Environmental Social Work in the Disciplinary Literature, 1991–2015

Despite increasing acknowledgment that the social work profession must address environmental concerns, relatively little is known about the state of scholarship on environmental social work. This study provides a scientometric summary of peer-reviewed articles (N=497) pertaining to environmental topics in social work journals between 1991 and 2015. We find that theoretical and empirical scholarship on environmental social work is growing, though this growth remains limited to specific geographical regions and topics. We note the need to clarify the relationship between environmental social work as a theoretical paradigm and as a research topic

Child Protective Service Referrals Involving Exposure to Domestic Violence: Prevalence, Associated Maltreatment Types, and Likelihood of Formal Case Openings

Childhood exposure to domestic violence (CEDV) is widely understood as potentially harmful to children. Accordingly, many child welfare systems in the United States construe CEDV as maltreatment when the exposure results in harm or threatened harm to the child. The purpose of the current study was to investigate substantiated child welfare referrals directly related to CEDV to better understand the prevalence and patterns of CEDV-related maltreatment and how child welfare workers respond under the “harm or threatened harm” standard. Data were drawn from 23,704 substantiated referrals between 2009 and 2013 in a large Midwestern child welfare system. Approximately 20% of substantiated referrals were CEDV related. A plurality of CEDV-related referrals included both a male caregiver and female caregiver who were co-substantiated for maltreatment. The most common maltreatment types substantiated for these referrals were neglect based rather than abuse based, and just under a quarter (23%) of CEDV-related referrals were formally opened for services. Referrals involving co-occurring substance abuse were most likely to be opened for services based on predicted probabilities derived from multilevel modeling. Implications for policy and practice are considered

Owl and Lizard: Patterns of Head Pose and Eye Pose in Driver Gaze Classification

Accurate, robust, inexpensive gaze tracking in the car can help keep a driver safe by facilitating the more effective study of how to improve (1) vehicle interfaces and (2) the design of future Advanced Driver Assistance Systems. In this paper, we estimate head pose and eye pose from monocular video using methods developed extensively in prior work and ask two new interesting questions. First, how much better can we classify driver gaze using head and eye pose versus just using head pose? Second, are there individual-specific gaze strategies that strongly correlate with how much gaze classification improves with the addition of eye pose information? We answer these questions by evaluating data drawn from an on-road study of 40 drivers. The main insight of the paper is conveyed through the analogy of an "owl" and "lizard" which describes the degree to which the eyes and the head move when shifting gaze. When the head moves a lot ("owl"), not much classification improvement is attained by estimating eye pose on top of head pose. On the other hand, when the head stays still and only the eyes move ("lizard"), classification accuracy increases significantly from adding in eye pose. We characterize how that accuracy varies between people, gaze strategies, and gaze regions.Comment: Accepted for Publication in IET Computer Vision. arXiv admin note: text overlap with arXiv:1507.0476

Complexity of the Ruminococcus flavefaciens FD-1 cellulosome reflects an expansion of family-related protein-protein interactions

This work was supported in part by the European Union, Area NMP.2013.1.1–2: Self-assembly of naturally occurring nanosystems: CellulosomePlus Project number: 604530, and by the EU Seventh Framework Programme (FP7 2007–2013) under the WallTraC project (Grant Agreement no 263916), and BioStruct-X (grant agreement no 283570). This paper reflects the author’s views only. The European Community is not liable for any use that may be made of the information contained herein. CMGAF is also supported by Fundação para a Ciência e a Tecnologia (Lisbon, Portugal) through grants PTDC/BIA-PRO/103980/2008 and EXPL/BIA-MIC/1176/2012. EAB is also funded by a grant (No. 1349/13) from the Israel Science Foundation (ISF), Jerusalem, Israel and by a grant (No. 2013284) from the U.S.-Israel Binational Science Foundation (BSF). E.A.B. is the incumbent of The Maynard I. and Elaine Wishner Chair of Bio-organic Chemistry.Peer reviewedPublisher PD

Child Protective Services Guidelines for Substantiating Exposure to Domestic Violence as Maltreatment and Assigning Caregiver Responsibility: Policy Analysis and Recommendations

