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Do quality improvement collaboratives' educational components match the dominant learning style preferences of the participants?

ABSTRACT: BACKGROUND:Quality improvement collaboratives are used to improve healthcare by various organizations. Despite their popularity literature shows mixed results on their effectiveness. A quality improvement collaborative can be seen as a temporary learning organization in which knowledge about improvement themes and methods is exchanged. In this research we studied: Does the learning approach of a quality improvement collaborative match the learning styles preferences of the individual participants and how does that affect the learning process of participants? METHODS:This research used a mixed methods design combining a validated learning style questionnaire with data collected in the tradition of action research methodology to study two Dutch quality improvement collaboratives. The questionnaire is based on the learning style model of Ruijters and Simons, distinguishing five learning style preferences: Acquisition of knowledge, Apperception from others, Discovery of new insights, Exercising in fictitious situations and Participation with others. RESULTS:The most preferred learning styles of the participants were Discovery and Participation. The learning style Acquisition was moderately preferred and Apperception and Exercising were least preferred. The educational components of the quality improvement collaboratives studied (national conferences, half-day learning sessions, faculty site visits and use of an online tool) were predominantly associated with the learning styles Acquisition and Apperception. We observed a decrease in attendance to the learning activities and non-conformance with the standardized set goals and approaches. CONCLUSIONS:We conclude that the participants' satisfaction with the offered learning approach changed over time. The lacking match between these learning style preferences and the learning approach in the educational components of the quality improvement collaboratives studied might be the reason why the participants felt they did not gain new insights and therefore ceased their participation in the collaborative. This study provides guidance for future organisers and participants of quality improvement collaboratives about which learning approaches will best suit the participants and enhance improvement work.

SUBMITTER: Weggelaar-Jansen AM

PROVIDER: S-EPMC4473844 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Do quality improvement collaboratives' educational components match the dominant learning style preferences of the participants?

Weggelaar-Jansen Anne Marie AM van Wijngaarden Jeroen J Slaghuis Sarah-Sue SS

BMC health services research 20150620

<h4>Background</h4>Quality improvement collaboratives are used to improve healthcare by various organizations. Despite their popularity literature shows mixed results on their effectiveness. A quality improvement collaborative can be seen as a temporary learning organization in which knowledge about improvement themes and methods is exchanged. In this research we studied: Does the learning approach of a quality improvement collaborative match the learning styles preferences of the individual par ...[more]

PMID: 26087653

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Project description:BACKGROUND:NIATx200, a quality improvement collaborative, involved 201 substance abuse clinics. Each clinic was randomized to one of four implementation strategies: (a) interest circle calls, (b) learning sessions, (c) coach only or (d) a combination of all three. Each strategy was led by NIATx200 coaches who provided direct coaching or facilitated the interest circle and learning session interventions. METHODS:Eligibility was limited to NIATx200 coaches (N?=?18), and the executive sponsor/change leader of participating clinics (N?=?389). Participants were invited to complete a modified Grasha Riechmann Student Learning Style Survey and Teaching Style Inventory. Principal components analysis determined participants' preferred learning and teaching styles. RESULTS:Responses were received from 17 (94.4 %) of the coaches. Seventy-two individuals were excluded from the initial sample of change leaders and executive sponsors (N?=?389). Responses were received from 80 persons (25.2 %) of the contactable individuals. Six learning profiles for the executive sponsors and change leaders were identified: Collaborative/Competitive (N?=?28, 36.4 %); Collaborative/Participatory (N?=?19, 24.7 %); Collaborative only (N?=?17, 22.1 %); Collaborative/Dependent (N?=?6, 7.8 %); Independent (N?=?3, 5.2 %); and Avoidant/Dependent (N?=?3, 3.9 %). NIATx200 coaches relied primarily on one of four coaching profiles: Facilitator (N?=?7, 41.2 %), Facilitator/Delegator (N?=?6, 35.3 %), Facilitator/Personal Model (N?=?3, 17.6 %) and Delegator (N?=?1, 5.9 %). Coaches also supported their primary coaching profiles with one of eight different secondary coaching profiles. CONCLUSIONS:The study is one of the first to assess teaching and learning styles within a QIC. Results indicate that individual learners (change leaders and executive sponsors) and coaches utilize multiple approaches in the teaching and practice-based learning of quality improvement (QI) processes. Identification teaching profiles could be used to tailor the collaborative structure and content delivery. Efforts to accommodate learning styles would facilitate knowledge acquisition enhancing the effectiveness of a QI collaborative to improve organizational processes and outcomes. TRIAL REGISTRATION:ClinicalTrials.gov Identifier: NCT00934141 Registered July 6, 2009. Retrospectively registered.

