Dataset Information

An alternative to the stay/switch equation assessed when using a changeover-delay.

ABSTRACT: An alternative to the generalized matching equation for understanding concurrent performances is the stay/switch model. For the stay/switch model, the important events are the contingencies and behaviors at each alternative. The current experiment compares the descriptions by two stay/switch equations, the original, empirically derived stay/switch equation and a more theoretically derived equation based on ratios of stay to switch responses matching ratios of stay to switch reinforcers. The present experiment compared descriptions by the original stay/switch equation when using and not using a changeover delay. It also compared descriptions by the more theoretical equation with and without a changeover delay. Finally, it compared descriptions of the concurrent performances by these two equations. Rats were trained in 15 conditions on identical concurrent random-interval schedules in each component of a multiple schedule. A COD operated in only one component. There were no consistent differences in the variance accounted for by each equation of concurrent performances whether or not a COD was used. The simpler equation found greater sensitivity to stay than to switch reinforcers. It also found a COD eliminated the influence of switch reinforcers. Because estimates of parameters were more meaningful when using the more theoretical stay/switch equation it is preferred.

SUBMITTER: MacDonall JS

PROVIDER: S-EPMC4618195 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An alternative to the stay/switch equation assessed when using a changeover-delay.

MacDonall James S JS

Behavioural processes 20150820

An alternative to the generalized matching equation for understanding concurrent performances is the stay/switch model. For the stay/switch model, the important events are the contingencies and behaviors at each alternative. The current experiment compares the descriptions by two stay/switch equations, the original, empirically derived stay/switch equation and a more theoretically derived equation based on ratios of stay to switch responses matching ratios of stay to switch reinforcers. The pres ...[more]

PMID: 26299548

Similar Datasets

Project description:Length-of-hospital stay (LOS) after lumbar spine surgery (LSS) can be affected by many factors. However, few studies have evaluated predictors of LOS, and all have used limited number of variables as predictors.The purpose of the study was to identify presurgical, surgical, and postsurgical predictors of LOS after LSS.Retrospective review of consecutive patients who had LSS at the University of Kansas Hospital from October 2008 to April, 2012.Five hundred ninety-three patients underwent LSS consisting of laminotomy, laminectomy, or arthrodesis.LOS. Multiple presurgical, surgical, and postsurgical variables were extracted from the patients' medical records and considered as possible predictors (independent variables) of LOS.Potential predictors that were significantly correlated with LOS were used as indicators to construct three latent factors presurgical, surgical, and postsurgical, which were in turn used to predict LOS in a structural equation model.The average LOS was 4.01±2.73 days. The presurgical factor was indicated by age (61.97±14.49 years), previous level of function (60.5% were totally independent), previous hemoglobin level (13.70±1.36 mg/dL), and use of assistive devices (60% were assistive device users). The surgical factor was indicated by severity of illness (50.2% had minor disease severity), presence of complications (1.9%), and stay in an intensive care unit (4.0%). The postsurgical factor was indicated by postsurgical walking distance (166.43±175.75 ft), level of assistance during walking (5.18±0.81 out of 7 points), balance scores (6.18±1.82 out of 10 points), and bed mobility and transfer dependency scores (9.81±1.99 out of 14 points). These three latent factors explained 47% of variation in LOS.Postsurgical factors predicted the highest variation in LOS in comparison with presurgical and surgical factors and should be taken into consideration for discharge planning. Postsurgical factors are related to the patient's function, modifiable with rehabilitation, and can be improved to shorten LOS. Inclusion of more reliable and standardized presurgical variables could improve the predictability of the model.

Project description:BACKGROUND:Failure in the timely follow-up of test results has been widely documented, contributing to delayed medical care. Yet, the impact of delay in reviewing test results on hospital length of stay (LOS) has not been studied. We examine the relationship between laboratory tests review time and hospital LOS. METHODS:A retrospective cohort study of inpatients admitted to a metropolitan teaching hospital in Sydney, Australia, between 2011 and 2012 (n = 5804). Generalized linear models were developed to examine the relationship between hospital LOS and cumulative clinician read time (CRT), defined as the time taken by clinicians to review laboratory test results performed during an inpatient stay after they were reported in the computerized test reporting system. The models were adjusted for patients' age, sex, and disease severity (measured by the Charlson Comorbidity index), the number of test panels performed, the number of unreviewed tests pre-discharge, and the cumulative laboratory turnaround time (LTAT) of tests performed during an inpatient stay. RESULTS:Cumulative CRT is significantly associated with prolonged LOS, with each day of delay in reviewing test results increasing the likelihood of prolonged LOS by 13.2% (p < 0.0001). Restricting the analysis to tests with abnormal results strengthened the relationship between cumulative CRT and prolonged LOS, with each day of delay in reviewing test results increasing the likelihood of delayed discharge by 33.6% (p < 0.0001). Increasing age, disease severity and total number of tests were also significantly associated with prolonged LOS. Increasing number of unreviewed tests was negatively associated with prolonged LOS. CONCLUSIONS:Reducing unnecessary hospital LOS has become a critical health policy goal as healthcare costs escalate. Preventing delay in reviewing test results represents an important opportunity to address potentially avoidable hospital stays and unnecessary resource utilization.

Dataset Information

An alternative to the stay/switch equation assessed when using a changeover-delay.

Publications

An alternative to the stay/switch equation assessed when using a changeover-delay.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets