Satisfaction and Acceptability Ratings of a Web-Based Self-help Intervention for Depression: Retrospective Cross-sectional Study From a Resource-Limited Country.

BACKGROUND: Web-based interventions are at an early stage in non-English-speaking low- and middle-income countries, where they remain scarce. Help for Depression (HDep) is one of the few unguided web-based interventions available in Latin America. The results of a use/usability analysis of the original version served as the basis for generating a more user-friendly second version. OBJECTIVE: The aim of this study is to explore participants' satisfaction and acceptability for the second version of HDep. METHODS: A retrospective cross-sectional design was used. An email invitation to complete a web-based survey was sent to all people who accessed HDep in 2018. The questionnaire included satisfaction and acceptability scales and open-ended questions. Complete questionnaires were retrieved from 191 participants: 35.1% (67/191) from those who visited only the home page (home page users [HPUs]) and 6.47% (124/1916) from those who registered to use the program (program users [PUs]). RESULTS: In all groups, users experienced high levels of depressive symptoms (189/191, 98.9%; Center for Epidemiological Studies Scale-Depression >16). Moderate levels of satisfaction (HPUs: mean 21.9, SD 6.7; PUs: mean 21.1, SD 5.8; range: 8-32) and acceptability (HPUs: mean 13.8, SD 3.9; PUs: mean 13.9, SD 3.2; range: 5-20) were found in both groups. Logistic regression analyses showed that among HPUs, women were more satisfied with HDep (odds ratio [OR] 3.4, 95% CI 1.1-10.0), whereas among PUs, older respondents (OR 1.04, 95% CI 1.01-1.08), those with paid work (OR 3.1, 95% CI 2.4-7.6), those who had not been in therapy (OR 2.42, 95% CI 1.09-5.98), and those who had not attempted suicide (OR 3.4, 95% CI 1.1-11.1) showed higher satisfaction. None of the sociodemographic/mental health variables distinguished the acceptability ratings among HPUs. Among PUs, those with paid work (OR 2.5, 95% CI 1.1-5.5), those who had not been in therapy (OR 3.1, 95% CI 1.3-7.3), those without disability (OR 2.9, 95% CI 1.3-6.6), and those who had not attempted suicide (OR 2.6, 95% CI 1.0-6.6) showed higher acceptability. CONCLUSIONS: HDep has good levels of satisfaction and acceptability for approximately half of its users, and the information provided by respondents suggested feasible ways to remedy some of the deficiencies. This qualitative-quantitative study from a low- to middle-income, non-English-speaking country adds to existing knowledge regarding acceptance and satisfaction with web-based interventions for depression in resource-limited countries. This information is important for the creation and adaptation of web-based interventions in low- and middle-income countries, where access to treatment is a major concern, and web-based prevention and treatment programs can help deliver evidence-based alternatives. It is necessary to document the pitfalls, strengths, and challenges of such interventions in this context. Understanding how users perceive an intervention might suggest modifications to increase adherence.

Effectiveness of an Internet-Based Machine-Guided Stress Management Program Based on Cognitive Behavioral Therapy for Improving Depression Among Workers: Protocol for a Randomized Controlled Trial.

BACKGROUND: The effect of an unguided internet-based cognitive behavioral therapy (iCBT) stress management program on depression may be enhanced by applying artificial intelligence (AI) technologies to guide participants adopting the program. OBJECTIVE: The aim of this study is to describe a research protocol to investigate the effect of a newly developed iCBT stress management program adopting AI technologies on improving depression among healthy workers during the COVID-19 pandemic. METHODS: This study is a two-arm, parallel, randomized controlled trial. Participants (N=1400) will be recruited, and those who meet the inclusion criteria will be randomly allocated to the intervention or control (treatment as usual) group. A 6-week, six-module, internet-based stress management program, SMART-CBT, has been developed that includes machine-guided exercises to help participants acquire CBT skills, and it applies machine learning and deep learning technologies. The intervention group will participate in the program for 10 weeks. The primary outcome, depression, will be measured using the Beck Depression Inventory II at baseline and 3- and 6-month follow-ups. A mixed model repeated measures analysis will be used to test the intervention effect (group × time interactions) in the total sample (universal prevention) on an intention-to-treat basis. RESULTS: The study was at the stage of recruitment of participants at the time of submission. The data analysis related to the primary outcome will start in January 2022, and the results might be published in 2022 or 2023. CONCLUSIONS: This is the first study to investigate the effectiveness of a fully automated machine-guided iCBT program for improving subthreshold depression among workers using a randomized controlled trial design. The study will explore the potential of a machine-guided stress management program that can be disseminated online to a large number of workers with minimal cost in the post-COVID-19 era. TRIAL REGISTRATION: UMIN Clinical Trials Registry（UMIN-CTR) UMIN000043897; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000050125. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30305.

Results from a trial of an unsupported internet intervention for depressive symptoms.

Internet interventions provide an option for those who either cannot or choose not to engage with traditional treatments. Most research on internet interventions involves guided or supported interventions. However, unsupported interventions offer considerably more scalability and cost-effectiveness, which makes them attractive for large-scale implementation. In this study, 309 participants recruited via Google AdWords entered an unsupported cognitive-behavioral internet intervention for depressive symptoms. To maximize the ecological validity of the study, participants received no incentives or live contact with study personnel. Furthermore, the study was open to individuals at any level of depressive symptoms, and all participants received the active intervention. The main outcome measures were depressive symptom level and self-efficacy in managing depressive symptoms. At follow-up, depression scores were significantly lower than baseline scores at each follow-up point (1, 2, 4, and 7 months), with pre-post effect sizes ranging from medium to large. Follow-up depression self-efficacy scores were significantly higher than baseline scores at each follow-up point, with pre-post effect sizes in the medium range. The results remained significant when analyzing only participants with depression scores indicative of a presence of a major depressive episode; results likewise remained significant when employing the conservative last observation carried forward convention, even in the presence of high attrition observed in this study. The results illustrate the potential of unsupported internet intervention to address the health needs of the global community.