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Assessment of adult psychopathology relies heavily on self-reports. To determine how well self-reports agree with reports by "informants" who know the person being assessed, the authors examined 51,000 articles published over 10 years in 52 peer-reviewed journals for correlations between self-reports and "informants" reports. Qualifying correlations were found in 108 (0.2%) of the articles. When self-reports and informant reports were obtained with parallel instruments, mean cross-informant correlations were .681 for substance use, .428 for internalizing, and .438 for externalizing problems. When based on different instruments, the mean cross-informant correlation was .304. The moderate sizes of the correlations argue for systematically obtaining multi-informant data. National survey findings were used to illustrate practical ways to obtain and use such data.

Objectives To evaluate the efficacy of an Internet behavioral weight loss program; and determine if adding periodic in-person sessions to an Internet intervention improves outcomes. Methods 481 healthy overweight adults (28% minority) were randomized to one of 3 delivery methods of a behavioral weight loss program with weekly meetings: Internet (n=160), InPerson (n=159), or Hybrid (Internet+InPerson, n=162). Outcome variables were weight at baseline and 6 months and percent of subjects achieving a 5 and 7% weight loss. The study took place in two centers in Vermont and Arkansas from 2003 to 2008. Results Conditions differed significantly in mean weight loss [8.0 (6.1)kg vs. 5.5 (5.6)kg vs. 6.0 (5.5)kg], for InPerson, Internet, and Hybrid respectively, p<0.01, n=462). Weight loss for InPerson was significantly greater than the Internet and Hybrid conditions (p<0.05). Although the proportion reaching a 5% weight loss did not differ, the proportion losing 7% did differ significantly (56.3% vs. 37.3% vs. 44.4% for InPerson, Internet, and Hybrid respectively, p<0.01). Conclusions These results demonstrate that the Internet is a viable alternative to in-person treatment for the delivery and dissemination of a behavioral weight-control intervention. The addition of periodic in-person sessions did not improve outcomes.

Background: Due to the COVID-19 pandemic, most faculty in science, technology, engineering, mathematics, and medicine (STEMM) began working from home, including many who were simultaneously caring for children. The objective was to assess associations of gender and parental status with self-reported academic productivity before (i.e., mid-January to mid-March 2020) and during the pandemic (i.e., mid-March to mid-May 2020). Materials and Methods: STEMM faculty in the United States (N = 284, 67.6% women, 57.0% with children younger than the age of 18 years living at home) completed a survey about the number of hours worked and the frequency of academic productivity activities. Results: There was no significant difference in the hours worked per week by gender (men, M [standard deviation, SD] = 45.8 [16.7], women = 43.1 [16.3]). Faculty with 0-5-year-old children reported significantly fewer work hours (33.7 [13.9]) compared to all other groups (No children = 49.2 [14.9], 6-11 years old = 48.3 [13.9], and 12-17 years old = 49.5 [13.9], p < 0.0001). Women's self-reported first/corresponding author's and coauthor's article submissions decreased significantly between the two time periods; men's productivity metrics did not change. Faculty with 0-5year-old children completed significantly fewer peer review assignments, attended fewer funding panel meetings, and submitted fewer first authors' articles during the pandemic compared to the previous period. Those with children aged 6 years or older at home or without children at home reported significant increases or stable productivity. Conclusions: Overall, significant disparities were observed in academic productivity by gender and child age during the pandemic and if confirmed by further research, should be considered by academic institutions and funding agencies when making decisions regarding funding and hiring as well as promotion and tenure.

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The objective of this study was to assess the costs associated with a group behavioral weight loss intervention and compare cost-effectiveness based on treatment delivery modality (in-person versus Internet). A randomized controlled trial examined efficacy of a group behavioral obesity intervention across in-person and Internet treatment modalities. Participants (N=323, 93% women, mean body mass index=35.8) from two centers were randomized to treatment modality, and contact time was matched between conditions. Primary outcome was weight loss. Cost-effectiveness measures calculated life years gained (LYG) from changes in weight at 6 months, based on excess years of life lost algorithm and the cost of the two modalities. In-person participants had significantly greater weight losses (−8.0±6.1 kg) than Internet participants (−5.5±5.6 kg), whereas differences in LYG were insignificant. Estimated LYG was 0.58 (95% CI: 0.45, 0.71) and 0.47 (95% CI: 0.34, 0.60) for the in-person and internet condition respectively. Total cost of conducting the In-person condition was $706 per person and the Internet condition was $372 per person with the difference mainly due to increased travel cost of $158 per person. The incremental cost effectiveness ratio was $2,160 per (discounted) LYG for the Internet modality relative to no intervention/no weight loss and $7,177 per (discounted) LYG for the in-person modality relative to the internet modality. Participant time costs are recognized as an important cost of medical and behavioral interventions. When participant time costs are included in an economic evaluation of a behavioral weight loss intervention, internet-based weight loss delivery may be a more cost-effective approach to obesity treatment.

Objectives Online weight control technologies could reduce barriers to treatment, including increased ease and convenience of self-monitoring. Self-monitoring consistently predicts outcomes in behavioral weight loss programs; however, little is known about patterns of self-monitoring associated with success. Methods The current study examines 161 participants (93% female; 31% African-American; mean BMI=35.7±5.7) randomized to a 6-month online behavioral weight control program which offered weekly group “chat” sessions and online self-monitoring. Self-monitoring log-ins were continuously monitored electronically during treatment and examined in association with weight change and demographics. Weekend and weekday log-ins were examined separately and length of periods of continuous self-monitoring were examined. Results We found that 91% of participants logged in to the self-monitoring webpage at least once. Over 6 months, these participants monitored on an average of 28% of weekdays and 17% of weekend days, with most log-ins earlier in the program. Women were less likely to log-in, and there were trends for greater self-monitoring by older participants. Race, education and marital status were not significant predictors of self-monitoring. Both weekday and weekend log-ins were significant independent predictors of weight loss. Patterns of consistent self-monitoring emerged early for participants who went on to achieve greater than a five percent weight loss. Conclusions Patterns of online self-monitoring were strongly associated with weight loss outcomes. These results suggest a specific focus on consistent self-monitoring early in a behavioral weight control program might be beneficial for achieving clinically significant weight losses.

Internet-based weight control programs have been showing promising results; however, as of yet, it is unclear which website components are critical for producing and maintaining weight loss. The aim of this study is to examine the utilization patterns of a weight control website and the relationship of the Web features to weight loss and maintenance. One hundred and twenty three (N = 123) participants took part in a 12-month behavioral weight control program over the Internet and their website utilization patterns were monitored. When examining the clustering of Web feature utilization and weight loss, the "feedback" factor (progress charts, physiological calculators, and past journals) was the best predictor of weight loss during the treatment period (baseline to 6 months), while the "social support" factor (Web chats and biographical information/e-mail addresses of participants) was the best predictor during maintenance. Weight loss in an online weight control program was related to dynamic Web features that provided feedback, support, and motivation to participants.