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Objective: The need for clinical services in U.S. colleges exceeds the supply. Digital Mental health Interventions (DMHIs) are a potential solution, but successful implementation depends on stakeholder acceptance. This study investigated the relevance of DMHIs from students perspectives. Methods: In 2020-2021, an online cross-sectional survey using mixed methods was conducted with 479 students at 23 colleges and universities. Respondents reported views and use of standard mental health services and DMHIs and rated the priority of various DMHIs to be offered through campus services. Qualitative data included open-ended responses. Findings: Among respondents, 91% reported having experienced mental health problems, of which 91% reported barriers to receiving mental health services. Students highlighted therapy and counseling as desired and saw flexible access to services as important. With respect to DMHIs, respondents had the most experience with physical health apps (46%), mental health questionnaires (41%), and mental well-being apps (39%). Most were unaware of or had not used apps or self-help programs for mental health problems. Students were most likely to report the following DMHIs as high priorities: a crisis text line (76%), telehealth (66%), websites for connecting to services (62%), and text/messaging with counselors (62%). They considered a self-help program with coach support to be convenient but some also perceived such services to be possibly less effective than in-person therapy. Conclusions: Students welcome DMHIs on campus and indicate preference for mental health services that include human support. The findings, with particular focus on characteristics of the DMHIs prioritized, and students awareness and perceptions of scalable DMHIs emphasized by policymakers, should inform schools looking to implement DMHIs., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [K08 MH120341]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]

Background: Chatbots have the potential to provide cost-effective mental health prevention programs at scale and increase interactivity, ease of use, and accessibility of intervention programs. Objective: The development of chatbot prevention for eating disorders (EDs) is still in its infancy. Our aim is to present examples of and solutions to challenges in designing and refining a rule-based prevention chatbot program for EDs, targeted at adult women at risk for developing an ED. Methods: Participants were 2409 individuals who at least began to use an EDs prevention chatbot in response to social media advertising. Over 6 months, the research team reviewed up to 52,129 comments from these users to identify inappropriate responses that negatively impacted users experience and technical glitches. Problems identified by reviewers were then presented to the entire research team, who then generated possible solutions and implemented new responses. Results: The most common problem with the chatbot was a general limitation in understanding and responding appropriately to unanticipated user responses. We developed several workarounds to limit these problems while retaining some interactivity. Conclusions: Rule-based chatbots have the potential to reach large populations at low cost but are limited in understanding and responding appropriately to unanticipated user responses. They can be most effective in providing information and simple conversations. Workarounds can reduce conversation errors., Funding Agencies|National Eating Disorders Association through the Feeding Hope Fund; National Institute of Mental Health [R01 MH123482, K08 MH120341, R01 MH115128]; National Heart, Lung, and Blood Institute [T32 HL130357]; Swedish Research Council [2018-06585]; National Health and Medical Research Council [APP1170937]

Background: Chatbots have the potential to provide cost-effective mental health prevention programs at scale and increase interactivity, ease of use, and accessibility of intervention programs. Objective: The development of chatbot prevention for eating disorders (EDs) is still in its infancy. Our aim is to present examples of and solutions to challenges in designing and refining a rule-based prevention chatbot program for EDs, targeted at adult women at risk for developing an ED. Methods: Participants were 2409 individuals who at least began to use an EDs prevention chatbot in response to social media advertising. Over 6 months, the research team reviewed up to 52,129 comments from these users to identify inappropriate responses that negatively impacted users experience and technical glitches. Problems identified by reviewers were then presented to the entire research team, who then generated possible solutions and implemented new responses. Results: The most common problem with the chatbot was a general limitation in understanding and responding appropriately to unanticipated user responses. We developed several workarounds to limit these problems while retaining some interactivity. Conclusions: Rule-based chatbots have the potential to reach large populations at low cost but are limited in understanding and responding appropriately to unanticipated user responses. They can be most effective in providing information and simple conversations. Workarounds can reduce conversation errors., Funding Agencies|National Eating Disorders Association through the Feeding Hope Fund; National Institute of Mental Health [R01 MH123482, K08 MH120341, R01 MH115128]; National Heart, Lung, and Blood Institute [T32 HL130357]; Swedish Research Council [2018-06585]; National Health and Medical Research Council [APP1170937]

Objective: The need for clinical services in U.S. colleges exceeds the supply. Digital Mental health Interventions (DMHIs) are a potential solution, but successful implementation depends on stakeholder acceptance. This study investigated the relevance of DMHIs from students perspectives. Methods: In 2020-2021, an online cross-sectional survey using mixed methods was conducted with 479 students at 23 colleges and universities. Respondents reported views and use of standard mental health services and DMHIs and rated the priority of various DMHIs to be offered through campus services. Qualitative data included open-ended responses. Findings: Among respondents, 91% reported having experienced mental health problems, of which 91% reported barriers to receiving mental health services. Students highlighted therapy and counseling as desired and saw flexible access to services as important. With respect to DMHIs, respondents had the most experience with physical health apps (46%), mental health questionnaires (41%), and mental well-being apps (39%). Most were unaware of or had not used apps or self-help programs for mental health problems. Students were most likely to report the following DMHIs as high priorities: a crisis text line (76%), telehealth (66%), websites for connecting to services (62%), and text/messaging with counselors (62%). They considered a self-help program with coach support to be convenient but some also perceived such services to be possibly less effective than in-person therapy. Conclusions: Students welcome DMHIs on campus and indicate preference for mental health services that include human support. The findings, with particular focus on characteristics of the DMHIs prioritized, and students awareness and perceptions of scalable DMHIs emphasized by policymakers, should inform schools looking to implement DMHIs., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [K08 MH120341]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]

