6 research outputs found

    Additional file 1: of Age and African-American race impact the validity and reliability of the asthma control test in persistent asthmatics

    No full text
    Table S1. Standardized asthma history obtained by study physicians at both study visits. Table S2. Correlation between baseline ACT score and spirometry measurements (as Pearson correlation coefficients). Table S3. Screening accuracy of individual ACT questions for detection of not well controlled asthma in African-American adolescents. Table S4. Screening accuracy of individual ACT questions for detection of not well controlled asthma in non-African American adolescents. Table S5. Correlations between change in ACT score and change in spirometry measurements between study visits (as Pearson correlation coefficients). (DOCX 31 kb

    Additional file 2 of The efficacy of behavioural activation treatment for co-occurring depression and substance use disorder (the activate study): a randomized controlled trial

    No full text
    “Groups overseeing the trial, insurance coverage provided by UNSW, and authorship guidelines”—This document outlines the role and composition of groups overseeing the trial, the insurance coverage provided by UNSW and the authorship guidelines that will be used for papers based on trial data (DOCX 16 kb

    Measurement properties of smartphone approaches to assess key lifestyle behaviours: protocol of a systematic review

    Get PDF
    Background: Six core behavioural risk factors (poor diet, physical activity, sedentary behaviour, alcohol misuse, smoking and unhealthy sleep patterns) have been identified as strong determinants of chronic disease, such as cardiovascular disease, diabetes and cancers. Smartphones have the potential to provide a real-time, pervasive, unobtrusive and cost-effective way to measure health behaviours and deliver instant feedback to users. Despite this, validity of using smartphones to measure these six key behaviours is largely unknown. The proposed systematic review aims to address this gap by identifying existing smartphone-based approaches to measure these health behaviours and critically appraising, comparing and summarizing the quality of their measurement properties. Methods: A systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsychINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost) and IEEE Xplore Digital Library databases will be conducted from January 2007 to March 2020. Eligible studies will be those written in English that measure at least one of the six health behaviours of interest via a smartphone and report on at least one measurement property. The primary outcomes will be validity, reliability and/or responsiveness of these measurement approaches. A secondary outcome will be the feasibility (e.g. user burden, usability and cost) of identified approaches. No restrictions will be placed on the participant population or study design. Two reviewers will independently screen studies for eligibility, extract data and assess the risk of bias. The study methodological quality (or bias) will be appraised using an appropriate tool. Our results will be described in a narrative synthesis. If feasible, random effects meta-analysis will be conducted where appropriate.Discussion: The results from this review will provide important information about the types of smartphone-based approaches currently available to measure the core behavioural risk factors for chronic disease and the quality of their measurement properties. It will allow recommendations on the most suitable and effective measures of these lifestyle behaviours using smartphones. Valid and reliable measurement of these behaviours and risk factor opens the door to targeted and real-time delivery of health behaviour interventions, providing unprecedented opportunities to offset the trajectory toward chronic disease
    corecore