There is a recognized nursing shortage in Canada, including specialty areas such as critical care (CC). Nursing shortages impact health care delivery, including economic, patient, and nursing outcomes. Job satisfaction is one of the most significant outcomes affected by the nursing shortage. Recruitment of inexperienced nurses in CC is a relatively new hiring practice and has resulted in a more diverse level of clinical expertise among CC nurses. Little is known about how differences in level of clinical expertise affect job satisfaction. The purpose of this study was to explore the relationship between CC nurses’ self -reported level of clinical expertise and job satisfaction. Interrelationships between additional influencing factors, such as organizational climate and personal factors were also explored. Utilizing a web based online survey, a cross-sectional survey was sent to all 788 Manitoba hospital based CC nurses, via the College of Registered Nurses of Manitoba. Respondents (N = 188) completed the Critical Care Nurse Retention Survey, which operationalized the key study variables. Sixty-five percent of the sample reported overall job satisfaction. Based on multivariate analysis, the most influential factors affecting CC nurses’ job satisfaction were nursing management, control over practice, and level of clinical expertise. Nursing management plays a vital role in facilitating optimal nursing practice. Control and autonomy may reflect a sense of satisfaction in the achievement of the knowledge and skills necessary for effective decision-making in CC. Finally, this study provides pioneering data on the importance of advancing clinical expertise to improve job satisfaction in CC nurses.

There is a recognized nursing shortage in Canada, including specialty areas such as critical care (CC). Nursing shortages impact health care delivery, including economic, patient, and nursing outcomes. Job satisfaction is one of the most significant outcomes affected by the nursing shortage. Recruitment of inexperienced nurses in CC is a relatively new hiring practice and has resulted in a more diverse level of clinical expertise among CC nurses. Little is known about how differences in level of clinical expertise affect job satisfaction. The purpose of this study was to explore the relationship between CC nurses’ self -reported level of clinical expertise and job satisfaction. Interrelationships between additional influencing factors, such as organizational climate and personal factors were also explored. Utilizing a web based online survey, a cross-sectional survey was sent to all 788 Manitoba hospital based CC nurses, via the College of Registered Nurses of Manitoba. Respondents (N = 188) completed the Critical Care Nurse Retention Survey, which operationalized the key study variables. Sixty-five percent of the sample reported overall job satisfaction. Based on multivariate analysis, the most influential factors affecting CC nurses’ job satisfaction were nursing management, control over practice, and level of clinical expertise. Nursing management plays a vital role in facilitating optimal nursing practice. Control and autonomy may reflect a sense of satisfaction in the achievement of the knowledge and skills necessary for effective decision-making in CC. Finally, this study provides pioneering data on the importance of advancing clinical expertise to improve job satisfaction in CC nurses.

