Browsing by Subject "Knowledge"

In the face of declines in memory related to specific events, people maintain intact general knowledge into very old age. Older adults often use this knowledge to support their remembering. Semantic illusions involve situations in which presented information contradicts correct knowledge; the illusion occurs when people fail to notice a contradiction with what they know. Compared to younger adults, older adults' later memories are surprisingly less affected by semantic illusions. That is, they use fewer errors seen in the semantic illusions as answers when later asked related general knowledge questions. Why do older adults show this reduced suggestibility, and what role does their intact knowledge play? In 5 experiments, I explored these questions. Older adults' reduced suggestibility was not due to an age difference in error detection: older adults were no better than younger adults at detecting the errors that contradicted their stored knowledge. In addition, episodic memory failures were not a major factor either; the evidence for their direct involvement was mixed. Instead, prior knowledge seems to have been particularly protective for older adults. They demonstrated more knowledge to begin with but also gained access to even more of their stored knowledge across the duration of experiments, leading them to be less suggestible following semantic illusions. There was also an indication that when knowledge was stably accessible, older adults had a tendency to rely on it more than did younger adults. Broadly, these findings indicate that older adults' intact prior knowledge provides important benefits to their remembering and can even protect them against acquiring erroneous information about the world.

Background: Hypertension presents a public health challenge globally, both in developing and developed countries such as the Netherlands. Complications of hypertension accounted for a total number of 10.46 million deaths every year in the world, and disability-adjusted life years associated with high blood pressure is 143.0 million in 2015. Among Dutch people aged between 30 and 70, 31.4% suffer from hypertension. Dutch guideline recommendations for treating patients with SBP between 160 and 180 mmHg is unique: low-risk patients are recommended without BP lowering medication, and middle-risk patients should be treated only in the presence of other risk-increasing factors. For these two groups of patients, guidelines from other countries, like United Kingdom and the United States, suggests “lifestyle advice with prompt drug initiation”. This study explores attitudes of health professionals, the target users of the unique Dutch guideline, towards the risk table and two guideline recommendations of commencing antihypertensive drug treatment for low- and middle-risk patients. In addition to health professionals’ attitude, this study also explores their perceived application barriers of the risk table. The risk table and two recommendations are only a small part of the CVRM guideline. This study focused on the risk table and the two recommendations because these are the guidance for treating hypertension patients.

Methods: A cross-sectional, mixed-method study was conducted in the Netherlands, mainly in Amsterdam. A total of 77 online questionnaires in English were conducted among health professionals in the Netherlands, while 13 face-to-face in-depth interviews in English were conducted among participants in Amsterdam. All participants completed the online questionnaire that assessed their knowledge, attitude, and practice of the Dutch General Practitioner’s Society (Nederlands Huisartsen Genootschap NHG) CVRM guideline and the risk table, as well as their attitude towards the two recommendations of antihypertensive drug prescription for low- and middle-risk patients. The in-depth interview aimed to further explore barriers of applying the risk table and the reasons for their attitude towards the two recommendations.

Results: Majority of our survey respondents have positive attitudes towards the NHG CVRM guideline in general and the risk table. Knowledge and attitude are not barriers of applying NHG CVRM guideline. All the respondents reported that they knew the existence of the guideline, and almost all of them (97%) agreed that they knew the guideline content. 92% respondents think that NHG CVRM guidelines are valuable, and 92% report that they believe NHG guidelines are well-supported by scientific evidence. Despite that only 3.9% participants reported they did not apply the risk table to every patient, health professionals perceived lacking important risk factors as an important barrier of applying the risk table.

Regarding attitudes towards pharmacological treatment for low- and middle-risk patents, 66% agreed that middle-risk patients required drug treatment only in the event of risk-increasing factors and SBP > 140mmHg and/or LDL> 2.5 mmol/L, 58% agreed low-risk patients rarely required drug treatment. The most reported reasons to follow the unique recommendations include: follow the guideline, clinical uncertainty of the persistency of the elevated BP, perceived patient attitude and drug adherence, and drug burden. Confusion of guideline interpretation for treatment advice on low-risk patient with SBP over 180 mmHg is detected in this study.

