Pub Date : 2025-06-10DOI: 10.1016/j.invent.2025.100844
Ellen Svensson , Walter Osika , Per Carlbring
The use of AI in digital mental healthcare promises to make treatments more effective, accessible, and scalable than ever before. At the same time, the use of AI opens a myriad of ethical concerns, including the lack of transparency, the risk of bias leading to increasing social inequalities, and the risk of responsibility gaps. This raises a crucial question: Can we rely on these systems to deliver care that is both ethical and effective? In attempts to regulate and ensure the safe usage of AI-powered tools, calls to trustworthy AI systems have become central. However, the use of terms such as “trust” and “trustworthiness” risks increasing anthropomorphization of AI systems, attaching human moral activities, such as trust, to artificial systems. In this article, we propose that terms such as “trustworthiness” be used with caution regarding AI and that when used, they should reflect an AI system's ability to consistently demonstrate measurable adherence to ethical principles, such as respect for human autonomy, nonmaleficence, fairness, and transparency. On this approach, trustworthy and ethical AI has the possibility of becoming a tangible goal rather than wishful thinking.
{"title":"Commentary: Trustworthy and ethical AI in digital mental healthcare – wishful thinking or tangible goal?","authors":"Ellen Svensson , Walter Osika , Per Carlbring","doi":"10.1016/j.invent.2025.100844","DOIUrl":"10.1016/j.invent.2025.100844","url":null,"abstract":"<div><div>The use of AI in digital mental healthcare promises to make treatments more effective, accessible, and scalable than ever before. At the same time, the use of AI opens a myriad of ethical concerns, including the lack of transparency, the risk of bias leading to increasing social inequalities, and the risk of responsibility gaps. This raises a crucial question: Can we rely on these systems to deliver care that is both ethical and effective? In attempts to regulate and ensure the safe usage of AI-powered tools, calls to trustworthy AI systems have become central. However, the use of terms such as “trust” and “trustworthiness” risks increasing anthropomorphization of AI systems, attaching human moral activities, such as trust, to artificial systems. In this article, we propose that terms such as “trustworthiness” be used with caution regarding AI and that when used, they should reflect an AI system's ability to consistently demonstrate measurable adherence to ethical principles, such as respect for human autonomy, nonmaleficence, fairness, and transparency. On this approach, trustworthy and ethical AI has the possibility of becoming a tangible goal rather than wishful thinking.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"41 ","pages":"Article 100844"},"PeriodicalIF":3.6,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144262874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-10DOI: 10.1016/j.invent.2025.100842
Tove Wahlund, Fredrik Spångberg , Viktor Vadenmark , Erik Andersson
Excessive worry is common among treatment-seeking individuals in primary care and has a negative impact on daily functioning, which may also lead to other mental health problems. The current study tested whether a worry-focused online intervention – provided in both a guided and an unguided format – was efficacious in reducing worry-related symptoms and if these effects were specifically linked to improvements in daily functioning. A total of 82 participants were randomized to intervention with therapist support (guided; n = 28), intervention without therapist support (unguided; n = 27) or to waiting list (n = 27). Results showed that the online intervention was more effective than waiting list in reducing worry at week 5 (between-group d = 0.96). The intervention was effective against waiting list irrespective of whether it was provided in a guided (between-group d = 0.90) or unguided format (between-group d = 1.07) with sustained results at the 7-week follow-up. Reduction in worry mediated improvement in daily functioning (between-group d = 0.58; indirect effect estimate = −1.06 [95 % CI: −1.76 to −0.51], 66 % mediated effect). The mediation effects were fairly robust to mediator-outcome confounding, with residual correlation values set to r = 0.3 in a sensitivity analysis. The results provide further evidence that it is beneficial to provide a low-threshold, easy access intervention to patients with excessive worry, irrespective of primary diagnosis. Clinical implications are discussed.
