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Record W2332063811 · doi:10.1097/acm.0b013e3182308d25

The Neglect of Chronic Disease Self-Management in Medical Education: Involving Patients as Educators

2011· article· en· W2332063811 on OpenAlexaff
Angela Towle, William Godolphin

Bibliographic record

VenueAcademic Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineTeamworkHealth careSelf-managementDisease managementPopulationNursingDiseaseFamily medicineInterprofessional educationChronic conditionHealth management systemAlternative medicine

Abstract

fetched live from OpenAlex

An estimated 133 million Americans and 16 million Canadians (roughly half the population of both countries) live with at least one chronic illness; about one in four suffers limitations to daily activities as a consequence. As the population ages and people live longer, we can expect to see an increase in the prevalence and complexity of chronic illness. Chronic disease management will become a major part of the work of health professionals, both as individuals and as members of interprofessional teams. The need to align medical education with changes in health care delivery will require more emphasis on chronic disease management as well as on the related topics of behavioral and social sciences and interprofessional teamwork.1 Yet medical education is still focused on, and in, acute care. A PubMed search of all issues of two top medical education journals for the term “chronic disease management” yielded four papers in Academic Medicine and nine in Medical Education. In chronic disease, the patient/family is the chief provider of care. Patient chronic disease self-management (CDSM) and self-management support by clinicians have been identified as essential components of chronic care programs. The need for health professionals to be trained in the core competencies required in CDSM support has been identified. Yet there appears to be a wide gap between health professionals' understanding of CDSM and the wider concerns and realities of patients. Whereas health professionals identify self-management primarily as structured patient education, patients identify self-management as a process initiated to bring about order in their lives that involves recognizing and monitoring the boundaries, mobilizing resources, managing the shift in self-identity, and balancing, pacing, planning, and prioritizing. A seminal study identified three lines of work that people managing chronic illnesses at home must undertake: illness work, referred to as trajectory management (symptom management, diagnostic-related work, crisis prevention and management); everyday life work (house work, looking after family, paid work, eating, etc.); and biographical work (reconstruction of the patient's biography).2 These tasks may compete or conflict with medical management, especially in patients with multiple chronic conditions. Since this research, more recent studies of patients' experiences have identified further forms of work including information work, moral work, and time work. Through doing this work, many patients living with chronic illness become “experts by experience.” There is strong evidence in the literature that many physicians are unaware of the scope of work involved in CDSM, do not recognize the expertise that patients acquire, and do not provide appropriate support. These problems are hardly surprising given the lack of, or narrow (biomedical) focus on, chronic disease management in medical education. Learning about chronic disease has a low profile, and the few educational programs described have been defined by professionals within a biomedical model, the goal being primarily to influence patients' behavior so they can better control their disease and improve their health status. It is important that medical students and trainees learn about chronic disease from the patients' perspective and explore more fully their roles in supporting the many tasks of self-management. We believe that this is best done through the active involvement of patients as teachers. Examples of such initiatives in North America and the United Kingdom include longitudinal programs in which learners are mentored by an individual or family, taught by parents of children with disabilities, or learn from users of mental health services.3 Our own work, in which interprofessional workshops are designed and delivered by patients (community educators) with chronic conditions, has demonstrated the acceptability and impact of this patient-led and patient-centered model of education. These and other examples demonstrate the increasing recognition that patients and community members have important experiences that can enrich medical education at all levels, from basic education through residency and continuing professional development. However, currently these are sporadic, often single, educational experiences that rely on a small group of enthusiasts and external funding. We need to move to a systemic approach which includes institutional commitment and an infrastructure that supports and values patients as educators. If medical education is truly to address the pressing health problem of chronic disease management, it needs to embrace the concept that patients with chronic disease and their families should be partners in education so that students and trainees can learn directly from “experts by experience” about the work involved in living with and managing chronic disease. This will lead to better support for CDSM within the context of a partnership relationship between professionals and patients, and ultimately better health outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.075
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0050.004
Scholarly communication0.0120.013
Open science0.0020.009
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.306
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations16
Published2011
Admission routes1
Has abstractyes

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