Citizen Science as a New Tool in Dog Cognition Research.

Family dogs and dog owners offer a potentially powerful way to conduct citizen science to answer questions about animal behavior that are difficult to answer with more conventional approaches. Here we evaluate the quality of the first data on dog cognition collected by citizen scientists using the Dognition.com website. We conducted analyses to understand if data generated by over 500 citizen scientists replicates internally and in comparison to previously published findings. Half of participants participated for free while the other half paid for access. The website provided each participant a temperament questionnaire and instructions on how to conduct a series of ten cognitive tests. Participation required internet access, a dog and some common household items. Participants could record their responses on any PC, tablet or smartphone from anywhere in the world and data were retained on servers. Results from citizen scientists and their dogs replicated a number of previously described phenomena from conventional lab-based research. There was little evidence that citizen scientists manipulated their results. To illustrate the potential uses of relatively large samples of citizen science data, we then used factor analysis to examine individual differences across the cognitive tasks. The data were best explained by multiple factors in support of the hypothesis that nonhumans, including dogs, can evolve multiple cognitive domains that vary independently. This analysis suggests that in the future, citizen scientists will generate useful datasets that test hypotheses and answer questions as a complement to conventional laboratory techniques used to study dog psychology.

Social-Cognitive Determinants of Success in Online Communities for Weight Management

Background: Online communities may be an effective, convenient, and relatively inexpensive intervention platform for individuals seeking assistance with weight management. Recent research suggests that these communities may be as effective as in-person treatments for weight management; however, very little is known about the characteristics that predict weight loss amongst those using an online community. Methods: Within a social-cognitive framework, we sought to identify the psychosocial characteristics that are associated with successful weight management for users of MyFitnessPal, a popular online community for weight management. We recruited participants who were new to the online community and asked them to complete 2 surveys (one at baseline and one 3 months later) that assessed various psychosocial constructs as well as self-reported height and weight. Results: Participants in our sample reported losing, on average, 4.55 kg during the 3-month time period. We found that engaging in weight control behaviors (e.g., monitoring food intake, weighing oneself, etc.) fully mediated the relationship between several of our variables of interest (i.e., baseline self-efficacy and perceived social support within the community) and weight loss. We also found that participants who expected to lose more weight at baseline were significantly more likely to have lost more weight at follow-up. Conclusions: On average, participants in our study lost a clinically meaningful amount of weight. Predictors of weight loss within this community included perceived support within the community (mediated by weight control behaviors), baseline self-efficacy (mediated by weight control behaviors), and baseline outcome expectations. Results of this study can ultimately serve to inform the design of future eHealth interventions for weight management.