenting confidence were associated with
greater overall satisfaction, and reductions in negative parental beliefs about anxiety was
associated with greater number of weeks in the program. A multiple regression showed
that program credibility/expectancy, number of weeks in the program, and overall
satisfaction did not predict child symptom improvement. Thus, while using the D&M
Model provided a comprehensive framework to assess parents’ perceptions of the ACE
program, the utility of the model was not fully supported. Qualitative responses to
relevant questions were organized into themes (e.g., The content was engaging, The
layout was user-friendly). This research yields significant implications for future
implementation of low-intensity parent-directed therapist-assisted ICBT interventions, as
results demonstrate that ACE completion is associated with improvement in child
anxiety symptoms and good satisfaction was observed across ACE content, website, and
e-therapist support. Results from this study may inform aspects of related interventions
that need to be improved upon in order to maximize impact (i.e., inclusion of
supplementary materials, videos, summaries).
Keywords: Parent-delivered, guided, ICBT, child anxiety, D&M model, evaluationStudentye