Journal of Arboriculture 31(5): September 2005 229 the decades, statutes have become more and more specific to arboriculture. In 1979, it became mandatory for arborists to obtain a state license to practice, and the Louisiana Depart- ment of Agriculture and Forestry (LDAF) became the regulatory agency overseeing arborist licenses. In 1992, responding to the growing number of accidents involving arborists and their customers, Louisiana lawmakers dictated that, in addition to other licensing requirements, arborists must attend at least one continuing education training each year to maintain licensure (Roussel 2003). From 1992 until 2002, a private professional society provided continuing education for licensed arborists. In 2002, the Louisiana State University Agricultural Center and Cooperative Extension Service (hereafter LSUAC) assumed this responsibility. Program organizers identified safety and professionalism as the two main training needs for enhancing the profession of arboriculture in Louisiana. This decision, to focus on safety and professionalism, grew out of advice from a steering committee composed of tree care and urban forestry professionals from across Louisiana and on common themes presented in trade and professional journals. The continuing education program includes formal assessment of the training’s effectiveness. The objectives of this assessment are (1) to develop a baseline description of safety and professional practices of Louisiana arborists, and (2) to identify changes in safety and profes- sional practices that result from the training. Here we present a baseline description of Louisiana arborists from the first year of data collection. Planned future work includes job-site observations and follow-up study to assess changes in arborist safety and professionalism 2 years after initiating the new program. METHODS We examined arborist safety and professionalism using a written questionnaire to collect information. We used Rasch analysis to evaluate the pilot questionnaire and, later, to test the modified questionnaire for its validity and reliability in measuring safety and professionalism and to create response variables for comparison of subgroups (e.g., male versus female). Statistical Analyses Rasch analysis, originally developed for use in psychologi- cal and educational testing, uses a logistic–odds ratio to (1) transform raw person scores (summed across questions) to a person score, and (2) transform raw question scores (summed across respondents) to a question score. Transfor- mations are based on the probabilistic relationship between a question’s difficulty and a respondent’s ability to answer the question correctly. Question difficulty refers to the probability that a respondent will answer a question “correctly,” that is, in a way that indicates safe or profes- sional behavior. Person ability refers to the proportion of questions a respondent is expected to answer correctly (e.g., the higher the person’s ability, the more questions he or she will answer correctly). For this survey, a correct answer (yes) affirms safe or professional behavior and is coded as 1 (example: “I wear leg protection when on the job”). An “incorrect” answer (no) fails to affirm the behavior and receives the code 0. The Rasch model expresses the probability of respond- ing to a question correctly as a function of the size of the difference between the person’s ability and the question’s difficulty (Bond and Fox 2001), and it provides a standard- ized, central, shared linear logistic scale that gives expected person ability and question difficulty values against which to compare individual questions and persons. Question score and person score estimates are expressed on a scale of logistics–odds ratios, or logits, with the average logit set to zero. Positive scores reflect higher than average probabili- ties, and negative scores reflect lower than average prob- abilities. A positive question score indicates that the question is more difficult than average for a respondent to answer “yes,” (e.g., “I always keep both hands on the chain saw while making a cut”). A negative question score describes a question that is easier than average for the respondent to answer “yes” (e.g., “I recommend against topping”). Similarly, positive person score estimates identify respondents with higher than average levels of safety and professionalism. Negative estimates identify respondents whose responses indicate they are less professional and safe. Another benefit of using Rasch analysis with a survey questionnaire is that it generates statistics useful in determin- ing the quality of the questionnaire and the appropriateness of the survey respondents. These statistics are particularly useful during survey piloting and when determining sam- pling procedures, including identifying problematic ques- tions (e.g., poorly worded or eliciting inappropriate information) and respondents (e.g., those who answer all questions the same way or who have large skip patterns in their responses). Verifying questionnaire quality and reliabil- ity and the appropriateness of the sampled population with Rasch-generated statistics allows broader interpretation of the results than would be possible with a traditional question-by- question analysis. It also supports the survey as a good means for making interpretive statements regarding arborist safety and professionalism and for exploring questions about differences between subgroups. Questionnaire Development and Survey Procedures The pilot questionnaire contained 62 questions addressing the main constructs, or areas of interest, we wished to measure: professionalism and safety. Questions were based primarily on information provided in ISA’s Arborists’ ©2005 International Society of Arboriculture
September 2005
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