An Epidemiological Examination of the Subluxation Construct Using Hill’s Criteria of Causation

Background Chiropractors claim to locate, analyze and diagnose a putative spinal lesion known as subluxation and apply the mode of spinal manipulation (adjustment) for the correction of this lesion. Aim The purpose of this examination is to review the current evidence on the epidemiology of the subluxation construct and to evaluate the subluxation by applying epidemiologic criteria for it's significance as a causal factor. Methods The databases of PubMed, Cinahl, and Mantis were searched for studies using the keywords subluxation, epidemiology, manipulation, dose-response, temporality, odds ratio, relative risk, biological plausibility, coherence, and analogy. Results The criteria for causation in epidemiology are strength (strength of association), consistency, specificity, temporality (temporal sequence), dose response, experimental evidence, biological plausibility, coherence, and analogy. Applied to the subluxation all of these criteria remain for the most part unfulfilled. Conclusion There is a significant lack of evidence to fulfill the basic criteria of causation. This lack of crucial supportive epidemiologic evidence prohibits the accurate promulgation of the chiropractic subluxation

An epidemiological examination of the subluxation construct using Hill's criteria of causation

<p>Abstract</p> <p>Background</p> <p>Chiropractors claim to locate, analyze and diagnose a putative spinal lesion known as subluxation and apply the mode of spinal manipulation (adjustment) for the correction of this lesion.</p> <p>Aim</p> <p>The purpose of this examination is to review the current evidence on the epidemiology of the subluxation construct and to evaluate the subluxation by applying epidemiologic criteria for it's significance as a causal factor.</p> <p>Methods</p> <p>The databases of PubMed, Cinahl, and Mantis were searched for studies using the keywords subluxation, epidemiology, manipulation, dose-response, temporality, odds ratio, relative risk, biological plausibility, coherence, and analogy.</p> <p>Results</p> <p>The criteria for causation in epidemiology are strength (strength of association), consistency, specificity, temporality (temporal sequence), dose response, experimental evidence, biological plausibility, coherence, and analogy. Applied to the subluxation all of these criteria remain for the most part unfulfilled.</p> <p>Conclusion</p> <p>There is a significant lack of evidence to fulfill the basic criteria of causation. This lack of crucial supportive epidemiologic evidence prohibits the accurate promulgation of the chiropractic subluxation.</p

Stressors, Self-Esteem, Social Activities, and Depression: A Sample of Patients at a Federally Qualified Health Center Who Experienced Homelessness

This study examined the relationships between current stressors and depressive symptoms among Federally Qualified Health Center (FQHC) patients who experienced homelessness, with a particular focus on the role of self-esteem and social activities on these relationships. The sample included patients who visited any clinic site of a FQHC in the southern part of Mississippi and qualified for the Health Care for the Homeless (HCH) Program. Assessments included the Patient Health Questionnaire (PHQ-9), the DUKE Health Profile, and a checklist of stressors. Results of the multivariate analysis using structural equation modeling revealed that ambulation difficulties were related to depressive symptoms directly and indirectly through social activities. SES-related stressors were related to depressive symptoms directly and indirectly through self-esteem and social activities. Relational and legal/police-related stressors were linked to depressive symptoms only through self-esteem. These results indicate the importance of integrated community healthcare services to address the physical, social, and mental healthcare needs of the homeless population

Large-Area, High Spatial Resolution Land Cover Mapping Using Random Forests, GEOBIA, and NAIP Orthophotography: Findings and Recommendations

Despite the need for quality land cover information, large-area, high spatial resolution land cover mapping has proven to be a difficult task for a variety of reasons including large data volumes, complexity of developing training and validation datasets, data availability, and heterogeneity in data and landscape conditions. We investigate the use of geographic object-based image analysis (GEOBIA), random forest (RF) machine learning, and National Agriculture Imagery Program (NAIP) orthophotography for mapping general land cover across the entire state of West Virginia, USA, an area of roughly 62,000 km2. We obtained an overall accuracy of 96.7% and a Kappa statistic of 0.886 using a combination of NAIP orthophotography and ancillary data. Despite the high overall classification accuracy, some classes were difficult to differentiate, as highlight by the low user’s and producer’s accuracies for the barren, impervious, and mixed developed classes. In contrast, forest, low vegetation, and water were generally mapped with accuracy. The inclusion of ancillary data and first- and second-order textural measures generally improved classification accuracy whereas band indices and object geometric measures were less valuable. Including super-object attributes improved the classification slightly; however, this increased the computational time and complexity. From the findings of this research and previous studies, recommendations are provided for mapping large spatial extents

