Clinical Expertise in Psychotherapy: How Expert Therapists Use Theory in Generating Case Conceptualizations and Interventions

Purpose The current investigation is a follow-up from a previous study examining child language diagnostic decision making in school-based speech-language pathologists (SLPs). The purpose of this study was to examine the SLPs' perspectives regarding the use of evidence-based practice (EBP) in their clinical work. Method Semistructured phone interviews were conducted with 25 school-based SLPs who previously participated in an earlier study by Fulcher-Rood et al. 2018). SLPs were asked questions regarding their definition of EBP, the value of research evidence, contexts in which they implement scientific literature in clinical practice, and the barriers to implementing EBP. Results SLPs' definitions of EBP differed from current definitions, in that SLPs only included the use of research findings. SLPs seem to discuss EBP as it relates to treatment and not assessment. Reported barriers to EBP implementation were insufficient time, limited funding, and restrictions from their employment setting. SLPs found it difficult to translate research findings to clinical practice. SLPs implemented external research evidence when they did not have enough clinical expertise regarding a specific client or when they needed scientific evidence to support a strategy they used. Conclusions SLPs appear to use EBP for specific reasons and not for every clinical decision they make. In addition, SLPs rely on EBP for treatment decisions and not for assessment decisions. Educational systems potentially present other challenges that need to be considered for EBP implementation. Considerations for implementation science and the research-to-practice gap are discussed.

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Emergency medicine consensus conference examines the role of health care simulation in developing clinical expertise

PsycEXTRA Dataset ◽

10.1037/e504342010-015 ◽

2009 ◽

Keyword(s):

Health Care ◽

Emergency Medicine ◽

Consensus Conference ◽

Clinical Expertise

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Life Experience or Clinical Expertise: Exploring Instructor Content Knowledge in Cross-Cultural Courses

PsycEXTRA Dataset ◽

10.1037/e623772013-001 ◽

2013 ◽

Author(s):

Sheena M. Turner ◽

Sylvie Taylor ◽

Theodore R. Burnes ◽

Gregor V. Sarkisian ◽

Amanda L. Archer ◽

...

Keyword(s):

Content Knowledge ◽

Life Experience ◽

Cross Cultural ◽

Clinical Expertise

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Marital and Family Therapists' Case Conceptualizations of an Interracial Family

PsycEXTRA Dataset ◽

10.1037/e709182007-001 ◽

2007 ◽

Author(s):

Rebecca M. Redington ◽

Mai M. Kindaichi ◽

Cristina Dorazio ◽

Madonna G. Constantine

Keyword(s):

Family Therapists ◽

Case Conceptualizations ◽

Interracial Family

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Solution-Focused Brief Therapy with Clients Managing Trauma

10.1093/oso/9780190678784.001.0001 ◽

2018 ◽

Cited By ~ 1

Keyword(s):

Brief Therapy ◽

Treatment Approach ◽

Traumatic Experiences ◽

Clinical Expertise ◽

Therapeutic Approaches ◽

Comprehensive Overview ◽

Strength Based ◽

Solution Focused Brief Therapy ◽

Unique Approach ◽

Solution Focused

This book is a comprehensive overview of how solution-focused brief therapy (SFBT) can be used as a treatment approach for working with clients managing various forms of trauma. This book includes an overview of SFBT with its basic tenets and a description of the current research supporting SFBT as an evidence-based practice. This is followed by a comparison of how SFBT clinicians may approach trauma cases differently than clinicians from other therapeutic approaches. The bulk of the book includes various chapters contributed by skilled SFBT clinicians, with differing clinical expertise, illustrating SFBT as it is applied to different traumatic experiences/clinical cases. This book is the first solution-focused book to comprehensively discuss how traumatized clients can be helped to develop a unique preferred future and move toward healing and health. The distinguishing feature of this book lies not only in its unique approach to trauma but also in the outstanding contributors from various specialties in the field of trauma and SFBT: These contributors will share their knowledge and describe their strength-based, resiliency focus of applying SFBT in different traumatic circumstances.

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Predicting COVID-19 mortality with electronic medical records

npj Digital Medicine ◽

10.1038/s41746-021-00383-x ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Hossein Estiri ◽

Zachary H. Strasser ◽

Jeffy G. Klann ◽

Pourandokht Naseri ◽

Kavishwar B. Wagholikar ◽

...

