Introduction: that urban design plays a role in moulding

Introduction:This report will talk about how secondary data analysiscan be helpful in conducting a research about studying the negative effectsurban life has on the mental health.

ConceptualFrameworkA healthy population means a healthy, thriving, andresilient urban city, and it is with time becoming clear that urban designplays a role in moulding this. This realisation has led to varioushealth-themed planning and design guidelines for innovation, and yet amidst theneed to integrate health promotion into urban design projects, one key questionis often missing: what about mental health?Cities offer economic, cultural, and educationalopportunities that most rural areas might not be able to. Urban areas in thefuture are expected to house about two-thirds of the world’s population by 2050and some urban areas, mostly in the Asian countries, are predicted toexperience unparalleled development, thus bringing forth the relationshipbetween urban environments and mental health more rapidly.

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Cities continue to grow with unprecedented challenges anduncertainties, making mental health of the city dwellers a more concerningfactor to consider, while charting planning policies and designing urbanexpansions and development.There have been studies pointing out about how living inan urban area undesirably affects mental health. It is equally beneficial and harmfulto be living in a city when considering mental health.

One of the factorsaffecting is the sensory overload due to the many things bombarded on to ahuman in a single particular moment. Some scholars have argued that the highstimulation of the human brain to capture and process all the fast informationof the surrounding environment is challenging for the mental health in the longterm.There is also a substantial amount of study done internationallyby psychologists and neuroscientists proposing that urban living, particularly unthoughtfullydesigned environments, are one of the reasons to the negative implications onmental health of the city dwellers.

For example, insufficient, overcrowded, unhygienichousing has been proven to reduce the human coping capacity, while the lack of abasic amenity as simple as a playground can influence children’s wellbeing. Citiesare becoming more crowded by the day and the rising proportion of people livingalone is considerably leading to higher levels of loneliness, creating a futurerisk for deterioration of mental health. (Rapoport, 2016) It has thus, alsobeen studied that in comparison to non-urban areas, cities around the worldhave a rising occurrence of acute mental illnesses, and problems such as stressand isolation. (Adli, 2011)A recent study showed that urban dwellers have a 20 percent higher risk of developing anxiety disorders, and a 40 per cent higher riskof developing mood disorders. Longitudinal studies on patients withschizophrenia indicate that it is urban living and upbringing per se, rather thanother epidemiological variables, which increase the risk for mental disorders.(Adli, 2011)It has been marked that living in an urban environment couldbe a concerning factor for psychiatric diseases such as depression orschizophrenia.

The high exposure to stress and specifically social stress seemsto play a crucial role in increasing the risk of mental disorders. Highlypopulated cities lead to people facing higher social evaluation and socialstress, outweighing other urban stressors like pollution or noise.The major purpose of the conceptual framework is to pointout the necessity of understanding the negative effects of rapid unthoughtfulurban expansions and thus the importance of making sensitive design amendmentsand planning policies to avert such an unhealthy development. It is also tounderstand the different dimensions of the negative consequences that city lifecan give rise to, other than just the benefits it has to offer.The major objectives to achieve a reasonable result of mystudy are outlined below:·        To explore the various design factorsaffecting mental health·        To explore the non-design factors affectingmental health·        To identify the impact of population growthon urbanism and deterioration of mental health·        To identify the cognitive responses to thephysical environment·        To explore how different police making bodieslike the Government, Non-government organisations can help cater to theproblem.·        To understand if urban design can really helpmake a difference·        To make policy recommendations MethodologyTo initiate a dissertation as outlined in the conceptualframework it is necessary to understand the methodological inferences and whatkind of a research method can be useful for analysing the data to come to anykind of conclusion for the research question in hand. Secondary data analysis provesto be a helpful research method to overcome the restrains of the limitingfactors like time and cost.