Background: Chatbots have the potential to provide cost-effective mental health prevention programs at scale and increase interactivity, ease of use, and accessibility of intervention programs. Objective: The development of chatbot prevention for eating disorders (EDs) is still in its infancy. Our aim is to present examples of and solutions to challenges in designing and refining a rule-based prevention chatbot program for EDs, targeted at adult women at risk for developing an ED. Methods: Participants were 2409 individuals who at least began to use an EDs prevention chatbot in response to social media advertising. Over 6 months, the research team reviewed up to 52,129 comments from these users to identify inappropriate responses that negatively impacted users experience and technical glitches. Problems identified by reviewers were then presented to the entire research team, who then generated possible solutions and implemented new responses. Results: The most common problem with the chatbot was a general limitation in understanding and responding appropriately to unanticipated user responses. We developed several workarounds to limit these problems while retaining some interactivity. Conclusions: Rule-based chatbots have the potential to reach large populations at low cost but are limited in understanding and responding appropriately to unanticipated user responses. They can be most effective in providing information and simple conversations. Workarounds can reduce conversation errors., Funding Agencies|National Eating Disorders Association through the Feeding Hope Fund; National Institute of Mental Health [R01 MH123482, K08 MH120341, R01 MH115128]; National Heart, Lung, and Blood Institute [T32 HL130357]; Swedish Research Council [2018-06585]; National Health and Medical Research Council [APP1170937]

Objective: The need for clinical services in U.S. colleges exceeds the supply. Digital Mental health Interventions (DMHIs) are a potential solution, but successful implementation depends on stakeholder acceptance. This study investigated the relevance of DMHIs from students perspectives. Methods: In 2020-2021, an online cross-sectional survey using mixed methods was conducted with 479 students at 23 colleges and universities. Respondents reported views and use of standard mental health services and DMHIs and rated the priority of various DMHIs to be offered through campus services. Qualitative data included open-ended responses. Findings: Among respondents, 91% reported having experienced mental health problems, of which 91% reported barriers to receiving mental health services. Students highlighted therapy and counseling as desired and saw flexible access to services as important. With respect to DMHIs, respondents had the most experience with physical health apps (46%), mental health questionnaires (41%), and mental well-being apps (39%). Most were unaware of or had not used apps or self-help programs for mental health problems. Students were most likely to report the following DMHIs as high priorities: a crisis text line (76%), telehealth (66%), websites for connecting to services (62%), and text/messaging with counselors (62%). They considered a self-help program with coach support to be convenient but some also perceived such services to be possibly less effective than in-person therapy. Conclusions: Students welcome DMHIs on campus and indicate preference for mental health services that include human support. The findings, with particular focus on characteristics of the DMHIs prioritized, and students awareness and perceptions of scalable DMHIs emphasized by policymakers, should inform schools looking to implement DMHIs., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [K08 MH120341]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]

Background: Chatbots have the potential to provide cost-effective mental health prevention programs at scale and increase interactivity, ease of use, and accessibility of intervention programs. Objective: The development of chatbot prevention for eating disorders (EDs) is still in its infancy. Our aim is to present examples of and solutions to challenges in designing and refining a rule-based prevention chatbot program for EDs, targeted at adult women at risk for developing an ED. Methods: Participants were 2409 individuals who at least began to use an EDs prevention chatbot in response to social media advertising. Over 6 months, the research team reviewed up to 52,129 comments from these users to identify inappropriate responses that negatively impacted users experience and technical glitches. Problems identified by reviewers were then presented to the entire research team, who then generated possible solutions and implemented new responses. Results: The most common problem with the chatbot was a general limitation in understanding and responding appropriately to unanticipated user responses. We developed several workarounds to limit these problems while retaining some interactivity. Conclusions: Rule-based chatbots have the potential to reach large populations at low cost but are limited in understanding and responding appropriately to unanticipated user responses. They can be most effective in providing information and simple conversations. Workarounds can reduce conversation errors., Funding Agencies|National Eating Disorders Association through the Feeding Hope Fund; National Institute of Mental Health [R01 MH123482, K08 MH120341, R01 MH115128]; National Heart, Lung, and Blood Institute [T32 HL130357]; Swedish Research Council [2018-06585]; National Health and Medical Research Council [APP1170937]

Background: Chatbots have the potential to provide cost-effective mental health prevention programs at scale and increase interactivity, ease of use, and accessibility of intervention programs. Objective: The development of chatbot prevention for eating disorders (EDs) is still in its infancy. Our aim is to present examples of and solutions to challenges in designing and refining a rule-based prevention chatbot program for EDs, targeted at adult women at risk for developing an ED. Methods: Participants were 2409 individuals who at least began to use an EDs prevention chatbot in response to social media advertising. Over 6 months, the research team reviewed up to 52,129 comments from these users to identify inappropriate responses that negatively impacted users experience and technical glitches. Problems identified by reviewers were then presented to the entire research team, who then generated possible solutions and implemented new responses. Results: The most common problem with the chatbot was a general limitation in understanding and responding appropriately to unanticipated user responses. We developed several workarounds to limit these problems while retaining some interactivity. Conclusions: Rule-based chatbots have the potential to reach large populations at low cost but are limited in understanding and responding appropriately to unanticipated user responses. They can be most effective in providing information and simple conversations. Workarounds can reduce conversation errors., Funding Agencies|National Eating Disorders Association through the Feeding Hope Fund; National Institute of Mental Health [R01 MH123482, K08 MH120341, R01 MH115128]; National Heart, Lung, and Blood Institute [T32 HL130357]; Swedish Research Council [2018-06585]; National Health and Medical Research Council [APP1170937]

