dc.contributor.author | Koschate-Reis, M | |
dc.contributor.author | Naserian, E | |
dc.date.accessioned | 2021-02-17T13:01:22Z | |
dc.date.issued | 2021-04-30 | |
dc.description.abstract | The Social Identity Model of Recovery (SIMOR) suggests that addiction recovery is a journey through time where membership in various groups facilitates success. 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. 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. 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. 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 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 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. | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | Vol. 5 , Issue CSCW1, article 68 | en_GB |
dc.identifier.doi | 10.1145/3449142 | |
dc.identifier.grantnumber | EP/S001409/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/124777 | |
dc.language.iso | en | en_GB |
dc.publisher | Association for Computing Machinery (ACM) | en_GB |
dc.rights | © 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee
provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the
full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored.
Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires
prior specific permission and/or a fee. Request permissions from permissions@acm.org. | en_GB |
dc.subject | addiction recovery | en_GB |
dc.subject | social cure | en_GB |
dc.subject | online communities | en_GB |
dc.subject | survival analysis | en_GB |
dc.title | Do Group Memberships Online Protect Addicts in Recovery against Relapse? Testing the Social Identity Model of Recovery in the Online World | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2021-02-17T13:01:22Z | |
dc.identifier.issn | 2573-0142 | |
dc.description | This is the author accepted manuscript. The final version is available from ACM via the DOI in this record | en_GB |
dc.description | CSCW 2021: 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing, 23 - 27 October 2021. Online | en_GB |
dc.identifier.journal | Proceedings of the ACM on Human-Computer Interaction | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
pubs.funder-ackownledgement | Yes | en_GB |
exeter.funder | ::Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
rioxxterms.version | AM | en_GB |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2021-02-16T17:54:36Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2021-05-07T14:09:19Z | |
refterms.panel | A | en_GB |