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The Symptom Assessment and Management (SAM) program is a structured, online, nurse-supported intervention to support symptom self-management in people receiving adjuvant chemotherapy post surgery for breast or colorectal cancer.

The objective of this study was to describe the development, implementation strategy, and evaluation of the SAM system.

The development of the SAM program involved 3 phases. check details In phase 1, the web app was developed through consultation with consumers and clinicians and of the literature to ensure that the system was evidence-based and reflected the realities of receiving treatment and supporting patients through treatment. In phase 2, 7 participants recorded the severity of 6 symptoms daily over the course of 1 cycle of chemotherapy. In phase 3, 17 participants recorded their symptoms daily over the course of 3 cycles of chemotherapy. Once symptoms were recorded, participants received immediate feedback on the severity of their symptoms and self-management recommendations, which coease engagement with the system, the value of the system for people diagnosed with other tumor types and treatment regimes, and the incorporation of the system into everyday clinical practice are needed.

Tobacco use is disproportionately higher in people who smoke cannabis than in the general population, increasing the severity of dependence for cannabis use, decreasing the likelihood of successful quit attempts for both cannabis and tobacco, and increasing the risk of relapse for both substances. Opportunities to address tobacco use in people using cannabis are being missed.

This study aims to investigate the feasibility of engaging tobacco smokers who were accessing treatment for cannabis, with a tobacco-focused internet-based Healthy Lifestyle Program (iHeLP; 4 modules). It was hypothesized that iHeLP completion would be associated with decreases in tobacco use and improved quality of life (QoL) and psychological health. It was also hypothesized that iHeLP completion would be higher in those who additionally received telephone support. Given that iHeLP aimed to improve healthy lifestyle behaviors, it was also hypothesized that there would be reductions in cannabis use.

A total of 13 smokers seeking tion of 9.337 ppm of expired CO (SD 5.65). A urinalysis indicated that abstinence from cannabis was achieved by 2 participants in the iHeLP-alone group and three participants in the iHeLP plus telephone support group. Between baseline and follow-up assessments, iHeLP-alone participants reported a mean reduction in days of use of cannabis in the prior month of 6.17 days (SD 13.30). The average reduction in the number of days of cannabis use for the iHeLP plus telephone support group was also 6.17 days (SD 13.59).

Despite the small sample size, this study provides preliminary support for the use of internet-delivered, tobacco-focused interventions in tobacco smokers seeking treatment for cannabis use.

Despite the small sample size, this study provides preliminary support for the use of internet-delivered, tobacco-focused interventions in tobacco smokers seeking treatment for cannabis use.

Prior research suggests that social media-based public health campaigns are often targeted by countercampaigns.

Using reactance theory as the theoretical framework, this research characterizes the nature of public response to tobacco prevention messages disseminated via a social media-based campaign. We also examine whether agreement with the prevention messages is associated with comment tone and nature of the contribution to the overall discussion.

User comments to tobacco prevention messages, posted between April 19, 2017 and July 12, 2017, were extracted from Twitter, Facebook, and Instagram. Two coders categorized comments in terms of tone, agreement with message, nature of contribution, mentions of government agency and regulation, promotional or spam comments, and format of comment. Chi-square analyses tested associations between agreement with the message and tone of the public response and the nature of contributions to the discussions.

Of the 1242 comments received (Twitter n=1004; Facebook r.

The majority of user comments in response to a tobacco prevention campaign made healthy contributions. Our findings encourage the use of social media to promote dialogue about controversial health topics such as smoking. However, toxicity was characteristic of comments that disagreed with the health messages. Managing negative and toxic comments on social media is a crucial issue for social media-based tobacco prevention campaigns to consider.

Tuberculosis (TB) is one of the most infectious diseases that can be fatal. Its early diagnosis and treatment can significantly reduce the mortality rate. In the literature, several computer-aided diagnosis (CAD) tools have been proposed for the efficient diagnosis of TB from chest radiograph (CXR) images. However, the majority of previous studies adopted conventional handcrafted feature-based algorithms. In addition, some recent CAD tools utilized the strength of deep learning methods to further enhance diagnostic performance. Nevertheless, all these existing methods can only classify a given CXR image into binary class (either TB positive or TB negative) without providing further descriptive information.

The main objective of this study is to propose a comprehensive CAD framework for the effective diagnosis of TB by providing visual as well as descriptive information from the previous patients’ database.

To accomplish our objective, first we propose a fusion-based deep classification network for the Cion of a patient. Moreover, the retrieval results can facilitate the radiologists in subjectively validating the CAD decision.

This paper presents a comprehensive CAD framework to diagnose TB from CXR images by retrieving the relevant cases and their clinical observations from the previous patients’ database. These retrieval results assist the radiologist in making an effective diagnostic decision related to the current medical condition of a patient. Moreover, the retrieval results can facilitate the radiologists in subjectively validating the CAD decision.