My research would be based on urban development andits effects on mental health globally but I would try and focus more on the Asiancountries like India and China and thus it would be necessary to analyse theofficial data collected by various government institutions. Another factorwould be to compare the eastern countries with the western countries in termsof the population growth and rapid development effecting mental disorders. Thiswill help gain more insight and clarity for the policy recommendations to bemade at the end of the research. ResearchMethod: Secondary Data AnalysisIn terms of finances and time context, methods likesurvey research by questionnaire or structured interview or experimentationscan prove to be expensive to conduct. As a student, time and financial resourcesare the main limiting factors when it comes to conducting research for thedissertation.

Many organisations, both private and government departmentcollect a wide range of data presented in a statistical form that can beutilised by a social scientist. (Bryman, 2012). Generation of new hypothesis oranswer to a critical research question can be analysed by the use of existingdata (Tripathi, 2013).

Moreover, technological advancement has created ascenario where a huge amount of data can be collected, compiled and archivedand is easily accessible to researchers (Johnson, 2014). Secondary data analysis is the analysis of data withoutbeing involved in the data collection process (Bryman, 2012). These means thatthe data was collected for another primary process (Bryman, 2012). This meansthat the data was collected for another primary reason but is utilised byanother researcher to find the answer to a different research question.However, there is a debate around analysis between quantitative and qualitativedata set.

For example, quantitative data sets like national census track surveyare considered to be a common and cost effective way of utilising the data forsecondary data analysis (Cherlin 1991; Greit andGraham 1989; Miller 1982). Onthe other hand, secondary analysis of qualitative data has been neglectedbecause of doubts about the quality of the qualitatively generated data (Thorne1994).Strengthof Secondary data analysis:Secondary data analysis offers varied advantages toresearchers with limited resources.1.

Time and cost effectiveness:The first advantage of secondary data analysis is itsaves time (Ghauri, 2005). It offers access to quality data for a minimalexpense of resources compared to resources that would have been required tocollect the data themselves (Bryman, 2012) For example, to collect data fromscratch, it will require expenses like salaries, transportation, and so on,where on the other hand even if the secondary data set needs to be purchased,the cost would be minimal. There is also time savings because the data is alreadycollected and updated electronically so the researcher can utilise the valuabletime analysing the data and writing hypothesis around it. (Borslaugh, 2007).

For instance, numerous data sets are available from the data archive availablein the University library for its students to carry out data analysis forresearch projects. In addition, web platforms like google scholar always givean extra advantage of all the information made available by other researchersto work on. Moreover, the search engines are technologically very advanced thatonly the keywords are necessary to find out abundant information for thatspecific topic. 2. Good quality data:The majority of the data sets most frequently used are ofvery good quality (Bryman, 2012). To elaborate this claim by Bryman, firstly,there is a rigorous process involved in the sampling process. Secondly, thesample data are often national samples governed by the government with lack oflimitations in labour and finance.

The geographical coverage and the samplesize if these data are enormous as well which wouldn’t be possible for aresearcher under time and financial constraint. Thirdly, highly experiencedresearchers generate majority of the data, and some cases which have huge datasets are collected by social research organisations which are well equippeddeveloped structures and control procedures to update and check the quality ofthe data all the time. (Bryman, 2012)3. Feasibility of both longitudinal and cross-culturalanalysis:Longitudinal analysis is very expensive and timeconsuming in social sciences. Research that requires analysis of any trend withtime, secondary data analysis provides that opportunity in a very reasonableway (Boslaugh, 2007). For example, ..

..These surveys are carried out by a worldwide network ofsocial scientists since such work isn’t feasible one on one throughout almost100 countries. (Boslaugh, 2007). To collect such volumes of data throughprimary data collection is extremely difficult and often fails to include the diversecomparison of social …. necessary.4. Generating new insights:New insights can be generated from previous analysis andmay lead to unanticipated new discoveries.

For example, a particular set ofdata can be analysed in many ways and the secondary data analyst may choose totake certain variations of interest and consider the impact of it (Bryman,2012) As new methods and techniques of quantitative data analysis are developedby the statistics and —- disciplines, researchers become more —- in applyingthem in the data sets and come up with new conclusions and perceptions.(Bryman, 2012)5. Responsibility of Social researcher:The research participants give some of their time withbasically no reward for the purpose of the social research. If the data setscollected are surely used for a single study, that research is under analysedand does not justify the time given both by the participant and the whole datacollection process.

