{"id":{"repo_id":"regina","oai_identifier":"oai:uregina.scholaris.ca:10294/14473"},"canonical_url":"https://search.dev.ndltd.org/etd/regina/oai:uregina.scholaris.ca:10294/14473","repository":{"repo_id":"regina","name":"University of Regina","base_url":"https://uregina.scholaris.ca/server/oai/request"},"display":{"title":"Facilitators and Barriers to Technology Adoption: An Automated Pain Detection System for Long-Term Care","abstract":"Canada’s population is aging at an unprecedented rate. That is, older adults—defined as persons who are at least 65 years of age—make up a rapidly growing segment of the population. With age as one of the strongest risk factors for the development of chronic health conditions, the Canadian healthcare system will be met with increasingly complex challenges in providing care as its population ages. The co-occurrence of dementia and pain among long-term care (LTC) residents, for example, presents a significant challenge since residents with dementia are less likely able to self-report their pain. Furthermore, despite the increased prevalence of—and greater adverse consequences associated with—pain among LTC residents living with dementia, pain continues to be underassessed among this population due to resource limitations. If pain behaviours were detected and monitored in an automated way, however, the additional resources needed to regularly assess each resident for pain could be significantly reduced. Accordingly, an automated pain detection system for LTC residents is currently being developed. Importantly, the successful implementation of this system in LTC is dependent on individual and organizational variables beyond its mere development. This study was therefore aimed at examining the influence of individual and organizational variables on intentions to adopt the automated pain detection system. With the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical framework, Study 1 examined on the role of individual factors and perceptions in predicting behavioural intentions to use the system. Nurses currently working in LTC facilities in Saskatchewan (N = 164) completed a set of online questionnaires measuring constructs relevant to the implementation of the automated pain detection system. Statistical analyses involved a series of mediation analyses to test whether the influence of individual factors and perceptions on behavioural intentions was mediated by original predictor variables posited by the UTAUT (i.e., performance expectancy, effort expectancy, social influence, facilitative conditions). Results suggested that nurses who more strongly endorsed that the automated pain detection system would be useful and easy-to-use had greater intentions to adopt the system. Nurses also had greater intentions to adopt the system if they felt that they could successfully implement the automated pain detection system in their LTC facility and that implementing this system would be both appropriate to the context and personally beneficial. In contrast, having a strong distrust of technology’s ability to work properly and its potential harmful consequences was associated with lower intentions to adopt the system. It was recommended that these constructs be assessed among nurses at regular intervals when the automated pain detection system is implemented in LTC facilities. With the Consolidated Framework for Implementation Research (CFIR) as its theoretical framework, Study 2 focused on understanding the role of organizational barriers and facilitators on behavioural intentions to use the automated pain detection system. Administrators, nurses, care aides, family members, and residents (N = 74) from two LTC facilities in Saskatchewan participated in semi-structured interviews. Analysis of narrative responses involved a thematic analysis guided by the CFIR. It was recommended that an intervention to increase the likelihood of successful implementation of the system in LTC highlight its benefits and address relevant ethical considerations prior to its implementation. Drawing on findings from Study 1 and 2, a tailored version of the UTAUT and CFIR were proposed to guide the implementation of the automated pain detection system and other patient-oriented technologies in LTC.","abstract_html":"Canada’s population is aging at an unprecedented rate. That is, older adults—defined as persons who are at least 65 years of age—make up a rapidly growing segment of the population. With age as one of the strongest risk factors for the development of chronic health conditions, the Canadian healthcare system will be met with increasingly complex challenges in providing care as its population ages. The co-occurrence of dementia and pain among long-term care (LTC) residents, for example, presents a significant challenge since residents with dementia are less likely able to self-report their pain. Furthermore, despite the increased prevalence of—and greater adverse consequences associated with—pain among LTC residents living with dementia, pain continues to be underassessed among this population due to resource limitations. If pain behaviours were detected and monitored in an automated way, however, the additional resources needed to regularly assess each resident for pain could be significantly reduced. Accordingly, an automated pain detection system for LTC residents is currently being developed. Importantly, the successful implementation of this system in LTC is dependent on individual and organizational variables beyond its mere development. This study was therefore aimed at examining the influence of individual and organizational variables on intentions to adopt the automated pain detection system. With the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical framework, Study 1 examined on the role of individual factors and perceptions in predicting behavioural intentions to use the system. Nurses currently working in LTC facilities in Saskatchewan (N = 164) completed a set of online questionnaires measuring constructs relevant to the implementation of the automated pain detection system. Statistical analyses involved a series of mediation analyses to test whether the influence of individual factors and perceptions on behavioural intentions was mediated by original predictor variables posited by the UTAUT (i.e., performance