Intention to Use Wiki-Based Knowledge Tools: Survey of Quebec Emergency Health Professionals (Preprint)

BACKGROUND Clinical decision support systems are information technologies that assist clinicians in making better decisions. Their adoption has been limited because their content is difficult to adapt to local contexts and slow to adapt to emerging evidence. Collaborative writing applications such as wikis have the potential to increase access to existing and emerging evidence-based knowledge at the point of care, standardize emergency clinical decision making, and quickly adapt this knowledge to local contexts. However, little is known about the factors influencing health professionals’ use of wiki-based knowledge tools. OBJECTIVE This study aims to measure emergency physicians’ (EPs) and other acute care health professionals’ (ACHPs) intentions to use wiki-based knowledge tools in trauma care and identify determinants of this intention that can be used in future theory-based interventions for promoting the use of wiki-based knowledge tools in trauma care. METHODS In total, 266 EPs and 907 ACHPs (nurses, respiratory therapists, and pharmacists) from 12 Quebec trauma centers were asked to answer a survey based on the theory of planned behavior (TPB). The TPB constructs were measured using a 7-point Likert scale. Descriptive statistics and Pearson correlations between the TPB constructs and intention were calculated. Multiple linear regression analysis was conducted to identify the salient beliefs. RESULTS Among the eligible participants, 57.1% (152/266) of EPs and 31.9% (290/907) of ACHPs completed the questionnaire. For EPs, we found that attitude, perceived behavioral control (PBC), and subjective norm (SN) were significant determinants of the intention to use wiki-based knowledge tools and explained 62% of its variance. None of the sociodemographic variables were related to EPs’ intentions to use wiki-based knowledge tools. The regression model identified two normative beliefs ("approval by physicians" and "approval by patients") and two behavioral beliefs ("refreshes my memory" and "reduces errors"). For ACHPs, attitude, PBC, SN, and two sociodemographic variables (profession and the previous personal use of a wiki) were significantly related to the intention to use wiki-based knowledge tools and explained 60% of the variance in behavioral intention. The final regression model for ACHPs included two normative beliefs ("approval by the hospital trauma team" and "people less comfortable with information technology"), one control belief ("time constraints"), and one behavioral belief ("access to evidence"). CONCLUSIONS The intentions of EPs and ACHPs to use wiki-based knowledge tools to promote best practices in trauma care can be predicted in part by attitude, SN, and PBC. We also identified salient beliefs that future theory-based interventions should promote for the use of wiki-based knowledge tools in trauma care. These interventions will address the barriers to using wiki-based knowledge tools, find ways to ensure the quality of their content, foster contributions, and support the exploration of wiki-based knowledge tools as potential effective knowledge translation tools in trauma care.

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Intention to Use Wiki-Based Knowledge Tools: Survey of Quebec Emergency Health Professionals

JMIR Medical Informatics ◽

10.2196/24649 ◽

2021 ◽

Vol 9 (6) ◽

pp. e24649

Author(s):

Patrick Archambault ◽

Stéphane Turcotte ◽

Pascal Y Smith ◽

Kassim Said Abasse ◽

Catherine Paquet ◽

...

Keyword(s):

