Participation, Agency and Gender: The Impacts of Participatory Video Practices on Young Women in India

The use of Participatory Video (PV) in development projects with marginalised communities by Non-government organisations is increasing. Though PV practice has expanded, there has been limited academic discussion and debate on the subject. PV is often assumed to be a non-problematic process that enables less powerful groups to gain power and participate in social change processes. This research contributes to the emerging academic debates by critically investigating how participating in a long-term PV project can provide participants the opportunity to gain agency and to engage with local social change in a sustained manner. It studies projects by two NGOs in Hyderabad and Mumbai, which work with young women participants, using gender as a lens to examine the role of power relations within the projects. This thesis draws on three key concepts: (i) participation, (ii) agency and (iii) gender norms. Using the conceptualisation of agency in the Capability Approach, it focuses on the various aspects of a long-term PV project that can either promote or restrict young women’s agency. The methods of collecting data were interviews, group discussions, participatory observation and participatory video-making with the research participants. The analysis of the data was carried out using a framework which maps the relationships between the various phases of a long-term PV project and the participants’ agency. Based on the findings of the analysis, this thesis argues that oppressive gender power relations within their household and the community, and hierarchy within a supposedly participatory project are critical influences on young women’s ability to become agents of change. In particular, the thesis draws attention to: (i) participants’ need to continuously negotiate power with the household and community members, (ii) inherent hierarchy and the nature of participation in a long-term PV project, (iii) the relation between participants’ need to access resources and hierarchy within a project, and (iv) the difference in needs, goals and impacts identified by donors/NGOs and the participants. The thesis proposes a conceptual model of participatory video as an agency-development process, which shows how these factors are crucial in developing and sustaining participants’ agency. This thesis builds new knowledge by providing an in-depth understanding of power relations in long-term PV projects and what impacts agency - areas which are often overlooked in the literature on PV

Predicting Hospital Length of Stay in Intensive Care Unit

In this thesis, we investigate the performance of a series of classification methods for the Prediction of the hospital Length of Stay (LoS) in Intensive Care Unit (ICU). Predicting LOS for an inpatient in an hospital is a challenging task but is essential for the operational success of a hospital. Since hospitals are faced with severely limited resources including beds to hold admitted patients, prediction of LoS will assist the hospital staff for better planning and management of hospital resources. The goal of this project is to create a machine learning model that predicts the length-of stay for each patient at the time of admission. MIMIC-III database has been used for this project due to detailed information it contains about ICU stays. MIMIC is an openly available dataset developed by the MIT Lab for Computational Physiology, comprising de-identified health data associated with ~40,000 critical care patients at Beth Israel Deaconess Medical Centre. It includes demographics, vital signs, laboratory tests, medications, and more. Different machine learning techniques/classifiers have been investigated in this thesis. We experimented with regression models as well as classification models with different classes of varying granularity as target for LoS prediction. It turned out that granular classes (in small unit of days) work better than regression models trying to predict exact duration in days and hours. The overall performance of our classifiers was ranging from fair to very good and has been discussed in the results. Secondly, we also experimented with building separate LoS prediction models built for patients with different disease conditions and compared it to the joint model built for all patients

Predicting Hospital Length of Stay in Intensive Care Unit

In this thesis, we investigate the performance of a series of classification methods for the Prediction of the hospital Length of Stay (LoS) in Intensive Care Unit (ICU). Predicting LOS for an inpatient in an hospital is a challenging task but is essential for the operational success of a hospital. Since hospitals are faced with severely limited resources including beds to hold admitted patients, prediction of LoS will assist the hospital staff for better planning and management of hospital resources. The goal of this project is to create a machine learning model that predicts the length-of stay for each patient at the time of admission. MIMIC-III database has been used for this project due to detailed information it contains about ICU stays. MIMIC is an openly available dataset developed by the MIT Lab for Computational Physiology, comprising de-identified health data associated with ~40,000 critical care patients at Beth Israel Deaconess Medical Centre. It includes demographics, vital signs, laboratory tests, medications, and more. Different machine learning techniques/classifiers have been investigated in this thesis. We experimented with regression models as well as classification models with different classes of varying granularity as target for LoS prediction. It turned out that granular classes (in small unit of days) work better than regression models trying to predict exact duration in days and hours. The overall performance of our classifiers was ranging from fair to very good and has been discussed in the results. Secondly, we also experimented with building separate LoS prediction models built for patients with different disease conditions and compared it to the joint model built for all patients

