462 research outputs found
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Relational Care - with Mary Larkin and Manik Deepak-Gopinath [Podcast]
No full textWhat is 'relational care' and how can it improve the day-to-day experience of carers and those they care for? What are its implications for relationships between staff and service users in care settings? And how does the concept of relational care enable us to re-imagine the role of place and space in the experience of care? These are some of the questions we explore in this episode with Mary Larkin and Manik Deepak-Gopinath who recently completed a research project on the value and practice of relational care with older people.
Mary is Professor of Care, Carers and Caring at The Open University in the UK, where her research has focused on carers and caring and adult social care. She is the co-author, most recently of Family Carers and Caring, published in 2023 by Emerald. Manik is a Lecturer in Ageing, also at The Open University, and is a critical gerontologist with interests in the intersection of ageing, place and wellbeing, and in the intimate and family ties of older adults
My Name Is Deepak
No full textThis chapter looks at the author's responses to being given a nickname by his co-workers: Tupac. They do it in a friendly manner, but the author doesn’t understand the connection with the American rapper. It makes him think about who he is, his identity, and how people see him in his adopted country.</p
Sideffective - system to mine patient reviews: sentiment analysis
No full textSideffective is the system to crawl, rank and analyze patient testimonials about side ffeects from common medications. Since the wealth of any mining model is the Data corpus, the data collection phase involved extensive crawling of massive medical websites comprised of user forums from the internet. Subsequently, the raw files were subjected to certain site-specific parsing routines, yielding outputs conforming to a well-defined data model. Currently, the system holds close to 400,000 user testimonials pertaining to more than 2500 drugs/medicines. Sideffective aims at gathering and aggregating this wealth of information, build useful associations and present interesting observations and numeric validations, all in a user-friendly interface. The important issues that we have tried to tackle are: Extracting side effects without relying on pre-built lists, aggregating distribution of different side effect for a give drug, site-specific search, ranking and determining the negativity of reviews. The system has been jointly built by Deepak Yalamanchi and Sangeetha Rajagopalan under the guidance of Prof. Tomasz Imielinski. This thesis focuses mainly on Sentiment Analysis of patient reviews. While most existing sentiment analysis systems are predicated by POS (parts of speech) tagging or Bayesian sentiment analysis methods, the same cannot be applied to medical reviews as they generally carry a negative flavor in them. We thereby approached the problem by identifying the features in the sentence and calibrating the sentiment on a Negativity Meter based on their relation to sentiment words. A feature, as defined for the purpose of this thesis, can be a medicine, a side effect or a symptom. The sentiment of each feature is determined by the aggregate of all its polarities with respect to each sentiment word, where the polarity is determined by an inverse relation to the distance of the feature from the sentiment word. Each sentence is then evaluated by the cumulative polarity of all the features contained in it. Sentiment of a review is determined by individually determining the sentiment of each sentence and then getting a weighted sum score of all the sentences in the review. The accuracy of a sentiment analysis system is, in principle, how well it agrees with human judgments. Experimental results, involving human reviewers (extracted from site: www.askapatient.com) and correlating them back to the negativity rating of each review yield conclusive results, demonstrating the effectiveness of the technique. We have also implemented a customized Lucene search on the data using a multi-review summarization approach and a ranking scheme based on the feature-list. Ranking priority is given to the review that has the largest feature list size.M.S.Includes bibliographical referencesby Deepak Yalamanch
Feasibility of conducting a randomised controlled trial on the effect of motivational interviewing in facilitating hearing aid use
No full textThe aim of this study was to investigate the feasibility of conducting a randomised controlled trial (RCT) on the effect of motivational interviewing (MI) in facilitating hearing aid use.
Methods used and their results are presented in the 3 sections below:
(1) A cross-sectional survey where a questionnaire, including the International Outcome Inventory for Hearing Aids was posted to all patients fitted with hearing aids at the Royal Surrey County Hospital, Guildford, between 2011 and 2012 (N=1874). 1023 questionnaires were completed and returned (response rate of 55%). 29% of responders did not use their hearing aids on a regular basis (i.e., used them less than 4 hours per day).
(2) 220 patients who reported using their hearing aid(s) less than 4 hours per day in the above survey were invited to take part in a pilot single-blind RCT. 37 were enrolled and randomised to MI combined with hearing aid adjustments (n=20) or hearing aid adjustments only (n=17). The results showed that it was feasible to deliver MI for facilitating hearing aid use. Hearing aid use as measured via data logging 1 month after interventions favoured the MI group.
(3) A qualitative enquiry embedded in the above pilot RCT was conducted. 34 out of 37 participants underwent in-depth interviews. Interviews were transcribed and thematically analysed. Five themes were identified in relation to participants’ perspectives about the key components of the research programme which influenced their decision about using their hearing aids.
Conclusion: Conducting an RCT on the effect of MI in facilitating hearing aid use in people who do not use their hearing aids is feasible and that MI combined with audiology standard care may have positive effects on hearing aid use
Differential effect of adaptation on the ipsi- and contralateral auditory brainstem pathways
No full text
Building Thermal Performance Varies During Extreme Heat within Cities
No full textabstract: This document has been superseded by our peer-reviewed publication:
Building Thermal Performance, Climate Change, and Urban Heat Vulnerability, Matthew Nahlik, Mikhail Chester, Stephanie Pincetl, David Eisenman, Deepak Sivaraman, and Paul English, 2017, ASCE Journal of Infrastructure Systems, 23(3), doi:10.1061/(ASCE)IS.1943-555X.0000349
The publication is available at: http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000349
The leading source of weather-related deaths in the United States is heat, and future projections show that the frequency, duration, and intensity of heat events will increase in the Southwest. Presently, there is a dearth of knowledge about how infrastructure may perform during heat waves or could contribute to social vulnerability. To understand how buildings perform in heat and potentially stress people, indoor air temperature changes when air conditioning is inaccessible are modeled for building archetypes in Los Angeles, California, and Phoenix, Arizona, when air conditioning is inaccessible is estimated. An energy simulation model is used to estimate how quickly indoor air temperature changes when building archetypes are exposed to extreme heat. Building age and geometry (which together determine the building envelope material composition) are found to be the strongest indicators of thermal envelope performance. Older neighborhoods in Los Angeles and Phoenix (often more centrally located in the metropolitan areas) are found to contain the buildings whose interiors warm the fastest, raising particular concern because these regions are also forecast to experience temperature increases. To combat infrastructure vulnerability and provide heat refuge for residents, incentives should be adopted to strategically retrofit buildings where both socially vulnerable populations reside and increasing temperatures are forecast
Building and processing a dataset containing articles related to food adulteration
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (page 69).In this thesis, I explored the problem of building a dataset containing news articles related to adulteration, and curating this dataset in an automated fashion. In particular, we looked at food-adulterant co-existence detection, query reforumulation, and entity extraction and text deduplication. All proposed algorithms were implemented in Python, and performance was evaluated on multiple datasets. Methods described in this thesis can be generalized to other applications as well.by Deepak Narayanan.M. Eng
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