{"title":"Efficacy of a brief online intervention in reducing excessive worry and improving daily functioning: A randomized trial with mediation analysis","authors":"Tove Wahlund, Fredrik Spångberg , Viktor Vadenmark , Erik Andersson","doi":"10.1016/j.invent.2025.100842","DOIUrl":"10.1016/j.invent.2025.100842","url":null,"abstract":"<div><div>Excessive worry is common among treatment-seeking individuals in primary care and has a negative impact on daily functioning, which may also lead to other mental health problems. The current study tested whether a worry-focused online intervention – provided in both a guided and an unguided format – was efficacious in reducing worry-related symptoms and if these effects were specifically linked to improvements in daily functioning. A total of 82 participants were randomized to intervention with therapist support (guided; <em>n</em> = 28), intervention without therapist support (unguided; <em>n</em> = 27) or to waiting list (n = 27). Results showed that the online intervention was more effective than waiting list in reducing worry at week 5 (between-group <em>d</em> = 0.96). The intervention was effective against waiting list irrespective of whether it was provided in a guided (between-group <em>d</em> = 0.90) or unguided format (between-group <em>d</em> = 1.07) with sustained results at the 7-week follow-up. Reduction in worry mediated improvement in daily functioning (between-group <em>d</em> = 0.58; indirect effect estimate = −1.06 [95 % CI: −1.76 to −0.51], 66 % mediated effect). The mediation effects were fairly robust to mediator-outcome confounding, with residual correlation values set to <em>r</em> = 0.3 in a sensitivity analysis. The results provide further evidence that it is beneficial to provide a low-threshold, easy access intervention to patients with excessive worry, irrespective of primary diagnosis. Clinical implications are discussed.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"41 ","pages":"Article 100842"},"PeriodicalIF":3.6,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-03DOI: 10.1016/j.invent.2025.100841
Ludwig Franke Föyen , Emma Zapel , Mats Lekander , Erik Hedman-Lagerlöf , Elin Lindsäter
Background
The use of artificial intelligence for psychological advice shows promise for enhancing accessibility and reducing costs, but it remains unclear whether AI-generated advice can match the quality and empathy of experts.
Method
In a blinded, comparative cross-sectional design, licensed psychologists and psychotherapists assessed the quality, empathy, and authorship of psychological advice, which was either AI-generated or authored by experts.
Results
AI-generated responses were rated significantly more favorable for emotional (OR = 1.79, 95 % CI [1.1, 2.93], p = .02) and motivational empathy (OR = 1.84, 95 % CI [1.12, 3.04], p = .02). Ratings for scientific quality (p = .10) and cognitive empathy (p = .08) were comparable to expert advice. Participants could not distinguish between AI- and expert-authored advice (p = .27), but perceived expert authorship was associated with more favorable ratings across these measures (ORs for perceived AI vs. perceived expert ranging from 0.03 to 0.15, all p < .001). For overall preference, AI-authored advice was favored when assessed blindly based on its actual source (β = 6.96, p = .002). Nevertheless, advice perceived as expert-authored was also strongly preferred (β = 6.26, p = .001), with 93.55 % of participants preferring the advice they believed came from an expert, irrespective of its true origin.
Conclusions
AI demonstrates potential to match expert performance in asynchronous written psychological advice, but biases favoring perceived expert authorship may hinder its broader acceptance. Mitigating these biases and evaluating AI's trustworthiness and empathy are important next steps for safe and effective integration of AI in clinical practice.
