Assessing decision regret in caregivers of deceased German people with cancer-A psychometric validation of the Decision Regret Scale for Caregivers.

BACKGROUND: Decisional regret during or after medical treatments is linked to significant distress. Regret affects not only patients but also caregivers having an active or passive role during decision making. The Decision Regret Scale (DRS) is a self-report measure for regret in patients after treatment decisions. However, practical and psychometrically robust instruments assessing regret in caregivers are lacking. OBJECTIVE: To develop and validate a caregiver version of the DRS (Decision Regret Scale for Caregivers [DRS-C]). DESIGN: Psychometric validation based on a web survey. SETTING AND PARTICIPANTS: 361 caregivers of deceased German people/patients with cancer. MAIN VARIABLES STUDIED: Besides structural validity and test-retest reliability, we evaluated measurement invariance accounting for gender, age and closeness of relationship, and tested hypotheses on convergent/discriminant validity. RESULTS: Forty-five per cent of all caregivers demonstrated decision regret. Confirmatory factor analyses strongly supported the unidimensional structure of the DRS-C and pointed to strict invariance. The DRS-C demonstrated very good internal consistency (α = 0.83, 95% CI [0.81, 0.86]) and test-retest reliability (ICC [A,1] = 0.73, 95% CI [0.59, 0.83]) along with sound convergent/discriminant validity. Concerning responsiveness, DRS-C scores remained stable over a 12-week period in 83.3% of all caregivers. Receiver operating characteristic analysis yielded a cut point of 43 for the identification of significant decision regret (AUC = 0.62, 95% CI [0.56, 0.68]). DISCUSSION AND CONCLUSIONS: The lack of a gold standard instrument prevented us from examining the criterion validity and determining a minimally important difference. Nevertheless, the DRS-C provides valid and reliable information regarding caregiver regret following medical decisions. Above all, it captures a crucial aspect of the treatment experience in caregivers.

Collective incentives reduce over-exploitation of social information in unconstrained human groups.

Collective dynamics emerge from countless individual decisions. Yet, we poorly understand the processes governing dynamically-interacting individuals in human collectives under realistic conditions. We present a naturalistic immersive-reality experiment where groups of participants searched for rewards in different environments, studying how individuals weigh personal and social information and how this shapes individual and collective outcomes. Capturing high-resolution visual-spatial data, behavioral analyses revealed individual-level gains-but group-level losses-of high social information use and spatial proximity in environments with concentrated (vs. distributed) resources. Incentivizing participants at the group (vs. individual) level facilitated adaptation to concentrated environments, buffering apparently excessive scrounging. To infer discrete choices from unconstrained interactions and uncover the underlying decision mechanisms, we developed an unsupervised Social Hidden Markov Decision model. Computational results showed that participants were more sensitive to social information in concentrated environments frequently switching to a social relocation state where they approach successful group members. Group-level incentives reduced participants' overall responsiveness to social information and promoted higher selectivity over time. Finally, mapping group-level spatio-temporal dynamics through time-lagged regressions revealed a collective exploration-exploitation trade-off across different timescales. Our study unravels the processes linking individual-level strategies to emerging collective dynamics, and provides tools to investigate decision-making in freely-interacting collectives.

The Inventory of Complicated Grief-A Systematic Psychometric Review and Conceptual Replication Study of the Structural Validity.

The Inventory of Complicated Grief (ICG) is a commonly used self-report measure in psycho-oncology, best supportive care, and palliative medicine. However, existing validation studies yielded conflicting results regarding the structural validity. This study provides a psychometric review and conceptual replication of the ICG latent structure to test the hypothesis that existing studies overfit unreliable sources of variance, which overshadow the unidimensionality of the ICG. All proposed latent models identified in the psychometric review were tested in a series of confirmatory and exploratory structural equation models. Specifically, at least five to six latent intercorrelated factors were necessary to reach acceptable model fit. However, a general CG factor accounted for most variance and ICG sum scores showed predictable associations with anxiety and depressive symptoms, which suggests that the ICG is essentially unidimensional. There are indications that other measures of pathological grief show similar inconsistencies. Overall, potentially emerging subfacets of the ICG should not be interpreted as distinct "symptom clusters." If time constraints are an issue as is often the case in clinical research, complicated grief may just be measured by a reduced item set without a significant loss of information or complexity.