Doctoral Theses and Dissertations

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Browsing Doctoral Theses and Dissertations by Author "Asmundson, Gordon"

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    A mixed methods study on barriers and facilitators to exercise for suicidal ideation management
    (Faculty of Graduate Studies and Research, University of Regina, 2024-10) Vig, Kelsey Danielle; Asmundson, Gordon; Hadjistavropoulos, Heather; Hadjistavropoulos, Thomas; Totosy, Julia; Gibb, Brandon E.
    Suicide is a leading cause of premature death. Innovative and effective interventions are needed to prevent suicide deaths. Randomized controlled trials (RCTs) have demonstrated that a variety of structured exercise programs (e.g., aerobic exercise, resistance training exercise) improve mental health, including reducing anxiety and depressive symptoms. Moreover, failure to meet established guidelines for physical activity is associated with increased odds of experiencing suicidal behaviours. Exercise may, therefore, be one intervention option to reduce the suicidal behaviours (i.e., suicidal ideation [SI] and plans for suicide) that often precede suicide. In order to benefit from the effects of exercise, individuals with suicidal ideation must perceive exercise as an accessible, acceptable, and effective treatment option, otherwise they are unlikely to initiate and sustain an exercise program. This mixed-methods dissertation includes two studies that explored how individuals with SI perceive and experience exercise, with an emphasis on identifying facilitators and barriers to exercise. In Study 1, grounded theory methods were used to analyze data from semi-structured interviews with 17 adult Canadian participants with past-month SI. The overall theory derived from Study 1 suggests that exercise for individuals with SI is complex and should be tailored to each individual. This theory is made up of a core category of individualization, as well as four key concepts that relate to three major categories. The four key concepts of the theory are that facilitators and barriers to exercise (a) have individualized weights/impacts on exercise decisions, (b) are cumulative, interactive, and opposing forces, (c) are dynamic, and (d) exist on a spectrum from internal to external. The three major categories included in the study theory are (a) the cognitive-behavioural cycle, (b) priorities, values, and identity, and (c) interpersonal factors. In Study 2, 261 Canadian adult participants with past-month SI completed an online survey. The survey included measures of suicidal behaviour, facilitators and barriers to exercise (open-ended and closed-ended questions), past-week physical activity, and demographic and health questions. Due to the exploratory nature of the study, quantitative analyses were restricted to descriptive statistics. The qualitative and quantitative results of Study 2 supported and added to the theory developed in Study 1, including offering additional evidence of the core category, the four key concepts, and the three major categories. Most participants thought exercise can reduce SI. Improved health, both mental and physical, was a commonly reported motivator to exercise, and poor mental health was also a commonly reported barrier to exercise. Overall, the results of both studies demonstrated the importance of individualization when it comes to exercise for individuals with SI. Exercise may or may not be an accessible, acceptable, and/or effective intervention for any given individual with SI. The results may be used by clinicians, researchers, policy makers, and advocacy groups considering whether exercise might be an intervention option for individuals with SI. The results may assist future researchers who endeavor to develop exercise-based interventions for individuals with SI by providing a theoretical framework to guide intervention development and study planning (e.g., by highlighting the need to anticipate and address individual and fluctuating facilitators and barriers). Keywords: suicidal ideation, exercise, physical activity, facilitators and barriers to exercise, exercise adherence, grounded theory
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    Real-time Evaluation of an Automated Computer Vision System to Monitor Pain Behaviour in Older Adults
    (Faculty of Graduate Studies and Research, University of Regina, 2024-09) Stopyn, Rhonda Jennifer Nicole; Hadjistavropoulos, Thomas; Asmundson, Gordon; Gallant, Natasha; Taati, Babak; Paranjape, Raman; Jutai, Jeffrey W.
    A large body of literature supports the systematic observation of facial expressions as a tool for assessing pain in both younger and older adults. Such observation is especially critical for older adults who have limited ability to communicate their pain experience due to dementia. While frequent monitoring of pain behaviours in dementia is constrained by resource limitations, computer vision technology has the potential to mitigate these challenges, especially in long-term care environments where many people with severe dementia reside. A computerized algorithm designed to assess pain behaviour in older adults with and without dementia was recently developed and validated against video recorded images. The algorithm was incorporated within an automated system that provided alerts when facial pain expressions were detected. This study conducted the first live, real-time evaluation of the automated pain behaviour detection system with community-dwelling older adults in a laboratory setting. Testing involved a total of 65 participants completing three safely-administered experimentally-induced pain tasks using a thermal pain stimulator. A video camera was used to facilitate recording and automatic processing of facial activity. Pain behaviour detection occurred when systemgenerated pain intensity scores of the facial expressions displayed by participants exceeded a predetermined threshold score. When the incidence of facial pain expression occurred, an electronic notification (e.g., email and a signal light) was generated as notifications of pain behaviour detection. Participants completed continuous self-report pain intensity ratings during the thermal pain tasks. Receiver Operating Characteristic curve analyses were used to determine the sensitivity and specificity of the system in identifying pain- and non-pain facial expressions using gold standard manual coding completed by trained coders. Gender differences were also explored in relation to system performance. Correlational procedures were used to evaluate the relationship between pain intensity scores generated by the system, continuous self-report pain ratings, observational pain coding, and stimulus temperatures. This study supported the potential viability of the automated pain behaviour detection system in correctly identifying live, real-time instances of facial pain expressions in older adults. System-generated pain behaviour scoring achieved a maximal greater correlation with gold standard manual coding compared to prior testing using video-recordings. Specifically, system performance improved when more intense facial pain expressiveness was considered compared to more subtle facial expressions at lower pain intensities. In comparing system scoring to manual coding, there was not a one-to-one correspondence in coding but a range of comparative values that varied from participant to participant. Correlational analyses showed that continuous self-report pain ratings were weakly correlated with system scoring and manual coding. While average pain scores remained homogenous across genders, results suggested that the system performed better at identifying pain expressions for women compared to men. As expected, the pain-related facial movements of brow lowering and levator contraction were unique predictors of system-generated scores. Future evaluations of the system involving field trials in long-term care settings with older clinical populations would further elucidate the performance of the system. This technology is expected to aid in the assessment of pain in people living with dementia while addressing resource constraints in long-term care environments and reduce burden for caregivers. Keywords: Pain, aging, technology, older adults, computer vision, dementia