人工智能在心理咨询方面的应用有望提高可及性并降低成本，但目前尚不清楚人工智能生成的建议是否能与专家的质量和同理心相媲美。方法采用盲法比较横断面设计，持牌心理学家和心理治疗师评估了人工智能生成或专家撰写的心理建议的质量、同理心和作者身份。结果人工智能产生的反应在情感共情（OR = 1.79, 95% CI [1.1, 2.93], p = 0.02）和动机共情（OR = 1.84, 95% CI [1.12, 3.04], p = 0.02）方面显著更有利。科学质量评分（p = 0.10）和认知同理心评分（p = 0.08）与专家建议相当。参与者无法区分人工智能和专家撰写的建议（p = 0.27），但感知到的专家撰写与这些措施中更有利的评分相关(感知到的人工智能与感知到的专家的or范围从0.03到0.15，所有p <；措施)。就总体偏好而言，人工智能撰写的建议在基于其实际来源进行盲目评估时更受青睐（β = 6.96, p = 0.002）。然而，被认为是专家撰写的建议也被强烈偏爱（β = 6.26, p = .001）， 93.55%的参与者更喜欢他们认为来自专家的建议，而不管其真实来源如何。结论：ai在异步书面心理咨询中具有与专家表现相匹配的潜力，但对专家作者的偏见可能会阻碍其被广泛接受。减轻这些偏见，评估人工智能的可信度和同理心，是将人工智能安全有效地整合到临床实践中的重要下一步。
{"title":"Artificial intelligence vs. human expert: Licensed mental health clinicians' blinded evaluation of AI-generated and expert psychological advice on quality, empathy, and perceived authorship","authors":"Ludwig Franke Föyen , Emma Zapel , Mats Lekander , Erik Hedman-Lagerlöf , Elin Lindsäter","doi":"10.1016/j.invent.2025.100841","DOIUrl":"10.1016/j.invent.2025.100841","url":null,"abstract":"<div><h3>Background</h3><div>The use of artificial intelligence for psychological advice shows promise for enhancing accessibility and reducing costs, but it remains unclear whether AI-generated advice can match the quality and empathy of experts.</div></div><div><h3>Method</h3><div>In a blinded, comparative cross-sectional design, licensed psychologists and psychotherapists assessed the quality, empathy, and authorship of psychological advice, which was either AI-generated or authored by experts.</div></div><div><h3>Results</h3><div>AI-generated responses were rated significantly more favorable for emotional (OR = 1.79, 95 % CI [1.1, 2.93], <em>p</em> = .02) and motivational empathy (OR = 1.84, 95 % CI [1.12, 3.04], <em>p</em> = .02). Ratings for scientific quality (<em>p</em> = .10) and cognitive empathy (<em>p</em> = .08) were comparable to expert advice. Participants could not distinguish between AI- and expert-authored advice (<em>p</em> = .27), but <em>perceived</em> expert authorship was associated with more favorable ratings across these measures (ORs for perceived AI vs. perceived expert ranging from 0.03 to 0.15, all <em>p</em> < .001). For overall preference, AI-authored advice was favored when assessed blindly based on its actual source (<em>β</em> = 6.96, <em>p</em> = .002). Nevertheless, advice <em>perceived</em> as expert-authored was also strongly preferred (<em>β</em> = 6.26, <em>p</em> = .001), with 93.55 % of participants preferring the advice they believed came from an expert, irrespective of its true origin.</div></div><div><h3>Conclusions</h3><div>AI demonstrates potential to match expert performance in asynchronous written psychological advice, but biases favoring perceived expert authorship may hinder its broader acceptance. Mitigating these biases and evaluating AI's trustworthiness and empathy are important next steps for safe and effective integration of AI in clinical practice.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"41 ","pages":"Article 100841"},"PeriodicalIF":3.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Co-design methods offer an opportunity to meaningfully involve young people in research to ensure that designed supports are useable and responsive to their needs. However, how co-design is currently being applied with young people in the digital mental health field is unclear. This review aimed to critically synthesise the use of co-design with young people to design or modify digital mental health interventions and supports. Six databases were searched for empirical papers published in English from 2012 onwards. Papers were included if they reported on young people aged up to 25 years of age who were involved in the co-design of an online mental health intervention or support. A narrative synthesis of 30 papers meeting these specific criteria was completed. The results highlighted an interchangeable and inconsistent terminology used to described co-design and related approaches across papers. The level of inclusion of young people varied and there was a lack of consideration for power dynamics. Future research should aim to establish a clear and consistent definition and terminology for co-design along with a rigorous gold-standard framework for reporting co-design in order to ensure the process is being carried out in line with its original purpose. Implications for research and practice in the youth co-design field are discussed.
