Applying terror management theory to patients with life-threatening illness: a systematic review.

BACKGROUND: Terror management theory (TMT) posits that people manage death-related anxiety through the meaning provided by their cultural world-views and the sense of personal value provided by self-esteem. While a large body of research has supported the core propositions of TMT, little research has focused on its application to individuals with terminal illness. If TMT can help healthcare providers better understand how belief systems adapt and change in life-threatening illness, and the role they play in managing death-related anxiety, it may provide guidance on how to improve communication around treatments near the end of life. As such, we set out to review the available research articles that focus on describing the relationship between TMT and life-threatening illness. METHODS: We reviewed PubMed, PsycINFO, Google Scholar, and EMBASE through May 2022 for original research articles focused on TMT and life-threatening illness. Articles were only deemed appropriate for inclusion if direct incorporation of the principles of TMT were made in reference to a population of interest whom had life-threatening illness Results were screened by title and abstract, followed by full review of candidate articles. References were also scanned. Articles were assessed qualitatively. RESULTS: Six relevant and original research articles were published which provide varied levels of support for TMT's application in critical illness, each article detailed evidence of ideological changes consistent with what TMT would predict. Building self-esteem, enhancing the experience of life as meaningful, incorporating spirituality, engaging family members, and caring for patients at home where meaning and self-esteem can be better maintained are strategies supported by the studies and serve as starting points for further research. CONCLUSION: These articles suggest that applying TMT to life-threatening illness can help identify psychological changes that may effectively minimize the distress from dying. Limitations of this study include a heterogenous group of relevant studies and qualitative assessment.

Patient Perspectives on Communication of Individualized Survival Estimates in Heart Failure.

BACKGROUND: Despite the availability of validated risk scores for survival in heart failure (HF), individualized estimates are not typically provided directly to patients. METHODS AND RESULTS: We explored patient perspectives regarding conveyance of individualized Seattle Heart Failure Model (SHFM) survival estimates. In 2014 and 2015, 24 HF patients completed a semistructured interview at the initial offering of SHFM survival estimates (baseline) and a follow-up interview. Themes emerging from questions of interest were identified: 1) preferences for receiving estimates: patients generally wished to see their SHFM estimates (acceptors; n = 17, and ideally would have received such information early after HF "diagnosis"; 2) reactions: viewing their personalized estimates restored some control and hope for most patients and rarely increased anxiety; 3) application: some acceptors found the information to be helpful in considering future plans, but its usefulness in specific decisions was restricted owing to perceived model limitations; 4) understanding uncertainty: participants contextualized estimates through observations that uncertainty is pervasive in life; acceptors qualitatively understood the population-based nature of the estimates. CONCLUSIONS: The majority of patients valued receiving individualized prognostic survival estimates. Acceptors generally understood the nature of the information and found it to provide clarity, control, and hope rather than invoking confusion or anxiety.

Developing a patient and family research advisory panel to include people with significant disease, multimorbidity and advanced age.

Background: People who have experienced illness due to significant disease, multimorbidity and/or advanced age are high utilizers of the health care system. Yet this population has had little formal opportunity to participate in guiding the health care research agenda, and few mechanisms exist for researchers to engage this population in an efficient way. Objective: We describe the process of developing a standing patient and family advisory panel to incorporate this population's voice into research in the USA. Methods: The panel was created at the University of Colorado. Preliminary panel development consisted of a needs assessment, information gathering and participant recruitment. We collected feedback from researchers who consulted with the panel and from panel members in order to better understand the experience from the patient and family member perspective. Results: The patient and family research advisory panel consists of eight advisors who have experience with significant disease, multimorbidity and/or advanced age, two physicians and a program manager. The panel meets every other month for 2 hours with the main purpose of advising diverse researchers on health care studies. Conclusion: People with significant disease, multimorbidity and/or advanced age represent a growing demographic in the USA, and their engagement in research is essential as the model of health care delivery moves from volume to value.

Use of Risk Models to Predict Death in the Next Year Among Individual Ambulatory Patients With Heart Failure.

Importance: The clinical practice guidelines for heart failure recommend the use of validated risk models to estimate prognosis. Understanding how well models identify individuals who will die in the next year informs decision making for advanced treatments and hospice. Objective: To quantify how risk models calculated in routine practice estimate more than 50% 1-year mortality among ambulatory patients with heart failure who die in the subsequent year. Design, Setting, and Participants: Ambulatory adults with heart failure from 3 integrated health systems were enrolled between 2005 and 2008. The probability of death was estimated using the Seattle Heart Failure Model (SHFM) and the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk calculator. Baseline covariates were collected from electronic health records. Missing covariates were imputed. Estimated mortality was compared with actual mortality at both population and individual levels. Main Outcomes and Measures: One-year mortality. Results: Among 10 930 patients with heart failure, the median age was 77 years, and 48.0% of these patients were female. In the year after study enrollment, 1661 patients died (15.9% by life-table analysis). At the population level, 1-year predicted mortality among the cohort was 9.7% for the SHFM (C statistic of 0.66) and 17.5% for the MAGGIC risk calculator (C statistic of 0.69). At the individual level, the SHFM predicted a more than 50% probability of dying in the next year for 8 of the 1661 patients who died (sensitivity for 1-year death was 0.5%) and for 5 patients who lived at least a year (positive predictive value, 61.5%). The MAGGIC risk calculator predicted a more than 50% probability of dying in the next year for 52 of the 1661 patients who died (sensitivity, 3.1%) and for 63 patients who lived at least a year (positive predictive value, 45.2%). Conversely, the SHFM estimated that 8496 patients (77.8%) had a less than 15% probability of dying at 1 year, yet this lower-risk end of the score range captured nearly two-thirds of deaths (n = 997); similarly, the MAGGIC risk calculator estimated a probability of dying of less than 25% for the majority of patients who died at 1 year (n = 914). Conclusions and Relevance: Although heart failure risk models perform reasonably well at the population level, they do not reliably predict which individual patients will die in the next year.