Regression Model ◽

Trauma Care ◽

Health Professionals ◽

Clinical Decision ◽

Intention To Use ◽

Normative Beliefs ◽

Sociodemographic Variables ◽

Salient Beliefs ◽

Local Contexts ◽

Future Theory

Background Clinical decision support systems are information technologies that assist clinicians in making better decisions. Their adoption has been limited because their content is difficult to adapt to local contexts and slow to adapt to emerging evidence. Collaborative writing applications such as wikis have the potential to increase access to existing and emerging evidence-based knowledge at the point of care, standardize emergency clinical decision making, and quickly adapt this knowledge to local contexts. However, little is known about the factors influencing health professionals’ use of wiki-based knowledge tools. Objective This study aims to measure emergency physicians’ (EPs) and other acute care health professionals’ (ACHPs) intentions to use wiki-based knowledge tools in trauma care and identify determinants of this intention that can be used in future theory-based interventions for promoting the use of wiki-based knowledge tools in trauma care. Methods In total, 266 EPs and 907 ACHPs (nurses, respiratory therapists, and pharmacists) from 12 Quebec trauma centers were asked to answer a survey based on the theory of planned behavior (TPB). The TPB constructs were measured using a 7-point Likert scale. Descriptive statistics and Pearson correlations between the TPB constructs and intention were calculated. Multiple linear regression analysis was conducted to identify the salient beliefs. Results Among the eligible participants, 57.1% (152/266) of EPs and 31.9% (290/907) of ACHPs completed the questionnaire. For EPs, we found that attitude, perceived behavioral control (PBC), and subjective norm (SN) were significant determinants of the intention to use wiki-based knowledge tools and explained 62% of its variance. None of the sociodemographic variables were related to EPs’ intentions to use wiki-based knowledge tools. The regression model identified two normative beliefs ("approval by physicians" and "approval by patients") and two behavioral beliefs ("refreshes my memory" and "reduces errors"). For ACHPs, attitude, PBC, SN, and two sociodemographic variables (profession and the previous personal use of a wiki) were significantly related to the intention to use wiki-based knowledge tools and explained 60% of the variance in behavioral intention. The final regression model for ACHPs included two normative beliefs ("approval by the hospital trauma team" and "people less comfortable with information technology"), one control belief ("time constraints"), and one behavioral belief ("access to evidence"). Conclusions The intentions of EPs and ACHPs to use wiki-based knowledge tools to promote best practices in trauma care can be predicted in part by attitude, SN, and PBC. We also identified salient beliefs that future theory-based interventions should promote for the use of wiki-based knowledge tools in trauma care. These interventions will address the barriers to using wiki-based knowledge tools, find ways to ensure the quality of their content, foster contributions, and support the exploration of wiki-based knowledge tools as potential effective knowledge translation tools in trauma care.

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Clinician acceptance of complex clinical decision support systems for treatment allocation of patients with chronic low back pain

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-021-01502-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Stephanie Jansen-Kosterink ◽

Lex van Velsen ◽

Miriam Cabrita

Keyword(s):

Low Back Pain ◽

Back Pain ◽

Clinical Decision Support Systems ◽

Clinical Decision ◽

Perceived Usefulness ◽

Intention To Use ◽

Low Back ◽

Research Model ◽

Online Questionnaire ◽

Treatment Allocation

Abstract Background The uptake of complex clinical decision support systems (CDSS) in daily practice remains low, despite the proven potential to reduce medical errors and to improve the quality of care. To improve successful implementation of a complex CDSS this study aims to identify the factors that hinder, or alleviate the acceptance of, clinicians toward the use of a complex CDSS for treatment allocation of patients with chronic low back pain. Methods We tested a research model in which the intention to use a CDSS by clinicians is influenced by the perceived usefulness; this usefulness, in turn is influenced by the perceived service benefits and perceived service risks. An online survey was created to test our research model and the data was analysed using Partial Least Squares Structural Equation Modelling. The study population consisted of clinicians. The online questionnaire started with demographic questions and continued with a video animation of the complex CDSS followed by the set of measurement items. The online questionnaire ended with two open questions enquiring the reasons to use and not use, a complex CDSS. Results Ninety-eight participants (46% general practitioners, 25% primary care physical therapists, and 29% clinicians at a rehabilitation centre) fully completed the questionnaire. Fifty-two percent of the respondents were male. The average age was 48 years (SD ± 12.2). The causal model suggests that perceived usefulness is the main factor contributing to the intention to use a complex CDSS. Perceived service benefits and risks are both significant antecedents of perceived usefulness and perceived service risks are affected by the perceived threat to autonomy and trusting beliefs, particularly benevolence and competence. Conclusions To improve the acceptance of complex CDSSs it is important to address the risks, but the main focus during the implementation phase should be on the expected improvements in patient outcomes and the overall gain for clinicians. Our results will help the development of complex CDSSs that fit more into the daily clinical practice of clinicians.

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NCOG-31. DEVELOPMENT AND EVALUATION OF PROGNOSTIC MODELS TO PREDICT SURVIVAL OF PATIENTS WITH GLIOBLASTOMA MULTIFORME

Neuro-Oncology ◽

10.1093/neuonc/noaa215.569 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii135-ii136

Author(s):

John Lin ◽

Michelle Mai ◽

Saba Paracha

Keyword(s):

