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Content and Effectiveness of Web-Based Treatments for Online Behavioral Addictions: Systematic Review
Background: Very few people seek in-person treatment for online behavioral addictions including gaming and gambling or problems associated with shopping, pornography use, or social media use. Web-based treatments have the potential to address low rates of help seeking due to their convenience, acces...
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Published in: | JMIR mental health 2022-09, Vol.9 (9), p.e36662-e36662 |
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description | Background: Very few people seek in-person treatment for online behavioral addictions including gaming and gambling or problems associated with shopping, pornography use, or social media use. Web-based treatments have the potential to address low rates of help seeking due to their convenience, accessibility, and capacity to address barriers to health care access (eg, shame, stigma, cost, and access to expert care). However, web-based treatments for online behavioral addictions have not been systematically evaluated. Objective: This review aimed to systematically describe the content of web-based treatments for online behavioral addictions and describe their therapeutic effectiveness on symptom severity and consumption behavior. Methods: A database search of MEDLINE, Embase, PsycInfo, Web of Science, Cochrane Central Register of Controlled Trials, and Google Scholar was conducted in June 2022. Studies were eligible if the study design was a randomized controlled trial or a pre-post study with at least 1 web-based intervention arm for an online behavioral addiction and if the study included the use of a validated measure of problem severity, frequency, or duration of online behavior. Data on change techniques were collected to analyze intervention content, using the Gambling Intervention System of CharacTerization. Quality assessment was conducted using the Effective Public Health Practice Project Quality Assessment Tool. Results: The review included 12 studies with 15 intervention arms, comprising 7 randomized controlled trials and 5 pre-post studies. The primary focus of interventions was gaming (n=4), followed by internet use inclusive of screen time and smartphone use (n=3), gambling (n=3), and pornography (n=2). A range of different technologies were used to deliver content, including websites (n=6), email (n=2), computer software (n=2), social media messaging (n=1), smartphone app (n=1), virtual reality (n=1), and videoconferencing (n=1). Interventions contained 15 different change techniques with an average of 4 per study. The techniques most frequently administered (>30% of intervention arms) were cognitive restructuring, relapse prevention, motivational enhancement, goal setting, and social support. Assessment of study quality indicated that 7 studies met the criteria for moderate or strong global ratings, but only 8 out of 12 studies evaluated change immediately following the treatment. Across included studies, two-thirds of participants completed |
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Web-based treatments have the potential to address low rates of help seeking due to their convenience, accessibility, and capacity to address barriers to health care access (eg, shame, stigma, cost, and access to expert care). However, web-based treatments for online behavioral addictions have not been systematically evaluated. Objective: This review aimed to systematically describe the content of web-based treatments for online behavioral addictions and describe their therapeutic effectiveness on symptom severity and consumption behavior. Methods: A database search of MEDLINE, Embase, PsycInfo, Web of Science, Cochrane Central Register of Controlled Trials, and Google Scholar was conducted in June 2022. Studies were eligible if the study design was a randomized controlled trial or a pre-post study with at least 1 web-based intervention arm for an online behavioral addiction and if the study included the use of a validated measure of problem severity, frequency, or duration of online behavior. Data on change techniques were collected to analyze intervention content, using the Gambling Intervention System of CharacTerization. Quality assessment was conducted using the Effective Public Health Practice Project Quality Assessment Tool. Results: The review included 12 studies with 15 intervention arms, comprising 7 randomized controlled trials and 5 pre-post studies. The primary focus of interventions was gaming (n=4), followed by internet use inclusive of screen time and smartphone use (n=3), gambling (n=3), and pornography (n=2). A range of different technologies were used to deliver content, including websites (n=6), email (n=2), computer