Objective: The need for clinical services in U.S. colleges exceeds the supply. Digital Mental health Interventions (DMHIs) are a potential solution, but successful implementation depends on stakeholder acceptance. This study investigated the relevance of DMHIs from students perspectives. Methods: In 2020-2021, an online cross-sectional survey using mixed methods was conducted with 479 students at 23 colleges and universities. Respondents reported views and use of standard mental health services and DMHIs and rated the priority of various DMHIs to be offered through campus services. Qualitative data included open-ended responses. Findings: Among respondents, 91% reported having experienced mental health problems, of which 91% reported barriers to receiving mental health services. Students highlighted therapy and counseling as desired and saw flexible access to services as important. With respect to DMHIs, respondents had the most experience with physical health apps (46%), mental health questionnaires (41%), and mental well-being apps (39%). Most were unaware of or had not used apps or self-help programs for mental health problems. Students were most likely to report the following DMHIs as high priorities: a crisis text line (76%), telehealth (66%), websites for connecting to services (62%), and text/messaging with counselors (62%). They considered a self-help program with coach support to be convenient but some also perceived such services to be possibly less effective than in-person therapy. Conclusions: Students welcome DMHIs on campus and indicate preference for mental health services that include human support. The findings, with particular focus on characteristics of the DMHIs prioritized, and students awareness and perceptions of scalable DMHIs emphasized by policymakers, should inform schools looking to implement DMHIs., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [K08 MH120341]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]

Objective: The need for clinical services in U.S. colleges exceeds the supply. Digital Mental health Interventions (DMHIs) are a potential solution, but successful implementation depends on stakeholder acceptance. This study investigated the relevance of DMHIs from students perspectives. Methods: In 2020-2021, an online cross-sectional survey using mixed methods was conducted with 479 students at 23 colleges and universities. Respondents reported views and use of standard mental health services and DMHIs and rated the priority of various DMHIs to be offered through campus services. Qualitative data included open-ended responses. Findings: Among respondents, 91% reported having experienced mental health problems, of which 91% reported barriers to receiving mental health services. Students highlighted therapy and counseling as desired and saw flexible access to services as important. With respect to DMHIs, respondents had the most experience with physical health apps (46%), mental health questionnaires (41%), and mental well-being apps (39%). Most were unaware of or had not used apps or self-help programs for mental health problems. Students were most likely to report the following DMHIs as high priorities: a crisis text line (76%), telehealth (66%), websites for connecting to services (62%), and text/messaging with counselors (62%). They considered a self-help program with coach support to be convenient but some also perceived such services to be possibly less effective than in-person therapy. Conclusions: Students welcome DMHIs on campus and indicate preference for mental health services that include human support. The findings, with particular focus on characteristics of the DMHIs prioritized, and students awareness and perceptions of scalable DMHIs emphasized by policymakers, should inform schools looking to implement DMHIs., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [K08 MH120341]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]

Objective Prevention of eating disorders (EDs) is of high importance. However, digital programs with human moderation are unlikely to be disseminated widely. The aim of this study was to test whether a chatbot (i.e., computer program simulating human conversation) would significantly reduce ED risk factors (i.e., weight/shape concerns, thin-ideal internalization) in women at high risk for an ED, compared to waitlist control, as well as whether it would significantly reduce overall ED psychopathology, depression, and anxiety and prevent ED onset. Method Women who screened as high risk for an ED were randomized (N = 700) to (1) chatbot based on the StudentBodies (c) program; or (2) waitlist control. Participants were followed for 6 months. Results For weight/shape concerns, there was a significantly greater reduction in intervention versus control at 3- (d = -0.20; p = .03) and 6-m-follow-up (d = -0.19; p = .04). There were no differences in change in thin-ideal internalization. The intervention was associated with significantly greater reductions than control in overall ED psychopathology at 3- (d = -0.29; p = .003) but not 6-month follow-up. There were no differences in change in depression or anxiety. The odds of remaining nonclinical for EDs were significantly higher in intervention versus control at both 3- (OR = 2.37, 95% CI [1.37, 4.11]) and 6-month follow-ups (OR = 2.13, 95% CI [1.26, 3.59]). Discussion Findings provide support for the use of a chatbot-based EDs prevention program in reducing weight/shape concerns through 6-month follow-up, as well as in reducing overall ED psychopathology, at least in the shorter-term. Results also suggest the intervention may reduce ED onset. Public Significance We found that a chatbot, or a computer program simulating human conversation, based on an established, cognitive-behavioral therapy-based eating disorders prevention program, was successful in reducing womens concerns about weight and shape through 6-month follow-up, Funding Agencies|National Eating Disorders Association Feeding Hope Fund; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]; National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [K08 MH120341]; Swedish Research CouncilSwedish Research CouncilEuropean Commission

Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users motivation and preferences., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH115128]; National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [NHMRC APP1170937]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K08 MH120341, K01 DK120778]; Na-tional Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K01 DK116925]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]

Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users motivation and preferences., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH115128]; National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [NHMRC APP1170937]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K08 MH120341, K01 DK120778]; Na-tional Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K01 DK116925]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]

Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users motivation and preferences., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH115128]; National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [NHMRC APP1170937]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K08 MH120341, K01 DK120778]; Na-tional Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K01 DK116925]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]

Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users motivation and preferences., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH115128]; National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [NHMRC APP1170937]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K08 MH120341, K01 DK120778]; Na-tional Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K01 DK116925]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]

Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users motivation and preferences., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH115128]; National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [NHMRC APP1170937]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K08 MH120341, K01 DK120778]; Na-tional Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K01 DK116925]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]

Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users motivation and preferences., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH115128]; National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [NHMRC APP1170937]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K08 MH120341, K01 DK120778]; Na-tional Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [K01 DK116925]; National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [T32 HL130357]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-06585]

About a third of college students struggle with anxiety, depression, or an eating disorder, and only 20?40% of college students with mental disorders receive treatment. Inadequacies in mental health care delivery result in prolonged illness, disease progression, poorer prognosis, and greater likelihood of relapse, highlighting the need for a new approach to detect mental health problems and engage college students in services. We have developed a transdiagnostic, low-cost mobile mental health targeted prevention and intervention platform that uses population-level screening to engage college students in tailored services that address common mental health problems. We will test the impact of this mobile mental health platform for service delivery in a large-scale trial across 20+ colleges. Students who screen positive or at high-risk for clinical anxiety, depression, or an eating disorder and who are not currently engaged in mental health services (N = 7884) will be randomly assigned to: 1) intervention via the mobile mental health platform; or 2) referral to usual care (i.e., campus health or counseling center). We will test whether the mobile mental health platform, compared to referral, is associated with improved uptake, reduced clinical cases, disorder-specific symptoms, and improved quality of life and functioning. We will also test mediators, predictors, and moderators of improved mental health outcomes, as well as stakeholder-relevant outcomes, including cost-effectiveness and academic performance. This population-level approach to service engagement has the potential to improve mental health outcomes for the millions of students enrolled in U.S. colleges and universities., Funding Agencies|National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [K08 MH120341]; National Institute of Diabetes and Digestive and Kidney DiseasesUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) [K01 DK116925]

Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions., Funding Agencies|National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH100455, T32 HL007456, T32 HL130357, K08 MH120341, K01 DK116925]; Australias National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [APP1057411]; Centre of Research Excellence from Australias National Health and Medical Research Council [APP1170937]

Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions., Funding Agencies|National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH100455, T32 HL007456, T32 HL130357, K08 MH120341, K01 DK116925]; Australias National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [APP1057411]; Centre of Research Excellence from Australias National Health and Medical Research Council [APP1170937]

Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions., Funding Agencies|National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH100455, T32 HL007456, T32 HL130357, K08 MH120341, K01 DK116925]; Australias National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [APP1057411]; Centre of Research Excellence from Australias National Health and Medical Research Council [APP1170937]

Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions., Funding Agencies|National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH100455, T32 HL007456, T32 HL130357, K08 MH120341, K01 DK116925]; Australias National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [APP1057411]; Centre of Research Excellence from Australias National Health and Medical Research Council [APP1170937]

Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions., Funding Agencies|National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH100455, T32 HL007456, T32 HL130357, K08 MH120341, K01 DK116925]; Australias National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [APP1057411]; Centre of Research Excellence from Australias National Health and Medical Research Council [APP1170937]

Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions., Funding Agencies|National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH100455, T32 HL007456, T32 HL130357, K08 MH120341, K01 DK116925]; Australias National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [APP1057411]; Centre of Research Excellence from Australias National Health and Medical Research Council [APP1170937]

Digital technology, which includes the collection, analysis, and use of data from a variety of digital devices, has the potential to reduce the prevalence of disorders and improve mental health in populations. Among the many advantages of digital technology is that it allows preventive and clinical interventions, both of which are needed to reduce the prevalence of mental health disorders, to be feasibly integrated into health care and community delivery systems and delivered at scale. However, the use of digital technology also presents several challenges, including how systems can manage and implement interventions in a rapidly changing digital environment and handle critical issues that affect population-wide outcomes, including reaching the targeted population, obtaining meaningful levels of uptake and use of interventions, and achieving significant outcomes. We describe a possible solution, which is to have an outcome optimization team that focuses on the dynamic use of data to adapt interventions for populations, while at the same time, addressing the complex relationships among reach, uptake, use, and outcome. We use the example of eating disorders in young people to illustrate how this solution could be implemented at scale. We also discuss system, practitioner-related, and other issues related to the adaptation of such an approach Digital technology has great potential for facilitating the reduction of mental illness rates in populations. However, achieving this goal will require the implementation of new approaches. As a solution, we argue for the need to create outcome optimization teams, tasked with integrating data from various sources and using advanced data analytics and new designs to develop interventions/strategies to increase reach, uptake, use/engagement, and outcomes for both preventive and treatment interventions., Funding Agencies|National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH100455, T32 HL007456, T32 HL130357, K08 MH120341, K01 DK116925]; Australias National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [APP1057411]; Centre of Research Excellence from Australias National Health and Medical Research Council [APP1170937]

