Seeing the Humanity in Health Care
Bibliographic record
Abstract
The practice of medicine relies on the love of humanity. In the race for efficiency and innovation, physicians can often overlook the personal circumstances behind the data and presentation of the patient they are treating. Physicians should be focused on treating the patient, and not be driven purely by biomarkers, lab values, and cost efficiencies. When patient goals and priorities are neither valued nor sought by health practitioners, patients are more likely to suffer mental distress, especially those with chronic conditions. For example, depression and anxiety show a significant association with cardiovascular disease (CVD),[1] with an estimated 20.8% overall prevalence of depression in patients with CVD.[2] Patients with characteristics that are underrepresented in clinical studies, including those who are pregnant, of advanced age and with comorbidities, can fall through the data gaps in evidence-based care guidelines.[3,4] Person-centered care aims to treat THIS patient, not patients “like this.”[5] Health care also loses sight of the humanity of health workers. In one of the latest survey of US physicians, 45.2% of respondents reported at least one symptom of burnout compared with 62.8% in 2021 (which is likely due to the strain on the health care system caused by the COVID-19 pandemic), 38.2% in 2020, 43.9% in 2017, 54.4% in 2014, and 45.5% in 2011.[6] Burnout could pose risks to care quality, workforce stability, and patient safety. Aligning with the philosophy of Heart and Mind, HEALTH (WHO) is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity, we are pleased to present this special issue. Randall Scott Stafford witnessed the humanity exhibited by a long-term patient in the Massachusetts General Hospital Coronary Care Unit, as detailed in “Jim Kane: Cardiomyopathy, Heart Failure, and the Energizer Bunny.” Jim endured multiple cancers, received several pacemakers, survived kidney failure with a transplant from his wife, and lost his left leg. Yet, he resumed an active life. Grace E. Kim discussed physician burnout from the perspective of a former resident. In “Impact of Sleep Loss in Residency – A Reflection,” Kim indicated health workers have the second highest percentage of sleep deprivation at 45%, even though the importance of sleep hygiene is stressed during medical training. The author suggests decreasing the patient-to-resident ratio and increasing rest times between shifts. “A Systematic Review of Medication Adherence Interventions for Patients with Heart Failure” was contributed by de Tantillo et al. They searched databases including CINAHL, PubMed, and Scopus and identified relevant intervention studies (n = 40). The inclusion criteria identified articles that are original reports of intervention studies exclusively in patients diagnosed with heart failure. They suggest clinicians should incorporate a multidimensional approach when promoting adherence to medication regimens, which includes patient-related factors (e.g., knowledge), socioeconomic factors (e.g., income), therapy-related factors (e.g., side effects), health care team and health system factors (e.g., communication with health care team), and condition-related factors (e.g., cognition). Among these, additional focus should be given to the health care team and health system factors. A study by Liu et al. titled “Advances in Cardiac Telerehabilitation for Older Adults in the Digital Age: A Narrative Review” provides an overview of the importance of cardiac telerehabilitation (CTR) related to issues of safety, efficacy, cost-effectiveness, and implementation in an effort to draw attention to such programs for older adults, enhance secondary prevention, and provide a reference basis for future users. The current high number of older adults with CVD, coupled with strained and limited medical resources, creates an urgent need for multiple cardiac rehabilitation modalities. The future design of CTR programs is expected to be more refined, standardized, richer in content, and easier to operate. An article titled “How Urban Design Science Can Reduce Stress: Current Understanding and Future Prospects” by Koohsari et al. presents a comprehensive framework on how urban design attributes can affect stress by modulating physiological responses. It also discusses current gaps and future directions on this topic. The paper concludes that some urban design attributes, such as walkability and availability of green spaces, may be associated with influencing stress and mental health in urban populations. The theme of this issue encompasses a diverse range of topics – such as the intersection of mental health and other diseases, the experiences of underrepresented groups, patient-centered design in health care environment, AI-driven medicine,[7] and therapy dogs.[8] Many important topics remain unexplored in this issue. Heart and Mind looks forward to publishing additional papers on humanity in health care.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".