5/2/2023 0 Comments Reddit painaWe also report factors that impact self-induced addiction recovery and relapse. The paper describes how observable variables can be extracted from social media and then be used to model important latent constructs that impact addiction recovery and relapse. Moreover, geography, especially life in rural areas, appears to have a greater correlation with addiction relapse. We also determined that lack of social activities and physical exercise can enable a relapse. Furthermore, within the context of self-development activities, those that were related to influencing the mental and physical well-being of substance users were found to be positively associated with addiction recovery. Self-development activities and social relationships of the substance users were also found to enable recovery. We found that both emotional distress and physical pain significantly influence addiction recovery behavior. We then employed a statistical analysis technique called structural equation modeling to assess the effects of these latent factors on recovery and relapse. Based on social media posts of users engaged in substance use and recovery on the forum Reddit, we employed two psycholinguistic tools, Linguistic Inquiry and Word Count and Empath and activities of substance users on various Reddit sub-forums to analyze behavior underlining addiction recovery and relapse. Unfortunately, many of these factors are not directly observable and quantifying, and assessing their impact can be difficult. In particular emotional distress, physical pain, relationships, and self-development efforts are known to be some of the factors associated with addiction recovery. Several context-specific reasons influence drug use and recovery. We discuss our findings with regards to the opportunity, but also risk, that online group membership poses for recovering opioid addicts, as well as the possible contribution that computational social science methods can make to the study of addiction and recovery.Īddiction to drugs and alcohol constitutes one of the significant factors underlying the decline in life expectancy in the US. We find that multiple group membership – in terms of the number of other forums that a subject had posted in - as well as active participation - in terms of how evenly their posts were spread amongst the different forums - reduced the risk of relapse. We applied our analysis to a dataset of 457 recovering opioid addicts that self-announced the date of their recovery, indicating that at least 219 (48%) addicts relapsed during the recovery period. We then model recovery from addiction by applying the extended Cox regression model which accounts for the effect of these two factors on time to relapse. In this work, we study the effects of two main social factors on recovery success: first, multiple group membership defined in terms of richness of online community engagement second, active participation operationalized as the evenness in engagement with these groups. With the help of computational approaches, we now have access to new resources to study whether a wide variety of different online communities can be part of the addiction recovery journey. The Social Identity Model of Recovery (SIMOR) suggests that addiction recovery is a journey through time where membership in various groups facilitates success. Using unfiltered drug-related posts, our research delineates drugs that are associated with higher rates of transitions from recreational drug discussion to support/recovery discussion, offers insight into modern drug culture, and provides tools with potential applications in combating the opioid crisis. In doing so, we found that utterances of select drugs and certain linguistic features contained in one's posts can help predict these transitions. We also proposed a Cox regression model that outputs likelihoods of such transitions. Specifically, using users' posts, we trained a binary classifier which predicts a user's transitions from casual drug discussion forums to drug recovery forums. In this work, we obtained data from Reddit, an online collection of forums, to gather insight into drug use/misuse using text snippets from users narratives. Increasing rates of opioid drug abuse and heightened prevalence of online support communities underscore the necessity of employing data mining techniques to better understand drug addiction using these rapidly developing online resources.
0 Comments
Leave a Reply. |