expectancy, effort expectancy, social influence, facilitative conditions). Results suggested that nurses who more strongly endorsed that the automated pain detection system would be useful and easy-to-use had greater intentions to adopt the system. Nurses also had greater intentions to adopt the system if they felt that they could successfully implement the automated pain detection system in their LTC facility and that implementing this system would be both appropriate to the context and personally beneficial. In contrast, having a strong distrust of technology’s ability to work properly and its potential harmful consequences was associated with lower intentions to adopt the system. It was recommended that these constructs be assessed among nurses at regular intervals when the automated pain detection system is implemented in LTC facilities. With the Consolidated Framework for Implementation Research (CFIR) as its theoretical framework, Study 2 focused on understanding the role of organizational barriers and facilitators on behavioural intentions to use the automated pain detection system. Administrators, nurses, care aides, family members, and residents (N = 74) from two LTC facilities in Saskatchewan participated in semi-structured interviews. Analysis of narrative responses involved a thematic analysis guided by the CFIR. It was recommended that an intervention to increase the likelihood of successful implementation of the system in LTC highlight its benefits and address relevant ethical considerations prior to its implementation. Drawing on findings from Study 1 and 2, a tailored version of the UTAUT and CFIR were proposed to guide the implementation of the automated pain detection system and other patient-oriented technologies in LTC.","abstract_has_math":false,"creators":["Gallant, Natasha Louise"],"institution":"Faculty of Graduate Studies and Research, University of Regina","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral -- first","degree_discipline":"Clinical Psychology","degree_department":null,"school":null,"contributors":[],"advisors":["Hadjistavropoulos, Thomas"],"committee_chairs":[],"committee_members":["Hadjistavropoulos, Heather","Klest, Bridget","Wickson-Griffiths, Abigail"],"year":2021,"date_issued":"2021-03","date_published":"2021-03","updated_at":"2026-07-24T04:03:45Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/4861"],"render_values":[{"text":"https://doi.org/10.82465/4861","href":"https://doi.org/10.82465/4861","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10294/14473","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hadjistavropoulos, Thomas"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Hadjistavropoulos, Heather","Klest, Bridget","Wickson-Griffiths, Abigail"]},{"key":"dc:creator","label":"Author","values":["Gallant, Natasha Louise"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-12-13T17:12:11Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-12-13T17:12:11Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-03"]},{"key":"dc:publisher","label":"Institution","values":["Faculty of Graduate Studies and Research, University of Regina"]},{"key":"dc:type","label":"Dc Type","values":["master thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Clinical Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral -- first"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Faculty of Graduate Studies and Research, University of Regina"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/4861"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10294/14473"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Clinical Psychology, University of Regina. xv, 217 p."]},{"key":"dc:description.abstract","label":"Abstract","values":["Canada’s population is aging at an unprecedented rate. That is, older adults—defined as persons who are at least 65 years of age—make up a rapidly growing segment of the population. With age as one of the strongest risk factors for the development of chronic health conditions, the Canadian healthcare system will be met with increasingly complex challenges in providing care as its population ages. The co-occurrence of dementia and pain among long-term care (LTC) residents, for example, presents a significant challenge since residents with dementia are less likely able to self-report their pain. Furthermore, despite the increased prevalence of—and greater adverse consequences associated with—pain among LTC residents living with dementia, pain continues to be underassessed among this population due to resource limitations. If pain behaviours were detected and monitored in an automated way, however, the additional resources needed to regularly assess each resident for pain could be significantly reduced. Accordingly, an automated pain detection system for LTC residents is currently being developed. Importantly, the successful implementation of this system in LTC is dependent on individual and organizational variables beyond its mere development. This study was therefore aimed at examining the influence of individual and organizational variables on intentions to adopt the automated pain detection system. With the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical framework, Study 1 examined on the role of individual factors and perceptions in predicting behavioural intentions to use the system. Nurses currently working in LTC facilities in Saskatchewan (N = 164) completed a set of online questionnaires measuring constructs relevant to the implementation of the automated pain detection system. Statistical analyses involved a series of mediation analyses to test whether the influence of individual factors and perceptions on behavioural intentions was mediated by original predictor variables posited by the UTAUT (i.e., performance expectancy, effort expectancy, social influence, facilitative conditions). Results suggested that nurses who more strongly endorsed that the automated pain detection system would be useful and easy-to-use had greater intentions to adopt the system. Nurses also had greater intentions to adopt the system if they felt that they could successfully implement the automated pain detection system in their LTC facility and that implementing this system would be both appropriate to the context and personally beneficial. In contrast, having a strong