The purpose of this study was to examine the range of policy approaches used by child welfare systems in the United States to guide workers in classifying and substantiating child exposure to domestic violence (CEDV) as an actionable form of maltreatment. To that end, we conducted a qualitative document analysis of child protective services (CPS) policy manuals from all state-administered child welfare systems in the U.S. ( N = 41). Our findings indicate that a majority of state-administered systems (71%) have adopted policy requiring workers to demonstrate that children have endured harm or the threat of harm before substantiating CEDV-related maltreatment. Many state systems (51%) also include policy directives that require workers to identify a primary aggressor during CPS investigations involving CEDV, while far fewer (37%) provide language that potentially exonerates survivors of domestic violence from being held accountable for failure to protect on the basis of their own victimization. Based on our findings and identification of policy exemplars, we offer a recommended set of quality policy indicators for states to consider in the formulation of their policy guidelines for substantiating children’s exposure to domestic violence that promotes the safety and wellbeing of both children and adult survivors of domestic violence

Welcoming gallium- and indium-fumarate MOFs to the family:synthesis, comprehensive characterization, observation of porous hydrophobicity, and CO₂ dynamics

The properties and applications of metal–organic frameworks (MOFs) are strongly dependent on the nature of the metals and linkers, along with the specific conditions employed during synthesis. Al-fumarate, trademarked as Basolite A520, is a porous MOF that incorporates aluminum centers along with fumarate linkers and is a promising material for applications involving adsorption of gases such as CO2. In this work, the solvothermal synthesis and detailed characterization of the gallium- and indium-fumarate MOFs (Ga-fumarate, In-fumarate) are described. Using a combination of powder X-ray diffraction, Rietveld refinements, solid-state NMR spectroscopy, IR spectroscopy, and thermogravimetric analysis, the topologies of Ga-fumarate and In-fumarate are revealed to be analogous to Al-fumarate. Ultra-wideline 69Ga, 71Ga, and 115In NMR experiments at 21.1 T strongly support our refined structure. Adsorption isotherms show that the Al-, Ga-, and In-fumarate MOFs all exhibit an affinity for CO2, with Al-fumarate being the superior adsorbent at 1 bar and 273 K. Static direct excitation and cross-polarized 13C NMR experiments permit investigation of CO2 adsorption locations, binding strengths, motional rates, and motional angles that are critical to increasing adsorption capacity and selectivity in these materials. Conducting the synthesis of the indium-based framework in methanol demonstrates a simple route to introduce porous hydrophobicity into a MIL-53-type framework by incorporation of metal-bridging −OCH3 groups in the MOF pores

Prevalence and context of firearms-related problems in child protective service investigations

Background: Despite the significance of firearm safety, we need additional data to understand the prevalence and context surrounding firearm-related problems within the child welfare system. Objective: Estimate proportion of cases reporting a firearm-related problem during case initiation and the contexts in which these problems exist. Sample and setting: 75,809 caseworker-written investigation summaries that represented all substantiated referrals of maltreatment in Michigan from 2015 to 2017. Methods: We developed an expert dictionary of firearm-related terms to search investigation summaries. We retrieved summaries that contained any of the terms to confirm whether a firearm was present (construct accurate) and whether it posed a threat to the child. Finally, we coded summaries that contained firearm-related problems to identify contexts in which problems exist. Results: Of the 75,809 substantiated cases, the dictionary flagged 2397 cases that used a firearm term (3.2 %), with a construct accuracy rate of 96 %. Among construct accurate cases, 79 % contained a firearm-related problem. The most common intent for a firearm-related problem was violence against a person (45 %). The co-occurrence of domestic violence and/or substance use with a firearm-related problem was high (41 % and 48 %, respectively). 49 % of summaries that contained a firearm-related problem did not provide information regarding storage. Conclusion: When caseworkers document a firearm within investigative summaries, a firearm-related risk to the child likely exists. Improved documentation of firearms and storage practices among investigated families may better identify families needing firearm-related services

Detecting substance-related problems in narrative investigation summaries of child abuse and neglect using text mining and machine learning

Background State child welfare agencies collect, store, and manage vast amounts of data. However, they often do not have the right data, or the data is problematic or difficult to inform strategies to improve services and system processes. Considerable resources are required to read and code these text data. Data science and text mining offer potentially efficient and cost-effective strategies for maximizing the value of these data. Objective The current study tests the feasibility of using text mining for extracting information from unstructured text to better understand substance-related problems among families investigated for abuse or neglect. Method A state child welfare agency provided written summaries from investigations of child abuse and neglect. Expert human reviewers coded 2956 investigation summaries based on whether the caseworker observed a substance-related problem. These coded documents were used to develop, train, and validate computer models that could perform the coding on an automated basis. Results A set of computer models achieved greater than 90% accuracy when judged against expert human reviewers. Fleiss kappa estimates among computer models and expert human reviewers exceeded .80, indicating that expert human reviewer ratings are exchangeable with the computer models. Conclusion These results provide compelling evidence that text mining procedures can be a cost-effective and efficient solution for extracting meaningful insights from unstructured text data. Additional research is necessary to understand how to extract the actionable insights from these under-utilized stores of data in child welfare

