Child-computer interaction, ubiquitous technologies, and big data

In this forum we celebrate research that helps to successfully bring the benefits of computing technologies to children, older adults, people with disabilities, and other populations that are often ignored in the design of mass-marketed products. The children’s technology landscape is changing quickly. The ubiquity of interactive technologies means children can access them just about anytime, anywhere. At the same time, these technologies constantly collect data from and about children, bringing them into the age of big data, voluntarily or not. These developments have the potential to significantly change children’s relationship to technology and the long-term impact of technology use. To discuss these changes, the child-computer-interaction community held a special interest group (SIG) meeting during the CHI 2018 conference

What can the language of musicians tell us about music interaction design?

It is difficult to create good interaction designs for music software or to substantially improve existing designs. One reason is that music involves diverse and complex concepts, entities, relationships, processes, terminologies, and notations. An open challenge for interaction designers is to find systematic ways of channeling the tacit, specialized knowledge of musicians into designs for intuitive user interfaces that can capably support musically skilled users, without excluding those with less technical musical knowledge. One promising new approach to this challenge involves the application of research from the theory of image schemas and conceptual metaphors This theory has already been applied with some success to analyzing musical concepts, mathematical concepts, general-purpose user-interface design, and sound-generation interaction designs involving simple musical parameters such as tempo, volume, and pitch. We propose that by identifying the conceptual metaphors and image schemas used by musical experts when analyzing an excerpt of music, and then assessing the extent to which these conceptual metaphors are supported by existing music-interaction designs, it is possible to identify areas where the designs do not match musicians’ understanding of the domain concepts. This process provides a principled basis for identifying points at which designs could be improved to better support musicians’ understanding and tasks, and for the provisional identification of possible improvements. We present the results of an analysis of dialogue between three musicians as they discuss an excerpt of music. A methodology for the systematic identification of image schemas and conceptual metaphors is detailed. We report on the use of the results of the dialogue analysis to illuminate the designs of two contrasting examples of music software. Areas in which the designs might be made more intuitive are identified, and corresponding suggestions for improvements are outlined. The present research appears to be the first to investigate the potential of conceptual metaphor theory for investigating and improving music-interaction designs that deal with complex musical concepts, such as harmonic progressions, modulation, and voice leading

Disclosure of Maternal HIV Status to Children: To Tell or Not To Tell . . . That Is the Question

HIV-infected mothers face the challenging decision of whether to disclose their serostatus to their children. From the perspective of both mother and child, we explored the process of disclosure, providing descriptive information and examining the relationships among disclosure, demographic variables, and child adjustment. Participants were 23 mothers and one of their noninfected children (9 to 16 years of age). Sixty-one percent of mothers disclosed. Consistent with previous research, disclosure was not related to child functioning. However, children sworn to secrecy demonstrated lower social competence and more externalizing problems. Differential disclosure, which occurred in one-third of the families, was associated with higher levels of depressive and anxiety symptoms. Finally, knowing more than mothers had themselves disclosed was related to child maladjustment across multiple domains. Clinical implications and the need for future research are considered

Renegotiation and Relative Performance Evaluation: Why an Informative Signal may be Useless

Although Holmström's informativeness criterion provides a theoretical foundation for the controllability principle and inter firm relative performance evaluation, empirical and field studies provide only weak evidence on such practices. This paper refines the traditional informativeness criterion by abandoning the conventional full-commitment assumption. With the possibility of renegotiation, a signal's usefulness in incentive contracting depends on its information quality, not simply on whether the signal is informative. This paper derives conditions for determining when a signal is useless and when it is useful. In particular, these conditions will be met when the signal's information quality is either sufficiently poor or sufficiently rich

Using AgMIP Regional Integrated Assessment Methods to Evaluate Vulnerability, Resilience and Adaptive Capacity for Climate Smart Agricultural Systems

