RESUMEN
Cigarette smoking is the leading preventable cause of death and illness in the United States. We tested the usability, acceptability, and efficacy of a smartphone-based contingency management treatment to promote cessation. We used a nonconcurrent multiple-baseline design. Participants (N = 14) provided breath carbon monoxide (CO) samples by using a CO meter that was connected to the user's smartphone. An app (mMotiv8) housed on participants' smartphones automatically captured pictures of the CO sampling procedure to validate the end user's identity, and it prompted submissions via a push message delivered to participants' smartphones. Participants earned a $10 incentive for daily abstinence, which was added to a reloadable debit card. Overall, 4% of the CO samples were negative during baseline, and 89% were negative during treatment. Self-reported usability and acceptability were high, and 85% of the prompted samples were submitted. A smartphone intervention could be scalable and reduce the health consequences and costs associated with cigarette smoking, particularly in rural and low-income populations.
Asunto(s)
Teléfono Inteligente , Cese del Hábito de Fumar , Terapia Conductista , Humanos , Motivación , FumarRESUMEN
OBJECTIVE: To synthesize data quality (DQ) dimensions and assessment methods of real-world data, especially electronic health records, through a systematic scoping review and to assess the practice of DQ assessment in the national Patient-centered Clinical Research Network (PCORnet). MATERIALS AND METHODS: We started with 3 widely cited DQ literature-2 reviews from Chan et al (2010) and Weiskopf et al (2013a) and 1 DQ framework from Kahn et al (2016)-and expanded our review systematically to cover relevant articles published up to February 2020. We extracted DQ dimensions and assessment methods from these studies, mapped their relationships, and organized a synthesized summarization of existing DQ dimensions and assessment methods. We reviewed the data checks employed by the PCORnet and mapped them to the synthesized DQ dimensions and methods. RESULTS: We analyzed a total of 3 reviews, 20 DQ frameworks, and 226 DQ studies and extracted 14 DQ dimensions and 10 assessment methods. We found that completeness, concordance, and correctness/accuracy were commonly assessed. Element presence, validity check, and conformance were commonly used DQ assessment methods and were the main focuses of the PCORnet data checks. DISCUSSION: Definitions of DQ dimensions and methods were not consistent in the literature, and the DQ assessment practice was not evenly distributed (eg, usability and ease-of-use were rarely discussed). Challenges in DQ assessments, given the complex and heterogeneous nature of real-world data, exist. CONCLUSION: The practice of DQ assessment is still limited in scope. Future work is warranted to generate understandable, executable, and reusable DQ measures.