A Systematic Review of International Guidance for Self-Report and Proxy Completion of Child-Specific Utility Instruments

OBJECTIVES

This study aimed to identify and summarize published guidance and recommendations for child self- and proxy assessment of existing child-specific instruments of health-related quality of life (HRQoL) that are accompanied by utilities.

METHODS

A total of 9 databases plus websites of (1) health technology assessment and health economics outcomes research organizations and (2) instrument developers were systematically searched. Studies were included if they reported guidance for child self- and proxy assessment for child populations (0-18 years old). Three reviewers independently screened titles, abstracts, and full-text reviews against the inclusion criteria. Key features of the guidance identified were summarized.

RESULTS

A total of 19 studies met the inclusion criteria. In general, journal articles provided little guidance on child self- and proxy assessment, with the majority focused on instrument development and psychometric performance more broadly. Instrument developers' websites provided more guidance for child self- and proxy reports with specific guidance found for the EQ-5D-Y and the Pediatric Quality of Life Inventory. This guidance included the minimum age for self-report and mode of administration; recommended proxy types, age range of child for whom proxy report can be completed, and target population; and recall period. Websites of leading organizations provided general guidance on HRQoL evaluation in children but lacked specific guidance about self- and proxy completion.

CONCLUSIONS

EQ-5D-Y and Pediatric Quality of Life Inventory developers' websites provided the most comprehensive guidance for self-report and proxy report of their respective instruments. More evidence is required for developing best practice guidance on why, when, and how to use self- and proxy reports in assessing HRQoL in child populations.

Storage Management Strategy in Mobile Phones for Photo Crowdsensing

In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to quickly upload them to the PoIs, which are actually the edge services. In this paper, we propose a utility-based Storage Management strategy in mobile phones for Photo Crowdsensing (SMPC), which makes a sending/deleting decision on a user's device for either maximizing photo delivery ratio (SMPC-R) or minimizing average delay (SMPC-D). The decision is made according to the photo's utility, which is calculated by measuring the impact of reproducing or deleting a photo on the above performance goals. We have done simulations based on the random-waypoint model and three real traces: roma/taxi, epfl, and geolife. The results show that, compared with other storage management strategies, SMPC-R gets the highest delivery ratio and SMPC-D achieves the lowest average delay.