The predicted effects of climate change call for a multi-dimensional method to assess the performance of various agricultural systems across economic, environmental and social dimensions. Climate smart agriculture (CSA) recognizes that the three goals of climate adaptation, mitigation and resilience must be integrated into the framework of a sustainable agricultural system. However, current methods to determine a systems’ ability to achieve CSA goals are lacking. This paper presents a new simulation-based method based on the Regional Integrated Assessment (RIA) methods developed by the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for climate impact assessment. This method combines available data, field- and stakeholder-based surveys, biophysical and economic models, and future climate and socio-economic scenarios. It features an integrated farm and household approach and accounts for heterogeneity across biophysical and socioeconomic variables as well as temporal variability of climate indicators. This method allows for assessment of the technologies and practices of an agricultural system to achieve the three goals of CSA. The case study of a mixed crop livestock system in western Zimbabwe is highlighted as a typical smallholder agricultural systems in Africa

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregn, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments

Effect of Computer-Assisted Cognitive Behavior Therapy vs Usual Care on Depression Among Adults in Primary Care: A Randomized Clinical Trial

Importance Depression is a common disorder that may go untreated or receive suboptimal care in primary care settings. Computer-assisted cognitive behavior therapy (CCBT) has been proposed as a method for improving access to effective psychotherapy, reducing cost, and increasing the convenience and efficiency of treatment for depression. Objectives To evaluate whether clinician-supported CCBT is more effective than treatment as usual (TAU) in primary care patients with depression and to examine the feasibility and implementation of CCBT in a primary care population with substantial numbers of patients with low income, limited internet access, and low levels of educational attainment. Design, Setting, and Participants This randomized clinical trial included adult primary care patients from clinical practices at the University of Louisville who scored 10 or greater on the Patient Health Questionnaire–9 (PHQ-9) and were randomly assigned to CCBT or TAU for 12 weeks of active treatment. Follow-up assessments were conducted 3 and 6 months after treatment completion. Enrollment occurred from June 24, 2016, to May 13, 2019. The last follow-up assessment was conducted on January 30, 2020. Interventions CCBT included use of the 9-lesson computer program Good Days Ahead, along with as many as 12 weekly telephonic support sessions of approximately 20 minutes with a master’s level therapist, in addition to TAU, which consisted of the standard clinical management procedures at the primary care sites. TAU was uncontrolled, but use of antidepressants and psychotherapy other than CCBT was recorded. Main Outcomes and Measures The primary outcome measure (PHQ-9) and secondary outcome measures (Automatic Thoughts Questionnaire for negative cognitions, Generalized Anxiety Disorder–7, and the Satisfaction with Life Scale for quality of life) were administered at baseline, 12 weeks, and 3 and 6 months after treatment completion. Satisfaction with treatment was assessed with the Client Satisfaction Questionnaire–8. Results The sample of 175 patients was predominately female (147 of 174 [84.5%]) and had a high proportion of individuals who identified as racial and ethnic minority groups (African American, 44 of 162 patients who reported [27.2%]; American Indian or Alaska Native, 2 [1.2%]; Hispanic, 4 [2.5%]; multiracial, 14 [8.6%]). An annual income of less than $30 000 was reported by 88 of 143 patients (61.5%). Overall, 95 patients (54.3%) were randomly assigned to CCBT and 80 (45.7%) to TAU. Dropout rates were 22.1% for CCBT (21 patients) and 30.0% for TAU (24 patients). An intent-to-treat analysis found that CCBT led to significantly greater improvement in PHQ-9 scores than TAU at posttreatment (mean difference, −2.5; 95% CI, −4.5 to −0.8; P = .005) and 3 month (mean difference, −2.3; 95% CI, −4.5 to −0.8; P = .006) and 6 month (mean difference, −3.2; 95% CI, −4.5 to −0.8; P = .007) follow-up points. Posttreatment response and remission rates were also significantly higher for CCBT (response, 58.4% [95% CI, 46.4-70.4%]; remission, 27.3% [95% CI, 16.4%-38.2%]) than TAU (response, 33.1% [95% CI, 20.7%-45.5%]; remission, 12.0% [95% CI, 3.3%- 20.7%]). Conclusions and Relevance In this randomized clinical trial, CCBT was found to have significantly greater effects on depressive symptoms than TAU in primary care patients with depression. Because the study population included people with lower income and lack of internet access who typically have been underrepresented or not included in earlier investigations of CCBT, results suggest that this form of treatment can be acceptable and useful in diverse primary care settings. Additional studies with larger samples are needed to address implementation procedures that could enhance the effectiveness of CCBT and to examine potential factors associated with treatment outcome