Fuelwood collection and consumption: a case study in Lupeta Tanzania

Fuelwood is a major resource in rural areas. Fuelwood collection and consumption habits were monitored in Lupeta, Tanzania through household interviews and fuelwood collection walks. Social dimensions, economic aspects of fuelwood, and alternative fuel sources were also examined. The study found that for all wealth classes, fuelwood is the primary source of fuel used within the village, with the middle and upper classes occasionally supplementing fuelwood with charcoal. Women collect and consume fuelwood for cooking. The majority of women (69%) prefer to use charcoal because fuelwood collection is labor intensive and time consuming. While the use of charcoal would provide more time for other required household activities, local economic constraints inhibit their adoption. The fuel shift from biomass fuels to transition fuels is happening slowly in Lupeta from fuelwood to charcoal. As fuelwood becomes scarcer, improved methods will need to be adopted or the fuel source will change.

DEVELOPMENT AND VALIDATION OF THE ANTERIOR CRUCIATE LIGAMENT INJURY-RISK-ESTIMATION QUIZ (ACL-IQ)

Over 2 million Anterior Cruciate Ligament (ACL) injuries occur annually worldwide resulting in considerable economic and health burdens (e.g., suffering, surgery, loss of function, risk for re-injury, and osteoarthritis). Current screening methods are effective but they generally rely on expensive and time-consuming biomechanical movement analysis, and thus are impractical solutions. In this dissertation, I report on a series of studies that begins to investigate one potentially efficient alternative to biomechanical screening, namely skilled observational risk assessment (e.g., having experts estimate risk based on observations of athletes movements). Specifically, in Study 1 I discovered that ACL injury risk can be accurately and reliably estimated with nearly instantaneous visual inspection when observed by skilled and knowledgeable professionals. Modern psychometric optimization techniques were then used to develop a robust and efficient 5-item test of ACL injury risk prediction skill—i.e., the ACL Injury-Risk-Estimation Quiz or ACL-IQ. Study 2 cross-validated the results from Study 1 in a larger representative sample of both skilled (Exercise Science/Sports Medicine) and un-skilled (General Population) groups. In accord with research on human expertise, quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., ignoring irrelevant information), independent of domain general cognitive abilities (e.g., metal rotation, general decision skill). These cognitive models suggest that ACL-IQ is a trainable skill, providing a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations. Overall, I present the first evidence that observational ACL injury risk prediction is possible including a robust technology for fast, accurate and reliable measurement—i.e., the ACL-IQ. Discussion focuses on applications and outreach including a web platform that was developed to house the test, provide a repository for further data collection, and increase public and professional awareness and outreach (www.ACL-IQ.org). Future directions and general applications of the skilled movement analysis approach are also discussed.