BACKGROUND: Although communication quality is associated with patient outcomes, racial disparities in communication exist, disproportionately burdening Black patients. However, most communication research focuses on verbal behaviors in predominantly White patient populations. We used a newly developed and theory-guided network analysis that examines the dynamic interplay and behavioral convergence and divergence between Black patients with cancer and their oncologists during cancer treatment discussions. METHODS: We applied a nonverbal behavioral coding system to thin slices of video recordings of Black patients and their oncologists discussing treatment. We then estimated 3 networks: 1) a temporal network to determine whether a nonverbal behavior predicts another nonverbal behavior at the next time point in an interaction, and how much each nonverbal behavior influences other nonverbal behaviors and is influenced by other nonverbal behaviors; 2) a contemporaneous network to determine whether a nonverbal behavior co-occurs with other nonverbal behaviors at the same time point in an interaction; and 3) a between-dyads network to examine the covariation between nonverbal behaviors across all dyads. RESULTS: Black patients (n = 74) and their non-Black physicians (n = 15) showed a mix of convergence and divergence in their nonverbal behaviors at the same points in time, from one time point to the next, and across dyads. Across analyses, convergence was most likely to occur when physicians matched their behaviors to their patients; especially with smiling, gaze, leaning, and laughter behaviors. CONCLUSION: Our findings reveal patterns of modifiable behaviors that can potentially inform interventions to reduce disparities in clinical communication and, in turn, treatment and mortality disparities.
BACKGROUND: Although communication quality is associated with patient outcomes, racial disparities in communication exist, disproportionately burdening Black patients. However, most communication research focuses on verbal behaviors in predominantly White patient populations. We used a newly developed and theory-guided network analysis that examines the dynamic interplay and behavioral convergence and divergence between Black patients with cancer and their oncologists during cancer treatment discussions. METHODS: We applied a nonverbal behavioral coding system to thin slices of video recordings of Black patients and their oncologists discussing treatment. We then estimated 3 networks: 1) a temporal network to determine whether a nonverbal behavior predicts another nonverbal behavior at the next time point in an interaction, and how much each nonverbal behavior influences other nonverbal behaviors and is influenced by other nonverbal behaviors; 2) a contemporaneous network to determine whether a nonverbal behavior co-occurs with other nonverbal behaviors at the same time point in an interaction; and 3) a between-dyads network to examine the covariation between nonverbal behaviors across all dyads. RESULTS: Black patients (n = 74) and their non-Black physicians (n = 15) showed a mix of convergence and divergence in their nonverbal behaviors at the same points in time, from one time point to the next, and across dyads. Across analyses, convergence was most likely to occur when physicians matched their behaviors to their patients; especially with smiling, gaze, leaning, and laughter behaviors. CONCLUSION: Our findings reveal patterns of modifiable behaviors that can potentially inform interventions to reduce disparities in clinical communication and, in turn, treatment and mortality disparities.
Authors: Lauren M Hamel; Robert Moulder; Fabian T Ramseyer; Louis A Penner; Terrance L Albrecht; Steven Boker; Susan Eggly Journal: Cancer Control Date: 2022 Jan-Dec Impact factor: 2.339
Authors: Michael S Simon; Sreejata Raychaudhuri; Lauren M Hamel; Louis A Penner; Kendra L Schwartz; Felicity W K Harper; Hayley S Thompson; Jason C Booza; Michele Cote; Ann G Schwartz; Susan Eggly Journal: Front Oncol Date: 2021-07-07 Impact factor: 6.244