scholarly journals Sensitivity of Disease Management Decision Aids to Temperature Input Errors Associated with Sampling Interval and Out-of-Canopy Sensor Placement

Plant Disease ◽  
2012 ◽  
Vol 96 (5) ◽  
pp. 726-736 ◽  
Author(s):  
W. F. Pfender ◽  
D. H. Gent ◽  
W. F. Mahaffee
Keyword(s):  
Disease Management ◽  
Stem Rust ◽  
Measurement Errors ◽  
Decision Aid ◽  
Decision Aids ◽  
Sampling Interval ◽  
Temperature Measurements ◽  
Management Decision ◽  
Weather Station ◽  
Crop Canopy

Many plant disease epidemic models, and the disease management decision aids developed from them, are created based on temperature or other weather conditions measured in or above the crop canopy at intervals of 15 or 30 min. Disease management decision aids, however, commonly are implemented based on hourly weather measurements made from sensors sited at a standard placement of 1.5 m above the ground or are estimated from off-site weather measurements. We investigated temperature measurement errors introduced when sampling interval was increased from 15 to 60 min, and when actual in-canopy conditions were represented by temperature measurements collected by standard-placement sensors (1.5 m above the ground, outside the canopy) in each of three crops (grass seed, grape, and hops) and assessed the impact of these errors on outcomes of decision aids for grass stem rust as well as grape and hops powdery mildews. Decreasing time resolution from 15 to 60 min resulted in statistically significant underestimates of daily maximum temperatures and overestimates of daily minimum temperatures that averaged 0.2 to 0.4°C. Sensor location (in-canopy versus standard-placement) also had a statistically significant effect on measured temperature, and this effect was significantly less in grape or hops than in the grass seed crop. Effects of these temperature errors on performance of disease management decision aids were affected by magnitude of the errors as well as the type of decision aid. The grape and hops powdery mildew decision aids used rule-based indices, and the relatively small (±0.8°C) differences in temperature observed between in-canopy and standard placement sensors in these crops resulted in differences in rule outcomes when actual in-canopy temperatures were near a threshold for declaring that a rule had been met. However, there were only minor differences in the management decision (i.e., fungicide application interval). The decision aid for grass stem rust was a simulation model, for which temperature recording errors associated with location of the weather station resulted in incremental (not threshold) effects on the model of pathogen growth and plant infection probability. Simple algorithms were devised to correct the recorded temperatures or the computed infection probability to produce outcomes similar to those resulting from in-canopy temperature measurements. This study illustrates an example of evaluating (and, if necessary, correcting) temperature measurement errors from weather station sensors not located within the crop canopy, and provides an estimate of uncertainty in temperature measurements associated with location and sampling interval of weather station sensors.

scholarly journals Evaluation of the Ryegrass Stem Rust Model STEMRUST_G and Its Implementation as a Decision Aid

2015 ◽  
Vol 105 (1) ◽  
pp. 35-44 ◽  
Author(s):  
W. F. Pfender ◽  
L. B. Coop ◽  
S. G. Seguin ◽  
M. E. Mellbye ◽  
G. A. Gingrich ◽  
...  
Keyword(s):  
Disease Management ◽  
Pacific Northwest ◽  
Stem Rust ◽  
Decision Aid ◽  
Decision Aids ◽  
Weather Conditions ◽  
The United States ◽  
Weather Data ◽  
Daily Weather Data ◽  
Epidemic Development

STEMRUST_G, a simulation model for epidemics of stem rust in perennial ryegrass grown to maturity as a seed crop, was validated for use as a heuristic tool and as a decision aid for disease management with fungicides. Multistage validation had been used in model creation by incorporating previously validated submodels for infection, latent period duration, sporulation, fungicide effects, and plant growth. Validation of the complete model was by comparison of model output with observed disease severities in 35 epidemics at nine location-years in the Pacific Northwest of the United States. We judge the model acceptable for its purposes, based on several tests. Graphs of modeled disease progress were generally congruent with plotted disease severity observations. There was negligible average bias in the 570 modeled-versus-observed comparisons across all data, although there was large variance in size of the deviances. Modeled severities were accurate in >80% of the comparisons, where accuracy is defined as the modeled value being within twice the 95% confidence interval of the observed value, within ± 1 day of the observation date. An interactive website was created to produce disease estimates by running STEMRUST_G with user-supplied disease scouting information and automated daily weather data inputs from field sites. The model and decision aid supplement disease managers' information by estimating the level of latent (invisible) and expressed disease since the last scouting observation, given season-long weather conditions up to the present, and it estimates effects of fungicides on epidemic development. In additional large-plot experiments conducted in grower fields, the decision aid produced disease management outcomes (management cost and seed yield) as good as or better than the growers' standard practice. In future, STEMRUST_G could be modified to create similar models and decision aids for stem rust of wheat and barley, after additional experiments to determine appropriate parameters for the disease in these small-grain hosts.

