Evaluating the effectiveness and cost-effectiveness of a digital, app-based intervention for depression (VMood) in community-based settings in Vietnam: Protocol for a stepped-wedge randomized controlled trial.

The COVID-19 pandemic has amplified mental health problems and highlighted inequitable gaps in care worldwide. In response there has been an explosion of digital interventions such as smartphone applications ("apps") to extend care. The objective of this trial is to evaluate the effectiveness and cost-effectiveness of a digital depression intervention (VMood), delivered via a smartphone app. VMood is adapted from an in-person intervention that was delivered by non-specialist providers and shown to be effective in the Vietnamese context in our previous trial (2016-2019). A stepped-wedge, randomized controlled trial will be conducted across eight provinces in Vietnam. Adults aged 18 years and over will be recruited through community-based primary care centres and screened for depression using the embedded Patient Health Questionnaire-9 (primary outcome measure). Participants scoring 10-19, indicating depression caseness, will be randomly allocated to the intervention or control group until the target of 336 is reached. Secondary outcome measures will examine the effect of the intervention on commonly co-occuring anxiety, quality of life and work productivity, along with use of alcohol and tobacco products. Assessments will be administered through an online survey platform (REDCap) at baseline, and at every 3 months until 3 months post-intervention. Intervention-group participants will receive VMood for a 3-month period, with online support provided by social workers. Control-group participants will receive a limited version of the app until they cross into the intervention group. Generalized Linear Mixed-effect Models for clustered measures will be used for all outcomes data. We will conduct a cost-effectiveness analysis alongside the trial to capture VMood's costs and benefits. This trial will provide evidence on the effectiveness and cost-effectiveness of a digital mental health intervention adapted from an in-person intervention. This trial will also contribute important information to the growing and promising field of digital mental health. Trail regulation. Registered at ClinicalTrials.gov, identifier [NCT05783531].

A three-dimensional approach to pennation angle estimation for human skeletal muscle.

Pennation angle (PA) is an important property of human skeletal muscle that plays a significant role in determining the force contribution of fascicles to skeletal movement. Two-dimensional (2D) ultrasonography is the most common approach to measure PA. However, in principle, it is challenging to infer knowledge of three-dimensional (3D) architecture from 2D assessment. Furthermore, architectural complexity and variation impose more difficulties on reliable and consistent quantification of PA. Thus, the purpose of our study is to provide accurate insight into the correspondence between 2D assessment and the underlying 3D architecture. To this end, a 3D method was developed to directly quantify PA based on 3D architectural data that were acquired from cadaveric specimens through dissection and digitization. Those data were then assessed two-dimensionally by simulating ultrasound imaging. To achieve consistency over intermuscular variation, our proposed 3D method is based on the geometric analysis of fascicle attachment. Comparative results show a wide range of differences (1.1-47.1%) between 2D and 3D measurements. That is, ultrasound can under- or over-estimate PA, depending on the architecture.

Robust estimation of physiological cross-sectional area and geometric reconstruction for human skeletal muscle.

Understanding muscle architecture is crucial to determining the mechanical function of muscle during body movements, because architectural parameters directly correspond to muscle performance. Accurate parameters are thus essential for reliable simulation. Human cadaveric muscle specimen data provides the anatomical detail needed for in-depth understanding of muscle and accurate parameter estimation. However, as muscle generally has non-uniform architecture, parameter estimation, specifically, physiological cross-sectional area (PCSA), is rarely straightforward. To deal effectively with this non-uniformity, we propose a geometric approach in which a polygon is sought to best approximate the cross-sectional area of each fascicle by accounting for its three-dimensional trajectory and arrangement in the muscle. Those polygons are then aggregated to determine PCSA and volume of muscle. Experiments are run using both synthetic data and muscle specimen data. From comparison of PCSA using synthetic data, we conclude that the proposed method enhances the robustness of PCSA estimation against variation in muscle architecture. Furthermore, we suggest reconstruction methods to extract 3D muscle geometry directly from fascicle data and estimated parameters using the level set method.

Documentation and three-dimensional modelling of human soleus muscle architecture.

The purpose of this study was to visualize and document the architecture of the human soleus muscle throughout its entire volume. The architecture was visualized by creating a three-dimensional (3D) manipulatable computer model of an entire cadaveric soleus, in situ, using B-spline solid to display muscle fiber bundles that had been serially dissected, pinned, and digitized. A database of fiber bundle length and angle of pennation throughout the marginal, posterior, and anterior soleus was compiled. The computer model allowed documentation of the architectural parameters in 3D space, with the angle of pennation being measured relative to the tangent plane of the point of attachment of a fiber bundle. Before this study, the only architectural parameters that have been recorded have been 2D. Three-dimensional reconstruction is an exciting innovation because it makes feasible the creation of an architectural database and allows visualization of each fiber bundle in situ from any perspective. It was concluded that the architecture is non-uniform throughout the volume of soleus. Detailed architectural studies may lead to the development of muscle models that can more accurately predict interaction between muscle parts, force generation, and the effect of pathologic states on muscle function.