Impact Of Learning Effect Research Articles

Impact of learning effect on reliability factors and global indices in visual field testing by standard automated perimetry in normal healthy subjects and primary open-angle glaucoma patients to obtain an accurate baseline perimetry chart.

To record and evaluate the reliability parameters (fixation loss (FL) %, false positive (FP) %) and global indices (mean sensitivity (MS), mean deviation (MD), pattern standard deviation in dB) in three visual field test sessions within two weeks to assess the learning effect in normal healthy subjects and POAG patients and comparison of learning effect gender wise and age wise in primary open-angle glaucoma (POAG) patients. This study was a prospective observational study. An oculus visual field testing was done and analyzed in 30 eyes of POAG patients and 30 eyes of normal healthy subjects in three visits. There were 16 (53.3%) males and 14 (46.6%) females in the POAG group and 16 (53.33%) males and 14 (46.66%) females in the normal healthy subject group. A significant difference in data change between each visit in FL, FP, MD, MS was found though the difference was more pronounced in the second visit than in the third visit. The pattern standard deviation does not change significantly in subsequent visits in both groups. Gender wise and age wise no significant difference was found in the POAG group. Significant improvement in reliability parameters and global indices with each subsequent visit in both the POAG group and normal patients signifies the importance of learning effect on these parameters and the need to perform at least three tests to get the baseline perimetry chart, especially in POAG patients, while in normal subjects, second perimetric result can be accepted. It was also concluded that the learning effect is not influenced by age and gender.

Retailer vs. vendor managed inventory with considering stochastic learning effect

Extending the research on the impact of learning effect on inventory management is of particular importance, this paper studies two different inventory management models with considering stochastic learning effect, one is retailer-managed inventory (RMI) scenario, and another is vendor-managed inventory (VMI) scenario. We find that inventory exists in equilibrium provided that the holding cost is under a respective threshold both in the RMI and VMI scenarios, also, the threshold in the RMI scenario is significantly larger than that in the VMI scenario. Moreover, the RMI scenario is Pareto dominant over the VMI scenario except for a very large holding cost, and the advantage in enhancing profit is highlighted in the RMI scenario as the variability of the learning rate increases. Furthermore, the traditional double marginalization effect is weakened by a large variability in the RMI scenario while intensified in the VMI scenario. The results obtained in this paper can provide guidance for the inventory management with considering stochastic learning effect.

Learning effects in coders and their implications for managing content analyses

ABSTRACTFrom the perspective of study management, research is surprisingly lacking on two of the major challenges for planning and performing content analysis: determining the sample size (i.e. number of objects to code) and the required number of coders to hire. The optimization of both of these numbers will ultimately determine how efficiently available resources are used. This study contributes to the methodological discussion on coding by identifying and conceptualizing the role of learning effects with respect to the coding task and by highlighting the importance of considering the coding process when managing a content analysis. We present empirical evidence for the existence and impact of learning effects on coders’ coding speed. Accordingly, study management should take account of learning effects when determining the sample size and number of coders. We also provide an illustrative example of how learning effects can impact the results of pretests.

P-247 A follow-up results of team management approach for XELOX therapy in patients with advanced/recurrent colorectal cancer: the SMILE Study (Study of Metastatic colorectal cancer to investigate Impact of Learning Effect)

P-247 A follow-up results of team management approach for XELOX therapy in patients with advanced/recurrent colorectal cancer: the SMILE Study (Study of Metastatic colorectal cancer to investigate Impact of Learning Effect)

An observational study of a team management approach for first-line XELOX therapy in patients with advanced/recurrent colorectal cancer: The SMILE study (the study of metastatic colorectal cancer to investigate impact of learning effect).

554 Background: Although oral chemotherapies such as XELOX are widely favored for convenience and flexibility, these have several disadvantages such as drug non-compliance and delayed discovery of adverse events. So we designed a multicenter, prospective, observational study to evaluate the efficacy of supportive interventions in first-line XELOX for colorectal cancer (CRC) patients (pts). Methods: CRC pts undergoing first-line XELOX (+Bevacizumab) therapy practicing one or more of supportive interventions as follows: 1) a telephone follow-up (TF), 2) instruction on dosage and administration by a pharmacist, 3) skin care instruction by a nurse, and 4) pts education by a doctor were eligible. The objective was to evaluate the incident rate of grade 2 or worse hand-foot syndrome (HFS), QoL, safety, and efficacy. QoL was assessed at baseline, 2, 4, 5 and 8 cycles after the treatment started, using the Hospital Anxiety and Depression Scale (HADS) and the Mental adjustment to cancer scale (MAC). Results: From April 2011 to September 2012, 80 pts were enrolled from 14 institutes. The characteristics were as follows: male/female: 46/34, age median: 63 (36-75), and supportive intervention 1)/2)/3)/4): 36/68/73/78. The incidence of grade 2 or worse HFS during 6 months were 11.1% (n=4) for those received TF (n=36), and 20.5% (n=9) for those received other intervention except TF (n=44). Relative dose intensity (RDI) was 75.7% (TF+/-: 77.7/74.3%) in oxaliplatin and 77.5% (TF+/-: 80.2/75.3%) in capecitabine, respectively. Although a tendency of the QoL score improvement about anxiety, fighting spirit and helplessness in a TF group was observed during the periods from start of therapy to 4 courses, there were no significant differences compared to other interventions except TF. Conclusions: We confirmed that HFS incidence was mitigated in a TF group. In regard to QoL, although we could not show the statistical differences due to some limitations of this study such as small sample size and non-randomized, it was indicated that TS had the potential to improve several QoL about anxiety, fighting spirit, and helplessness. Clinical trial information: UMIN000007185.

Service quality decisions for express delivery companies with learning effect

With the rapid development of express delivery industry, the service quality becomes a topic of interest for academic research. This paper extended the previous research by studying the learning effect in express delivery industry. We propose a two-period model to analyse how the learning effect would influence the service quality. We first examine the optimal decisions of a monopoly express company in two different scenarios, i.e., myopic and foresighted respectively. For each scenario, we characterise the optimal decisions and examine the impact of learning effect. We then extend the model into the case that there are two competing express companies and derive the firms’ equilibrium decisions in the presence of service competition. We find the service quality is positively related to learning effect. We also discuss the impact of ‘price war’ on the development of the industry.

Assessing Learning Effects and Nonrandom Dropout in a Contraceptive Device Trial

When there is a new device involved in a randomized trial, participants in the new device group might need more time to become skilled at using the new device than those who are in the control group. In addition, participants who are not used to the new device might drop out from the study at a different rate than participants in the control group. Such learning effects and possible nonrandom dropout can substantially influence the evaluation of treatment effects. Without considering these factors, the conclusion of the main study result is vulnerable to potential bias. In this paper we propose a transition model under a Markov process to assess the effects of learning and nonrandom dropout in a randomized control device trial. The transition probabilities of the proposed model can be obtained by maximum likelihood approaches, and then fit by weighted local regressions to describe patterns of learning and participant dropout. A generalized estimating equation approach is applied to evaluate the impact of prognostic factors on those patterns. We use data from a randomized contraceptive device trial to illustrate the usefulness of the proposed method. The potential impact of learning effects and nonrandom dropout on the primary study objective is discussed.

Implications of learning effects for hospital costs of new health technologies: The case of intensity modulated radiation therapy

The impact of learning effects on the variability of costs of new health technologies in a prospective payment system (PPS) through the case of intensity modulated radiation therapy (IMRT) was studied. A series of consecutive patients treated in nine medical centers was enrolled in a prospective study. Direct costs were assessed from the perspective of the healthcare providers. We used a two-level model to explain the variability of costs: patients nested within centers. Learning effects at the center level were considered through a fixed effect (the learning curve slope) and a random effect (the initial cost level). Covariates were introduced to explain the patterns of variation in terms of patient characteristics. The mean direct cost of IMRT was 5,962 euro (range, 2,414 euro-24,733 euro). Manpower accounted for 53 percent of this cost. Learning effects explained 42 percent of the variance between centers (which was 88 percent of the total variance) and were associated with a substantial decrease in treatment costs. The mean initial treatment direct cost was 6,332 euro in centers with a previous experience of IMRT, whereas it was 14,192 euro in centers implementing IMRT for the first time. Including logistics costs and overhead, the full cost of IMRT was 10,916 euro. Average reimbursement was 6,987 euro. Learning effects are a strong confounding factor in the analysis of costs of innovative health technologies involving learning effects. In a PPS, innovative health technology involving learning effects necessitates specific reimbursement mechanisms.