scholarly journals Decision Aids for Multiple-Decision Disease Management as Affected by Weather Input Errors

2011 ◽  
Vol 101 (6) ◽  
pp. 644-653 ◽  
Author(s):  
W. F. Pfender ◽  
D. H. Gent ◽  
W. F. Mahaffee ◽  
L. B. Coop ◽  
A. D. Fox
Keyword(s):  
Disease Management ◽  
Decision Process ◽  
Decision Aids ◽  
Risk Index ◽  
Original Data ◽  
Weather Data ◽  
Management Decision ◽  
Model Calculations ◽  
Cropping Season ◽  
Management Context

Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.

KRiskSM: A Computerized Decision Aid for Client Acceptance and Continuance Risk Assessments

2002 ◽  
Vol 21 (2) ◽  
pp. 97-113 ◽  
Author(s):  
Timothy B. Bell ◽  
Jean C. Bedard ◽  
Karla M. Johnstone ◽  
Edward F. Smith
Keyword(s):  
Risk Management ◽  
Quality Control ◽  
Decision Aid ◽  
Audit Quality ◽  
Decision Aids ◽  
Risk Assessments ◽  
Innovative Technology ◽  
Full Potential ◽  
Business Risk ◽  
Client Acceptance

This paper describes the development and implementation of KRisk, an innovative technology-enabled auditor decision aid for making client acceptance and continuance risk assessments. KRisk, developed and designed by KPMG LLP, is part of the firm's audit quality control and risk management processes. In this paper, we discuss the environmental and technological forces that affect auditor business risk management. We also describe important aspects of the development, functionality, and implementation of KRisk. We discuss possible impediments to realizing the full potential of decision aids that have been reported in prior auditing research, and describe how KRisk and related audit quality control procedures implemented at KPMG were designed to overcome such impediments. Also, we present some ideas for scholarly research dealing with auditor business risk management issues, and issues related to the design and use of decision aids in general.

The Effects of Decision Aid Orientation on Risk Factor Identification and Audit Test Planning

2002 ◽  
Vol 21 (2) ◽  
pp. 39-56 ◽  
Author(s):  
Jean C. Bedard ◽  
Lynford E. Graham
Keyword(s):  
Risk Factors ◽  
Risk Management ◽  
Decision Aid ◽  
Decision Aids ◽  
Management Strategies ◽  
Risk Identification ◽  
Matched Pair ◽  
Audit Planning ◽  
Audit Firms ◽  
Risk Management Strategies

In auditing, risk management involves identifying client facts or issues that may affect engagement risk, and planning evidence-gathering strategies accordingly. The purpose of this paper is to examine whether auditors' identification of risk factors and planning of audit tests is affected by decision aid orientation, i.e., a “negative” focus wherein client risk and its consequences are emphasized, or a “positive” focus where such factors are not emphasized. Specifically, we expect that auditors will identify more risk factors using a negatively oriented risk identification decision aid, but only when engagement risk is relatively high. We address this issue in the context of auditors' knowledge of actual clients, manipulating decision aid orientation as negative or positive in a matched-pair design. Results show that auditors using the negative decision aid orientation identify more risk factors than do those using a positive orientation, for their higher-risk clients. We also find that decisions to apply substantive tests are more directly linked to specific risk factors identified than to direct risk assessments. Further, our results show that auditors with repeat engagement experience with the client identify more risk factors. The findings of this study imply that audit firms may improve their risk management strategies through simple changes in the design of decision aids used to support audit planning.