Risk Factors for Symptomatic Hyperlactatemia and Lactic Acidosis Among Combination Antiretroviral Therapy-Treated Adults in Botswana: Results from a Clinical Trial

Nucleoside analogue reverse transcriptase inhibitors are an integral component of combination antiretroviral treatment regimens. However, their ability to inhibit polymerase-γ has been associated with several mitochondrial toxicities, including potentially life-threatening lactic acidosis. A total of 650 antiretroviral-naive adults (69% female) initiated combination antiretroviral therapy (cART) and were intensively screened for toxicities including lactic acidosis as part of a 3-year clinical trial in Botswana. Patients were categorized as no lactic acidosis symptoms, minor symptoms but lactate <4.4 mmol/liter, and symptoms with lactate ≥ 4.4 mmol/liter [moderate to severe symptomatic hyperlactatemia (SH) or lactic acidosis (LA)]. Of 650 participants 111 (17.1%) developed symptoms and/or laboratory results suggestive of lactic acidosis and had a serum lactate drawn; 97 (87.4%) of these were female. There were 20 events, 13 having SH and 7 with LA; all 20 (100%) were female (p<0.001). Cox proportional hazard analysis limited to the 451 females revealed that having a higher baseline BMI was predictive for the development of SH/LA [aHR=1.17 per one-unit increase (1.08-1.25), p<0.0001]. Ordered logistic regression performed among all 650 patients revealed that having a lower baseline hemoglobin [aOR=1.28 per one-unit decrease (1.1-1.49), p=0.002] and being randomized to d4T/3TC-based cART [aOR=1.76 relative to ZDV/3TC (1.03-3.01), p=0.04] were predictive of the symptoms and/or the development of SH/LA. cART-treated women in sub-Saharan Africa, especially those having higher body mass indices, should receive additional monitoring for SH/LA. Women presently receiving d4T/3TC-based cART in such settings also warrant more intensive monitoring

Estimating malaria incidence from routine health facility-based surveillance data in Uganda.

BACKGROUND: Accurate measures of malaria incidence are essential to track progress and target high-risk populations. While health management information system (HMIS) data provide counts of malaria cases, quantifying the denominator for incidence using these data is challenging because catchment areas and care-seeking behaviours are not well defined. This study's aim was to estimate malaria incidence using HMIS data by adjusting the population denominator accounting for travel time to the health facility. METHODS: Outpatient data from two public health facilities in Uganda (Kihihi and Nagongera) over a 3-year period (2011-2014) were used to model the relationship between travel time from patient village of residence (available for each individual) to the facility and the relative probability of attendance using Poisson generalized additive models. Outputs from the model were used to generate a weighted population denominator for each health facility and estimate malaria incidence. Among children aged 6 months to 11 years, monthly HMIS-derived incidence estimates, with and without population denominators weighted by probability of attendance, were compared with gold standard measures of malaria incidence measured in prospective cohorts. RESULTS: A total of 48,898 outpatient visits were recorded across the two sites over the study period. HMIS incidence correlated with cohort incidence over time at both study sites (correlation in Kihihi = 0.64, p < 0.001; correlation in Nagongera = 0.34, p = 0.045). HMIS incidence measures with denominators unweighted by probability of attendance underestimated cohort incidence aggregated over the 3 years in Kihihi (0.5 cases per person-year (PPY) vs 1.7 cases PPY) and Nagongera (0.3 cases PPY vs 3.0 cases PPY). HMIS incidence measures with denominators weighted by probability of attendance were closer to cohort incidence, but remained underestimates (1.1 cases PPY in Kihihi and 1.4 cases PPY in Nagongera). CONCLUSIONS: Although malaria incidence measured using HMIS underestimated incidence measured in cohorts, even when adjusting for probability of attendance, HMIS surveillance data are a promising and scalable source for tracking relative changes in malaria incidence over time, particularly when the population denominator can be estimated by incorporating information on village of residence