Virtual Organizing: Using Threads to Coordinate Distributed Work

This paper explores the critical role of conversational threads in facilitating the ongoing, distributed work of one virtual organization. In studying the electronic mail exchanges of organizational members during one year, we found that they engaged in a range of threading activity to establish and maintain continuity, coherence, and coordination in their collaborative work over time. In particular, we found that organizational members relied on simple threads to focus their attention and action on a particular topic over a short period of time, concurrent threads to enable their participation in multiple topics at the same time, and compound threads to allow provisional settlement of key issues that were subsequently revisited over extended periods of time. We conclude by discussing the implications of conversational threads for research and practice of virtual organizin

Conversational Coherence in Instant Messaging and Getting Work Done

This paper explores the critical role conversational coherence plays in facilitating the ongoing, distributed work of one virtual team as they engage in instant messaging (IM) conversations to communicate, coordinate, and collaborate. In studying the IM conversations of team members over the course of a month, a number of challenges to coherence emerged as they communicated with each other and worked together. These challenges include two previously identified challenges—lack of simultaneous feedback, and disrupted turn adjacency—and two additional challenges: multi-tasking, and authority. We describe the team’s responses to these challenges and conclude by discussing implications for research

Do Some Business Models Perform Better than Others?

This paper defines four basic business models based on what asset rights are sold (Creators, Distributors, Landlords and Brokers) and four variations of each based on what type of assets are involved (Financial, Physical, Intangible, and Human). Using this framework, we classified the business models of all 10,970 publicly traded firms in the US economy from 1998 through 2002. Some of these classifications were done manually, based on the firms' descriptions of sources of revenue in their financial reports; the rest were done automatically by a rule-based system using the same data. Based on this analysis, we first document important stylized facts about the distribution of business models in the U.S. economy. Then we analyze the firms' financial performance in three categories: market value, profitability, and operating efficiency. We find that no model outperforms others on all dimensions. Surprisingly, however, we find that some models do, indeed, have better financial performance than others. For instance, Physical Creators (which we call Manufacturers) and Physical Landlords have greater cash flow on assets, and Intellectual Landlords have poorer q's, than Physical Distributors (Wholesaler/Retailers). These findings are robust to a large number of robustness checks and alternative interpretations. We conclude with some hypotheses to explain our findings.business models; performance

Do Some Business Models Perform Better than Others?

This paper defines four basic business models based on what asset rights are sold (Creators, Distributors, Landlords and Brokers) and four variations of each based on what type of assets are involved (Financial, Physical, Intangible, and Human). Using this framework, we classified the business models of all 10,970 publicly traded firms in the US economy from 1998 through 2002. Some of these classifications were done manually, based on the firms' descriptions of sources of revenue in their financial reports; the rest were done automatically by a rule-based system using the same data. Based on this analysis, we first document important stylized facts about the distribution of business models in the U.S. economy. Then we analyze the firms' financial performance in three categories: market value, profitability, and operating efficiency. We find that no model outperforms others on all dimensions. Surprisingly, however, we find that some models do, indeed, have better financial performance than others. For instance, Physical Creators (which we call Manufacturers) and Physical Landlords have greater cash flow on assets, and Intellectual Landlords have poorer q's, than Physical Distributors (Wholesaler/Retailers). These findings are robust to a large number of robustness checks and alternative interpretations. We conclude with some hypotheses to explain our findings.business models; performance

Do Some Business Models Perform Better than Others?

This paper defines four basic business models based on what asset rights are sold (Creators, Distributors, Landlords and Brokers) and four variations of each based on what type of assets are involved (Financial, Physical, Intangible, and Human). Using this framework, we classified the business models of all 10,970 publicly traded firms in the US economy from 1998 through 2002. Some of these classifications were done manually, based on the firms' descriptions of sources of revenue in their financial reports; the rest were done automatically by a rule-based system using the same data. Based on this analysis, we first document important stylized facts about the distribution of business models in the U.S. economy. Then we analyze the firms' financial performance in three categories: market value, profitability, and operating efficiency. We find that no model outperforms others on all dimensions. Surprisingly, however, we find that some models do, indeed, have better financial performance than others. For instance, Physical Creators (which we call Manufacturers) and Physical Landlords have greater cash flow on assets, and Intellectual Landlords have poorer q's, than Physical Distributors (Wholesaler/Retailers). These findings are robust to a large number of robustness checks and alternative interpretations. We conclude with some hypotheses to explain our findings

Optimizing the use of continuous glucose monitoring in young children with type 1 diabetes with an adaptive study design and multiple randomizations

Parents of young children with type 1 diabetes (T1D) experience unique, developmental challenges in managing their child's T1D, resulting in psychosocial distress. Only a small portion of young children reach glucose goals and adherence to diabetes devices that help improve T1D management have historically been low in this population. The purpose of this study is to test four interventions that couple developmentally tailored behavioral supports with education to optimize use of diabetes devices, improve glucose control, and reduce psychosocial distress for parents of young children with T1D. The study team designed four behavioral interventions, two aimed at improving glucose control and two aimed at optimizing use of diabetes devices. The goal of this paper is to describe the behavioral interventions developed for this study, including the results of a pilot test, and describe the methods and analysis plan to test this intervention strategy with ninety participants in a large-scale, randomized trial using a sequential multiple assignment randomization trial (SMART) design. A SMART design will permit a clinically relevant evaluation of the intervention strategy, as it allows multiple randomizations based on individualized assessments throughout the study instead of a fixed intervention dose seen in most traditional randomized controlled trials

Nighttime is the worst time: Parental fear of hypoglycemia in young children with type 1 diabetes

