Friday, April 11

1. Friday, April 11 Evaluating scientific arguments: to generate content, revise content, and review peers’ position papers IPHY 3700 Writing Process Map

2. Answer the key diagnostic questions for evaluating scientific arguments, using the think-ahead and think-through strategies Diagnostic Question: How strong are the data-driven lines of support for the claim? --Is there a critical mass of data to convince readers? If so, has the writer synthesized the data convincingly? --To what degree are the data statistically significant? Considering the statistical significance of the data, are you strongly convinced to accept the writer’s claim? --To what degree are the data practically significant? Considering the practical significance of the data, are you strongly convinced to accept the writer’s claim?

3. Diagnostic question: To what degree are the data statistically and practically significant? Considering the significance of the data, are you strongly convinced to accept the writer’s claim? Lane et al. Answer the key diagnostic questions for evaluating scientific arguments, using the think-ahead and think-through strategies Lane et al.

4. Answer the key diagnostic questions for evaluating scientific arguments, using the think-ahead and think-through strategies Diagnostic Question: How strong are the concept-driven lines of support for the claim? Osteoarthritis is defined on x-rays by osteophyte formation, sclerosis of subchondral bone, cyst formation, and joint space narrowing (15). There are known inconsistencies between findings on x-ray films and clinical symptoms, with only 25 % to 30 % of subjects with osteoarthritis by x-ray being clinically symptomatic (16). Overall, we found few differences except in bone density, which was strongly associated with running in both sexes. Female runners tended to show more sclerosis and spur formation in knees and spine, but the cartilage width in the knees and spine, measured as joint space narrowing, was not different in the two groups. We cannot exclude the possibility that increased bone density resulted in increased ability to "read" sclerosis and new bone formation (spurs) in the running group. Lane et al.'s Results Lane et al.'s Discussion

5. Generating Content through Evaluating Arguments: My Draft Lane et al. argued that extreme amounts of running do not increase the risk for osteoarthritis. Some data from this study do indeed support the researchers' claim. For example, for men and women, no differences existed between runners and nonrunners in joint space width, which is a valid measure of osteoarthritis. However, Lane et al. present other data and reasoning that fail to support their claim. The women runners had more severe indices of knee joint sclerosis and bone spurs (6.7 and 8.4, respectively) compared to their non-running counterparts (5.1 and 5.1, respectively). Because sclerosis and bone spurs are valid measures of osteoarthritis, these results indicate a greater risks for developing the disease in women runners versus normally active women. To support their view that the greater incidence of sclerosis and bone spurs does not reflect greater risk for osteoarthritis, Lane et al. argued that the results were simply an artifact of the greater bone density in the women runners. Because the runners had 40 percent more bone mass than the nonrunners, Lane et al. argued that the runners' x-rays were "easier to read" and therefore that the bone spurs and sclerosis were easier to detect. Two problems limit this reasoning. First, regardless of whether the runners' x-rays were easier to read, they still had more severe incidences of bone spurs and sclerosis. Second, Lane et al. overlooked the fact that the men runners also had greater bone density than their nonrunning counterparts. Thus, by the reasoning of Lane et al., the men runners should have had easier x-rays to read and a greater incidence of bone spurs and sclerosis. However, no significant differences existed between the men runners and nonrunners for these measures. Thus, I would argue that the results of this study support the claim that, at least for women, long-distance running increases the risk for developing osteoarthritis.

6. Answer the key diagnostic questions for evaluating scientific arguments, using the think-ahead and think-through strategies Diagnostic Question: How strong are the concept-driven lines of support for the claim? One theory of the development of osteoarthritis is that joints "wear out" by repetitive impulse loading (21). This impulse loading results in microfracture, then bone remodeling and sclerosis, and stiffened bone. This rigidity increases stress on articular cartilage, with subsequent cartilage breakdown and joint degeneration. It has been observed that total paralysis severely reduces interarticular stress and appears to spare joints from further degeneration. Other authors suggest that it requires both impulse loading and a mechanical derangement to the joint to result in osteoarthritis (22,23). A careful review by Hadler (24) emphasizes that the postulated relationship of osteoarthritis and heavy work rests on almost entirely on anecdotal evidence. Lane et al.'s Results Lane et al.'s Discussion

7. Author: Lane et al. || Reviewer: Larry Greene My review focuses on your explanation of the greater incidence of sclerosis and spurs in the women runners (in the first paragraph of your discussion section). It's appropriate that you're trying to argue that these results do not necessarily reflect a greater risk of osteoarthritis in women runners; the content nicely reflects the important rhetorical goal to acknowledge and refute possible limitations to one's own argument. However, your reasoning in this section is not completely logical and, therefore, convincing. You say that the greater severity of sclerosis and spurs may have been due to the greater bone density in women runners vs. controls, which made it easier to detect the abnormalities on the x-rays. Your results appear to support this argument because the women runners had 40% greater bone density than their nonrunning counterparts. So, as you suggest, it is possible that the bone spurs and sclerosis were more evident in the x-rays for the women runners. But consider that the bone density in the male runners was also significantly greater than in the nonrunning controls, by a similar magnitude of approximately 40%. So, if your reasoning is accurate, the male runners should also have had a greater severity of sclerosis and spurs than the controls. In the male runners' x-rays, these abnormalities should also have been easier to read. But your results do not support this line of reasoning, because the severity of sclerosis and spurs was not different across the two groups of males. So, because your reasoning does not hold for the males, readers might not be convinced that the women runners are not at a greater risk for developing osteoarthritis. Word count: 274 words Lane et al. Example Peer Review

8. I will argue that lifelong patterns of exercise reduce risk of breast cancer by (a) presenting studies that have used lifetime exercise methods and shown exercise to reduce risk of developing breast cancer and (b) explaining how lifetime exercise reduces breast cancer risk by reducing cumulative lifetime exposure to cyclic estrogen. Studies using lifetime exercise methods have shown that exercise reduces the risk of developing breast cancer Bernstein et al. conducted a study using lifetime histories of physical exercise and determined that measuring lifetime exercise was extremely effective in determining what effect exercise had on breast cancer risk (2). Among women exercising more than 3.8 hours a week, risk of developing breast cancer decreased 58% when compared to women exercising 0 hours a week (RR = .42) (2). Bernstein and her colleagues held personal interviews with subjects who had recently been diagnosed with breast cancer and their individually matched control subjects. Participants responded to questions about physical activity participation between 10 years of age and present age (majority of subjects were between 36 and 40 years old). Bernstein and her colleagues then revised the results to a general measurement of lifetime exercise with regular participation in physical activity defined as more than 2 hours a week of physical exercise (2). In using these methods to conduct her study, Bernstein showed that lifetime physical activity did significantly reduce risk of developing breast cancer. Bernstein concluded from this study that lifetime physical activity measurements are crucial to effective analysis of the impact exercise has on risk of breast cancer (2, 8). Draft || Example Peer Review Peer Review Practice