{"title":"The use of co-design with young people for digital mental health support development: A systematic review","authors":"Órla McGovern, Shauna Glennon, Isobel Walsh, Pamela Gallagher, Darragh McCashin","doi":"10.1016/j.invent.2025.100835","DOIUrl":"10.1016/j.invent.2025.100835","url":null,"abstract":"<div><div>Co-design methods offer an opportunity to meaningfully involve young people in research to ensure that designed supports are useable and responsive to their needs. However, how co-design is currently being applied with young people in the digital mental health field is unclear. This review aimed to critically synthesise the use of co-design with young people to design or modify digital mental health interventions and supports. Six databases were searched for empirical papers published in English from 2012 onwards. Papers were included if they reported on young people aged up to 25 years of age who were involved in the co-design of an online mental health intervention or support. A narrative synthesis of 30 papers meeting these specific criteria was completed. The results highlighted an interchangeable and inconsistent terminology used to described co-design and related approaches across papers. The level of inclusion of young people varied and there was a lack of consideration for power dynamics. Future research should aim to establish a clear and consistent definition and terminology for co-design along with a rigorous gold-standard framework for reporting co-design in order to ensure the process is being carried out in line with its original purpose. Implications for research and practice in the youth co-design field are discussed.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"41 ","pages":"Article 100835"},"PeriodicalIF":3.6,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-23DOI: 10.1016/j.invent.2025.100836
Anna-Carlotta Zarski
{"title":"ISRII 2025: Advancing equity in digital interventions across the lifespan - an introduction to this year's conference in San Diego, CA — August 4–7, 2025","authors":"Anna-Carlotta Zarski","doi":"10.1016/j.invent.2025.100836","DOIUrl":"10.1016/j.invent.2025.100836","url":null,"abstract":"","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"41 ","pages":"Article 100836"},"PeriodicalIF":4.1,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Students often report depression and stress symptomatology but may differ in their symptoms and their symptom-specific changes during interventions. This study adopted a symptom-specific approach and examined 1) individual symptoms in students experiencing mild to severe depression symptomatology and 2) changes in individual symptoms during a guided, internet-based intervention. We zoomed in on how these (changes in) symptoms were related to each other and to (changes in) overall quality of life.
Methods
This study included 1816 students with mild to severe baseline depression symptomatology, of which 412 activated their account for an eight-week, guided, internet-based Cognitive Behavioural Therapy intervention (Moodpep) and completed the post-treatment assessment. Depression symptomatology was assessed with the Patient Health Questionnaire, stress symptomatology with the Perceived Stress Scale and overall quality of life with a single item from the Mental Health Quality of Life questionnaire. Network estimations were conducted to examine the interrelations of (changes in) symptoms.
Results
Mean scores of baseline symptoms differed substantially, and network estimations showed multiple positive connections across symptoms and negative connections of symptoms with overall quality of life. During the intervention, all symptoms reduced significantly, although with differential magnitude, and network estimations showed that changes in symptoms were differentially related to other changes in symptoms and changes in overall quality of life.
Conclusions
Our findings highlight the importance of considering individual symptoms and their interrelations as a more complete and nuanced measure for 1) the heterogeneity of baseline symptomatology and 2) the heterogeneity of changes in symptomatology during an intervention.
{"title":"Symptom heterogeneity in students with mild to severe depression symptomatology and their differential symptom-specific changes during an internet-based, guided cognitive behavioural therapy intervention","authors":"Lynn Boschloo , Jasmijn Wijnands , Nadia Garnefski , Vivian Kraaij , Petra Hurks , Danielle Remmerswaal , Reinout W. Wiers , Sascha Struijs , Elske Salemink","doi":"10.1016/j.invent.2025.100834","DOIUrl":"10.1016/j.invent.2025.100834","url":null,"abstract":"<div><h3>Background</h3><div>Students often report depression and stress symptomatology but may differ in their symptoms and their symptom-specific changes during interventions. This study adopted a symptom-specific approach and examined 1) individual symptoms in students experiencing mild to severe depression symptomatology and 2) changes in individual symptoms during a guided, internet-based intervention. We zoomed in on how these (changes in) symptoms were related to each other and to (changes in) overall quality of life.</div></div><div><h3>Methods</h3><div>This study included 1816 students with mild to severe baseline depression symptomatology, of which 412 activated their account for an eight-week, guided, internet-based Cognitive Behavioural Therapy intervention (<em>Moodpep</em>) and completed the post-treatment assessment. Depression symptomatology was assessed with the Patient Health Questionnaire, stress symptomatology with the Perceived Stress Scale and overall quality of life with a single item from the Mental Health Quality of Life questionnaire. Network estimations were conducted to examine the interrelations of (changes in) symptoms.