This pilot study adapted family-based treatment (FBT) for youth with potentially prodromal anorexia nervosa (AN). Fifty-nine youth with clinically significant AN symptom constellations, but who never met full Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.) (DSM-IV) criteria for AN, were enrolled in a partially randomized preference design study. Participants were offered randomization to FBT or supportive psychotherapy (SPT); those who declined to be randomized because of a strong treatment preference were entered into a parallel, non-randomized self-selected intervention study. Without accessing outcome data, an observational analysis with three diagnostic subclasses was designed based on AN symptom severity profiles, combining randomized and non-randomized participants, such that participants receiving FBT and SPT within each subclass were similar on key baseline characteristics. Outcomes of this pilot study were explored by calculating effect sizes for end-of-treatment values within each subclass, and also with a longitudinal mixed effect model that accounted for subclass. Weight trajectory was measured by percent expected body weight. Psychological outcomes were fear of weight gain, feeling fat, importance of weight, and importance of shape. Results show that the pattern of symptom observations over time was dependent on subclass of SAN (least symptomatic, moderately symptomatic, or most symptomatic) and on the target outcome variable category (weight or psychological). Results from this study, which should be considered in the context of the small sample sizes overall and within groups, can generate hypotheses for future, larger research trials on early treatment strategies. Feasibility findings illustrate how the innovative partially randomized preference design has potential broader application for AN intervention research.Clinical trial registrationClinicalTrials.gov, identifier NCT00418977.

Background: Although there is extensive evidence for the efficacy of online eating disorder (ED) prevention programs in clinical trials, these programs have rarely been adopted beyond the trial phase and offered to a wider audience. As risk factors for eating disorders are partly associated with overweight and overweight in turn is correlated to disordered eating, this study will offer a combined eating disorder prevention program which also promotes a balanced lifestyle to normal weight and overweight individuals alike. The efficacy of the program has been proven in previous trials. The study aims to evaluate the dissemination of a combined eating disorder prevention and health promotion program (everyBody) to women of all age groups and varying levels of ED risk status in the general population. Methods: A dissemination trial will be conducted in German-speaking countries, including 4160 women from the general population. Participants will be screened to exclude participants who are likely to have an ED. Eligible participants will be allocated to one of five program arms based on their BMI and respective ED symptoms. The guided program consists of 4 to 12 weeks of weekly sessions offering CBT-based exercises, psychoeducational material, self-monitoring, and group discussions. Outcomes will be assessed according to the RE-AIM model, including measures of effectiveness, reach, adoption, implementation, and maintenance of the program. Discussion/conclusions: This trial aims to disseminate a combined ED prevention and health promotion program in the general population, offering universal, selective and indicated prevention in one program. To our knowledge, it is the first trial to systematically evaluate dissemination efforts based on the RE-AIM model. This trial will be conducted as part of the EU-funded ICare (Integrating Technology into Mental Health Care Delivery in Europe) project.

Background: Although there is extensive evidence for the efficacy of online eating disorder (ED) prevention programs in clinical trials, these programs have rarely been adopted beyond the trial phase and offered to a wider audience. As risk factors for eating disorders are partly associated with overweight and overweight in turn is correlated to disordered eating, this study will offer a combined eating disorder prevention program which also promotes a balanced lifestyle to normal weight and overweight individuals alike. The efficacy of the program has been proven in previous trials. The study aims to evaluate the dissemination of a combined eating disorder prevention and health promotion program (everyBody) to women of all age groups and varying levels of ED risk status in the general population. Methods: A dissemination trial will be conducted in German-speaking countries, including 4160 women from the general population. Participants will be screened to exclude participants who are likely to have an ED. Eligible participants will be allocated to one of five program arms based on their BMI and respective ED symptoms. The guided program consists of 4 to 12 weeks of weekly sessions offering CBT-based exercises, psychoeducational material, self-monitoring, and group discussions. Outcomes will be assessed according to the RE-AIM model, including measures of effectiveness, reach, adoption, implementation, and maintenance of the program. Discussion/conclusions: This trial aims to disseminate a combined ED prevention and health promotion program in the general population, offering universal, selective and indicated prevention in one program. To our knowledge, it is the first trial to systematically evaluate dissemination efforts based on the RE-AIM model. This trial will be conducted as part of the EU-funded ICare (Integrating Technology into Mental Health Care Delivery in Europe) project.

Background: Although there is extensive evidence for the efficacy of online eating disorder (ED) prevention programs in clinical trials, these programs have rarely been adopted beyond the trial phase and offered to a wider audience. As risk factors for eating disorders are partly associated with overweight and overweight in turn is correlated to disordered eating, this study will offer a combined eating disorder prevention program which also promotes a balanced lifestyle to normal weight and overweight individuals alike. The efficacy of the program has been proven in previous trials. The study aims to evaluate the dissemination of a combined eating disorder prevention and health promotion program (everyBody) to women of all age groups and varying levels of ED risk status in the general population. Methods: A dissemination trial will be conducted in German-speaking countries, including 4160 women from the general population. Participants will be screened to exclude participants who are likely to have an ED. Eligible participants will be allocated to one of five program arms based on their BMI and respective ED symptoms. The guided program consists of 4 to 12 weeks of weekly sessions offering CBT-based exercises, psychoeducational material, self-monitoring, and group discussions. Outcomes will be assessed according to the RE-AIM model, including measures of effectiveness, reach, adoption, implementation, and maintenance of the program. Discussion/conclusions: This trial aims to disseminate a combined ED prevention and health promotion program in the general population, offering universal, selective and indicated prevention in one program. To our knowledge, it is the first trial to systematically evaluate dissemination efforts based on the RE-AIM model. This trial will be conducted as part of the EU-funded ICare (Integrating Technology into Mental Health Care Delivery in Europe) project.