Keyword(s):

Risk Factors ◽

Medical Information ◽

Age Groups ◽

Prognostic Models ◽

Smoking History ◽

Risk Scores ◽

Gradient Boosting ◽

Chronic Obstructive ◽

Clinical Expertise ◽

History Of

AbstractThis study aims to predict death after COVID-19 using only the past medical information routinely collected in electronic health records (EHRs) and to understand the differences in risk factors across age groups. Combining computational methods and clinical expertise, we curated clusters that represent 46 clinical conditions as potential risk factors for death after a COVID-19 infection. We trained age-stratified generalized linear models (GLMs) with component-wise gradient boosting to predict the probability of death based on what we know from the patients before they contracted the virus. Despite only relying on previously documented demographics and comorbidities, our models demonstrated similar performance to other prognostic models that require an assortment of symptoms, laboratory values, and images at the time of diagnosis or during the course of the illness. In general, we found age as the most important predictor of mortality in COVID-19 patients. A history of pneumonia, which is rarely asked in typical epidemiology studies, was one of the most important risk factors for predicting COVID-19 mortality. A history of diabetes with complications and cancer (breast and prostate) were notable risk factors for patients between the ages of 45 and 65 years. In patients aged 65–85 years, diseases that affect the pulmonary system, including interstitial lung disease, chronic obstructive pulmonary disease, lung cancer, and a smoking history, were important for predicting mortality. The ability to compute precise individual-level risk scores exclusively based on the EHR is crucial for effectively allocating and distributing resources, such as prioritizing vaccination among the general population.

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How will artificial intelligence and bioinformatics change our understanding of IgA in the next decade?

Seminars in Immunopathology ◽

10.1007/s00281-021-00847-y ◽

2021 ◽

Author(s):

Roman David Bülow ◽

Daniel Dimitrov ◽

Peter Boor ◽

Julio Saez-Rodriguez

Keyword(s):

Artificial Intelligence ◽

Multidisciplinary Approach ◽

Immunoglobulin A ◽

Improve Patient Care ◽

Integrated Analysis ◽

Clinical Expertise ◽

End Stage ◽

The Complement System ◽

Improve Patient ◽

Generation Sequencing

AbstractIgA nephropathy (IgAN) is the most common glomerulonephritis. It is characterized by the deposition of immune complexes containing immunoglobulin A (IgA) in the kidney’s glomeruli, triggering an inflammatory process. In many patients, the disease has a progressive course, eventually leading to end-stage kidney disease. The current understanding of IgAN’s pathophysiology is incomplete, with the involvement of several potential players, including the mucosal immune system, the complement system, and the microbiome. Dissecting this complex pathophysiology requires an integrated analysis across molecular, cellular, and organ scales. Such data can be obtained by employing emerging technologies, including single-cell sequencing, next-generation sequencing, proteomics, and complex imaging approaches. These techniques generate complex “big data,” requiring advanced computational methods for their analyses and interpretation. Here, we introduce such methods, focusing on the broad areas of bioinformatics and artificial intelligence and discuss how they can advance our understanding of IgAN and ultimately improve patient care. The close integration of advanced experimental and computational technologies with medical and clinical expertise is essential to improve our understanding of human diseases. We argue that IgAN is a paradigmatic disease to demonstrate the value of such a multidisciplinary approach.

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Strategies Australian Hospitals Utilize to Incorporate Patient Feedback in the Delivery and Measurement of Person-Centered Care: A Scoping Review

Clinical Nursing Research ◽

10.1177/10547738211033098 ◽

2021 ◽

pp. 105477382110330

Author(s):

Joy Davis ◽

Sue Sinni ◽

Stephen Maloney ◽

Lorraine Walker

Keyword(s):

Scoping Review ◽

Clinical Expertise ◽

Educational Strategies ◽

Hospital Governance ◽

Societal Values ◽

Patient Feedback ◽

Person Centered Care ◽

Acute Hospitals ◽

Centered Care ◽

Strategy Design

Patients are central to healthcare clinicians and organizations but often subsidiary to clinical expertise, knowledge, workplace processes, and culture. Shifting societal values, technology, and regulations have remoulded the patient-clinician relationship, augmenting the patient’s voice within the healthcare construct. Scaffolding this restructure is the global imperative to deliver person-centered care (PCC). The aim of the scoping review was to explore and map the intersection between patient feedback and strategies to improve the provision of PCC within acute hospitals in Australia. Database searches yielded 493 articles, with 16 studies meeting inclusion criteria. Integration of patient feedback varied from strategy design, through to multi-staged input throughout the initiative and beyond. Initiatives actioning patient feedback fell broadly into four categories: clinical practice, educational strategies, governance, and measurement. How clinicians can invite feedback and support patients to engage equally remains unclear, requiring further exploration of strategies to propel clinician-patient partnerships, scaffolded by hospital governance structures.

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