Decision Aids for Generating Analytical Review Alternatives: The Impact of Goal Framing and Audit-Risk Level

2002 ◽  
Vol 14 (1) ◽  
pp. 157-177 ◽  
Author(s):  
Jennifer M. Mueller ◽  
John C. Anderson
Keyword(s):  
High Risk ◽  
Cognitive Load ◽  
Information Search ◽  
Decision Aid ◽  
Decision Aids ◽  
Risk Level ◽  
Audit Risk ◽  
Goal Framing ◽  
Analytical Review ◽  
The Impact

An auditor generating potential explanations for an unusual variance in analytical review may utilize a decision aid, which provides many explanations. However, circumstances of budgetary constraints and limited cognitive load deter an auditor from using a lengthy list of explanations in an information search. A two-way between-subjects design was created to investigate the effects of two complementary approaches to trimming down the lengthy list on the number of remaining explanations carried forward into an information search. These two approaches, which represent the same goal (reducing the list) but framed differently, are found to result in a significantly different number of remaining explanations, in both low- and high-risk audit environments. The results of the study suggest that the extent to which an auditor narrows the lengthy list of explanations is important to the implementation of decision aids in analytical review.

scholarly journals Systematic Development of Patient Decision Aids: An Update from the IPDAS Collaboration

2021 ◽  
pp. 0272989X2110141
Author(s):  
Holly O. Witteman ◽  
Kristin G. Maki ◽  
Gratianne Vaisson ◽  
Jeanette Finderup ◽  
Krystina B. Lewis ◽  
...  
Keyword(s):  
Decision Aid ◽  
Decision Aids ◽  
Rapid Development ◽  
User Involvement ◽  
User Centered Design ◽  
Patient Decision Aid ◽  
Patient Decision Aids ◽  
Patient Decision ◽  
Development Processes ◽  
Systematic Development

Background The 2013 update of the evidence informing the quality dimensions behind the International Patient Decision Aid Standards (IPDAS) offered a model process for developers of patient decision aids. Objective To summarize and update the evidence used to inform the systematic development of patient decision aids from the IPDAS Collaboration. Methods To provide further details about design and development methods, we summarized findings from a subgroup ( n = 283 patient decision aid projects) in a recent systematic review of user involvement by Vaisson et al. Using a new measure of user-centeredness (UCD-11), we then rated the degree of user-centeredness reported in 66 articles describing patient decision aid development and citing the 2013 IPDAS update on systematic development. We contacted the 66 articles’ authors to request their self-reports of UCD-11 items. Results The 283 development processes varied substantially from minimal iteration cycles to more complex processes, with multiple iterations, needs assessments, and extensive involvement of end users. We summarized minimal, medium, and maximal processes from the data. Authors of 54 of 66 articles (82%) provided self-reported UCD-11 ratings. Self-reported scores were significantly higher than reviewer ratings (reviewers: mean [SD] = 6.45 [3.10]; authors: mean [SD] = 9.62 [1.16], P < 0.001). Conclusions Decision aid developers have embraced principles of user-centered design in the development of patient decision aids while also underreporting aspects of user involvement in publications about their tools. Templates may reduce the need for extensive development, and new approaches for rapid development of aids have been proposed when a more detailed approach is not feasible. We provide empirically derived benchmark processes and a reporting checklist to support developers in more fully describing their development processes. [Box: see text]

scholarly journals Basing Information on Comprehensive, Critically Appraised, and Up-to-Date Syntheses of the Scientific Evidence: An Update from the International Patient Decision Aid Standards

2021 ◽  
pp. 0272989X2199662
Author(s):  
Tammy C. Hoffmann ◽  
Mina Bakhit ◽  
Marie-Anne Durand ◽  
Lilisbeth Perestelo-Pérez ◽  
Catherine Saunders ◽  
...  
Keyword(s):  
Decision Aid ◽  
Scientific Evidence ◽  
Decision Aids ◽  
Future Research ◽  
Patient Decision Aid ◽  
Patient Decision Aids ◽  
Research Areas ◽  
Patient Decision ◽  
Evidence Quality ◽  
Emerging Issues

