Education for Information

The Information Assessment Method (IAM) is unique, theory-driven, and validated by and for different audiences. Based on a theoretical model of information outcomes, the IAM questionnaire is organized in four levels: situational relevance, cognitive impact, use, and health outcomes of information. To evaluate health information, the IAM questionnaire has been used as an outcome measure providing feedback from the viewpoint of information users, who are clinicians, managers, patients or the public. The IAM stimulates the user to rate specific health information content online (e.g., on a webpage), thereby capturing their reflection (e.g., reflective learning) and feedback. Subsequently, ratings and comments can be used by information providers to improve their content.

The cancer survival rate has increased and family physicians (FPs) follow cancer survivors who experience long-term problems. Clinical practice guidelines outline best practices in cancer survivor care, but most FPs are unaware of this information. Little is known about specific barriers to survivorship guideline implementation in primary health care. Thus, our objectives are to identify patterns of FP non-use of survivorship guideline recommendations and describe key use-related barriers. The present paper reports a mixed methods study protocol that is implemented. Participants are FPs providing care to at least one breast cancer survivor. Quantitative component: Recommendations are integrated in a mobile application. Through this app, we deliver a weekly alert to one recommendation. FPs can rate recommendations using the validated Information Assessment Method (IAM) questionnaire. We will identify patterns of non-use of recommendations. Qualitative component: We will interview FPs who do not use a recommendation, identify use-related barriers, and assign them to themes related to information non-use. Integration: We will compare quantitative and qualitative results. We anticipate that results will identify unique barriers to implementation of survivorship information, as well as potential solutions and strategies to improve patient care, for example, information specialists producing and disseminating patient health information. Thus, finding barriers and solutions will contribute to the practice of informationists and FPs.

Spaced education (SE) is a learning strategy that can improve long-term knowledge retention. Inspired by the concept of SE, we conducted a mixed methods study of a smartphone application (app) as a platform of SE. Objectives were to: (phase 1 quantitative) estimate the extent to which weekly alerts on the app can stimulate medical residents to visit the app, (connection of phases) identify participants for a second qualitative phase, and (phase 2 qualitative) describe factors, from the resident perspective, which influence sustainable participation in SE, and describe strategies for improvement of the app. Methodology and methods: phase-1 design was pre-experimental, phase-2 design was qualitative descriptive (deductive-inductive thematic analysis). Results: We observed a stimulating effect of weekly alerts for the first two months of the one-year study. Per participant, alert visits varied from 0 to 34 (mean = 1.7, SD = 4.5) and total page visits varied from 1 to 442 (mean = 28.3, SD = 61.4). Barriers and facilitators to sustainable participation in SE fell into five dimensions: user-related factors, information content factors, mobile app design factors, alert system factors, and service factors. Four strategies for app improvement were described. In conclusion, we propose five dimensions pertaining to potential predictors of sustainable participation in SE to deliver clinical information.

In this commentary, we will describe our study and report results that will be of interest to information and education professionals and researchers. Evidence-based medicine requires health professionals to keep up to date with new research-based knowledge. Canadian physicians must now participate in Continuing Medical Education (CME) activities. CME strives to improve clinician performance as well as patient health outcomes. Our study was aimed to assess whether physicians who participated in a CME program and expected health benefits for their patients following an elearning activity were more likely to have higher participation in the program in subsequent years. Weekly treatment Highlights were delivered by email to practicing family physicians across Canada, who rated them using the Information Assessment Method (IAM). The number of expected benefits for patients reported by participants during 2016 was plotted against the number of instances of participation in 2017. Results show that the number of expected benefits in 2016 was correlated with the number of IAM ratings in 2017.

