Understanding social network support, composition, and structure among cancer caregivers.

OBJECTIVE: We examined the social network support, composition, and structure of pediatric cancer caregivers. METHODS: We used a self-report survey to collect egocentric social network data from 107 caregivers of pediatric cancer patients and calculated descriptive statistics to examine cancer-related support network composition, function, and structure. We then ran logistic regressions to examine the relationships between network characteristics and overall satisfaction with social support. RESULTS: Family members were the most common source of emotional support and logistical support, and health care providers were the most common source of informational support. Participants perceived the "most helpful" forms of support as being: (1) emotional support from family and health care providers; (2) informational support from health care providers and other cancer caregivers; and (3) logistical support from family. Overall, caregivers wished that 9.8% of their network ties had provided more support, with family members being the most common alter type to disappoint caregivers and offer less support than needed/expected. Caregivers who reported higher network disappointment (having network members who offered less support than needed/expected) were significantly less satisfied with emotional support than those with lower network disappointment (Odds Ratio = 0.18, p = 0.02), and caregivers with higher network disappointment were significantly less satisfied with logistical support compared to those with lower network disappointment (Odds Ratio = 0.14, p = 0.01). CONCLUSION: Our results show differences in the nature of social support provided by different types of network members. These findings have implications for tailoring social network interventions to improve caregiver and family outcomes.

Secure Messaging and COVID-19: A Content Analysis of Patient-Clinician Communication During the Pandemic.

Background: Coronavirus disease 2019 (COVID-19) immediately impacted patient-clinician communication, particularly in the oncology setting. Relatedly, secure messaging (SM) usage greatly increased, yet it is unknown what was discussed and whether the technology was utilized to disseminate information. Aims: This study aimed at identifying the most frequently discussed topics using SM as well as at understanding how the communication process transpired during the early stages of the pandemic. Materials and Methods: A mixed-methods design was utilized, consisting of a content analysis of more than 4,200 secure messages, aggregated into 1,454 patient-clinician discussions. Data were collected from February 2020 to May 2020. Discussions were from various oncology departments and included physicians, physician assistants, and nurses. Based on the identified categories, a thematic analysis was conducted to understand the nuances occurring within discussions. Results: Out of the 1,454 discussions, 26% (n = 373) related to COVID-19. Of the COVID-19 discussion, the most frequently coded category was "changes, adjustments, and re-arranging care" (65%, n = 241), followed by "risk for COVID-19" (24%, n = 90), "precautions inside the hospital" (18%, n = 66), and "precautions outside the hospital" (14%, n = 52). Natural language processing techniques were used to confirm the validity of the results. Thematic analysis revealed that patients were proactive in rescheduling appointments, expressed anxiety about being immunocompromised, and clinicians were uncertain about providing recommendations related to COVID-19. Conclusions: The COVID-19 outbreak revealed the need for responsive and effective public health communication. The SM can disseminate information from trusted sources, clinicians, but can be better utilized to deliver tailored information for specific patient populations.

Great minds think alike, or do they often differ? Research topic overlap and the formation of scientific teams.

Over the last century scientific research has become an increasingly collaborative endeavor. Commentators have pointed to different factors which contribute to this trend, including the specialization of science and growing need for diversity of interest and expertise areas in a scientific team. Very few studies, however, have precisely evaluated how the diversity of interest topics between researchers is related to the emergence of collaboration. Existing theoretical arguments suggest a curvilinear relationship between topic similarity and collaboration: too little similarity can complicate communication and agreement, yet too much overlap can increase competition and limit the potential for synergy. We test this idea using data on six years of publications across all disciplines at a large U.S. research university (approximately 14,300 articles, 12,500 collaborations, and 3,400 authors). Employing topic modelling and network statistical models, we analyze the relationship between topic overlap and the likelihood of coauthorship between two researchers while controlling for potential confounders. We find an inverted-U relationship in which the probability of collaboration initially increases with topic similarity, then rapidly declines after peaking at a similarity "sweet spot". Collaboration is most likely at low-to-moderate levels of topic overlap, which are substantially lower than the average self-similarity of scientists or research groups. These findings - which we replicate for different units of analysis (individuals and groups), genders of collaborators, disciplines, and collaboration types (intra- and interdisciplinary) - support the notion that researchers seek collaborators to augment their scientific and technical human capital. We discuss implications for theories of scientific collaboration and research policy.