RESUMO
Background: different studies revealed strong correlation between smoking cessation and a worsening of the diet, whose consequence include loss of appetite, weight loss, etc. Objective: the objective of FoodRec project is to exploit technology to monitor the dietary habits of people during their smoke quitting process, catching relevant changes which can affect the patient health and the success of the process. This work was an uncontrolled pre-test post-test open pilot study in which an interdisciplinary group created an app for food recognition (FoodRec) to monitor their mood status and dietary habits during the test period. Methods: participants used the FoodRec App for two consecutive weeks for usability and suitability assessment. Tests included 149 smokers involved in a smoke quitting process, aged between 19 and 80. For the quantitative test, data were analyzed regarding users features, meals uploads, mood states and drink intakes. For the qualitative test, a user evaluation test of the app has been performed with four assignments being carried out on a group of 50 participants. Results: the App was perceived as extremely user-friendly and lightweight. It also turned out to be useful in the perception of users' dietary habits and helpful in relieving the stress of a food intake reduction process. Conclusion: this work investigated the role and impact of the FoodRec App in a large international and multicultural context. The experience gained in the current study will be used to modify and refine the large international RCT protocol version of the app.
RESUMO
Mobile health technologies are being developed for personal lifestyle and medical healthcare support, of which a growing number are designed to assist smokers to quit. The potential impact of these technologies in the fight against smoking addiction and on improving quitting rates must be systematically evaluated. The aim of this report is to identify and appraise the most promising smoking detection and quitting technologies (e.g., smartphone apps, wearable devices) supporting smoking reduction or quitting programs. We searched PubMed and Scopus databases (2008-2019) for studies on mobile health technologies developed to assist smokers to quit using a combination of Medical Subject Headings topics and free text terms. A Google search was also performed to retrieve the most relevant smartphone apps for quitting smoking, considering the average user's rating and the ranking computed by the search engine algorithms. All included studies were evaluated using consolidated criteria for reporting qualitative research, such as applied methodologies and the performed evaluation protocol. Main outcome measures were usability and effectiveness of smoking detection and quitting technologies supporting smoking reduction or quitting programs. Our search identified 32 smoking detection and quitting technologies (12 smoking detection systems and 20 smoking quitting smartphone apps). Most of the existing apps for quitting smoking require the users to register every smoking event. Moreover, only a restricted group of them have been scientifically evaluated. The works supported by documented experimental evaluation show very high detection scores, however the experimental protocols usually lack in variability (e.g., only right-hand patients, not natural sequence of gestures) and have been conducted with limited numbers of patients as well as under constrained settings quite far from real-life use scenarios. Several recent scientific works show very promising results but, at the same time, present obstacles for the application on real-life daily scenarios.