A New Description of a Healthcare Professional’s Resilience, Incorporating an Eastern Philosophical Perspectives of Self-definition. How to Bridge the Gap between Independent and Interdependent Self-definition in Medical Education
Bibliographic record
Abstract
Teaching about resilience is one of the biggest challenges in medical education. One of the problems is that medical educators might still ascribe to the individualistic self-definition mainly promoted in the North American society. This definition includes characteristics such as “enduring ongoing hardship,” “thriving on challenges,” “being healthy,” and “being stronger,” which may raise hidden expectations that a healthcare professional’s personality should be strong enough to bounce back to his or her original condition even in a psychologically demanding situation. Psychological theorists describe two broad modes of self-definition in two different cultures: independent self-definition in North American individualism and interdependent self-definition in East Asian collectivism. Despite this seemingly stereotypical discussion on the characteristics of self-definition, a discussion of the two types of self-definition can still encourage medical educators to propose a broader model of resilience in medical education. More specifically, a person using an independent self-definition may become be a complete, whole, autonomous entity, without others, and thus tends to achieve more and become more productive in a competitive society. In contrast, a person using an interdependent self-definition is more likely to be open to another aspect of the context and thus might be able to find and value the self in different ways even in the same context. However, these two self-definitions may not be dichotomous or mutually exclusive but occur in varying ratios in any one individual, particularly as trends of increased globalization, immigration, and technology call for changes in an individual’s value systems in countries. From this standpoint, this review proposes a new definition of resilience in medical education, which is ‘a person’s capacity to be aware of the aspects of the self differently identified in each context, and to consciously value oneself and others in the context’. This is the first article that incorporates the concept of the two self-definitions into resilience education in healthcare. The proposed definition may provide a broader model of resilience in a healthcare professional for educators as well as trainees in medical education.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".