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A thematic analysis of theoretical models for translational science in nursing: mapping the field.

ABSTRACT: The quantity and diversity of conceptual models in translational science may complicate rather than advance the use of theory. This paper offers a comparative thematic analysis of the models available to inform knowledge development, transfer, and utilization. Literature searches identified 47 models for knowledge translation. Four thematic areas emerged: (1) evidence-based practice and knowledge transformation processes, (2) strategic change to promote adoption of new knowledge, (3) knowledge exchange and synthesis for application and inquiry, and (4) designing and interpreting dissemination research. This analysis distinguishes the contributions made by leaders and researchers at each phase in the process of discovery, development, and service delivery. It also informs the selection of models to guide activities in knowledge translation. A flexible theoretical stance is essential to simultaneously develop new knowledge and accelerate the translation of that knowledge into practice behaviors and programs of care that support optimal patient outcomes.

SUBMITTER: Mitchell SA

PROVIDER: S-EPMC3011939 | biostudies-other | 2010 Nov-Dec

REPOSITORIES: biostudies-other

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A thematic analysis of theoretical models for translational science in nursing: mapping the field.

Mitchell Sandra A SA Fisher Cheryl A CA Hastings Clare E CE Silverman Leanne B LB Wallen Gwenyth R GR

Nursing outlook 20101101 6

The quantity and diversity of conceptual models in translational science may complicate rather than advance the use of theory. This paper offers a comparative thematic analysis of the models available to inform knowledge development, transfer, and utilization. Literature searches identified 47 models for knowledge translation. Four thematic areas emerged: (1) evidence-based practice and knowledge transformation processes, (2) strategic change to promote adoption of new knowledge, (3) knowledge e ...[more]

PMID: 21074646

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Project description:BackgroundBehavioural science and its contribution towards improving public health is receiving increased recognition. Yet, the translation of these insights into public health practice is under-researched. This study explored the factors influencing the use of behavioural science within public health at a local authority level.MethodsFourteen local authority staff (n = 13 female) in the south of England participated in semi-structured interviews, which were analysed inductively to identify key themes. These were later mapped deductively to the COM-B model and Theoretical Domains Framework.FindingsNine themes were identified as factors that influence the use of behavioural science in local authority public health: (1) "Limited past experience," (2) "Narrow understanding," (3) "Perceived value of behavioural science," (4) "Translational gap from theory-to-practice," (5) "No protected time," (6) "Old ways of working," (7) "Political influence and organisational culture," (8) "Relationships with key stakeholders," (9) "Access to behavioural science resources". Deductive mapping of these themes revealed that five of the COM constructs (excluding Physical Capability) and eleven of the TDF domains influenced behavioural science use, with "Social influences" and "Knowledge" being the most prominent.DiscussionUse of behavioural science within local authority public health practice is limited and inconsistent. For it to be successfully implemented, there must be an understanding of its role and value, alongside strategies to overcome a translational gap from theory to practice. Public health teams would benefit from protected time to enable application and strategies to break old habits of using a common-sense approach. System-wide buy-in, particularly related to senior leadership and system partners is needed, which would benefit from organisational and political culture change. Training opportunities, practical resources and expert in-house support should be considered a priority across public health teams.

Project description:BackgroundWorkforce studies often identify burnout as a nursing 'outcome'. Yet, burnout itself-what constitutes it, what factors contribute to its development, and what the wider consequences are for individuals, organisations, or their patients-is rarely made explicit. We aimed to provide a comprehensive summary of research that examines theorised relationships between burnout and other variables, in order to determine what is known (and not known) about the causes and consequences of burnout in nursing, and how this relates to theories of burnout.MethodsWe searched MEDLINE, CINAHL, and PsycINFO. We included quantitative primary empirical studies (published in English) which examined associations between burnout and work-related factors in the nursing workforce.ResultsNinety-one papers were identified. The majority (n = 87) were cross-sectional studies; 39 studies used all three subscales of the Maslach Burnout Inventory (MBI) Scale to measure burnout. As hypothesised by Maslach, we identified high workload, value incongruence, low control over the job, low decision latitude, poor social climate/social support, and low rewards as predictors of burnout. Maslach suggested that turnover, sickness absence, and general health were effects of burnout; however, we identified relationships only with general health and sickness absence. Other factors that were classified as predictors of burnout in the nursing literature were low/inadequate nurse staffing levels, ≥ 12-h shifts, low schedule flexibility, time pressure, high job and psychological demands, low task variety, role conflict, low autonomy, negative nurse-physician relationship, poor supervisor/leader support, poor leadership, negative team relationship, and job insecurity. Among the outcomes of burnout, we found reduced job performance, poor quality of care, poor patient safety, adverse events, patient negative experience, medication errors, infections, patient falls, and intention to leave.ConclusionsThe patterns identified by these studies consistently show that adverse job characteristics-high workload, low staffing levels, long shifts, and low control-are associated with burnout in nursing. The potential consequences for staff and patients are severe. The literature on burnout in nursing partly supports Maslach's theory, but some areas are insufficiently tested, in particular, the association between burnout and turnover, and relationships were found for some MBI dimensions only.

Project description:PURPOSE:This article reports on recommendations arising from an invitational workshop series held at the National Institutes of Health for the purposes of identifying critical genomics problems important to the health of the public that can be addressed through nursing science. The overall purpose of the Genomic Nursing State of the Science Initiative is to establish a nursing research blueprint based on gaps in the evidence and expert evaluation of the current state of the science and through public comment. ORGANIZING CONSTRUCTS:A Genomic Nursing State of the Science Advisory Panel was convened in 2012 to develop the nursing research blueprint. The Advisory Panel, which met via two webinars and two in-person meetings, considered existing evidence from evidence reviews, testimony from key stakeholder groups, presentations from experts in research synthesis, and public comment. FINDINGS:The genomic nursing science blueprint arising from the Genomic Nursing State of Science Advisory Panel focuses on biologic plausibility studies as well as interventions likely to improve a variety of outcomes (e.g., clinical, economic, environmental). It also includes all care settings and diverse populations. The focus is on (a) the client, defined as person, family, community, or population; (b) the context, targeting informatics support systems, capacity building, education, and environmental influences; and (c) cross-cutting themes. It was agreed that building capacity to measure the impact of nursing actions on costs, quality, and outcomes of patient care is a strategic and scientific priority if findings are to be synthesized and aggregated to inform practice and policy. CONCLUSIONS:The genomic nursing science blueprint provides the framework for furthering genomic nursing science to improve health outcomes. This blueprint is an independent recommendation of the Advisory Panel with input from the public and is not a policy statement of the National Institutes of Health or the federal government. CLINICAL RELEVANCE:This genomic nursing science blueprint targets research to build the evidence base to inform integration of genomics into nursing practice and regulation (such as nursing licensure requirements, institutional accreditation, and academic nursing school accreditation).

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A thematic analysis of theoretical models for translational science in nursing: mapping the field.

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A thematic analysis of theoretical models for translational science in nursing: mapping the field.

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