Non-paretic Forelimb Training Does Not Interfere with Recovery of Paretic Forelimb Strength After Experimental Middle Cerebral Artery Occlusion

Humans often compensate with their unimpaired (non-paretic) forelimb after surviving a stroke. Research in rats suggests that this can be maladaptive after focal motor cortical strokes. Forelimb weakness is understudied in rodent models of stroke. The purpose of the study is to determine whether behavioral experience with the non-paretic forelimb differentially affects paretic forelimb strength recovery after ischemic injury caused by middle cerebral artery occlusion (MCAo). Because behavioral manipulations can influence patterns of neural connectivity post-stroke, the present study also examined how training with non-paretic limb influenced corticostriatal projections. After training to proficiency with the preferred forelimb on the Isometric Pull Task, rats underwent MCAo in the hemisphere contralateral to this limb. One week after MCAo, rats were probed for initial impairment level and then assigned to either Non-Paretic Limb Training (NPT) or non-training control conditions for 14 days. Paretic limb performance was probed one day later. All rats then received six weeks of Rehabilitative Training (RT). The anterograde tract tracer BDA was then injected into the lesioned hemisphere. Training with the non-paretic limb (NPT) does not interfere with paretic limb recovery on the Isometric Pull Task, increase reliance on the impaired forelimb, or influence ipsi corticostriatal axon quantities after MCAo. Compensatory use of the non-paretic forelimb after strokes involving subcortical damage or cortical damage primarily in the somatosensory region may not be maladaptive for strength. Understanding how behavioral recovery varies with lesion locus could influence clinical management of patients

Hypothesis Generation Using Network Structures on Community Health Center Cancer-Screening Performance

RESEARCH OBJECTIVES: Nationally sponsored cancer-care quality-improvement efforts have been deployed in community health centers to increase breast, cervical, and colorectal cancer-screening rates among vulnerable populations. Despite several immediate and short-term gains, screening rates remain below national benchmark objectives. Overall improvement has been both difficult to sustain over time in some organizational settings and/or challenging to diffuse to other settings as repeatable best practices. Reasons for this include facility-level changes, which typically occur in dynamic organizational environments that are complex, adaptive, and unpredictable. This study seeks to understand the factors that shape community health center facility-level cancer-screening performance over time. This study applies a computational-modeling approach, combining principles of health-services research, health informatics, network theory, and systems science. METHODS: To investigate the roles of knowledge acquisition, retention, and sharing within the setting of the community health center and to examine their effects on the relationship between clinical decision support capabilities and improvement in cancer-screening rate improvement, we employed Construct-TM to create simulated community health centers using previously collected point-in-time survey data. Construct-TM is a multi-agent model of network evolution. Because social, knowledge, and belief networks co-evolve, groups and organizations are treated as complex systems to capture the variability of human and organizational factors. In Construct-TM, individuals and groups interact by communicating, learning, and making decisions in a continuous cycle. Data from the survey was used to differentiate high-performing simulated community health centers from low-performing ones based on computer-based decision support usage and self-reported cancer-screening improvement. RESULTS: This virtual experiment revealed that patterns of overall network symmetry, agent cohesion, and connectedness varied by community health center performance level. Visual assessment of both the agent-to-agent knowledge sharing network and agent-to-resource knowledge use network diagrams demonstrated that community health centers labeled as high performers typically showed higher levels of collaboration and cohesiveness among agent classes, faster knowledge-absorption rates, and fewer agents that were unconnected to key knowledge resources. Conclusions and research implications: Using the point-in-time survey data outlining community health center cancer-screening practices, our computational model successfully distinguished between high and low performers. Results indicated that high-performance environments displayed distinctive network characteristics in patterns of interaction among agents, as well as in the access and utilization of key knowledge resources. Our study demonstrated how non-network-specific data obtained from a point-in-time survey can be employed to forecast community health center performance over time, thereby enhancing the sustainability of long-term strategic-improvement efforts. Our results revealed a strategic profile for community health center cancer-screening improvement via simulation over a projected 10-year period. The use of computational modeling allows additional inferential knowledge to be drawn from existing data when examining organizational performance in increasingly complex environments