Global Mental Health: Five Areas for Value-Driven Training Innovation.

OBJECTIVE: In the field of global mental health, there is a need for identifying core values and competencies to guide training programs in professional practice as well as in academia. This paper presents the results of interdisciplinary discussions fostered during an annual meeting of the Society for the Study of Psychiatry and Culture to develop recommendations for value-driven innovation in global mental health training. METHODS: Participants (n = 48), who registered for a dedicated workshop on global mental health training advertised in conference proceedings, included both established faculty and current students engaged in learning, practice, and research. They proffered recommendations in five areas of training curriculum: values, competencies, training experiences, resources, and evaluation. RESULTS: Priority values included humility, ethical awareness of power differentials, collaborative action, and "deep accountability" when working in low-resource settings in low- and middle-income countries and high-income countries. Competencies included flexibility and tolerating ambiguity when working across diverse settings, the ability to systematically evaluate personal biases, historical and linguistic proficiency, and evaluation skills across a range of stakeholders. Training experiences included didactics, language training, self-awareness, and supervision in immersive activities related to professional or academic work. Resources included connections with diverse faculty such as social scientists and mentors in addition to medical practitioners, institutional commitment through protected time and funding, and sustainable collaborations with partners in low resource settings. Finally, evaluation skills built upon community-based participatory methods, 360-degree feedback from partners in low-resource settings, and observed structured clinical evaluations (OSCEs) with people of different cultural backgrounds. CONCLUSIONS: Global mental health training, as envisioned in this workshop, exemplifies an ethos of working through power differentials across clinical, professional, and social contexts in order to form longstanding collaborations. If incorporated into the ACGME/ABPN Psychiatry Milestone Project, such recommendations will improve training gained through international experiences as well as the everyday training of mental health professionals, global health practitioners, and social scientists.

The lung cancer exercise training study: a randomized trial of aerobic training, resistance training, or both in postsurgical lung cancer patients: rationale and design.

BACKGROUND: The Lung Cancer Exercise Training Study (LUNGEVITY) is a randomized trial to investigate the efficacy of different types of exercise training on cardiorespiratory fitness (VO2peak), patient-reported outcomes, and the organ components that govern VO2peak in post-operative non-small cell lung cancer (NSCLC) patients. METHODS/DESIGN: Using a single-center, randomized design, 160 subjects (40 patients/study arm) with histologically confirmed stage I-IIIA NSCLC following curative-intent complete surgical resection at Duke University Medical Center (DUMC) will be potentially eligible for this trial. Following baseline assessments, eligible participants will be randomly assigned to one of four conditions: (1) aerobic training alone, (2) resistance training alone, (3) the combination of aerobic and resistance training, or (4) attention-control (progressive stretching). The ultimate goal for all exercise training groups will be 3 supervised exercise sessions per week an intensity above 70% of the individually determined VO2peak for aerobic training and an intensity between 60 and 80% of one-repetition maximum for resistance training, for 30-45 minutes/session. Progressive stretching will be matched to the exercise groups in terms of program length (i.e., 16 weeks), social interaction (participants will receive one-on-one instruction), and duration (30-45 mins/session). The primary study endpoint is VO2peak. Secondary endpoints include: patient-reported outcomes (PROs) (e.g., quality of life, fatigue, depression, etc.) and organ components of the oxygen cascade (i.e., pulmonary function, cardiac function, skeletal muscle function). All endpoints will be assessed at baseline and postintervention (16 weeks). Substudies will include genetic studies regarding individual responses to an exercise stimulus, theoretical determinants of exercise adherence, examination of the psychological mediators of the exercise - PRO relationship, and exercise-induced changes in gene expression. DISCUSSION: VO2peak is becoming increasingly recognized as an outcome of major importance in NSCLC. LUNGEVITY will identify the optimal form of exercise training for NSCLC survivors as well as provide insight into the physiological mechanisms underlying this effect. Overall, this study will contribute to the establishment of clinical exercise therapy rehabilitation guidelines for patients across the entire NSCLC continuum. TRIAL REGISTRATION: NCT00018255.

Rationale and design of the Exercise Intensity Trial (EXCITE): A randomized trial comparing the effects of moderate versus moderate to high-intensity aerobic training in women with operable breast cancer.