A significant relationship existed between attitudes towards lowering current treatment threshold and sex (p=.011). Female health professionals were more likely to agree with lowering treatment threshold compared to male.

Conclusions: Knowledge is not a barrier of applying NHG CVRM guideline, and attitudes towards the guideline are found to be generally positive. The highest perceived barriers to applying the risk table is lack of important risk factors, for example SES, ethnicity, psychological factors, physical exercise, BMI, family history of CVD, and chronic conditions like chronic kidney diseases and autoimmune disease. Most participants agree that low-risk patients rarely require drug treatment, and middle-risk patients require drug treatment only in the event of risk-increasing factors and SBP> 140mmHg and/or LDL> 2.5 mmol/L. The most reported reasons to follow the unique recommendations include: follow the guideline, clinical uncertainty of the persistency of the elevated BP, perceived patient attitude and drug adherence, and drug burden. Confusion of guideline interpretation for treatment advice on low-risk patient with SBP over 180 mmHg is detected in this study.

Psychological research on aging typically characterizes it as a period of decline. Numerous studies have reported age-related deficits in episodic memory, sensory perception, and fluid intelligence. These reports only add to society’s negative views of aging, which inevitably have a detrimental impact on older adults’ cognition, health, and general well-being. However, there are several other domains of cognition that remain stable or improve during healthy aging. For example, emotional functioning increases with age: older adults can better regulate their emotions and resist their desires compared to younger adults. Older adults are also more skilled at solving interpersonal problems and display intact implicit and procedural memory. This dissertation highlights two other areas that show improvement with age (i.e., decision making and knowledge) and considers how we can use these positive aspects to offset the negative aspects of aging. Chapter 2 investigates heuristic decision making. While some work suggests that older adults are more reliant on these shortcuts, there is little evidence to support this claim. To clarify this issue, participants from across the adult lifespan solved decision scenarios that tapped each of the following classic heuristics: anchoring, availability, recognition, representativeness, and sunk cost fallacy. Chapter 3 further explores knowledge. While the literature confirms that knowledge increases across the lifespan, it is unclear 1) if people are generally aware of this increase and 2) whether they hold expectations about the scope of younger vs. older adults' knowledge. To address these questions, younger and older participants predicted the knowledge of hypothetical younger and older adults. Chapter 4 focuses on application. While many studies have demonstrated that negative aging stereotypes negatively impact older adults’ memory performance, research on positive aging stereotypes’ influence is still inconclusive. In order to address this gap, older participants demonstrated their memory performance before and after viewing a neutral intervention or positive stereotype intervention about their knowledge advantage. Altogether, I find that older adults continue to use cognitively efficient decision strategies; they are not more reliant on classic heuristics and use them to the same degree as younger adults. Furthermore, I demonstrate that adults of all ages recognize that older individuals have a knowledge advantage over younger individuals, regardless of the difficulty of the information. Critically, if older adults are reminded of this advantage, they remember more words during a memory test. Taken together, this body of work sheds light on the cognitive improvements that accompany healthy aging and considers ways to leverage these positive aspects, with the goal of offsetting age-related deficits and promoting positive self-perceptions of aging.

Misleading claims surround us – we encounter them in news stories, advertising campaigns, and political propaganda. How do people separate facts from fiction? Decades of work implicate fluency, or subjective ease. Repeated statements feel easier to process, and thus more truthful, than new ones (i.e., illusory truth). This dissertation identifies additional cues for truth and takes a lifespan perspective. Older adults accumulate impressive amounts of knowledge (which may protect them), but also unduly attend to positive information (which may leave them vulnerable to emotional appeals). In two experiments, older adults exhibited illusory truth only when they lacked knowledge about claims, unlike young adults. Three additional experiments encouraged young adults to “stick with” what they knew. Evaluating truth at exposure prompted young adults to use their knowledge later, wiping out the illusion. Three final experiments disproved the idea that positivity “feels like” truth. Young adults exhibited a negativity bias, where negative faces made claims seem less true than neutral ones. Neither positive nor negative faces swayed older adults’ judgments. These results inform many theoretical perspectives – from fluency and referential theories of truth, to dual-process and socioemotional selectivity theories of aging. They also have important practical implications for preventing and correcting misconceptions in a “post-truth world,” where falsehoods travel farther and faster than the truth.