Background: Although there is extensive evidence for the efficacy of online eating disorder (ED) prevention programs in clinical trials, these programs have rarely been adopted beyond the trial phase and offered to a wider audience. As risk factors for eating disorders are partly associated with overweight and overweight in turn is correlated to disordered eating, this study will offer a combined eating disorder prevention program which also promotes a balanced lifestyle to normal weight and overweight individuals alike. The efficacy of the program has been proven in previous trials. The study aims to evaluate the dissemination of a combined eating disorder prevention and health promotion program (everyBody) to women of all age groups and varying levels of ED risk status in the general population. Methods: A dissemination trial will be conducted in German-speaking countries, including 4160 women from the general population. Participants will be screened to exclude participants who are likely to have an ED. Eligible participants will be allocated to one of five program arms based on their BMI and respective ED symptoms. The guided program consists of 4 to 12 weeks of weekly sessions offering CBT-based exercises, psychoeducational material, self-monitoring, and group discussions. Outcomes will be assessed according to the RE-AIM model, including measures of effectiveness, reach, adoption, implementation, and maintenance of the program. Discussion/conclusions: This trial aims to disseminate a combined ED prevention and health promotion program in the general population, offering universal, selective and indicated prevention in one program. To our knowledge, it is the first trial to systematically evaluate dissemination efforts based on the RE-AIM model. This trial will be conducted as part of the EU-funded ICare (Integrating Technology into Mental Health Care Delivery in Europe) project.

While there have been important recent advances in the development of effective universal prevention and intervention programs, it is not yet clear how to engage large numbers of students in these programs. In this paper, we report findings from a two-phase pilot study. In the first phase, we used a population-level, online survey to assess eating disorder symptom level and habits/attitudes related to service utilization (N=2180). Using validated screening tools, we found that roughly one in three students has significant symptoms of eating disorders or elevated weight concerns, the vast majority of whom (86.5%) have not received treatment. In the second phase, we referred students to online prevention and selective/indicated intervention programs based on symptom classification (N=1916). We find that program enrollment is highest for students in the indicated intervention (18.1%) and lowest for students in the universal prevention (4.1%). We find that traditionally-emphasized barriers such as stigma, misinformation, and financial limitations do not appear to be the most important factors preventing treatment-seeking. Rather students report not seeking help for reasons such as lack of time, lack of perceived need, and a desire to deal with the issue "on my own." Findings offer insight into the treatment-seeking habits and attitudes of college students, including those barriers that may be overcome by offering online programs and those that persist despite increased access to and convenience of relevant resources.

Objective: Body dissatisfaction in females is common and a risk factor for the development of an eating disorder. This study tested whether body dissatisfaction could be improved using a brief conditioning intervention in which photographs of participants' bodies were selectively paired with positive social stimuli (smiling faces) and photographs of other bodies were paired with neutral or negative social stimuli (neutral and frowning faces). Method: 39 women (mean age = 22.46; 64.1% Caucasian) with high body dissatisfaction were randomized to either the evaluative conditioning intervention (n = 22) or to a delayed waitlist control condition (n 17). Body dissatisfaction (specifically, shape and weight concern), restraint, eating concern, and self-esteem were assessed at baseline, post treatment and again after four and 12 weeks. Results: Compared to women in the delayed waitlist control condition, women in the treatment condition demonstrated a significant decrease in shape and weight concern, and a significant increase in self-esteem. Similar trends were found for the control condition after they completed the intervention. Changes at post treatment related to body dissatisfaction were maintained at 12-week follow-up. Conclusions: Repeatedly pairing photographs of an individual's body with positive social feedback may lead to improved body image and self-esteem.

Objective: Body dissatisfaction in females is common and a risk factor for the development of an eating disorder. This study tested whether body dissatisfaction could be improved using a brief conditioning intervention in which photographs of participants' bodies were selectively paired with positive social stimuli (smiling faces) and photographs of other bodies were paired with neutral or negative social stimuli (neutral and frowning faces). Method: 39 women (mean age = 22.46; 64.1% Caucasian) with high body dissatisfaction were randomized to either the evaluative conditioning intervention (n = 22) or to a delayed waitlist control condition (n 17). Body dissatisfaction (specifically, shape and weight concern), restraint, eating concern, and self-esteem were assessed at baseline, post treatment and again after four and 12 weeks. Results: Compared to women in the delayed waitlist control condition, women in the treatment condition demonstrated a significant decrease in shape and weight concern, and a significant increase in self-esteem. Similar trends were found for the control condition after they completed the intervention. Changes at post treatment related to body dissatisfaction were maintained at 12-week follow-up. Conclusions: Repeatedly pairing photographs of an individual's body with positive social feedback may lead to improved body image and self-esteem.

