American Indian and Alaska Native (AI/AN) people experience high rates of acute, chronic, and intergenerational trauma. Traumatic experiences often increase the risk of both medical and behavioral health problems making primary care settings opportune places to screen for trauma exposure or symptomology. The objective of this study was to determine considerations and recommendations provided by patients, health care providers, health care administrators, and tribal leaders in the development of an adult trauma screening, brief intervention, and referral for treatment process to pilot at two large AI/AN primary care systems. A qualitative and iterative data collection and analysis process was undertaken using a community-based participatory research approach guided by a cross-site steering committee. Twenty-four leaders and providers participated in individual interviews, and 13 patients participated in four focus groups. Data were thematically analyzed to select a trauma screening instrument, develop a screening process, and develop brief intervention materials. The nature of traumas experienced in the AI/AN community, the need to develop trusting patient-provider relationships, and the human resources available at each site drove the screening, brief intervention, and referral process decisions for a future trauma screening pilot in these health systems.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5177536PMC
http://dx.doi.org/10.1007/s11414-016-9519-6DOI Listing

Publication Analysis

Top Keywords

screening intervention
12
primary care
12
trauma screening
12
american indian
8
indian alaska
8
alaska native
8
health systems
8
health care
8
intervention referral
8
trauma
6

Similar Publications

Background: Depression and anxiety disorders frequently co-occur with Type 2 Diabetes Mellitus, leading to poor glycaemic control and quality of life through complex biopsychosocial mechanisms. A dual diagnosis of chronic medical and mental health conditions reduces the probability of early recognition and intervention for either. This study was aimed at assessing the prevalence and correlates of depression and anxiety disorders among persons with Type 2 Diabetes Mellitus in a tertiary hospital in North-West Nigeria.

View Article and Find Full Text PDF

Purpose: To explore the effect of different reconstruction algorithms (ASIR-V and DLIR) on image quality and emphysema quantification in chronic obstructive pulmonary disease (COPD) patients under ultra-low-dose scanning conditions.

Materials And Methods: This prospective study with patient consent included 62 COPD patients. Patients were examined by pulmonary function test (PFT), standard-dose CT (SDCT) and ultra-low-dose CT (ULDCT).

View Article and Find Full Text PDF

Objectives: To facilitate earlier diagnosis of autoimmune rheumatic diseases (ARDs), we aimed to 1) develop START, a novel multimedia-based symptom appraisal tool for ARDs and 2) pilot test START among established ARD cases and non-ARD controls.

Methods: We developed START using a social cognitive theory-based theoretical framework and consensus-based lists of ARDs and manifestations from our previous work. START was revised through reviews by an expert panel of rheumatologists and cognitive debriefing interviews (CDIs) with patients newly referred for assessment of ARDs.

View Article and Find Full Text PDF

How Painful are Lumbar Hernias? A Comprehensive Review of Intervention Strategies.

Curr Pain Headache Rep

January 2025

Universidad de Alcalá, School of Medicine and Health Sciences, Department of Surgery, Medical and Social Sciences, Area of Human Anatomy and Embryology, Universidad de Alcalá, University Campus - C/ 19 Av de Madrid Km 33 600, 28871, Alcalá de Henares, Madrid, Spain.

Purpose Of Review: Low back pain (LBP) is considered an important issue of public health, with annual prevalence estimations almost achieving 60% of the worldwide population. Available treatments have a limited impact on this condition, although they allow to alleviate pain and recover the patient's quality of life. This review aims to go deeper on the understanding of this condition, providing an updated, brief, and concise whole picture of this common musculoskeletal problem.

View Article and Find Full Text PDF

A multiscale molecular structural neural network for molecular property prediction.

Mol Divers

January 2025

Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.

Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!