distrust of technology’s ability to work properly and its potential harmful consequences was associated with lower intentions to adopt the system. It was recommended that these constructs be assessed among nurses at regular intervals when the automated pain detection system is implemented in LTC facilities. With the Consolidated Framework for Implementation Research (CFIR) as its theoretical framework, Study 2 focused on understanding the role of organizational barriers and facilitators on behavioural intentions to use the automated pain detection system. Administrators, nurses, care aides, family members, and residents (N = 74) from two LTC facilities in Saskatchewan participated in semi-structured interviews. Analysis of narrative responses involved a thematic analysis guided by the CFIR. It was recommended that an intervention to increase the likelihood of successful implementation of the system in LTC highlight its benefits and address relevant ethical considerations prior to its implementation. Drawing on findings from Study 1 and 2, a tailored version of the UTAUT and CFIR were proposed to guide the implementation of the automated pain detection system and other patient-oriented technologies in LTC."]},{"key":"dc:title","label":"Title","values":["Facilitators and Barriers to Technology Adoption: An Automated Pain Detection System for Long-Term Care"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hadjistavropoulos, Thomas"],"dc:contributor.committeemember":["Hadjistavropoulos, Heather","Klest, Bridget","Wickson-Griffiths, Abigail"],"dc:creator":["Gallant, Natasha Louise"],"dc:date.accessioned":["2021-12-13T17:12:11Z"],"dc:date.available":["2021-12-13T17:12:11Z"],"dc:date.issued":["2021-03"],"dc:description":["A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Clinical Psychology, University of Regina. xv, 217 p."],"dc:description.abstract":["Canada’s population is aging at an unprecedented rate. That is, older adults—defined as persons who are at least 65 years of age—make up a rapidly growing segment of the population. With age as one of the strongest risk factors for the development of chronic health conditions, the Canadian healthcare system will be met with increasingly complex challenges in providing care as its population ages. The co-occurrence of dementia and pain among long-term care (LTC) residents, for example, presents a significant challenge since residents with dementia are less likely able to self-report their pain. Furthermore, despite the increased prevalence of—and greater adverse consequences associated with—pain among LTC residents living with dementia, pain continues to be underassessed among this population due to resource limitations. If pain behaviours were detected and monitored in an automated way, however, the additional resources needed to regularly assess each resident for pain could be significantly reduced. Accordingly, an automated pain detection system for LTC residents is currently being developed. Importantly, the successful implementation of this system in LTC is dependent on individual and organizational variables beyond its mere development. This study was therefore aimed at examining the influence of individual and organizational variables on intentions to adopt the automated pain detection system. With the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical framework, Study 1 examined on the role of individual factors and perceptions in predicting behavioural intentions to use the system. Nurses currently working in LTC facilities in Saskatchewan (N = 164) completed a set of online questionnaires measuring constructs relevant to the implementation of the automated pain detection system. Statistical analyses involved a series of mediation analyses to test whether the influence of individual factors and perceptions on behavioural intentions was mediated by original predictor variables posited by the UTAUT (i.e., performance expectancy, effort expectancy, social influence, facilitative conditions). Results suggested that nurses who more strongly endorsed that the automated pain detection system would be useful and easy-to-use had greater intentions to adopt the system. Nurses also had greater intentions to adopt the system if they felt that they could successfully implement the automated pain detection system in their LTC facility and that implementing this system would be both appropriate to the context and personally beneficial. In contrast, having a strong distrust of technology’s ability to work properly and its potential harmful consequences was associated with lower intentions to adopt the system. It was recommended that these constructs be assessed among nurses at regular intervals when the automated pain detection system is implemented in LTC facilities. With the Consolidated Framework for Implementation Research (CFIR) as its theoretical framework, Study 2 focused on understanding the role of organizational barriers and facilitators on behavioural intentions to use the automated pain detection system. Administrators, nurses, care aides, family members, and residents (N = 74) from two LTC facilities in Saskatchewan participated in semi-structured interviews. Analysis of narrative responses involved a thematic analysis guided by the CFIR. It was recommended that an intervention to increase the likelihood of successful implementation of the system in LTC highlight its benefits and address relevant ethical considerations prior to its implementation. Drawing on findings from Study 1 and 2, a tailored version of the UTAUT and CFIR were proposed to guide the implementation of the automated pain detection system and other patient-oriented technologies in LTC."],"dc:identifier.doi":["https://doi.org/10.82465/4861"],"dc:identifier.uri":["https://hdl.handle.net/10294/14473"],"dc:language.iso":["en"],"dc:publisher":["Faculty of Graduate Studies and Research, University of Regina"],"dc:title":["Facilitators and Barriers to Technology Adoption: An Automated Pain Detection System for Long-Term Care"],"dc:type":["master thesis"],"thesis:degree_discipline":["Clinical Psychology"],"thesis:degree_level":["Doctoral -- first"],"thesis:degree_name":["Doctor of Philosophy (PhD)"],"thesis:institution_name":["Faculty of Graduate Studies and Research, University of Regina"]},"updated_at":"2026-07-24T04:03:45Z"}