software (n=2), social media messaging (n=1), smartphone app (n=1), virtual reality (n=1), and videoconferencing (n=1). Interventions contained 15 different change techniques with an average of 4 per study. The techniques most frequently administered (>30% of intervention arms) were cognitive restructuring, relapse prevention, motivational enhancement, goal setting, and social support. Assessment of study quality indicated that 7 studies met the criteria for moderate or strong global ratings, but only 8 out of 12 studies evaluated change immediately following the treatment. Across included studies, two-thirds of participants completed after-treatment evaluation, and one-quarter completed follow-up evaluation. After-intervention evaluation indicated reduced severity (5/9, 56%), frequency (2/3, 67%), and duration (3/7, 43%). Follow-up evaluation indicated that 3 pre-post studies for gaming, gambling, and internet use demonstrated reduced severity, frequency, and duration of consumption. At 3-month evaluation, just 1 pre-post study indicated significant change to mental health symptoms. Conclusions: Web-based treatments for online behavioral addictions use an array of mechanisms to deliver cognitive and behavioral change techniques. Web-based treatments demonstrate promise for short-term reduction in symptoms, duration, or frequency of online addictive behaviors. However, there is limited evidence on the effectiveness of web-based treatments over the longer term due to the absence of controlled trials.</description><identifier>ISSN: 2368-7959</identifier><identifier>EISSN: 2368-7959</identifier><identifier>DOI: 10.2196/36662</identifier><identifier>PMID: 36083612</identifier><language>eng</language><publisher>Toronto: JMIR Publications</publisher><subject>Addictions ; Addictive behaviors ; Behavior ; Gambling ; Internet ; Intervention ; Mental disorders ; Mental health ; Pornography & obscenity ; Psychotherapy ; Public health ; Review ; Shopping ; Smartphones ; Social networks ; Systematic review</subject><ispartof>JMIR mental health, 2022-09, Vol.9 (9), p.e36662-e36662</ispartof><rights>2022. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Jennifer J Park, Daniel L King, Laura Wilkinson-Meyers, Simone N Rodda. Originally published in JMIR Mental Health (https://mental.jmir.org), 09.09.2022. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c364t-adddf9b66df32f6c3cb1f173fcf1b6b9eaf022f8aa5458ad1d1a847402601f043</citedby><cites>FETCH-LOGICAL-c364t-adddf9b66df32f6c3cb1f173fcf1b6b9eaf022f8aa5458ad1d1a847402601f043</cites><orcidid>0000-0001-9807-7361 ; 0000-0002-7988-4704 ; 0000-0002-1762-2581 ; 0000-0002-7973-1003</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2719576708/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2719576708?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids></links><search><creatorcontrib>Park, Jennifer J</creatorcontrib><creatorcontrib>King, Daniel L</creatorcontrib><creatorcontrib>Wilkinson-Meyers, Laura</creatorcontrib><creatorcontrib>Rodda, Simone N</creatorcontrib><title>Content and Effectiveness of Web-Based Treatments for Online Behavioral Addictions: Systematic Review</title><title>JMIR mental health</title><description>Background: Very few people seek in-person treatment for online behavioral addictions including gaming and gambling or problems associated with shopping, pornography use, or social media use. Web-based treatments have the potential to address low rates of help seeking due to their convenience, accessibility, and capacity to address barriers to health care access (eg, shame, stigma, cost, and access to expert care). However, web-based treatments for online behavioral addictions have not been systematically evaluated. Objective: This review aimed to systematically describe the content of web-based treatments for online behavioral addictions and describe their therapeutic effectiveness on symptom severity and consumption behavior. Methods: A database search of MEDLINE, Embase, PsycInfo, Web of Science, Cochrane Central Register of Controlled Trials, and Google Scholar was conducted in June 2022. Studies were eligible if the study design was a randomized controlled trial or a pre-post study with at least 1 web-based intervention arm for an online behavioral addiction and if the study included the use of a validated measure of problem severity, frequency, or duration of online behavior. Data on change techniques were collected to analyze intervention content, using the Gambling Intervention System of CharacTerization. Quality assessment was conducted using the Effective Public Health Practice Project Quality Assessment Tool. Results: The review included 12 studies with 15 intervention arms, comprising 7 randomized controlled trials and 5 pre-post studies. The primary focus of interventions was gaming (n=4), followed