Secondary data analysis provides that window of utilisingthe data to the fullest (Bryman, 2012)6. Consistency of the primary data set:It is always beneficial as a secondary data analyst tocompare findings from two or more sources that have arrived at the sameconclusion or they did not provide an option for contrast. This gives theresearcher an extra confidence to check fo the consistency of the informationfor the most valid conclusion. (Johnson, 2014)Limitationsof Secondary Data Analysis:Compared to the benefits of the secondary data analysisexplained above the limitations might not be as dominant but still warrantssome attention. 1. Lack of familiarity with data:As researchers do not participate in the initial datacollection process, there will be a range of variables that the researcher willbe unaware of that took place during the data collection (Bryman, 2012). Forinstance, the secondary data analyst is unaware of the problems during datacollection such as participants misunderstanding of specific survey questionsor low response rates (Johnson, 2014).

2. Complexity of data:A data set consisting of large number of large numbers ofvariables and respondents might pose complexity to the secondary researchthrough the management of the information in hand and also to identify whichlevel of analysis is required (Bryman, 2012).3.

Quality of Data:Although secondary data analysis provides opportunitiesto researchers to verify data of higher quality compared to collecting itthemselves, quality of data should never be taken for granted (Bryman, 2012).As stated by Saunders (2009) that as the secondary analyst always lacks acontrol over data quality an intensive verification must be taken intoconsideration before using it.Usesof Secondary data analysis in research and practice:The secondary data analysis is widely used as researchmethod in both research and practice.

A case study of such a research was national workforcedataset to examine the support people with dementia receive from social careworkforce in England. The secondary analysis was done by taking 457031 uniqueworkers recorded from the national workforce dataset from England. Theresearchers came up with the results that reflected that dementia careworkforce are mainly female and are less qualified and should be provided withtraining and skills. (Hussein and Manthorpe, 2011)Ethicalimplications:As secondary analysis is the use of existing primaryresearch data to find answers to questions which are different from theoriginal one there is always pressing issue of what fundamental ethical issuesshould it follow (Tripathy, 2013) or are the secondary data analyst free fromany kind of burden of ethical approval for their research (Data Big and Small,2015). Although the whole process of secondary data analysis involves ethicalconsiderations regardless of primary data used or not. From the initial designof the research to the findings of results, it should aim at the ethical codesof public good, should pose no harm to the public and ensure transparency andreproducibility (Data Big and Small, 2015).

But the value of secondary analysiswill only be noticeable when ethical consents like re-identification ofparticipants and disclosure of sensitive information are considered. However,to make secondary data analysis a highly ethical practice the secondary analystmust meet some key ethical conditions outlined below.·        Consent of research participants can besensibly assumed·        De-identification must be maintained of the databefore releasing it to the researcher·        Results of the research analysis must notallow re-identification of the participants·        Utilisation of the data must not bring aboutany harm or misery Conclusion:Secondary data analysis offers methodological benefits andcan contribute to my research through generating new knowledge. The overallgoal of the study is to give policy recommendations regarding changes to bemade for reducing negative impacts on mental health due to rapid urbandevelopment. Regarding how complex and time intensive this study is, secondarydata analysis method gives me that advantage of analysing high quality datawith minimal cost and time and providing me with valuable insight.

Yet, toutilise secondary analysis method effectively, it requires a systematic processand planning that acknowledges the challenges of using huge official data setsand address the discrete characteristics of secondary data analysis. Althoughthe benefits of secondary analysis outweigh the limitations, careful measuresare required to minimise them. In addition, special emphasis should be given tothe ethical implications of secondary analysis as well. Thus, by ensuring amatch between the research question and the existing data as well as followingthe proposed procedure explained in conceptual framework and methodologysection above. I will try and minimise the errors and limitations of secondaryanalysis and help in providing a justifiable policy recommendation at the endof the study.