Mental Health Pathways in Internet Support Groups

NCT ID: NCT02396472

Last Updated: 2021-02-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

6500 participants

Study Classification

INTERVENTIONAL

Study Start Date

2016-06-30

Study Completion Date

2019-08-16

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Depression Stress Anxiety

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

SINGLE_GROUP

Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

DOUBLE

Participants Outcome Assessors

Study Groups

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Order by time and topic

Volunteers from the American Cancer Society's Cancer Survivors' Network (CSN) will see some of their messages delivered using CSN's default ordering, which shows messages within a conversational thread ordered by time stamp. Conversational threads are nested within a broad topic-based forum, like breast cancer or colorectal cancer survivors.

Note that this is a within-participant trial, so that all participants participate in all arms of the trial. Messages, not people, are randomly assigned to condition.

Group Type PLACEBO_COMPARATOR

Order by time and topic

Intervention Type BEHAVIORAL

Order by information relevance

In this condition some messages will be highlighted if they match the type of content the user has previously shown interest in, by previously contributing or reading semantically similar material.

Group Type ACTIVE_COMPARATOR

Order by information relevance

Intervention Type BEHAVIORAL

Order by social relationship

In this condition some messages will be highlighted because they come from people the user has previously shown interest in, by previously reading their posts or communicating with them.

Group Type ACTIVE_COMPARATOR

Order by social relationship

Intervention Type BEHAVIORAL

Order by help giving

In this condition some messages will be highlighted because they seek help and therefore provide an opportunity for participants to provide social support to others.

Group Type ACTIVE_COMPARATOR

Order by help giving

Intervention Type BEHAVIORAL

Order by self-disclosure

In this condition some messages will be highlighted because in them the writer is self-disclosing, and they provide provide an opportunity for participants to self-disclose in return.

Group Type ACTIVE_COMPARATOR

Order by self-disclosure

Intervention Type BEHAVIORAL

Interventions

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Order by time and topic

Intervention Type BEHAVIORAL

Order by information relevance

Intervention Type BEHAVIORAL

Order by social relationship

Intervention Type BEHAVIORAL

Order by help giving

Intervention Type BEHAVIORAL

Order by self-disclosure

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* Is an existing or new registrant to the American Cancer Society's Cancer Support Network.

Exclusion Criteria

\-
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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University of Pittsburgh

OTHER

Sponsor Role collaborator

National Institute of Mental Health (NIMH)

NIH

Sponsor Role collaborator

American Cancer Society, Inc.

OTHER

Sponsor Role collaborator

Carnegie Mellon University

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Robert E Kraut, PhD

Role: PRINCIPAL_INVESTIGATOR

Carnegie Mellon University

Locations

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Carnegie Mellon University

Pittsburgh, Pennsylvania, United States

Site Status

Countries

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United States

References

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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.

Reference Type BACKGROUND
PMID: 25896033 (View on PubMed)

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.

Reference Type BACKGROUND

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.

Reference Type BACKGROUND

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;2019:344. doi: 10.1145/3290605.3300574.

Reference Type BACKGROUND
PMID: 31423493 (View on PubMed)

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;2019:31. doi: 10.1145/3290605.3300261.

Reference Type BACKGROUND
PMID: 31448374 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 31423352 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 31423492 (View on PubMed)

Related Links

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https://kraut.hciresearch.info/articles/

Robert Kraut's recent articles and book chapters

Other Identifiers

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CarnegieMU

Identifier Type: -

Identifier Source: org_study_id

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