by internet use inclusive of screen time and smartphone use (n=3), gambling (n=3), and pornography (n=2). A range of different technologies were used to deliver content, including websites (n=6), email (n=2), computer software (n=2), social media messaging (n=1), smartphone app (n=1), virtual reality (n=1), and videoconferencing (n=1). Interventions contained 15 different change techniques with an average of 4 per study. The techniques most frequently administered (>30% of intervention arms) were cognitive restructuring, relapse prevention, motivational enhancement, goal setting, and social support. Assessment of study quality indicated that 7 studies met the criteria for moderate or strong global ratings, but only 8 out of 12 studies evaluated change immediately following the treatment. Across included studies, two-thirds of participants completed after-treatment evaluation, and one-quarter completed follow-up evaluation. After-intervention evaluation indicated reduced severity (5/9, 56%), frequency (2/3, 67%), and duration (3/7, 43%). Follow-up evaluation indicated that 3 pre-post studies for gaming, gambling, and internet use demonstrated reduced severity, frequency, and duration of consumption. At 3-month evaluation, just 1 pre-post study indicated significant change to mental health symptoms. Conclusions: Web-based treatments for online behavioral addictions use an array of mechanisms to deliver cognitive and behavioral change techniques. Web-based treatments demonstrate promise for short-term reduction in symptoms, duration, or frequency of online addictive behaviors. However, there is limited evidence on the effectiveness of web-based treatments over the longer term due to the absence of controlled trials.</description><subject>Addictions</subject><subject>Addictive behaviors</subject><subject>Behavior</subject><subject>Gambling</subject><subject>Internet</subject><subject>Intervention</subject><subject>Mental disorders</subject><subject>Mental health</subject><subject>Pornography & obscenity</subject><subject>Psychotherapy</subject><subject>Public health</subject><subject>Review</subject><subject>Shopping</subject><subject>Smartphones</subject><subject>Social networks</subject><subject>Systematic review</subject><issn>2368-7959</issn><issn>2368-7959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkt9rFDEQgIMotpz3PwRE8GU1vzbJ-iC0R9VCoaAVH0M2mbQ5dpOa7F3pf2_aK2IlDxMyXz5mkkFoTckHRgf5kUsp2Qt0zLjUnRr64eU_-yO0rnVLCKG9bou-RkdcEs0lZccINjktkBZsk8dnIYBb4h4S1IpzwL9g7E5tBY-vCthlbmDFIRd8maaYAJ_Cjd3HXOyET7yP7W5O9RP-cV8XmO0SHf4O-wh3b9CrYKcK66e4Qj-_nF1tvnUXl1_PNycXneNSLJ313odhlNIHzoJ03I00UMWDC3SU4wA2EMaCtrYXvbaeemq1UIIwSWgggq_Q-cHrs92a2xJnW-5NttE8HuRybWxpZU1gdBjEIPUoFXdCaaJHr6V0mgipgAvWXJ8PrtvdOIN3rffW5zPp80yKN-Y6783Qk2ZSTfD-SVDy7x3UxcyxOpgmmyDvqmGKMi20Eryhb_9Dt3lXUnuqB2rolVTtw1bo3YFyJddaIPwthhLzMAfmcQ74H6nGosQ</recordid><startdate>20220909</startdate><enddate>20220909</enddate><creator>Park, Jennifer J</creator><creator>King, Daniel L</creator><creator>Wilkinson-Meyers, Laura</creator><creator>Rodda, Simone N</creator><general>JMIR Publications</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88G</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M2M</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9807-7361</orcidid><orcidid>https://orcid.org/0000-0002-7988-4704</orcidid><orcidid>https://orcid.org/0000-0002-1762-2581</orcidid><orcidid>https://orcid.org/0000-0002-7973-1003</orcidid></search><sort><creationdate>20220909</creationdate><title>Content and Effectiveness of Web-Based Treatments for Online Behavioral Addictions: Systematic Review</title><author>Park, Jennifer J ; King, Daniel L ; Wilkinson-Meyers, Laura ; Rodda, Simone N</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-adddf9b66df32f6c3cb1f173fcf1b6b9eaf022f8aa5458ad1d1a847402601f043</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Addictions</topic><topic>Addictive behaviors</topic><topic>Behavior</topic><topic>Gambling</topic><topic>Internet</topic><topic>Intervention</topic><topic>Mental disorders</topic><topic>Mental health</topic><topic>Pornography & obscenity</topic><topic>Psychotherapy</topic><topic>Public health</topic><topic>Review</topic><topic>Shopping</topic><topic>Smartphones</topic><topic>Social networks</topic><topic>Systematic review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Park, Jennifer J</creatorcontrib><creatorcontrib>King, Daniel L</creatorcontrib><creatorcontrib>Wilkinson-Meyers, Laura</creatorcontrib><creatorcontrib>Rodda, Simone N</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Nursing and Allied Health Journals</collection><collection>ProQuest - Health & Medical Complete保健、医学与药学数据库</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Psychology Database (Alumni)</collection><collection>Public Health Database (Proquest)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>ProQuest