Background: Even though a recent increase in HIV prevalence has been noticed in Sri Lanka, not many studies have been done there relating to HIV/AIDS. In particular, little is known about HIV-related stigma among healthcare workers, which has been identified as an obstacle to addressing the HIV epidemic. To examine this issue, this study first aimed to assess knowledge and attitudes of PHMs, the frontline community health workers in Sri Lanka. Second, the study examined the factors associated with their knowledge and attitudes. Lastly, the study examined the association of demographic information, knowledge, and attitudes with extra precautionary behaviors. Methods: Two hundred and ninety-one PHMs were recruited for this cross-sectional study. The study team visited each of the 20 Medical Officers of Health areas (MOH: administrative division) in the Galle District and surveyed PHMs during their monthly meetings. The study utilized two questionnaires to assess knowledge (16 items), attitudes and stigma (37 items). After assessing the PHMs knowledge and attitudes, the study explored the association of demographic information with knowledge and attitudes, and then examined how such individual factors, knowledge, and attitudes were associated with extra precautionary behaviors. Results: PHMs’ knowledge level was good (79.9% of answers were correct) but could be improved. Those more knowledgeable about HIV and with higher education demonstrated a more positive attitude towards PLWH. A more negative attitude was associated with having a stronger intention to engage in extra precautionary behaviors. Conclusions: As PHMs are community health workers whose attitude can potentially influence to the general public’s point of view, they need further HIV training to improve their knowledge so as to better educate the community. By reducing the PHMs misperceptions about HIV, they may develop a more positive attitude and thus help reduce stigma towards PLWH.

Radiation has been utilized in medical domain for multiple purposes. Treating cancer using radiation has increasing popularity during the last century. Radiation beam is directed to the tumor cells while the surrounding healthy tissue is attempted to be avoided. Radiation therapy treatment planning serves the goal of delivering high concentrated radiation to the treatment volume while minimizing the normal tissue as much as possible. With the advent of more sophisticated delivery technology, treatment planning time increases over time. In addition, the treatment plan quality relies on the experience of the planner. Several computer assistance techniques emerged to help the treatment planning process, among which knowledge-based planning (KBP) has been successful in inverse planning IMRT. KBP falls under the umbrella of Knowledge Discovery in Databases (KDD) which originated in industry. The philosophy is to extract useful knowledge from previous application/data/observations to make predictions in the future practice. KBP reduces the iterative trial-and-error process in manual planning, and more importantly guarantees consistent plan quality. Despite the great potential of treatment planning KDD (TPKDD), three major challenges remain before TPKDD can be widely implemented in the clinical environment: 1. a good knowledge model asks for sufficient amount of training data to extract useful knowledge and is therefore less efficient; 2. a knowledge model is usually only applicable for the specific treatment site and treatment technique and is therefore less generalizable; 3. a knowledge model needs meticulous inspection before implementing in the clinic to verify the robustness.

This study aims at filling in the niche in TPKDD and improves current TPKDD workflow by tackling the aforementioned challenges. This study is divided into three parts. The first part of the study aims to improve the modeling efficiency by introducing an atlas-based treatment planning guidance. In the second part of the study, an automated treatment planning technique for whole breast radiation therapy (WBRT) is proposed to provide a solution for the area where TPKDD has not yet set foot on. In the third part of the study, several topics related to the knowledge model quality are addressed, including improving the model training workflow, identifying geometric novelty and dosimetric outlier case, building a global model and facilitating incremental learning.

I. Improvement of the modeling efficiency. First, a prostate cancer patient anatomy atlas was established to generate 3D dose distribution guidance for the new patient. The anatomy pattern of the prostate cancer patient was parameterized with two descriptors. Each training case was represented in 2D feature space. All training cases were clustered using the k-medoids algorithm. The optimal number of clusters was determined by the largest average silhouette width. For the new case, the most similar case in the atlas was identified and used to generate dose guidance. The anatomy of the atlas case and the query case was registered and the deformation field was applied to the 3D radiation dose of the atlas case. The deformed dose served as the goal dose for the query case. Dose volume objectives were then extracted from the goal dose to guide the inverse IMRT planning. Results showed that the plans generated with atlas guidance had similar dosimetric quality as compared to the clinical manual plans. The monitor units (MU) of the auto plan were also comparable with the clinical plan. Atlas-guided radiation therapy has proven to be effective and efficient in inverse IMRT planning.