BACKGROUND: Fear of hypoglycemia is common in parents of young children with type 1 diabetes (T1D), but little is known about the specific fears that parents most often experience. Hypoglycemia fear has been associated with poorer glycemic control in older children, though not yet studied in a large cohort of very young children. MATERIALS AND METHODS: Parents of 549 children <7 years (mean 5.2 ± 1.2 years [19% <3 years]) with a mean diabetes duration of 2.4 ± 1.0 years (range 1-6 years) and mean HbA1c 8.2% ± 1.1% (66 ± 12 mmol/mol) registered in the T1D Exchange completed the worry scale of the Hypoglycemia Fear Survey modified for parents (HFS-P). RESULTS: Mean parental fear of hypoglycemia worry score was 36.1 ± 23.1 (possible range 0-100), with most frequent worries related to the child having a low while asleep and the child not recognizing a low. The mean worry score was not associated with the child's age, glycemic control, or recent severe hypoglycemic event. Parental worries about lows while sleeping were significantly higher in pump users than non-users (61% vs. 45%; P < .001), and tended to be higher in CGM users than non-users (62% vs 51%; P = .02). CONCLUSIONS: The greatest worries of parents of young children with T1D were related to hypoglycemia during sleep and other times/circumstances during which it would be difficult to detect hypoglycemia. Using advanced diabetes technologies may be an effort to temper fears about hypoglycemia during sleep, though the directionality of this relationship is undetermined. Additional studies can clarify this association and leverage use of diabetes technologies to improve glycemic control

Maternal psychological distress in primary care and association with child behavioural outcomes at age three

Observational studies indicate children whose mothers have poor mental health are at increased risk of socio-emotional behavioural difficulties, but it is unknown whether these outcomes vary by the mothers’ mental health recognition and treatment status. To examine this question, we analysed linked longitudinal primary care and research data from 1078 women enrolled in the Born in Bradford cohort. A latent class analysis of treatment status and self-reported distress broadly categorised women as (a) not having a common mental disorder (CMD) that persisted through pregnancy and the first 2 years after delivery (N = 756, 70.1 %), (b) treated for CMD (N = 67, 6.2 %), or (c) untreated (N = 255, 23.7 %). Compared to children of mothers without CMD, 3-year-old children with mothers classified as having untreated CMD had higher standardised factor scores on the Strengths and Difficulties Questionnaire (d = 0.32), as did children with mothers classified as having treated CMD (d = 0.27). Results were only slightly attenuated in adjusted analyses. Children of mothers with CMD may be at risk for socio-emotional and behavioural difficulties. The development of effective treatments for CMD needs to be balanced by greater attempts to identify and treat women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00787-015-0777-2) contains supplementary material, which is available to authorized users

Peripheral immune circadian variation, synchronisation and possible dysrhythmia in established type 1 diabetes

Aims/hypothesis: The circadian clock influences both diabetes and immunity. Our goal in this study was to characterise more thoroughly the circadian patterns of immune cell populations and cytokines that are particularly relevant to the immune pathology of type 1 diabetes and thus fill in a current gap in our understanding of this disease. Methods: Ten individuals with established type 1 diabetes (mean disease duration 11 years, age 18-40 years, six female) participated in a circadian sampling protocol, each providing six blood samples over a 24 h period. Results: Daily ranges of population frequencies were sometimes large and possibly clinically significant. Several immune populations, such as dendritic cells, CD4 and CD8 T cells and their effector memory subpopulations, CD4 regulatory T cells, B cells and cytokine IL-6, exhibited statistically significant circadian rhythmicity. In a comparison with historical healthy control individuals, but using shipped samples, we observed that participants with type 1 diabetes had statistically significant phase shifts occurring in the time of peak occurrence of B cells (+4.8 h), CD4 and CD8 T cells (~ +5 h) and their naive and effector memory subsets (~ +3.3 to +4.5 h), and regulatory T cells (+4.1 h). An independent streptozotocin murine experiment confirmed the phase shifting of CD8 T cells and suggests that circadian dysrhythmia in type 1 diabetes might be an effect and not a cause of the disease. Conclusions/interpretation: Future efforts investigating this newly described aspect of type 1 diabetes in human participants are warranted. Peripheral immune populations should be measured near the same time of day in order to reduce circadian-related variation

Time spent outside of target glucose range for young children with type 1 diabetes: a continuous glucose monitor study

Aim To assess the associations between demographic and clinical characteristics and sensor glucose metrics in young children with type 1 diabetes, using masked, continuous glucose monitoring data from children aged 2 to < 8 years. Research design and methods The analysis included 143 children across 14 sites in the USA, enrolled in a separate clinical trial. Eligibility criteria were: age 2 to <8 years; type 1 diabetes duration ≥3 months; no continuous glucose monitoring use for past 30 days; and HbA1c concentration 53 to <86 mmol/mol (7.0 to <10.0%). All participants wore masked continuous glucose monitors up to 14 days. Results On average, participants spent the majority (13 h) of the day in hyperglycaemia (>10.0 mmol/l) and a median of ~1 h/day in hypoglycaemia (<3.9 mmol/l). Participants with minority race/ethnicity and higher parent education levels spent more time in target range, 3.9–10.0 mmol/l, and less time in hyperglycaemia. More time in hypoglycaemia was associated with minority race/ethnicity and younger age at diagnosis. Continuous glucose monitoring metrics were similar in pump and injection users. Conclusions Given that both hypo- and hyperglycaemia negatively impact neurocognitive development, strategies to increase time in target glucose range for young children are needed