Machine Learning ◽

Decision Support ◽

Glioblastoma Multiforme ◽

Random Forest ◽

Regression Model ◽

Clinical Decision Support ◽

Multivariate Regression ◽

Visual Analysis ◽

Clinical Decision ◽

Prognostic Models

Abstract Glioblastoma multiforme (GBM), the most common form of glioma, is a malignant tumor with a high risk of mortality. By providing accurate survival estimates, prognostic models have been identified as promising tools in clinical decision support. In this study, we produced and validated two machine learning-based models to predict survival time for GBM patients. Publicly available clinical and genomic data from The Cancer Genome Atlas (TCGA) and Broad Institute GDAC Firehouse were obtained through cBioPortal. Random forest and multivariate regression models were created to predict survival. Predictive accuracy was assessed and compared through mean absolute error (MAE) and root mean square error (RMSE) calculations. 619 GBM patients were included in the dataset. There were 381 (62.9%) cases of recurrence/progression and 53 (8.7%) cases of disease-free survival. The MAE and RMSE values were 0.553 and 0.887 years respectively for the random forest regression model, and they were 1.756 and 2.451 years respectively for the multivariate regression model. Both models accurately predicted overall survival. Comparison of models through MAE, RMSE, and visual analysis produced higher accuracy values for random forest than multivariate linear regression. Further investigation on feature selection and model optimization may improve predictive power. These findings suggest that using machine learning in GBM prognostic modeling will improve clinical decision support. *Co-first authors.

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Gender Differences in Young Adults’ Beliefs About Sunscreen Use

Health Education & Behavior ◽

10.1177/1090198102239257 ◽

2003 ◽

Vol 30 (1) ◽

pp. 29-43 ◽

Cited By ~ 51

Author(s):

Lorien Abroms ◽

Cynthia M. Jorgensen ◽

Brian G. Southwell ◽

Alan C. Geller ◽

Karen M. Emmons

Keyword(s):

Gender Differences ◽

Young Adults ◽

Focus Group ◽

Reasoned Action ◽

Normative Beliefs ◽

Behavioral Beliefs ◽

Sunscreen Use ◽

Salient Beliefs ◽

Focus Group Methodology ◽

Males And Females

This study employs focus group methodology to explore gender differences in sunscreen use. Guided by the theory of reasoned action, males and females were found to differ on each of the following constructs: behavior, behavioral beliefs, and normative beliefs. Males and females differed in their sunscreen use, with females adopting a more preventive style of sunscreen use and males a more reactive style. Males and females differed in their salient beliefs that motivated their sunscreen use, many of which were related to traditional American gender roles. In addition, although males and females were aware of both positive and negative sources of normative beliefs regarding sunscreen use, females received more encouragement from their mothers and peers than males. Findings are discussed in terms of their implications for the design of future interventions.

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Goals of palliative cancer therapy.

Journal of Clinical Oncology ◽

10.1200/jco.1993.11.2.378 ◽

1993 ◽

Vol 11 (2) ◽

pp. 378-381 ◽

Cited By ~ 53

Author(s):

F Porzsolt ◽

I Tannock

Keyword(s):

Quality Of Life ◽

Decision Making ◽

Cost Effectiveness ◽

Cancer Therapy ◽

Health Professionals ◽

Palliative Treatment ◽

Clinical Decision Making ◽

Clinical Decision ◽

Oncology Practice

The major conclusions of the Workshop on Goals of Palliative Cancer Therapy are as follows: 1. The goals of any cancer therapy should be stated explicitly. 2. If the goal of treatment is palliation, this should be documented according to one of the established and validated methods for assessment of quality of life. Several validated methods are available, and although imperfect, have been shown to give reliable information. 3. The use of simple measures of quality of life (eg, symptom checklists, pain assessment cards) should become routine in oncology practice. The act of introducing such measures improves palliation. 4. Measures of cost-effectiveness should be used more widely in clinical decision making to ensure the appropriate deployment of resources. 5. There must be improved education of all health professionals with regard to the multiple methods for provision of palliative treatment to cancer patients and the assessment of palliation.

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Variables Associated With Indiscriminate Friendliness Displayed by Chinese Adoptees in U.S. Families

The Family Journal ◽

10.1177/1066480717731345 ◽

2017 ◽

Vol 25 (4) ◽

pp. 414-422 ◽

Cited By ~ 2

Author(s):

Yanhong Liu ◽

Richard J. Hazler

Keyword(s):

Mental Health ◽

Regression Model ◽

Mental Health Professionals ◽

Health Professionals ◽

Institutional Care ◽

Adoptive Parents ◽

Adoptive Families ◽

Family Counselors ◽

Significant Regression ◽

Practical Implications

The study investigated potential variables associated with indiscriminate friendliness (IF) in children adopted from China by U.S. parents. Children in this study were adopted at a mean age of 19 months and have spent an average of 61 months with their adoptive parents. The sample comprised of 92 U.S. parents with children adopted from China. Children’s age at the time of adoption, length of postadoption time, prior institutional care, and postadoption parenting by adoptive parents were investigated in association with IF. Findings showed that prior institutional care was significantly associated children’s IF, whereas an increase in postadoption time shared with adoptive parents was not accompanied by a decrease in children’s IF. The significant regression model explained 9% of variance in children’s IF. Results provided practical implications for family counselors and other mental health professionals working with adoptive families.

