Experiences met in establishing a school camping program in the city of Medford.

Thesis (M.A.)--Boston Universit

A qualitative study of technology-based training in organizations that hire agriculture and life sciences students

Technological advances have created unlimited opportunities in education. Training and technology have merged to create new methods referred to as technology-based training. Technology-based training, for the purpose of this study, was defined as training that is delivered via the Internet, CD-ROM, or video conferencing either at a distance or in a local setting. A variety of forms of technology-based training were found throughout educational and workforce settings. The purpose of this study was to identify organizations that hire agriculture and life sciences students for positions involving technology-based training and identify competencies required for these positions from the perspective of the identified organizations. This study described the technologies that the identified organizations were using to design and deliver technology-based training, the audience to which the organizations were providing training, and the competencies that the identified organizations were seeking in potential employees. Findings from this study revealed a need for individuals with specialization in creating and providing technology-based training. Data suggested seven key skills and competencies needed to work in technology-based training: 1) instructional design, 2) technology/computer skills, 3) the ability to conduct a needs assessment, 4) interpersonal skills, 5) writing skills, 6) planning and organizational skills, and 7) evaluation skills. The identified skills and competencies related to technology-based training mirror those reported in previous research. Based on analysis of the data, it was concluded that students with expertise in these skill and competency areas are more marketable in organizations that hire agriculture and life sciences students

An Observational Study With the Janssen Autism Knowledge Engine (JAKE((R))) in Individuals With Autism Spectrum Disorder

Objective: The Janssen Autism Knowledge Engine (JAKE(R)) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum disorder (ASD). Here we describe JAKE and present results from its digital phenotyping (My JAKE) and biosensor (JAKE Sense) components. Methods: An observational, non-interventional, prospective study of JAKE in children and adults with ASD was conducted at nine sites in the United States. Feedback on JAKE usability was obtained from caregivers. JAKE Sense included electroencephalography, eye tracking, electrocardiography, electrodermal activity, facial affect analysis, and actigraphy. Caregivers of individuals with ASD reported behaviors using My JAKE. Results from My JAKE and JAKE Sense were compared to traditional ASD symptom measures. Results: Individuals with ASD (N = 144) and a cohort of typically developing (TD) individuals (N = 41) participated in JAKE Sense. Most caregivers reported that overall use and utility of My JAKE was easy (69%, 74/108) or very easy (74%, 80/108). My JAKE could detect differences in ASD symptoms as measured by traditional methods. The majority of biosensors included in JAKE Sense captured sizable amounts of quality data (i.e., 93-100% of eye tracker, facial affect analysis, and electrocardiogram data was of good quality), demonstrated differences between TD and ASD individuals, and correlated with ASD symptom scales. No significant safety events were reported. Conclusions: My JAKE was viewed as easy or very easy to use by caregivers participating in research outside of a clinical study. My JAKE sensitively measured a broad range of ASD symptoms. JAKE Sense biosensors were well-tolerated. JAKE functioned well when used at clinical sites previously inexperienced with some of the technologies. Lessons from the study will optimize JAKE for use in clinical trials to assess ASD interventions. Additionally, because biosensors were able to detect features differentiating TD and ASD individuals, and also were correlated with standardized symptom scales, these measures could be explored as potential biomarkers for ASD and as endpoints in future clinical studies. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02668991 identifier: NCT02668991

Mood Disorders and Trauma – What are the Associations? Future Directions

Background: Mood dysregulation in traumatized children often is misdiagnosed as Bipolar Disorder (BD) and conversely the diagnosis of BD is often overlooked. This presents a diagnostic quagmire that is critical to understand in more depth and to date has received little attention in the literature. We aim to characterize the relationship between childhood trauma and mood dysregulation and between childhood trauma and pediatric BD by describing clinical correlates of children with trauma and comorbid mood disorders in a community mental health setting. Methods: 40 youth between the ages of 8-18 years, who present to child psychiatry at Community Healthlink clinics with symptoms of mood dysregulation and history of trauma will be assessed. Children will be divided into two groups: (1) Mood Disorder NOS (MD NOS) (n=20); and (2) Unmodified DSM-IV-TR BD (n=20) At the end of 6 months, youth with MD NOS will be re-evaluated to determine if progressed to the diagnosis of BD Future Directions Better understanding the association between trauma and development of mood disorders will increase our knowledge of the diverse effects of such events on youths’ emotional and behavioral development Identifying clinical correlates that help predict later development of BD in mood dsyregulated, traumatized youth, will promote future research aimed at identifying biological markers and preventive treatment interventions Presented at the UMass Department of Psychiatry Research Day, October 2010

Mood Disorders and Trauma – What are the Associations?

Objectives: To characterize the relationship between childhood trauma/abuse, and mood dysregulation, and between childhood trauma/abuse and pediatric bipolar disorder (BD). To describe the clinical correlates and demographics of children with trauma/abuse and comorbid mood disorders in a community mental health setting. To explore associations between the diagnosis of BD in youth with histories of trauma and a family history of BD, the presence of specific symptom clusters, the presence of pretrauma mood symptoms. Methods We are assessing youths ages 8-18 who present with mood symptoms and past trauma divided into two groups: (1) Trauma Mood Disorder NOS (T+MD); (2) Trauma+Unmodified DSM-IV-TR BD (T+BD). Differences in clinical variables between groups are analyzed using t-tests for continuous and chi-square tests for categorical variables (α= 0.05). Youth are evaluated using the following psychiatric rating scales: (1) Structured Clinical Interview for DSM Disorders, Childhood Disorders Form (KID-SCID) mood module to establish the diagnosis of BD; (2) Brief Psychiatric Rating Scale for Children (BPRS-C); (3)Young Mania Rating Scale (YMRS); (4)Children’s Depression Rating Scale-Revised (CDRS-R); (5) Childhood Trauma Questionnaire (CTQ); (6) PTSD CheckList –Civilian Version (PCL-C); (7)Attention Deficit Hyperactivity Disorder IV (ADHD-IV) Rating Scale; (8) Substance Abuse (SA) screen: CRAFFT Other information obtained includes: Demographic characteristics and socioeconomic status; Number of medications and types; Percent of with a lifelong history of psychiatric hospitalization/out of home placement; Family history of psychiatric illness and substance use disorders Results - Clinical presentations: Mood Symptoms: BD\u3eMD in BPRS total score (p=0.06), BPRS Mania subscale (p=0.05),YMRS total score (p=0.06) BD\u3eMD in total number of mood episodes identified with KID-SCID: •MDE (p=0.04) Mania (without high outlying value) (p = 0.07) Substance use: No difference as assessed using CRAFT PTSD and trauma recollection: No differences in PTSD symptoms as assessed by PCL-C BD\u3eMD abuse identified with CTQ. Sexual abuse (without high outlying value) (p = 0.05). Physical neglect (p=0.07) Medications: BD\u3eMD 1.33 fewer medications (t=11.9, p=0.17) Conclusions Further data collection is ongoing to achieve our targeted sample size in order to identify clinical correlates in mood dsyregulated, traumatized youth. This will promote future research aimed at identifying biomarkers and preventive interventions

PARENTS' DESCRIPTIONS OF BARRIERS FACED AND STRATEGIES USED TO OBTAIN DENTAL CARE *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65428/1/j.1752-7325.1974.tb00670.x.pd