Psychology Journals</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest - Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>JMIR mental health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Park, Jennifer J</au><au>King, Daniel L</au><au>Wilkinson-Meyers, Laura</au><au>Rodda, Simone N</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Content and Effectiveness of Web-Based Treatments for Online Behavioral Addictions: Systematic Review</atitle><jtitle>JMIR mental health</jtitle><date>2022-09-09</date><risdate>2022</risdate><volume>9</volume><issue>9</issue><spage>e36662</spage><epage>e36662</epage><pages>e36662-e36662</pages><issn>2368-7959</issn><eissn>2368-7959</eissn><abstract>Background: Very few people seek in-person treatment for online behavioral addictions including gaming and gambling or problems associated with shopping, pornography use, or social media use. Web-based treatments have the potential to address low rates of help seeking due to their convenience, accessibility, and capacity to address barriers to health care access (eg, shame, stigma, cost, and access to expert care). However, web-based treatments for online behavioral addictions have not been systematically evaluated. Objective: This review aimed to systematically describe the content of web-based treatments for online behavioral addictions and describe their therapeutic effectiveness on symptom severity and consumption behavior. Methods: A database search of MEDLINE, Embase, PsycInfo, Web of Science, Cochrane Central Register of Controlled Trials, and Google Scholar was conducted in June 2022. Studies were eligible if the study design was a randomized controlled trial or a pre-post study with at least 1 web-based intervention arm for an online behavioral addiction and if the study included the use of a validated measure of problem severity, frequency, or duration of online behavior. Data on change techniques were collected to analyze intervention content, using the Gambling Intervention System of CharacTerization. Quality assessment was conducted using the Effective Public Health Practice Project Quality Assessment Tool. Results: The review included 12 studies with 15 intervention arms, comprising 7 randomized controlled trials and 5 pre-post studies. The primary focus of interventions was gaming (n=4), followed by internet use inclusive of screen time and smartphone use (n=3), gambling (n=3), and pornography (n=2). A range of different technologies were used to deliver content, including websites (n=6), email (n=2), computer software (n=2), social media messaging (n=1), smartphone app (n=1), virtual reality (n=1), and videoconferencing (n=1). Interventions contained 15 different change techniques with an average of 4 per study. The techniques most frequently administered (>30% of intervention arms) were cognitive restructuring, relapse prevention, motivational enhancement, goal setting, and social support. Assessment of study quality indicated that 7 studies met the criteria for moderate or strong global ratings, but only 8 out of 12 studies evaluated change immediately following the treatment. Across included studies, two-thirds of participants completed after-treatment evaluation, and one-quarter completed follow-up evaluation. After-intervention evaluation indicated reduced severity (5/9, 56%), frequency (2/3, 67%), and duration (3/7, 43%). Follow-up evaluation indicated that 3 pre-post studies for gaming, gambling, and internet use demonstrated reduced severity, frequency, and duration of consumption. At 3-month evaluation, just 1 pre-post study indicated significant change to mental health symptoms. Conclusions: Web-based treatments for online behavioral addictions use an array of mechanisms to deliver cognitive and behavioral change techniques. Web-based treatments demonstrate promise for short-term reduction in symptoms, duration, or frequency of online addictive behaviors. However, there is limited evidence on the effectiveness of web-based treatments over the longer term due to the absence of controlled trials.</abstract><cop>Toronto</cop><pub>JMIR Publications</pub><pmid>36083612</pmid><doi>10.2196/36662</doi><orcidid>https://orcid.org/0000-0001-9807-7361</orcidid><orcidid>https://orcid.org/0000-0002-7988-4704</orcidid><orcidid>https://orcid.org/0000-0002-1762-2581</orcidid><orcidid>https://orcid.org/0000-0002-7973-1003</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Addictions Addictive behaviors Behavior Gambling Internet Intervention Mental disorders Mental health Pornography & obscenity Psychotherapy Public health Review Shopping Smartphones Social networks Systematic review |
title | Content and Effectiveness of Web-Based Treatments for Online Behavioral Addictions: Systematic Review |
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