</div></div><div><h3>Results</h3><div>Mean scores of baseline symptoms differed substantially, and network estimations showed multiple positive connections across symptoms and negative connections of symptoms with overall quality of life. During the intervention, all symptoms reduced significantly, although with differential magnitude, and network estimations showed that changes in symptoms were differentially related to other changes in symptoms and changes in overall quality of life.</div></div><div><h3>Conclusions</h3><div>Our findings highlight the importance of considering individual symptoms and their interrelations as a more complete and nuanced measure for 1) the heterogeneity of baseline symptomatology and 2) the heterogeneity of changes in symptomatology during an intervention.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"41 ","pages":"Article 100834"},"PeriodicalIF":3.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-15DOI: 10.1016/j.invent.2025.100833
Hilary Weingarden , Xiang Meng , Michael Armey , Jukka-Pekka Onnela , Adam Jaroszewski , Caroline H. Armstrong , Sabine Wilhelm
Body dysmorphic disorder (BDD) is a debilitating and common psychiatric illness associated with high rates of suicide and substance use disorders. Negative emotions – particularly shame and anxiety – are elevated in BDD and correlate with suicide risk and substance use. It is critical to have reliable and valid tools to assess negative emotions in BDD. Retrospective self-reports are subject to recall biases, average one's experiences over broad time frames, and are burdensome to complete. Alternatively, sensor-based digital phenotyping has potential to yield low-burden emotion assessment within acute time frames. This study aimed to use smartphone sensor data (GPS, accelerometer, collected over 3 months) to predict next-day peak shame, anxiety, and general negative emotion states (collected via 28 days of ecological momentary assessment) in 83 adults with BDD. We tested cumulative link mixed models [CLMM]) and random forest [RF] models. RFs outperformed CLMMs across prediction performance metrics and had overall prediction accuracies (i.e., proportion of predicted scores that exactly matched actual scores, out of total predictions) of 42.1–50.0 %, versus 10.9–20.2 % for CLMMs. Binary predictive performance at high levels of negative emotion was moderate. Developing unobtrusive methods for predicting shame, anxiety, and general negative emotion states over acute time frames using smartphone sensor data can enable just-in-time intervention opportunities, as a future step to reduce risk for suicide and substance use in BDD. Models might be strengthened with larger samples, data collected over longer time frames, and incorporation of wearable-based physiological data.
{"title":"Predicting the strength of next-day negative emotion states in body dysmorphic disorder using passive smartphone data: An intensive longitudinal assessment study","authors":"Hilary Weingarden , Xiang Meng , Michael Armey , Jukka-Pekka Onnela , Adam Jaroszewski , Caroline H. Armstrong , Sabine Wilhelm","doi":"10.1016/j.invent.2025.100833","DOIUrl":"10.1016/j.invent.2025.100833","url":null,"abstract":"<div><div>Body dysmorphic disorder (BDD) is a debilitating and common psychiatric illness associated with high rates of suicide and substance use disorders. Negative emotions – particularly shame and anxiety – are elevated in BDD and correlate with suicide risk and substance use. It is critical to have reliable and valid tools to assess negative emotions in BDD. Retrospective self-reports are subject to recall biases, average one's experiences over broad time frames, and are burdensome to complete. Alternatively, sensor-based digital phenotyping has potential to yield low-burden emotion assessment within acute time frames. This study aimed to use smartphone sensor data (GPS, accelerometer, collected over 3 months) to predict next-day peak shame, anxiety, and general negative emotion states (collected via 28 days of ecological momentary assessment) in 83 adults with BDD. We tested cumulative link mixed models [CLMM]) and random forest [RF] models. RFs outperformed CLMMs across prediction performance metrics and had overall prediction accuracies (i.e., proportion of predicted scores that exactly matched actual scores, out of total predictions) of 42.1–50.0 %, versus 10.9–20.2 % for CLMMs. Binary predictive performance at high levels of negative emotion was moderate. Developing unobtrusive methods for predicting shame, anxiety, and general negative emotion states over acute time frames using smartphone sensor data can enable just-in-time intervention opportunities, as a future step to reduce risk for suicide and substance use in BDD. Models might be strengthened with larger samples, data collected over longer time frames, and incorporation of wearable-based physiological data.</div><div><strong>Trial Registration:</strong> <span><span>ClinicalTrials.gov</span><svg><path></path></svg></span> Identifier: <span><span>NCT04254575</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"40 ","pages":"Article 100833"},"PeriodicalIF":3.6,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-15DOI: 10.1016/j.invent.2025.100832
Luana Lenzi , Aaliya Ibrahim , David Brough , Alexander Thompson
Background and aims
Alcohol Use Disorders (AUD) are associated with numerous negative health and societal consequences. Relapse is common among individuals with AUD following discharge from treatment programs, often due to a lack of continuing care and barriers to accessing in-person interventions. Digital interventions may have the potential to overcome these barriers. This systematic review aims to assess the efficacy of digital interventions in supporting abstinence following AUD treatment.