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Attitudes of Patients and Health Professionals Regarding Screening Algorithms: Qualitative Study

JMIR Formative Research ◽

10.2196/17971 ◽

2021 ◽

Vol 5 (8) ◽

pp. e17971

Author(s):

Christina Oxholm ◽

Anne-Marie Soendergaard Christensen ◽

Regina Christiansen ◽

Uffe Kock Wiil ◽

Anette Søgaard Nielsen

Keyword(s):

Health Professionals ◽

Development Process ◽

Ad Hoc ◽

Clinical Decision Making ◽

Clinical Decision ◽

Alcohol Problems ◽

Close Reading ◽

Health Records ◽

Professional Discretion ◽

Semistructured Interviews

Background As a preamble to an attempt to develop a tool that can aid health professionals at hospitals in identifying whether the patient may have an alcohol abuse problem, this study investigates opinions and attitudes among both health professionals and patients about using patient data from electronic health records (EHRs) in an algorithm screening for alcohol problems. Objective The aim of this study was to investigate the attitudes and opinions of patients and health professionals at hospitals regarding the use of previously collected data in developing and implementing an algorithmic helping tool in EHR for screening inexpedient alcohol habits; in addition, the study aims to analyze how patients would feel about asking and being asked about alcohol by staff, based on a notification in the EHR from such a tool. Methods Using semistructured interviews, we interviewed 9 health professionals and 5 patients to explore their opinions and attitudes about an algorithm-based helping tool and about asking and being asked about alcohol usage when being given a reminder from this type of tool. The data were analyzed using an ad hoc method consistent with a close reading and meaning condensing. Results The health professionals were both positive and negative about a helping tool grounded in algorithms. They were optimistic about the potential of such a tool to save some time by providing a quick overview if it was easy to use but, on the negative side, noted that this type of helping tool might take away the professionals’ instinct. The patients were overall positive about the helping tool, stating that they would find this tool beneficial for preventive care. Some of the patients expressed concerns that the information provided by the tool could be misused. Conclusions When developing and implementing an algorithmic helping tool, the following aspects should be considered: (1) making the helping tool as transparent in its recommendations as possible, avoiding black boxing, and ensuring room for professional discretion in clinical decision making; and (2) including and taking into account the attitudes and opinions of patients and health professionals in the design and development process of such an algorithmic helping tool.

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A Clinical Recommendation System to Maternity Care

Innovations in Global Maternal Health ◽

10.4018/978-1-7998-2351-3.ch001 ◽

2020 ◽

pp. 1-20

Author(s):

Eliana Pereira ◽

Filipe Portela ◽

António Abelha

Keyword(s):

Health Professionals ◽

Maternity Care ◽

Recommendation System ◽

Clinical Decision Support Systems ◽

Clinical Decision ◽

Triage System ◽

Main Requirement ◽

Simulation Techniques ◽

Clinical Recommendation ◽

Using Data

Nowadays in healthcare, the Clinical Decision Support Systems are used in order to help health professionals to take an evidence-based decision. An example is the Clinical Recommendation Systems. In this sense, a pre-triage system was developed and implemented in Centro Hospitalar do Porto in order to group the patients on two levels (urgent or outpatient). However, although this system is calibrated and specific to the urgency of obstetrics and gynaecology, it does not meet all clinical requirements by the general department of the Portuguese HealthCare (Direção Geral de Saúde). The main requirement is the need of having priority triage system characterized by five levels. Thus some studies have been conducted with the aim of presenting a methodology able to evolve the pre-triage system on a Clinical Recommendation System with five levels. After some tests (using data mining and simulation techniques), it has been validated the possibility of transformation the pre-triage system in a Clinical Recommendation System in the obstetric context. At the end the main indicators achieved with this system are presented in the Business Intelligence Platform already deployed. This paper presents an overview of the Clinical Recommendation System for obstetric triage, the model developed and the main results achieved.