BACKGROUND: The Exercise Intensity Trial (EXcITe) is a randomized trial to compare the efficacy of supervised moderate-intensity aerobic training to moderate to high-intensity aerobic training, relative to attention control, on aerobic capacity, physiologic mechanisms, patient-reported outcomes, and biomarkers in women with operable breast cancer following the completion of definitive adjuvant therapy. METHODS/DESIGN: Using a single-center, randomized design, 174 postmenopausal women (58 patients/study arm) with histologically confirmed, operable breast cancer presenting to Duke University Medical Center (DUMC) will be enrolled in this trial following completion of primary therapy (including surgery, radiation therapy, and chemotherapy). After baseline assessments, eligible participants will be randomized to one of two supervised aerobic training interventions (moderate-intensity or moderate/high-intensity aerobic training) or an attention-control group (progressive stretching). The aerobic training interventions will include 150 mins.wk⁻¹ of supervised treadmill walking per week at an intensity of 60%-70% (moderate-intensity) or 60% to 100% (moderate to high-intensity) of the individually determined peak oxygen consumption (VO₂peak) between 20-45 minutes/session for 16 weeks. The progressive stretching program will be consistent with the exercise interventions in terms of program length (16 weeks), social interaction (participants will receive one-on-one instruction), and duration (20-45 mins/session). The primary study endpoint is VO₂peak, as measured by an incremental cardiopulmonary exercise test. Secondary endpoints include physiologic determinants that govern VO₂peak, patient-reported outcomes, and biomarkers associated with breast cancer recurrence/mortality. All endpoints will be assessed at baseline and after the intervention (16 weeks). DISCUSSION: EXCITE is designed to investigate the intensity of aerobic training required to induce optimal improvements in VO₂peak and other pertinent outcomes in women who have completed definitive adjuvant therapy for operable breast cancer. Overall, this trial will inform and refine exercise guidelines to optimize recovery in breast and other cancer survivors following the completion of primary cytotoxic therapy. TRIAL REGISTRATION: NCT01186367.

WriteSim TCExam--an open source text simulation environment for training novice researchers in scientific writing.

BACKGROUND: The ability to write clearly and effectively is of central importance to the scientific enterprise. Encouraged by the success of simulation environments in other biomedical sciences, we developed WriteSim TCExam, an open-source, Web-based, textual simulation environment for teaching effective writing techniques to novice researchers. We shortlisted and modified an existing open source application - TCExam to serve as a textual simulation environment. After testing usability internally in our team, we conducted formal field usability studies with novice researchers. These were followed by formal surveys with researchers fitting the role of administrators and users (novice researchers) RESULTS: The development process was guided by feedback from usability tests within our research team. Online surveys and formal studies, involving members of the Research on Research group and selected novice researchers, show that the application is user-friendly. Additionally it has been used to train 25 novice researchers in scientific writing to date and has generated encouraging results. CONCLUSION: WriteSim TCExam is the first Web-based, open-source textual simulation environment designed to complement traditional scientific writing instruction. While initial reviews by students and educators have been positive, a formal study is needed to measure its benefits in comparison to standard instructional methods.

Using Image Processing Methods to Improve the Detection of Buried Explosive Threats in GPR Data

Current state of the art techniques for landmine detection in ground penetrating radar (GPR) utilize statistical methods to identify characteristics of a landmine response. This research makes use of 2-D slices of data in which subsurface landmine responses have hyperbolic shapes. Various methods from the field of visual image processing are adapted to the 2-D GPR data, producing superior landmine detection results. This research goes on to develop a physics-based GPR augmentation method motivated by current advances in visual object detection. This GPR specific augmentation is used to mitigate issues caused by insufficient training sets. This work shows that augmentation improves detection performance under training conditions that are normally very difficult. Finally, this work introduces the use of convolutional neural networks as a method to learn feature extraction parameters. These learned convolutional features outperform hand-designed features in GPR detection tasks. This work presents a number of methods, both borrowed from and motivated by the substantial work in visual image processing. The methods developed and presented in this work show an improvement in overall detection performance and introduce a method to improve the robustness of statistical classification.