Project description:BACKGROUND:In increasingly constrained healthcare budgets worldwide, efforts to improve quality and reduce costs are vital. Quality Improvement Collaboratives (QICs) are often used in healthcare settings to implement proven clinical interventions within local and national programs. The cost of this method of implementation, however, is cited as a barrier to use. This systematic review aims to identify and describe studies reporting on costs and cost-effectiveness of QICs when used to implement clinical guidelines in healthcare. METHODS:Multiple databases (CINAHL, MEDLINE, PsycINFO, EMBASE, EconLit and ProQuest) were searched for economic evaluations or cost studies of QICs in healthcare. Studies were included if they reported on economic evaluations or costs of QICs. Two authors independently reviewed citations and full text papers. Key characteristics of eligible studies were extracted, and their quality assessed against the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). Evers CHEC-List was used for full economic evaluations. Cost-effectiveness findings were interpreted through the Johanna Briggs Institute 'three by three dominance matrix tool' to guide conclusions. Currencies were converted to United States dollars for 2018 using OECD and World Bank databases. RESULTS:Few studies reported on costs or economic evaluations of QICs despite their use in healthcare. Eight studies across multiple healthcare settings in acute and long-term care, community addiction treatment and chronic disease management were included. Five were considered good quality and favoured the establishment of QICs as cost-effective implementation methods. The cost savings to the healthcare setting identified in these studies outweighed the cost of the collaborative itself. CONCLUSIONS:Potential cost savings to the health care system in both acute and chronic conditions may be possible by applying QICs at scale. However, variations in effectiveness, costs and elements of the method within studies, indicated that caution is needed. Consistent identification of costs and description of the elements applied in QICs would better inform decisions for their use and may reduce perceived barriers. Lack of studies with negative findings may have been due to publication bias. Future research should include economic evaluations with societal perspectives of costs and savings and the cost-effectiveness of elements of QICs. TRIAL REGISTRATION:PROSPERO registration number: CRD42018107417.

Project description:Students commencing their medical training arrive with different educational backgrounds and a diverse range of learning experiences. Consequently, students would have developed preferred approaches to acquiring and processing information or learning style preferences. Understanding first-year students' learning style preferences is important to success in learning. However, little is understood about how learning styles impact learning and performance across different subjects within the medical curriculum. Greater understanding of the relationship between students' learning style preferences and academic performance in specific medical subjects would be valuable.This cross-sectional study examined the learning style preferences of first-year medical students and how they differ across gender. This research also analyzed the effect of learning styles on academic performance across different subjects within a medical education program in a Central Asian university. A total of 52 students (57.7% females) from two batches of first-year medical school completed the Index of Learning Styles Questionnaire, which measures four dimensions of learning styles: sensing-intuitive; visual-verbal; active-reflective; sequential-global.First-year medical students reported preferences for visual (80.8%) and sequential (60.5%) learning styles, suggesting that these students preferred to learn through demonstrations and diagrams and in a linear and sequential way. Our results indicate that male medical students have higher preference for visual learning style over verbal, while females seemed to have a higher preference for sequential learning style over global. Significant associations were found between sensing-intuitive learning styles and performance in Genetics [β = -0.46, B = -0.44, p < 0.01] and Anatomy [β = -0.41, B = -0.61, p < 0.05] and between sequential-global styles and performance in Genetics [β = 0.36, B = 0.43, p < 0.05]. More specifically, sensing learners were more likely to perform better than intuitive learners in the two subjects and global learners were more likely to perform better than sequential learners in Genetics.This knowledge will be helpful to individual students to improve their performance in these subjects by adopting new sensing learning techniques. Instructors can also benefit by modifying and adapting more appropriate teaching approaches in these subjects. Future studies to validate this observation will be valuable.

Project description:BACKGROUND: Quality improvement collaboratives (QICs) bring together groups of healthcare professionals to work in a structured manner to improve the quality of healthcare delivery within particular domains. We explored which characteristics of the composition, participation, functioning, and organization of these collaboratives related to changes in the healthcare for patients with anxiety disorders, dual diagnosis, or schizophrenia. METHODS: We studied three QICs involving 29 quality improvement (QI) teams representing a number of mental healthcare organizations in the Netherlands. The aims of the three QICs were the implementation of multidisciplinary practice guidelines in the domains of anxiety disorders, dual diagnosis, and schizophrenia, respectively. We used eight performance indicators to assess the impact of the QI teams on self-reported patient outcomes and process of care outcomes for 1,346 patients. The QI team members completed a questionnaire on the characteristics of the composition, participation in a national program, functioning, and organizational context for their teams. It was expected that an association would be found between these team characteristics and the quality of care for patients with anxiety disorders, dual diagnosis, and schizophrenia. RESULTS: No consistent patterns of association emerged. Theory-based factors did not perform better than practice-based factors. However, QI teams that received support from their management and both active and inspirational team leadership showed better results. Rather surprisingly, a lower average level of education among the team members was associated with better results, although less consistently than the management and leadership characteristics. Team views with regard to the QI goals of the team and attitudes towards multidisciplinary practice guidelines did not correlate with team success. CONCLUSIONS: No general conclusions about the impact of the characteristics of QI teams on the quality of healthcare can be drawn, but support of the management and active, inspirational team leadership appear to be important. Not only patient outcomes but also the performance indicators of monitoring and screening/assessment showed improvement in many but not all of the QI teams with such characteristics. More studies are needed to identify factors associated with the impact of multidisciplinary practice guidelines in mental healthcare.

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Do quality improvement collaboratives' educational components match the dominant learning style preferences of the participants?

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Do quality improvement collaboratives' educational components match the dominant learning style preferences of the participants?

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