Methods
We searched the databases Embase, Medline, and APA PsycInfo for randomized controlled trials (RCTs) that evaluated digital interventions designed to support alcohol-dependent individuals to maintain abstinence after discharge from treatment programs. Studies in which participants were not abstinent at the time of randomization were excluded.
Results
Eleven studies were identified, with interventions including text messages, smartphones apps, wireless breathalysers, telephone-based support, and e-books. Four studies (2 using apps and 2 using supportive text messages) reported statistically significant results in prolonging abstinence. However, one intervention using a cue exposure therapy (CET) app found increased relapse rates in all groups. The risk of bias across studies ranged from moderate to high.
Conclusion
There is insufficient evidence to support the efficacy of digital interventions in maintaining abstinence after AUD treatment discharge. While digital interventions may improve the accessibility and uptake of aftercare services to prevent relapse, further research is needed.
{"title":"Digital interventions for supporting alcohol abstinence in aftercare – a systematic review","authors":"Luana Lenzi , Aaliya Ibrahim , David Brough , Alexander Thompson","doi":"10.1016/j.invent.2025.100832","DOIUrl":"10.1016/j.invent.2025.100832","url":null,"abstract":"<div><h3>Background and aims</h3><div>Alcohol Use Disorders (AUD) are associated with numerous negative health and societal consequences. Relapse is common among individuals with AUD following discharge from treatment programs, often due to a lack of continuing care and barriers to accessing in-person interventions. Digital interventions may have the potential to overcome these barriers. This systematic review aims to assess the efficacy of digital interventions in supporting abstinence following AUD treatment.</div></div><div><h3>Methods</h3><div>We searched the databases <em>Embase, Medline,</em> and <em>APA PsycInfo</em> for randomized controlled trials (RCTs) that evaluated digital interventions designed to support alcohol-dependent individuals to maintain abstinence after discharge from treatment programs. Studies in which participants were not abstinent at the time of randomization were excluded.</div></div><div><h3>Results</h3><div>Eleven studies were identified, with interventions including text messages, smartphones apps, wireless breathalysers, telephone-based support, and e-books. Four studies (2 using apps and 2 using supportive text messages) reported statistically significant results in prolonging abstinence. However, one intervention using a cue exposure therapy (CET) app found increased relapse rates in all groups. The risk of bias across studies ranged from moderate to high.</div></div><div><h3>Conclusion</h3><div>There is insufficient evidence to support the efficacy of digital interventions in maintaining abstinence after AUD treatment discharge. While digital interventions may improve the accessibility and uptake of aftercare services to prevent relapse, further research is needed.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"40 ","pages":"Article 100832"},"PeriodicalIF":3.6,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-14DOI: 10.1016/j.invent.2025.100831
Jurrijn A. Koelen , Lisa de Koning , Matilda K. Nottage , Anke M. Klein , Claudia M. van der Heijde , Peter Vonk , Reinout W. Wiers
Online cognitive behavioral therapy (iCBT) is a promising treatment for depression and anxiety among university students but faces high dropout rates. Understanding the reasons behind dropout or completion can help improve the implementation of iCBT in educational settings. Semi-structured phone interviews were conducted with 32 students who dropped out early (n = 9), midway (n = 12), or completed (n = 11) guided or unguided iCBT in the context of a randomized controlled trial. Data were analyzed using Braun and Clarke's (2012) thematic analysis. Common themes among dropouts included personal factors (like competing priorities), perceived difficulty or redundancy of the intervention, and lack of human interaction. Early dropouts uniquely cited disbelief in the intervention's efficacy and preference for other mental health support. Midway dropouts mentioned issues with the interactivity, feedback, content, perceived effectiveness, and lack of personalization. Completers had positive initial impressions, valued the online format, found the exercises and guidance helpful, and felt cared for. The themes identified among participants who dropped out from or completed the iCBT intervention provide valuable insights into factors which may be of importance for retention. Implications regarding setting expectations, participant selection, interactive functionalities, personalized feedback, and the role of therapist guidance are discussed.
