FitMindKit: Randomised controlled trial of an automatically tailored online program for mood, anxiety, substance use and suicidality

被引:37
作者
Batterham, Philip J. [1 ]
Calear, Alison L. [1 ]
Farrer, Louise [1 ]
McCallum, Sonia M. [1 ]
Cheng, Vanessa Wan Sze [2 ]
机构
[1] Australian Natl Univ, Res Sch Populat Hlth, Mental Hlth Res Ctr, Canberra, ACT, Australia
[2] Univ Sydney, Brain & Mind Ctr, Sydney, NSW, Australia
来源
INTERNET INTERVENTIONS-THE APPLICATION OF INFORMATION TECHNOLOGY IN MENTAL AND BEHAVIOURAL HEALTH | 2018年 / 12卷
基金
澳大利亚国家健康与医学研究理事会;
关键词
Comorbidity; Depression; Anxiety; Substance use; Suicidal ideation; Tailored interventions; COGNITIVE-BEHAVIOR THERAPY; 2007; NATIONAL-SURVEY; MENTAL-HEALTH; INTERNET TREATMENT; DEPRESSION; DISORDERS; INTERVENTIONS; PREVENTION; SCREENER; ACCURATE;
D O I
10.1016/j.invent.2017.08.002
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
Purpose: Online mental health programs can be effective in reducing symptoms of depression, anxiety disorders, substance use and suicidal ideation. However, most existing e-mental health programs focus on a single domain of mental health, neglecting comorbidity. Furthermore, few programs are tailored to the symptom patterns of the individual user. FitMindKit was designed to overcome the gaps of existing e-mental health programs, providing tailored, transdiagnostic therapeutic content to address a range of comorbid mental health symptoms. A trial was conducted to test the program's efficacy. Methods: Australian adults with elevated symptoms of depression, anxiety, suicidal ideation and/or substance use were recruited through social media, with n = 194 randomised into a fully-automated trial of a 10-day brief intervention. Participants were randomly allocated to receive FitMindKit tailored to their symptoms, an untailored generic version of FitMindKit, or an attention control. Results: Mixed model repeated measures ANOVA indicated that participants in both FitMindKit and the attention control had significant reductions in symptom composite scores. Effects were not significantly greater in the FitMindKit program relative to control, either at post-test or 3-month follow-up. No effects were detected for specific decreases in depression, generalized anxiety, social anxiety, panic, suicidal ideation or alcohol/substance use. There were no significant differences between the tailored and static versions in effectiveness or adherence. Participants in the tailored and static conditions were more satisfied than in the control condition, with some evidence favouring the tailored condition. High attrition reduced power to find effects. Conclusions: FitMindKit provides a model for addressing comorbid mental health symptoms in an online program, using automated tailoring to symptom patterns. Modifications to the program are recommended, along with the need for larger trials to test the effects of tailoring on mental health outcomes.
引用
收藏
页码:91 / 99
页数:9
相关论文
共 43 条
[1]  
Andersson Gerhard, 2011, Cognitive Behaviour Therapy, V40, P57, DOI 10.1080/16506073.2010.529457
[2]  
[Anonymous], 2011, GAME DESIGN ELEMENTS
[3]  
[Anonymous], COMMUNITY BASED VALI
[4]  
[Anonymous], DIGIT HLTH
[5]  
[Anonymous], LECT NOTES COMPUT SC
[6]  
[Anonymous], PLOS ONE
[7]   Cohort Profile: The PATH through life project [J].
Anstey, Kaarin J. ;
Christensen, Helen ;
Butterworth, Peter ;
Easteal, Simon ;
Mackinnon, Andrew ;
Jacomb, Trish ;
Maxwell, Karen ;
Rodgers, Bryan ;
Windsor, Tim ;
Cherbuin, Nicolas ;
Jorm, Anthony F. .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2012, 41 (04) :951-960
[8]  
Babor TF., 1989, AUDIT ALCOHOL USE DI
[9]   Preferences for Internet-Based Mental Health Interventions in an Adult Online Sample: Findings From an Online Community Survey [J].
Batterham, Philip J. ;
Calear, Alison L. .
JMIR MENTAL HEALTH, 2017, 4 (02)
[10]   The Distress Questionnaire-5: Population screener for psychological distress was more accurate than the K6/K10 [J].
Batterham, Philip J. ;
Sunderland, Matthew ;
Carragher, Natacha ;
Calear, Alison L. ;
Mackinnon, Andrew J. ;
Slade, Tim .
JOURNAL OF CLINICAL EPIDEMIOLOGY, 2016, 71 :35-42