Background Patients and clinicians expect the information in patient decision aids to be based on the best available research evidence. The objectives of this International Patient Decision Aid Standards (IPDAS) review were to 1) check the currency of, and where needed, update evidence for the domain of “basing the information in decision aids on comprehensive, critically appraised, and up-to-date syntheses of the evidence”; 2) analyze the evidence characteristics of decision aids; and 3) propose updates to relevant IPDAS criteria. Methods We searched MEDLINE and PubMed to inform updates of this domain’s definitions, justifications, and components. We also searched 5 sources to identify all publicly available decision aids ( N = 471). Two assessors independently extracted each aid’s evidence characteristics. Results Minor updates to the definitions and theoretical justifications of this IPDAS domain are provided and changes to relevant IPDAS criteria proposed. Nearly all aids (97%) provided a year of creation/update, but most (81%) did not report an explicit update or expiration policy. No scientific references were cited in 33% of aids. Of the 314 that cited at least 1 reference, 39% cited at least 1 guideline, 44% cited at least 1 systematic review, and 23% cited at least 1 randomized trial. In 35%, it was unclear what statement in the aid the citations referred to. Only 14% reported any of the processes used to find and decide on evidence inclusion. Only 14% reported the evidence quality. Many emerging issues and future research areas were identified. Conclusions Although many emerging issues need to be addressed, this IPDAS domain is validated and criteria refined. High-quality patient decision aids should be based on comprehensive and up-to-date syntheses of critically appraised evidence.

The Impact of Transparency and Decision Risk on Human–Automation Teaming Outcomes

2021 ◽  
pp. 001872082110334
Author(s):  
Shayne Loft ◽  
Adella Bhaskara ◽  
Brittany A. Lock ◽  
Michael Skinner ◽  
James Brooks ◽  
...  
Keyword(s):  
Decision Aid ◽  
Financial Incentive ◽  
Decision Aids ◽  
Rejection Rate ◽  
Decision Time ◽  
Correct Rejection ◽  
Incentive Scheme ◽  
Operator Behavior ◽  
The Impact ◽  
Financial Penalty

Objective Examine the effects of decision risk and automation transparency on the accuracy and timeliness of operator decisions, automation verification rates, and subjective workload. Background Decision aids typically benefit performance, but can provide incorrect advice due to contextual factors, creating the potential for automation disuse or misuse. Decision aids can reduce an operator’s manual problem evaluation, and it can also be strategic for operators to minimize verifying automated advice in order to manage workload. Method Participants assigned the optimal unmanned vehicle to complete missions. A decision aid provided advice but was not always reliable. Two levels of decision aid transparency were manipulated between participants. The risk associated with each decision was manipulated using a financial incentive scheme. Participants could use a calculator to verify automated advice; however, this resulted in a financial penalty. Results For high- compared with low-risk decisions, participants were more likely to reject incorrect automated advice and were more likely to verify automation and reported higher workload. Increased transparency did not lead to more accurate decisions and did not impact workload but decreased automation verification and eliminated the increased decision time associated with high decision risk. Conclusion Increased automation transparency was beneficial in that it decreased automation verification and decreased decision time. The increased workload and automation verification for high-risk missions is not necessarily problematic given the improved automation correct rejection rate. Application The findings have potential application to the design of interfaces to improve human–automation teaming, and for anticipating the impact of decision risk on operator behavior.

Effective Financial Decision Aids for Retirement

2017 ◽  
Vol 49 (2) ◽  
pp. 102-118
Author(s):  
Susan L. Rose ◽  
John E. Morrison
Keyword(s):  
Financial Literacy ◽  
Decision Aid ◽  
Financial Training ◽  
Decision Aids ◽  
Armed Forces ◽  
Fiscal Year ◽  
National Defense ◽  
Review Of The Literature ◽  
Literacy Training ◽  
Financial Decision

The National Defense Authorization Act for Fiscal Year 2016 directs the Secretaries of the Armed Forces and the Chiefs of Staff of the Armed Forces to provide financial literacy training to Service members at certain critical points throughout their careers, including the transition to retirement. Based on a review of the literature, we find that general financial training is ineffective. More effective are decision aids that provide assistance at the time the decision is being made. This article provides a discussion of what such a decision aid would entail.

Sign in / Sign up

Export Citation Format

Share Document