Momentary intervention has been proposed as a cost-effective, generalizable, and ecologically valid method to increase the efficiency of face-to-face cognitive-behavioral therapy (CBT). The purpose of the current pilot study was to evaluate the efficacy of a six-session palmtop computer-assisted Group CBT for generalized anxiety disorder (GAD) (CAGT6) in comparison with a six-session Group CBT for GAD without the computer (CBGT6) and typical (12 session) Group CBT for GAD (CBGT12) in a randomized controlled trial. Thirty-four individuals with a primary diagnosis of GAD were randomized to one of the three conditions and completed measures of GAD and anxiety before therapy, after therapy, and at 6-, and 12-month follow-ups. Results indicated that CAGT6 was superior to CBGT6 at posttreatment, but not significantly different from CBGT12. At 6- and 12-month follow-ups, CAGT6 was neither significantly different from CBGT6, nor from CBGT12. Percentages of individuals achieving reliable change on two of the three GAD measures favored CAGT6 over CBGT6 at posttreatment, suggesting promise for the added value of the mobile technology.

Study and treatment dropout and adherence represent particular challenges in studies on Internet-based interventions. However, systematic investigations of the relationship between study, intervention and patient characteristics, participation, and intervention outcomes in online-prevention are scarce. A review of participation in trials investigating a cognitive-behavioral, Internet-based, 8-week prevention program (StudentBodies™) for eating disorders, moderators of participation, and the impact of participation on the relationship of outcome moderators and outcomes was performed. Seven US and three German studies with a total of N = 1059 female participants were included. Two of the U.S. and one of the German trials explicitly addressed high risk samples in a selective prevention approach. Across studies, dropout rates ranged from 3% to 26%. The women who participated in the trials accessed on average between 49% and 83% of the assigned intervention content. None of the study characteristics (universal vs. selective prevention, incentives, country, participants' age) predicted adherence or study dropout. After adjusting for adherence, intervention outcomes (EDI Drive for Thinness and EDI Bulimia) were only moderated by participant's age, with smaller effects in one sample of adolescent girls. Adherence to StudentBodies™ proved to be high across a number of trials, settings and countries. These findings are promising, but it is likely that adherence will be distinctly lower in the general public than in research settings, and intervention effects will turn out smaller. However, the intervention is readily available at minimal cost per participant, and the public health impact may still be notable.

Background: Given the rising rates of obesity in children and adolescents, developing evidence-based weight loss or weight maintenance interventions that can be widely disseminated, well implemented, and are highly scalable is a public health necessity. Such interventions should ensure that adolescents establish healthy weight regulation practices while also reducing eating disorder risk. Objective: This study describes an online program, StayingFit, which has two tracks for universal and targeted delivery and was designed to enhance healthy living skills, encourage healthy weight regulation, and improve weight/shape concerns among high school adolescents. Methods: Ninth grade students in two high schools in the San Francisco Bay area and in St Louis were invited to participate. Students who were overweight (body mass index [BMI] >85th percentile) were offered the weight management track of StayingFit; students who were normal weight were offered the healthy habits track. The 12-session program included a monitored discussion group and interactive self-monitoring logs. Measures completed pre- and post-intervention included self-report height and weight, used to calculate BMI percentile for age and sex and standardized BMI (zBMI), Youth Risk Behavior Survey (YRBS) nutrition data, the Weight Concerns Scale, and the Center for Epidemiological Studies Depression Scale. Results: A total of 336 students provided informed consent and were included in the analyses. The racial breakdown of the sample was as follows: 46.7% (157/336) multiracial/other, 31.0% (104/336) Caucasian, 16.7% (56/336) African American, and 5.7% (19/336) did not specify; 43.5% (146/336) of students identified as Hispanic/Latino. BMI percentile and zBMI significantly decreased among students in the weight management track. BMI percentile and zBMI did not significantly change among students in the healthy habits track, demonstrating that the

Background: Recently, we found a telephone-delivered secondary prevention programme using health coaching (‘ProActive Heart’) to be effective in improving a range of key behavioural outcomes for myocardial infarction (MI) patients. What remains unclear, however, is the extent to which these treatment effects translate to important psychological outcomes such as depression and anxiety outcomes, an issue of clinical significance due to the substantial proportion of MI patients who experience depression and anxiety. The objective of the study was to investigate, as a secondary hypothesis of a larger trial, the effects of a telephone-delivered health coaching programme on depression and anxiety outcomes of MI patients. Design: Two-arm, parallel-group, randomized, controlled design with six-months outcomes. Methods: Patients admitted to one of two tertiary hospitals in Brisbane, Australia following MI were assessed for eligibility. Four hundred and thirty patients were recruited and randomly assigned to usual care or an intervention group comprising up to 10 telephone-delivered ‘health coaching’ sessions (ProActive Heart). Regression analysis compared Hospital Anxiety and Depression Scale scores of completing participants at six months (intervention: n = 141 versus usual care: n = 156). Results: The intervention yielded reductions in anxiety at follow-up (mean difference = −0.7, 95% confidence interval=−1.4,−0.02) compared with usual care. A similar pattern was observed in mean depression scores but was not statistically significant. Conclusions: The ProActive Heart programme effectively improves anxiety outcomes of patients following myocardial infarction. If combined with psychological-specific treatment, this programme could impact anxiety of greater intensity in a clinically meaningful way.