{"title":"Dropout and completion in iCBT for university students: Insights from a thematic analysis","authors":"Jurrijn A. Koelen , Lisa de Koning , Matilda K. Nottage , Anke M. Klein , Claudia M. van der Heijde , Peter Vonk , Reinout W. Wiers","doi":"10.1016/j.invent.2025.100831","DOIUrl":"10.1016/j.invent.2025.100831","url":null,"abstract":"<div><div>Online cognitive behavioral therapy (iCBT) is a promising treatment for depression and anxiety among university students but faces high dropout rates. Understanding the reasons behind dropout or completion can help improve the implementation of iCBT in educational settings. Semi-structured phone interviews were conducted with 32 students who dropped out early (<em>n</em> = 9), midway (<em>n</em> = 12), or completed (<em>n</em> = 11) guided or unguided iCBT in the context of a randomized controlled trial. Data were analyzed using <span><span>Braun and Clarke's (2012)</span></span> thematic analysis. Common themes among dropouts included personal factors (like competing priorities), perceived difficulty or redundancy of the intervention, and lack of human interaction. Early dropouts uniquely cited disbelief in the intervention's efficacy and preference for other mental health support. Midway dropouts mentioned issues with the interactivity, feedback, content, perceived effectiveness, and lack of personalization. Completers had positive initial impressions, valued the online format, found the exercises and guidance helpful, and felt cared for. The themes identified among participants who dropped out from or completed the iCBT intervention provide valuable insights into factors which may be of importance for retention. Implications regarding setting expectations, participant selection, interactive functionalities, personalized feedback, and the role of therapist guidance are discussed.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"40 ","pages":"Article 100831"},"PeriodicalIF":3.6,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-19DOI: 10.1016/j.invent.2025.100830
Sara Winter , Sara Crocker , Tricia Rolls , Deanne Curtin , Jessica Haratsis , Irene Szollosi
In order to ensure access to insomnia treatment in our public health environment of increasing patient acuity, increasing demand and health care costs, we need to innovate and implement systematised models of care to achieve better outcomes and efficiencies.
The design of a new Stepped Care treatment model in the multidisciplinary sleep disorders service with consumer and stakeholder engagement is described. Patients, their referrers and staff were surveyed to explore their views and preferences towards Stepped Care, including digital transformation. A consensus group workshop using the Nominal Group Technique was undertaken with the multidisciplinary team to develop the model of care.
The team endorsed a hierarchy of treatment steps beginning with digital intervention, group and trainee interventions as first line, escalating to more intensive 1:1 ‘upstream’ for higher acuity presentations. Referrer surveys highlighted the need for education in primary care settings about the availability of evidence-based internet treatment options. While few patients were aware of the availability of digital insomnia intervention, they were largely supportive of digital transformation. Barriers and risks to the Stepped Care approach were identified which informed the refinement of the treatment pathway.
Stepped Care treatment models offer adaptability and flexibility, allowing for adjustments in interventions based on patients' response to treatment, and preventing unnecessary escalation of care while reducing costs and improving efficiencies.
{"title":"Stepped care and digital intervention service model design in the multidisciplinary sleep service","authors":"Sara Winter , Sara Crocker , Tricia Rolls , Deanne Curtin , Jessica Haratsis , Irene Szollosi","doi":"10.1016/j.invent.2025.100830","DOIUrl":"10.1016/j.invent.2025.100830","url":null,"abstract":"<div><div>In order to ensure access to insomnia treatment in our public health environment of increasing patient acuity, increasing demand and health care costs, we need to innovate and implement systematised models of care to achieve better outcomes and efficiencies.</div><div>The design of a new Stepped Care treatment model in the multidisciplinary sleep disorders service with consumer and stakeholder engagement is described. Patients, their referrers and staff were surveyed to explore their views and preferences towards Stepped Care, including digital transformation. A consensus group workshop using the Nominal Group Technique was undertaken with the multidisciplinary team to develop the model of care.</div><div>The team endorsed a hierarchy of treatment steps beginning with digital intervention, group and trainee interventions as first line, escalating to more intensive 1:1 ‘upstream’ for higher acuity presentations. Referrer surveys highlighted the need for education in primary care settings about the availability of evidence-based internet treatment options. While few patients were aware of the availability of digital insomnia intervention, they were largely supportive of digital transformation. Barriers and risks to the Stepped Care approach were identified which informed the refinement of the treatment pathway.</div><div>Stepped Care treatment models offer adaptability and flexibility, allowing for adjustments in interventions based on patients' response to treatment, and preventing unnecessary escalation of care while reducing costs and improving efficiencies.</div></div>","PeriodicalId":48615,"journal":{"name":"Internet Interventions-The Application of Information Technology in Mental and Behavioural Health","volume":"40 ","pages":"Article 100830"},"PeriodicalIF":3.6,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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