Defining participatory video from practice

In this chapter we explore the common threads within different strands of participatory video by considering some examples of practice. Taken together these reveal a rich diversity of purpose and application. Participatory video has been used as a term to describe some quite distinct practices, and conversely, there are instances of the use of video in social settings that seem to be closely related to participatory video without being described as such. This makes it difficult to immediately pin down what the term means, and indeed it is said that there is no common understanding of participatory video. To scholars the diversity of participatory video practice presents two separate issues. The first is that it is necessary to bear in mind that participatory video has been applied in many more ways outside of academic research and education than inside. Even if one is only interested in participatory video solely as a component of research, an understanding of non-academic practice is likely to enrich and enhance methodological choices. The second is that participatory video is a rich site for a pragmatic and phronetic scholarship that questions social experiences to explore what works and to what end. The question here is what lessons can be learned from diverse practices, and how to apply this learning elsewhere. Thus with participatory video, as with any practice, scholarship has a role to play in terms of providing a platform for considered and critical reflection, a space to consider the significance of what is and of what could be. Effective reflection rests on some basic taxonomic work in order to gain an overview of the field. We therefore have selected three vignettes to show some key features of participatory video in practice, with an eye to establishing a broad baseline. These examples are drawn from our personal research in two cases and some background research in the third. For the purpose of this chapter, breadth is more appropriate if we are interested in to explore the range of extant practice, and the vignettes are simple outlines to provide illustration for an exploratory discussion rather than fully developed case studies with all of the detailed evidence presented

Prescribing pattern of antimicrobial agents in intensive care unit of a teaching hospital in Central India

Background: Patients admitted to the Intensive care unit (ICU) receive multiple medications from a variety of pharmacological classes due to various life threatening illness and co-morbidities. The present study aims to evaluate the current usage of anti-microbial agents (AMAs) in the ICU of a teaching hospital in central India.Methods: A prospective observational study was carried out at the 11 bedded medical ICU of R. D. Gardi Medical College and Hospital, Ujjain (M.P.) for a period of 3 months from Aug 2012 to Oct 2012. The relevant data on drug prescription of each patients was collected from the inpatient case record. The demographic data, disease data and the utilization of different AMAs were analyzed.Results: A total of 1671 drugs out of which 343 AMAs were prescribed in 148 patients (male-78, female-70) studied, that is, an average of 11.3drugs/patients and 2.32 AMAs/patients. In ICU cefotaxime was the most commonly used AMAs in 17.5% patients, followed by metronidazole in 14% patients and ciprofloxacin in 8.8% patients. Most common indication for the anti-microbial therapy was infection (51.4%). 80.4% patients were given 1-3 AMAs, 19.6% patients were given 4-9 AMAs. amoxicillin+clavulanic acid was the most common FDC noticed.Conclusions: Interventional programme should focus on infection control with rational antibiotic prescription aimed at minimizing unnecessary cost, adverse drug reaction and emergence of bacterial resistance

Performance Evaluation in Energy consumption of Mobile Ad-Hoc Network to increase the Network Lifetime

MANET is self configuring network. It has many design issues like scalability, energy consumption etc.In this paper, an overview of the Distributed mutual exclusion algorithm & various enhanced variations done on distributed mutual exclusion. In DME Permission-based algorithm is used for discovering clusters of the nodes. The initial point selection effects on the results of the algorithm, in the number of clusters found and their cluster headers. Methods to enhance the Permission-based clustering algorithm are discussed. With the help of these methods increase the concurrency between the nodes, decrease the synchronization delay and decrease response time. Some enhanced variations improve the efficiency and accuracy of algorithm. Basically in all the methods the main aim is to increase the life of each node in the network or increase the battery power which will decrease the computational time. Various enhancements done on DME are collected, so by using these enhancements one can build a new hybrid algorithm which will be more efficient, accurate and less time consuming than the previous work

