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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT02396472
Other study ID # CarnegieMU
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date June 2016
Est. completion date August 16, 2019

Study information

Verified date August 2019
Source Carnegie Mellon University
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

People facing serious health threats increasingly use Internet health support communities to obtain informational support, emotional support and other resources. This study introduces software algorithms similar to those used by social media sites to put people in touch with helpful information and social interactions. Participants from the American Cancer Society's Cancer Support Network will have access to this online support group using the default interface that orders content by broad content category and date or with a new interface that highlights communication content and people that match users' interests and needs.


Description:

Internet support groups (ISGs) are online communities where people come together to exchange information, emotional support and other resources. They are an important resource for patients grappling with serious medical conditions. Although participation in health-related ISGs has been associated with significant reductions in participant-reported depression, anxiety and other indicators of psychological distress, many ISG members leave too soon to benefit. In a parallel study, we are using state-of-the art machine learning and automated language analysis techniques to assess the types of interactions that keep people participating in these groups and that lead to improved psychosocial well-being and health quality of life and how these interactions develop. The clinical trial described here uses these technologies and insights from our empirical research to build, deploy, and evaluate interventions that improve the interactions in Internet health support groups. We will develop and pilot-test interventions to encourage effective communication processes identified in our empirical research. Participants from the American Cancer Society's Cancer Support Network will access this support group using either the default interface that orders content by disease diagnosis and date or with a new interface that sometimes highlights communication content and people who match their interests and needs. We will test whether mood, satisfaction with interactions and engagement in the group increase following interventions that (a) increase participants' receipt of individualized support from others; (b) provide participants with opportunities to offer support to others; (c) facilitate participants' expression of emotions; and (d) help participants form relationships with compatible peers. In a series of small, randomized experiments, we will examine how these interventions affect participants' communication behaviors as well as short-term engagement and satisfaction with their online interactions.


Recruitment information / eligibility

Status Completed
Enrollment 6500
Est. completion date August 16, 2019
Est. primary completion date August 16, 2019
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - Is an existing or new registrant to the American Cancer Society's Cancer Support Network. Exclusion Criteria: -

Study Design


Related Conditions & MeSH terms


Intervention

Behavioral:
Order by time and topic

Order by information relevance

Order by social relationship

Order by help giving

Order by self-disclosure


Locations

Country Name City State
United States Carnegie Mellon University Pittsburgh Pennsylvania

Sponsors (4)

Lead Sponsor Collaborator
Carnegie Mellon University American Cancer Society, Inc., National Institute of Mental Health (NIMH), University of Pittsburgh

Country where clinical trial is conducted

United States, 

References & Publications (7)

Vlahovic, T., Wang, Y.-C., Kraut, R. E., & Levine, J. M. (2014). Support matching and satisfaction in an online breast cancer support community. CHI'14: Proceedings of the ACM Conference on Human Factors in Computing Systems (pp. 1625-1634 ). NY: ACM.

Wang YC, Kraut RE, Levine JM. Eliciting and receiving online support: using computer-aided content analysis to examine the dynamics of online social support. J Med Internet Res. 2015 Apr 20;17(4):e99. doi: 10.2196/jmir.3558. — View Citation

Wang, Y., Kraut, R., & Levine, J. (2012). To stay or leave? the relationship of emotional and informational support to commitment in online health support groups CSCW '12 Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work (pp. 833-842). NY: ACM.

Yang D, Kraut R, Levine JM. Commitment of Newcomers and Old-timers to Online Health Support Communities. Proc SIGCHI Conf Hum Factor Comput Syst. 2017 May;2017:6363-6375. doi: 10.1145/3025453.3026008. — View Citation

Yang D, Kraut R, Smith T, Mayfield E, Jurafsky D. Seekers, Providers, Welcomers, and Storytellers: Modeling Social Roles in Online Health Communities. Proc SIGCHI Conf Hum Factor Comput Syst. 2019 May;2019. pii: 344. doi: 10.1145/3290605.3300574. — View Citation

Yang D, Yao Z, Kraut R. Self-disclosure and Channel Difference in Online Health Support Groups. Proc Int AAAI Conf Weblogs Soc Media. 2017 May;2017:704-707. — View Citation

Yang D, Yao Z, Seering J, Kraut R. The Channel Matters: Self-disclosure, Reciprocity and Social Support in Online Cancer Support Groups. Proc SIGCHI Conf Hum Factor Comput Syst. 2019 May;2019. pii: 31. doi: 10.1145/3290605.3300261. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Read message (Does the user read the message they were exposed to?) 1 day
Secondary Interaction satisfaction (Self-report measure of satisfaction 3-item survey) Self-report measure of satisfaction with a random sample of messages. This is a 3-item survey that will be delivered as a pop-up questionnaire following a random sample of the messages users were exposed to. 1 day
Secondary Reply to message (How long does it take the users to reply to a message they were exposed to, if they reply at all.) How long does it take the users to reply to a message they were exposed to, if they reply at all. 2 days
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