Percevoir la douleur d’autrui présente des intérêts considérables, autant pour la personne qui exprime une douleur, que pour la personne qui y fait face. A ce jour, l’évaluation de la douleur d’autrui demeure sous-estimée. Il apparait donc nécessaire d’approfondir la connaissance des déterminants de l’évaluation de la douleur d’autrui. Ce travail doctoral s’intéresse à l’évaluation, par des observateurs, des comportements prototypiques émis par les personnes qui ressentent des douleurs. Dans un premier temps, il examine dans quelle mesure les observateurs s’appuient sur des comportements particuliers (i.e., comportements de communication : expressions faciales et paraverbales, et de comportements de protection : cinématiques lombopelviennes et boiterie d’esquive) lorsqu’ils doivent juger l’intensité de la douleur d’autrui. Les contributions de l’expertise clinique et de la familiarité avec la douleur y sont examinées. Dans un deuxième temps, il interroge la contribution des traits de personnalité du Big Five dans la réponse sociale à la douleur d’autrui. Les résultats montrent que lorsqu’il s’agit d’estimer l’intensité de la douleur lombaire d’autrui, les expressions faciales de la douleur priment sur les cinématiques lombopelviennes (étude 1). Toutefois, lorsqu’il s’agit d’évaluer l’intensité de la douleur podale d’autrui, l’expression paraverbale de douleur ne prime pas sur les comportements de boiterie (étude 2). Les études 1 et 2 ne font pas émerger de consensus relatif aux règles d’intégration utilisées par les observateurs. Par ailleurs, le caractère consciencieux (études 3 et 4), l’agréabilité (étude 3) et le névrosisme (étude 4) contribuent à la réponse sociale à la douleur d’autrui. La contribution de ces trois traits s’exprimerait à un niveau contrôlé, i.e., top-down (étude 5). Les résultats des études menées sont susceptibles d’enrichir le Modèle de la Communication de la Douleur et étendent le champ d’application des traits de personnalité du Big Five. / Recognizing and interpreting other’s pain can be of great importance to the person in pain as well as to the person witnessing the other’s distress. According to recent studies other’s pain remains underestimated. Thus, it appears necessary to better understand the knowledge of variables that contribute to other’s pain assessement. On one hand, this doctoral project aimed at determining if observers rely more on communicative than on protective pain behaviors (facial and paraverbal expressions) when estimating other’s pain. It also questioned how observers integrate information from pain behaviors. On the other hand, the contribution of Big Five personality trait in the social response to other’s pain has been examined. When assessing low back pain, observers particularly relied on facial expression than on lumbopelvic kinematics (study 1). Nevertheless, when estimating heel pain, paraverbal expression did not contribute more than limping behaviors to observers’ pain estimates (study 2). No concensus has emerged regarding the way observers integrated information from the different pain behaviors (studies 1 and 2). In addition, conscientiousness (studies 3 and 4), agreableness (study 3), and neuroticism (study 4) contributed to the social response to other’s pain. The contribution of these traits seems to be driven by top-down processes (study 5). These results are likely to expand the communication model of pain, and the contribution of Big Five personality traits.

Determining the prognosis or risk of an individual experiencing a specific health outcome within a certain time period is essential to improve health. An important aspect of prognostic research is the development of risk assessment models (RAMs). In support of the movement towards personalized medicine, health care professionals have employed RAMs to stratify an individual patient’s absolute risk of developing a health condition and select the optimal management strategy for that patient. The development of RAMs is generally conducted using data driven methods or through expert consensus. However, these methods present limitations. Accordingly, we recognized the need to select factors for RAM development or update that are evidence-based and clinically relevant using a structured and transparent approach. In this sandwich thesis, I highlight the methods used to select prognostic factors for VTE and bleeding RAMs for hospitalized medical patients. However, the same methods can be applied to any clinical outcome of interest. This work presents a conceptualized and tested novel mixed methods approach to select prognostic factors for VTE and bleeding in hospitalized medical patients that are evidence-based, clinically meaningful and relevant. Our findings may inform the development of new RAMs, the update of widely used RAMs, and external validation and prospective impact assessment studies. Also, these findings may assist decision makers in evaluating the risk of an individual having an outcome to optimize patient care. / Thesis / Doctor of Philosophy (PhD) / Measuring the probability of an individual experiencing a specific health outcome in a certain period of time based on that individual’s risk factors is important to improve health. Prediction tools are often used to calculate the probability of an outcome. Health care practitioners use prediction tools to assess an individual’s risk of a certain health outcome and in turn provide individualized management. Prediction tools include a number of agreed upon risk factors that should be assessed in order to best estimate the risk of an outcome. These risk factors are usually selected through exploring sets of data or by consulting a group of experts in the field. However, these methods have limitations. Therefore, we recognized that it is important, when developing prediction tools, to select risk factors that are evidence-based and clinically relevant by adopting a systematic, comprehensive, structured and transparent approach. These sets of risk factors can then aid health researchers when developing new prediction tools or updating existing ones and help clinicians predicting risk. In this thesis, I highlight the methods used to select factors for prediction tools that evaluate the risk of having a venous clot or a bleeding event in patients that are hospitalized for a medical condition. However, the same methods can be applied to any clinical condition and outcome of interest. This work presents a new approach that we conceptualized and tested to select risk factors for venous clots and bleeding events in hospitalized medical patients that are evidence-based, clinically meaningful and relevant. Our findings may inform the development of new prediction tools, the update of widely used tools, and the design of studies to validate these tools. Also, these findings may assist decision makers in evaluating the risk of an individual having an outcome to optimize patient care.