RESUMO
BACKGROUND: The increasing use of social media and mHealth apps has generated new opportunities for health care consumers to share information about their health and well-being. Information shared through social media contains not only medical information but also valuable information about how the survivors manage disease and recovery in the context of daily life. OBJECTIVE: The objective of this study was to determine the feasibility of acquiring and modeling the topics of a major online breast cancer support forum. Breast cancer patient support forums were selected to discover the hidden, less obvious aspects of disease management and recovery. METHODS: First, manual topic categorization was performed using qualitative content analysis (QCA) of each individual forum board. Second, we requested permission from the Breastcancer.org Community for a more in-depth analysis of the postings. Topic modeling was then performed using open source software Machine Learning Language Toolkit, followed by multiple linear regression (MLR) analysis to detect highly correlated topics among the different website forums. RESULTS: QCA of the forums resulted in 20 categories of user discussion. The final topic model organized >4 million postings into 30 manageable topics. Using qualitative analysis of the topic models and statistical analysis, we grouped these 30 topics into 4 distinct clusters with similarity scores of ≥0.80; these clusters were labeled Symptoms & Diagnosis, Treatment, Financial, and Family & Friends. A clinician review confirmed the clinical significance of the topic clusters, allowing for future detection of actionable items within social media postings. To identify the most significant topics across individual forums, MLR demonstrated that 6 topics-based on the Akaike information criterion values ranging from -642.75 to -412.32-were statistically significant. CONCLUSIONS: The developed method provides an insight into the areas of interest and concern, including those not ascertainable in the clinic. Such topics included support from lay and professional caregivers and late side effects of therapy that consumers discuss in social media and may be of interest to clinicians. The developed methods and results indicate the potential of social media to inform the clinical workflow with regards to the impact of recovery on daily life.
RESUMO
Angiotensin II and angiotensin converting enzyme (ACE) inhibitors have analgesic, anticonvulsant and antidepressive effects and in some cases they can antagonize morphine. In the present study effects of angiotensin II and ACE inhibitor captopril administered intracerobroventricularily (icv) on conditioned place preference induced by morphine as well as on morphine withdrawal signs has been evaluated in rats. Icv canullas were implanted in anesthetized male rats. Rats were allowed to recover from the surgery and conditioned place preference was induced by morphine, and the time spent in morphine compartment was compared in saline, morphine, captopril and Ang II groups. Morphine withdrawal signs were compared in three other groups of rats: morphine alone, captopril+morphine and Ang II+morphine 4 days after morphine injections (three times in each day) with naloxone injection on 4th day. Results with rats conditioned place preference induced by morphine showed that icv captopril decreased significantly the time in morphine compartment (P<0.01) while Ang II had no effect. In morphine dependent rats captopril decreased some withdrawal signs after naloxone precipitation (P<0.05 and P<0.01). Ang II administration augmented some of withdrawal signs than in the morphine group (P<0.01 and P<0.001). In conclusion captopril reduced conditioned place preference induced by morphine and some withdrawal signs in morphine dependent rats.
