Codesign of a cardiovascular disease prevention text message bank for older adults.

OBJECTIVE: Develop and validate a text message bank to support healthier lifestyle behaviors in older adults at risk for cardiovascular disease utilizing a codesign approach. METHODS: Initially, the researchers, based on literature, developed a bank of 68 SMS text messages focusing on healthy eating (24 messages), physical activity (24 messages), and motivational feedback (20 messages), based on a scoping review of the literature on promoting behavioral change to engage in healthy lifestyle behaviors. In the next step, a panel of five experts analyzed every subset of SMS text messages. Further validation was conducted by nine older adults (≥ 60 years). The user demographics, telephone literacy, understanding, and appeal for every SMS text message were evaluated using a 31-item questionnaire. RESULTS: Participants provided an acceptable understanding of the critical concept found in the 49 SMS text message (physical activity M = 1.73 ± 0.18; diet M = 1.73 ± 0.26; motivation M = 1.85 ± 0.25; range 0-2). The average ratings for physical activity (i.e., likability), healthy eating, and motivation were 8.62 ± 0.64, 8.57 ± 0.76, and 8.40 ± 0.83, respectively (range 0-10). CONCLUSION: Co-designers were able to identify the technological and content requirements for each text message and infographic to enhance understanding and appeal. PRACTICE IMPLICATIONS: A feasibility study will need to be conducted as a next step to testing the effectiveness of text messages in a mobile-based intervention to promote healthy behaviors in older adults at high CVD risk.

Data discovery with DATS: exemplar adoptions and lessons learned.

The DAta Tag Suite (DATS) is a model supporting dataset description, indexing, and discovery. It is available as an annotated serialization with schema.org, a vocabulary used by major search engines, thus making the datasets discoverable on the web. DATS underlies DataMed, the National Institutes of Health Big Data to Knowledge Data Discovery Index prototype, which aims to provide a "PubMed for datasets." The experience gained while indexing a heterogeneous range of >60 repositories in DataMed helped in evaluating DATS's entities, attributes, and scope. In this work, 3 additional exemplary and diverse data sources were mapped to DATS by their representatives or experts, offering a deep scan of DATS fitness against a new set of existing data. The procedure, including feedback from users and implementers, resulted in DATS implementation guidelines and best practices, and identification of a path for evolving and optimizing the model. Finally, the work exposed additional needs when defining datasets for indexing, especially in the context of clinical and observational information.