The theory of decision making.

Edwards, Ward

doi:10.1037/h0053870

Cited by 2,175 publications

(1,046 citation statements)

References 151 publications

(103 reference statements)

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“…As predicted by theories of health behaviour (e.g. Fishbein & Ajzen, 1972;Edwards, 1954), outcome expectancies and motives are important correlates of drinking behaviour. Outcome expectancies (see Table 1) distinguish between drinkers and abstainers (Leigh & Stacy, 2004), and are significantly related to drinkers' patterns of alcohol consumption (Bot, Engels & Knibbe, 2005;Dijkstra, Sweeney & Gebhardt, 2001;Farber, Khavari & Douglass, 1980;Hittner, 1997;Lee, Greely & Oei, 1999;Leigh & Stacy, 2004;Migneault, Pallonen & Velicer, 1997;Oei & Morawska, 2004;Stritzke & Butt, 2001;Williams & Clark, 1998).…”

Section: Expectancies and Motivesmentioning

confidence: 94%

Young men's ambivalence toward alcohol

Visser¹,

Smith²

2007

Social Science & Medicine

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Section: Expectancies and Motivesmentioning

confidence: 94%

Young men's ambivalence toward alcohol

Visser¹,

Smith²

2007

Social Science & Medicine

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“…The theory of decision making suggests that individual behavior is affected by individual characteristics, e.g., social-demographics, governmental and psychological factors [41]; based on this, our study develops 10 independent variables for analysis (see Table 4). These include characteristics of individual farmers such as their gender [42], education level [19], farming years [43], planting size [44], other economic features such as portion of household income generating from farming [45], government and policy factors such as the participation in pesticide use training organized by governments [46]; knowledge about types of prohibited pesticides [47], views towards frequent and massive use of pesticides on generating pesticide residue [29], view towards massive use of pesticides which in turn damage the surrounding environment [48].…”

Section: Resultsmentioning

confidence: 99%

Measuring Rice Farmer’s Pesticide Overuse Practice and the Determinants: A Statistical Analysis Based on Data Collected in Jiangsu and Anhui Provinces of China

Wang

Chu

2018

Sustainability

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Understanding the extent of pesticide overuse and what drives rice farmers to overuse pesticide in agricultural production theoretically and empirically is imperative to increase farmers' income, promote agricultural transformation and agricultural sustainable development. In this paper, we examined the phenomenon and pattern of pesticides overuse based on the data collected from 861 rice farmers in Jiangsu and Anhui, two provinces in China. By applying the Cobb-Douglas production function (C-D production function) and the damage control model, we estimated the marginal productivity of pesticides. We also adopted the Binary Probit model to further explore factors leading to overuse of pesticide among farmers. Our findings suggested that the marginal productivity of pesticides is close to zero, indicating that there is an excessive use of pesticides in the surveyed areas. According to the Binary Probit model, we also discovered that female farmers, farmers with knowledge about pesticide toxicity, pesticide residue and farmers who hold the view that massive use of pesticide is inimical to the environment, and farmers who participate in pesticide training organized by the government, are more likely to overuse pesticide. On the contrary, experienced farmers have a lower chance of overusing pesticides. Possible explanations to the above findings may be that applying pesticides in accordance with the instructions causes overusing and farmers who are loss-averse, in order to avoid the risk of income loss that may be caused by disease and insect pests, and keep its own income stable, will still increase the amount of pesticide application. It also indicates that farmers are insensitive to increased pesticide overuse.

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“…A theoretically driven approach was adopted in order to improve comparability across goals (the same questions were asked in relation to each goal) and also to explain why clinicians make certain decisions. The Subjective Expected Utility (SEU) theory of decision-making was selected (Edwards, 1954;Tversky, 1967). Using this approach 2 key factors believed to influence decision-making were examined.…”

mentioning

confidence: 99%

Chemotherapy for advanced breast cancer: what influences oncologists’ decision-making?

et al. 2001

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Chemotherapy is widely used in the management of patients with advanced breast cancer. However, a considerable proportion of patients experience toxic side effects without gaining benefit. This study aimed to elicit oncologists' views of the goals of chemotherapy for patients with advanced breast cancer and to elicit which factors are important in decisions to recommend chemotherapy to such patients. 30 oncologists underwent a semi-structured interview to examine their views of 5 goals of chemotherapy and of various disease, treatment and patient-related factors that might influence decisions to offer treatment. The clinicians also made decisions regarding treatment in relation to a hypothetical patient scenario under varying clinical conditions. Relief of symptoms and improvement of activity were rated as the most valuable and achievable goals of treatment. The patient's performance status, frailty and their wishes regarding treatment were the most important patient-related factors in determining decision-making. The most important disease/treatment-related factors were pace of the disease, previous poor response to chemotherapy, co-existing symptoms and concurrent medical conditions. The hypothetical scenario revealed that co-existing medical conditions, adverse previous response, increased age and depression would decrease the likelihood of recommending chemotherapy, whereas key symptoms (e.g. breathlessness) and the patient's goals would increase the likelihood. The findings suggest that British oncologists primarily aim to improve patients' physical function, although subjective factors, such as a patient's desire for anti-cancer treatment and their future goals, also influence decisions to offer treatment. © 2001 Cancer Research Campaign http://www.bjcancer.com

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The theory of decision making.

Abstract: and especially C. H. Coombs have kindly made much unpublished material available to me. A number of psychologists, economists, and mathematicians have given me excellent, but sometimes unheeded, criticism. Especially helpful were C.

Cited by 2,175 publications

References 151 publications

Young men's ambivalence toward alcohol

Young men's ambivalence toward alcohol

Measuring Rice Farmer’s Pesticide Overuse Practice and the Determinants: A Statistical Analysis Based on Data Collected in Jiangsu and Anhui Provinces of China

Chemotherapy for advanced breast cancer: what influences oncologists’ decision-making?

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