Serum homocysteine and folate levels as a predictor of materno-fetal outcome in preeclamptic women

Background: To study the role of serum homocysteine and serum folate levels in prediction of materno-fetal outcome in preeclamptic women, especially in early onset preeclampsia.Methods: This prospective study was conducted in a tertiary care teaching hospital in India. 60 preeclamptic women (Group A) that were matched with 60 normotensive pregnant women (Group B), with singleton pregnancy and gestational age between 24-32 weeks attending antenatal clinics were included in the study. Maternal blood was collected twice first at time of enrolment and second at delivery. Serum homocysteine and serum folate levels were analyzed using enzymatic assay and chemiluminescent immunoassay. Mean rise in serum homocysteine and folate levels were calculated individually in all patients.Results: Mean homocysteine levels were significantly higher in Group A as compared to Group B both at enrolment and delivery (p 0.05).Conclusions: Serum homocysteine can be used as a reliable marker for predicting the severity of preeclampsia and adverse pregnancy (both maternal and fetal) outcome thus helps in reducing maternal and fetal morbidity and mortality, especially in women with early onset preeclampsia

Retrospective analysis of indications of primary caesarean sections done at a tertiary care hospital

Background: Caesarean section rates have globally risen above the levels that can be considered medically necessary. The aim of the study is to analyze the rate and indications of caesarean sections for primigravidae in the period 2016 to 2018 at a tertiary care hospital in Delhi.Methods: It is a retrospective observational study conducted in the Department of Obstetrics and Gynaecology at PGIMER and Dr RML Hospital, New Delhi. A total of 552 caesarean deliveries in primigravidae were studied.Results: The total deliveries during the study period were 3346 and the total caesarean section rate observed was 30.66%. The caesarean section rate among primigravidae was 29.1%. The rate of caesarean section in primigravidae rose from 22.7% in 2016 to 39.3% in 2018 with 17% increase. Majority of them belonged to the age group 20-30 years (79.34%) and 2.53% were elderly primigravidae. Out of the total number of primigravidae caesarean deliveries, 67.2% were performed in emergency and 32.7% were performed electively. Among the emergency caesarean sections performed, 64% of patients had induced labor and 22% had spontaneous labor. The most common indication of caesarean section was fetal distress (19.77%) followed by arrest of labor (17.87%) and malpresentations (8.9%). The short-term caesarean morbidity rate was 25.4% including one mortality. Wound infection was the most common complication.Conclusions: Various reasons like changing maternal risk profile increased IVF pregnancies, scientific advances, personal choice and medico legal considerations have been cited for increased caesarean rate. Following evidence-based labor protocols, judicious use of cardiotocography, proper patient selection for labor induction and patient education will contribute in reduction of caesarean sections and related complications

Assessing patients' knowledge about their management plan

Introductions: Patients’ oliane for etter ealt an e aieed if patients are well aware about their disease and treatent lan. Patient’s knowledge about diagnosis and treatment plan improves outcomes. This study ais to araterie atient’s nolede aout teir osital admission and treatment plan in different wards of Patan Hospital. Methods: This was a cross sectional study, undertaken in Patan Hospital. A pilot survey using purposive sampling was conducted to find out prevalence for the sample size (N=160) calculation and pre-testing of the questionnaire. Systematic random sampling was done. Finally, 154 patients agreed to be interviewed and data on their knowledge about treatment plan were analysed. The collected data were entered in Epi-Info (Free) and analysed in SPSS®. Results: Out of 154 patients interviewed, 118 (76.6% knew about their diagnosis and 48 (31.2%) were able to recall in medical terms. Regarding 151 patients who had undergone investigations, 60 (39.7%) patients knew details of at least one test, 7 (4.6%) knew details of all the tests, 41 (27.2%) knew about the results of their tests. Out of 143 patients who were prescribed medications, 100 (69.9%) patients were not able to state any of the medicines given to them and 8 (5.6%) were able to tell each of them. Conclusions: Most of our patient knew about their diagnosis and treatment plan; however, there are significant room for improvement in terms of educating patients about the tests being performed and drugs administered. Keywords: hospital admission and treatment plan, patients’ oliane, patient'sknowledge, patient management plan, patient outcom