II. Improvement of model generalization. An automatic WBRT treatment planning workflow was developed. First of all, an energy selection tool was developed based on previous single energy and dual energy WBRT plans. The DRR intensity histograms of training cases were collected and the principal component analysis (PCA) was performed to reduce the dimension of the histogram. First two components were used to represent each case and the classification was performed in the 2D space. This tool helps new patient to select appropriate energy based on the anatomy information. Secondly, an anatomy feature based random forest (RF) model was proposed to predict the fluence map for the patient. The model took the input of multiple anatomical features and output the fluence intensity of each pixel within the fluence map. Finally, a physics rule based method was proposed to further fine tune the fluence map to achieve optimal dose distribution within the irradiated volume. Extra validation cases were tested on the proposed workflow. Results showed similar dosimetric quality between auto plan and clinical manual plan. The treatment planning time was reduced from between 1-4 hours for the manual planning to within 1 minute for the auto planning. The proposed automatic WBRT planning technique has proven to be efficient.

III. Rapid learning of radiation therapy KBP. Several topics were analyzed in this part of the study. First of all, a systematic workflow was established to improve the KBP model quality. The workflow started with identifying geometric novelty case using the statistical metric “leverage”, followed by removing the novelty case. Then the dosimetric outlier was identified using studentized residual and then cleaned. The cleaned model was compared with the uncleaned model using the extra validation cases. This study used pelvic cases as an example. Results showed that the existence of novelty and outlier cases did degrade the model quality. The proposed statistical tools can effectively identify novelty and outlier cases. The workflow is able to improve the quality of the knowledge-based model.

Secondly, a clustering-based method was proposed to identify multiple geometric novelty cases and dosimetric outlier cases at the same time. One class support vector machine (OCSVM) was applied to the feature vectors of all training cases to generate one class of inliers while cases falling out of the frontier belonged to the novelty case group. Once the novelty cases were identified and cleaned, the robust regression followed by outlier identification (ROUT) was applied to all remaining cases to identify dosimetric outliers. A cleaned model was trained with the novelty and outlier free case pool and was tested using 10 fold cross validation. Initial training pool included intentionally added outlier cases to evaluate the efficacy of the proposed method. The model prediction on the inlier cases was compared with that of novelty and outlier cases. Results showed that the method can successfully identify geometric novelty and dosimetric outliers. The model prediction accuracy between the inliers and novelty/outliers was significantly different, indicating different dosimetric behavior between two groups. The proposed method proved to be effective in identifying multiple geometric novelty and dosimetric outliers.

Thirdly, a global model using the model tree and the clustering-based model was proposed to include cases with different clinical conditions and indications. The model tree is a combination of decision tree and linear regression, where all cases are branched into leaves and regression is performed within each leaf. A clustering-based model used k-means algorithm to segment all cases into more aggregated groups, and then the regression was performed within each small group. The overall philosophy of both the model tree and the clustering-based method is that cases with similar features have similar geometry-dosimetry relation. Training cases within small feature range gives better model accuracy. The proposed method proved to be effective in improving the model accuracy over the model trained with all cases without segmenting the cases.

At last, the incremental learning was analyzed in radiation therapy treatment planning model. This study tries to answer the question when model re-training should be invoked. In the clinical environment, it is often unnecessary to re-train the model whenever there is a new case. The scenario of incrementally adapting the model was simulated using the pelvic cases with different number of training cases and new incoming cases. The result showed that re-training was often necessary for small training dataset and as the number of cases increased, re-training became less frequent.

In summary, this study addressed three major challenges in TPKDD. In the first part, an atlas-guided treatment planning technique was proposed to improve the modeling efficiency. In the second part, an automatic whole breast radiation therapy treatment planning technique was proposed to tackle the issue where TPKDD has not yet resolved. In the final part, outlier analysis, global model training and incremental learning was further analyzed to facilitate rapid learning, which lay the foundation of future clinical implementation of radiation therapy knowledge models.