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Intention to Use Behavioral Health Data from a Health Information Exchange: A Mixed Methods Study (Preprint)

10.2196/preprints.26746 ◽

2020 ◽

Author(s):

Randyl A. Cochran ◽

Sue S. Feldman ◽

Nataliya V. Ivankova ◽

Allyson G. Hall ◽

William Opoku-Agyeman

Keyword(s):

Behavioral Health ◽

Health Information ◽

Clinical Decision Making ◽

Clinical Decision ◽

Health Data ◽

Mixed Methods Study ◽

Intention To Use ◽

Coordinated Care ◽

Related Information ◽

Health Related

BACKGROUND Patients with co-occurring behavioral health and chronic medical conditions frequently overutilize inpatient hospital services. This pattern of overuse contributes to inefficient healthcare spending. These patients require coordinated care to achieve optimal health outcomes. However, the poor exchange of health-related information between various clinicians renders the delivery of coordinated care challenging. Health information exchanges (HIEs) facilitate health-related information sharing and have been shown to be effective in chronic disease management, but their effectiveness in the delivery of integrated care is less clear. It is prudent to consider new approaches to sharing both general medical and behavioral health information. OBJECTIVE We identified and described factors that influence the intention to use behavioral health information that is shared through HIEs. METHODS A mixed methods study consisting of two phases was conducted. A validated survey instrument was emailed to clinical and non-clinical staff in Alabama and Oklahoma. The survey captured information about the impact of predictors on the intention to use behavioral health data in clinical decision-making. Follow-up interviews were conducted with a subsample of participants to understand the survey results better. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data. Thematic analysis was used to identify themes from the interviews. RESULTS Sixty-two participants completed the survey. 62.91% of the participants were clinicians. Performance expectancy (β= .382, P= .01) and trust (β= .539, P= .00) predicted intention to use behavioral health information shared via HIEs. Interviewees expressed that behavioral health information could be useful in clinical decision-making. However, privacy and confidentiality concerns discourage sharing this information, and it is generally missing from the patient record altogether. The interviewees (n= 5) also stated that training for HIE use was not mandatory, and the training that was provided did not focus on the exchange of behavioral health information specifically. CONCLUSIONS Despite barriers, individuals are willing to use behavioral health information from HIEs if they believe that it will enhance job performance and if the information being transmitted is trustworthy. The findings contribute to our understanding of the role HIEs can play in delivering integrated care, particularly to vulnerable patients.

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Researcher Perceptions of a Self-Service Online Portal to Facilitate Volunteer Recruitment into Clinical Trials

ACI Open ◽

10.1055/s-0041-1732406 ◽

2021 ◽

Vol 05 (02) ◽

pp. e59-e66

Author(s):

Srinivas Emani ◽

Yichuan Grace Hsieh ◽

Greg Estey ◽

Holly M. Parker ◽

Xiaofeng Zhang ◽

...

Keyword(s):

Clinical Trials ◽

Regression Model ◽

Behavioral Intention ◽

Self Efficacy ◽

Hierarchical Regression ◽

Intention To Use ◽

Hierarchical Regression Model ◽

Volunteer Recruitment ◽

Facilitating Conditions ◽

Behavioral Intention To Use

Abstract Background Recruitment of volunteers is a major challenge for clinical trials. There has been increasing development and use of Internet-based portals in recruitment for clinical research. There has been little research on researcher use and perceptions of these portals. Objectives This study evaluated researcher perceptions of use of Rally, an Internet-based portal for clinical trial volunteer recruitment. Methods A cross-sectional survey was developed and implemented to understand researcher perceptions. From theoretical models of information technology use, the survey adopted items in four domains: ease of use, usefulness, facilitating conditions, and self-efficacy. The dependent variable was researchers' behavioral intention to use Rally. The survey captured characteristics of researchers such as gender, age, and role. It was implemented using the REDCap survey tool. An email invitation followed by three reminders was sent to researchers. A hierarchical regression model was applied to assess predictors of behavioral intention. Results The survey response rate was 35.6% (152 surveys received from 427 contacted researchers). In the hierarchical regression model, facilitating conditions and self-efficacy predicted behavioral intention (F (4,94) = 6.478; p <0.001). The model explained 21.6% of the variance in behavioral intention (R-square change = 21.3%, p <0.001). Conclusion Facilitating conditions and self-efficacy predicted researchers' behavioral intention to use Rally for volunteer recruitment into clinical trials. Future research should document best practices and strategies for enhancing researcher use of online portals for volunteer recruitment.

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