Health care professionals, be they researchers, clinicians or educators, routinely face the need to find and apply best evidence in the context of complex situations. In order to navigate an increasingly large body of evidence advanced information literacy skills are required. More than simply a set of skills, information literacy is an approach that makes possible all other professional activities and goals in evidence-based practice (EBP). The Association for College and Research Libraries (ACRL) recognized this by shifting focus from information literacy competencies to overarching ideas or frames. While it is unlikely that healthcare organizations and accreditation bodies will rescind specific competencies, it is important for educators to recognise and explore the overarching ideas identified by the ACRL Framework, and perhaps identify and engage with other foundational ideas unique to healthcare. Workshops and lectures that teach linear strategies using easy-to-teach examples do not teach skills that students can easily apply to real and complex scenarios requiring critical thinking and iterative strategies. The use of pedagogical approaches such as inquiry-based learning (IBL) have historically been useful in this regard. We have successfully used IBL at the McGill Ingram School of Nursing to teach EBP competencies and engage with higher-level concepts.

Information monitoring and keeping abreast of research trends is essential for researchers. However, as the volume of information and the number of tools for staying up to date continue to grow, researchers struggle to continuously monitor and filter scholarly articles. This is particularly true for researchers working in complex multidisciplinary fields like Patient Oriented Research, who need to cast their nets wide to identify relevant high-quality studies. The proposed multiple case study will explore and analyze the use and user perceptions regarding a collaborative research trend monitoring system, called eSRAP. This research will advance knowledge on processes and outcomes of collaborative monitoring of research publications. The findings will be significant to those providing monitoring services, studying collaborative information behaviour, training future researchers and information professionals, as well as to system designers.

Mixed methods (MM) involve combining qualitative (QUAL) and quantitative (QUAN) methods in program evaluation, primary research, and literature reviews. MM are being increasingly used in health and social sciences (in multiple fields and in an inter-field manner). Over the years, several strategies to integrate QUAL and QUAN phases, results, and data have been proposed. For MM teachers, one of the challenges is to explain specific MM strategies and their combinations, find current illustrative examples for trainees, and identify emerging innovative MM strategies. Our project is aimed at identifying and measuring the importance of facilitators and barriers associated with the implementation of an innovative cross-disciplinary monitoring of the research literature: the Collaborative eBibliography on Mixed Methods (CeBoMM). Results will facilitate CeBoMM implementation, and can contribute to MM teaching and learning, thereby, helping MM teachers and their trainees worldwide. Ultimately, CeBoMM can be adapted to be used by teachers in other academic areas and those interested in collaborative information monitoring.

Collective intelligence is shared or group intelligence that emerges from collaborative effort. We propose to harness collective intelligence through the specific tasks of producing and sharing constructive comments on synopses of clinical research, disseminated to a national community of physician members of the Canadian Medical Association. This proposal uses the power of many to bring the collective wisdom and resources of a community of physicians back to the individual. Building on an active program of continuing education to raise awareness of synopses of new clinical research for physicians, we describe the characteristics of a new system to be built upon an existing web platform. This new platform will offer physicians an opportunity to read and share their comments on Patient Oriented Evidence that Matters (POEMs), with other physicians, which will stimulate collective intelligence. In turn, this will further benefit the education of these physicians and help to improve the decisions they make in everyday clinical practice. Knowing about this endeavour may be of benefit to the community of information professionals in multiple fields, who seek to improve their use of evidence-based abstracts of scientific publications and experience-based (information users’ comments) information in their daily work.

Mixed studies reviews include empirical studies with diverse designs (qualitative, quantitative and mixed methods). To make the process of identifying relevant empirical studies for such reviews more efficient, we developed a mixed filter that included different keywords and subject headings for quantitative (e.g., cohort study), qualitative (e.g., focus group), and mixed methods studies. It was tested for six journals from three disciplines. We measured precision (proportion of retrieved documents being relevant), sensitivity (proportion of relevant documents retrieved), and specificity (proportion of non-relevant documents not retrieved). Records were coded before applying the filter and compared with retrieved records, and descriptive statistics were performed, suggesting the mixed filter has high sensitivity, but lower precision and specificity (close to 50%). Next, based on the success of the filter, we developed an automated text classification system that can automatically select empirical studies in order to facilitate systematic mixed studies reviews. Several algorithms were trained and validated with 8,050 database records that were previously manually categorized. Decision trees had the best results and surpassed the accuracy of the filter by 30% when using full-text documents. This algorithm was then adapted into an online format that can be used by researchers to analyze their bibliography and categorize records into “empirical” and “nonempirical”.