Momentary intervention has been proposed as a cost-effective, generalizable, and ecologically valid method to increase the efficiency of face-to-face cognitive-behavioral therapy (CBT). The purpose of the current pilot study was to evaluate the efficacy of a six-session palmtop computer-assisted Group CBT for generalized anxiety disorder (GAD) (CAGT6) in comparison with a six-session Group CBT for GAD without the computer (CBGT6) and typical (12 session) Group CBT for GAD (CBGT12) in a randomized controlled trial. Thirty-four individuals with a primary diagnosis of GAD were randomized to one of the three conditions and completed measures of GAD and anxiety before therapy, after therapy, and at 6-, and 12-month follow-ups. Results indicated that CAGT6 was superior to CBGT6 at posttreatment, but not significantly different from CBGT12. At 6- and 12-month follow-ups, CAGT6 was neither significantly different from CBGT6, nor from CBGT12. Percentages of individuals achieving reliable change on two of the three GAD measures favored CAGT6 over CBGT6 at posttreatment, suggesting promise for the added value of the mobile technology.

Study and treatment dropout and adherence represent particular challenges in studies on Internet-based interventions. However, systematic investigations of the relationship between study, intervention and patient characteristics, participation, and intervention outcomes in online-prevention are scarce. A review of participation in trials investigating a cognitive-behavioral, Internet-based, 8-week prevention program (StudentBodies™) for eating disorders, moderators of participation, and the impact of participation on the relationship of outcome moderators and outcomes was performed. Seven US and three German studies with a total of N = 1059 female participants were included. Two of the U.S. and one of the German trials explicitly addressed high risk samples in a selective prevention approach. Across studies, dropout rates ranged from 3% to 26%. The women who participated in the trials accessed on average between 49% and 83% of the assigned intervention content. None of the study characteristics (universal vs. selective prevention, incentives, country, participants' age) predicted adherence or study dropout. After adjusting for adherence, intervention outcomes (EDI Drive for Thinness and EDI Bulimia) were only moderated by participant's age, with smaller effects in one sample of adolescent girls. Adherence to StudentBodies™ proved to be high across a number of trials, settings and countries. These findings are promising, but it is likely that adherence will be distinctly lower in the general public than in research settings, and intervention effects will turn out smaller. However, the intervention is readily available at minimal cost per participant, and the public health impact may still be notable.

Background Coronary heart disease (CHD) and depression are leading causes of disease burden globally and the two often co-exist. Depression is common after Myocardial Infarction (MI) and it has been estimated that 15-35% of patients experience depressive symptoms. Co-morbid depression can impair health related quality of life (HRQOL), decrease medication adherence and appropriate utilisation of health services, lead to increased morbidity and suicide risk, and is associated with poorer CHD risk factor profiles and reduced survival. We aim to determine the feasibility of conducting a randomised, multi-centre trial designed to compare a tele-health program (MoodCare) for depression and CHD secondary prevention, with Usual Care (UC). Methods Over 1600 patients admitted after index admission for Acute Coronary Syndrome (ACS) are being screened for depression at six metropolitan hospitals in the Australian states of Victoria and Queensland. Consenting participants are then contacted at two weeks post-discharge for baseline assessment. One hundred eligible participants are to be randomised to an intervention or a usual medical care control group (50 per group). The intervention consists of up to 10 × 30-40 minute structured telephone sessions, delivered by registered psychologists, commencing within two weeks of baseline screening. The intervention focuses on depression management, lifestyle factors (physical activity, healthy eating, smoking cessation, alcohol intake), medication adherence and managing co-morbidities. Data collection occurs at baseline (Time 1), 6 months (post-intervention) (Time 2), 12 months (Time 3) and 24 months follow-up for longer term effects (Time 4). We are comparing depression (Cardiac Depression Scale [CDS]) and HRQOL (Short Form-12 [SF-12]) scores between treatment and UC groups, assessing the feasibility of the program through patient acceptability and exploring long term maintenance effects. A cost-effectivene

Background Coronary heart disease (CHD) and depression are leading causes of disease burden globally and the two often co-exist. Depression is common after Myocardial Infarction (MI) and it has been estimated that 15-35% of patients experience depressive symptoms. Co-morbid depression can impair health related quality of life (HRQOL), decrease medication adherence and appropriate utilisation of health services, lead to increased morbidity and suicide risk, and is associated with poorer CHD risk factor profiles and reduced survival. We aim to determine the feasibility of conducting a randomised, multi-centre trial designed to compare a tele-health program (MoodCare) for depression and CHD secondary prevention, with Usual Care (UC). Methods Over 1600 patients admitted after index admission for Acute Coronary Syndrome (ACS) are being screened for depression at six metropolitan hospitals in the Australian states of Victoria and Queensland. Consenting participants are then contacted at two weeks post-discharge for baseline assessment. One hundred eligible participants are to be randomised to an intervention or a usual medical care control group (50 per group). The intervention consists of up to 10 × 30-40 minute structured telephone sessions, delivered by registered psychologists, commencing within two weeks of baseline screening. The intervention focuses on depression management, lifestyle factors (physical activity, healthy eating, smoking cessation, alcohol intake), medication adherence and managing co-morbidities. Data collection occurs at baseline (Time 1), 6 months (post-intervention) (Time 2), 12 months (Time 3) and 24 months follow-up for longer term effects (Time 4). We are comparing depression (Cardiac Depression Scale [CDS]) and HRQOL (Short Form-12 [SF-12]) scores between treatment and UC groups, assessing the feasibility of the program through patient acceptability and exploring long term maintenance effects. A cost-effectiveness analysis of the costs and ou