Depression Across Community Environment †Myassignmrenthelp.Com

Question: Discuss About The Depression Across Community Environment? Answer: Introducation The research question in the presented case scenario attributes to the systematic analysis of the psychosocial experiences of the adolescent individuals affected by the pattern of depression across the community environment. The qualitative research analysis would analyse and investigate the impact of the clinical manifestations of the depressive episodes on the on the pattern of health and wellness of the depressed adolescents. For example, the pattern of emotional paralysis experienced by the depressed adolescents requires exploration in the context of evaluating their subjective experiences attributing to irritability, impatience, anxiety, fear and panic (Amini, Negarandeh, Cheraghi, Eftekhar, 2013). Depressed people might experience dyshedonia, leading to the development of inconsistent behaviour. Similarly, disturbed thought processes of the depressed adolescents require subjective qualitative analysis while identifying the state of their guilt, spiritual conventions, beliefs a nd level of frustration (Amini, Negarandeh, Cheraghi, Eftekhar, 2013). The qualitative analysis requires further utilization in the context of exploring the pattern of cognitive decline experienced by the depressed adolescents. The identification of the attributes including indecisiveness, adverse evaluation, absence of concentration and memory, physical constrains, pain pattern, sleeping issues, facial alterations, appetite problems as well as sexual dysfunction is necessarily required for their evidenced-based qualitative analysis (Amini , Negarandeh, Cheraghi, Eftekhar, 2013). The study design as well as study method for this qualitative intervention could include the administration of semi-structured interviews to the adolescent individuals affected with the pattern of depression and associated clinical manifestations (Overend, et al., 2015). The recruitment of the study participants will be based on the diagnosis of depression and age group of the eligible subjects. The findi ngs of the interview data require a subjective analysis by multiple healthcare professionals from diverse clinical backgrounds (Overend, et al., 2015). The analysis of the depression-based data would require the utilization of a grounded theory approach in the context of generating a theorized concept evolving from the research findings. Contrarily, the quantitative analysis of depression manifestations and experiences of the adolescent people requires their objective measurement with the utilization of pre-defined variables and scales for leading a hypothesis (Teixeira, Fernandes, Llonch, 2013). These scales could measure the intensity of depressive episodes experienced by the depressed people and interpret the severity in terms of scores. The higher scores will correlate to the elevated level of deterioration of self-esteem of adolescent individuals, under the influence of depression. However, lower scores will reveal minimal influence of depression episodes on the quality of lif e and wellness outcomes of the depressed adolescents (Teixeira, Fernandes, Llonch, 2013). Sample Recruitment The qualitative recruitment strategy focuses on including the study subjects in accordance with the subjective inclusion criteria specified for undertaking the research intervention (Mendez-Luck, et al., 2011). The research professionals would identify the potential participants after their systematic screening and the subjects who do not qualify in the adolescent age range would be summarily rejected in accordance with the inclusion criteria. Similarly, the healthy adolescents who do not experience depressive manifestations require exclusion from the research study. The qualitative sample recruitment strategy would not consider the subjects who refrain themselves from undertaking the preliminary screening process or quit the study during the follow-up period. The qualitative sampling of the depressed adolescents will take into consideration the knowledge base and subjective experiences of the adolescents in relation to the pattern of depression and associated experiences (Palinkas, et al., 2015). People without appropriate knowledge of the same will remain excluded from the study in accordance with the qualitative selection convention. The qualitative inclusion criteria will also consider the communication potential of the selected individuals in terms of sharing their depression experiences in a reflective, expressive and articulative manner (Palinkas, et al., 2015). The qualitative method of purposeful sampling attempts to acquire the in-depth understanding of selected subjects in the context of undertaking subjective analysis from the data obtained from the semi-structured interviews (Palinkas, et al., 2015). Contrarily, the quantitative selection methodology will acquire a more generalized selection approach while utilizing an established set of formulae on a wider scale (Palinkas, et al., 2015). The qualitative selection methodology advocates the concept of homogeneity warranting the selection of a smaller sample size in comparison to the quantitative sel ection approach that requires the selection of a larger number of research subjects (Palinkas, et al., 2015). Data Collection Approaches The data collected from the semi-structured interview sessions in the presented case scenario would require the production of larger data sets for their subjective evaluation by the healthcare professionals (Sutton, 2015). The transcription of the recorded data is necessarily required before initiating the qualitative data analysis process. Research professionals might also append annotations in relation to various behavioural and environmental attributes that could influence the qualitative data analysis and the associated results (Sutton, 2015). The appended field notes assist in evaluating the influence of circumstantial factors on the quality and accuracy of the extracted data. Contrarily, the data collection method acquired while undertaking quantitative research intervention advocates the requirement of data acquisition in the electronic format with the utilization of IT based interventions (Ponto, 2015). The tailormade self-administered questionnaires assist in collecting a hu ge amount of data in relation to the severity of depression experienced by the adolescent participants. The utilization of digital systems for capturing the non-verbal responses of the research participants assists in retaining the accuracy of the data collected and stored in the electronic medical records (Ponto, 2015). Data Analysis The qualitative data analysis of the experiences of depressed adolescents requires subjective execution by the research professionals (Austin, 2014). The research team members might perform coding of the retrieved information or interpret the same by appending their own remarks. The coding of the retrieved data requires its thematic capture with the identification of the concepts, thoughts and ideas requiring systematic evaluation by the research professionals (Austin, 2014). The text or phrases used by the study subjects during the semi-structured interview sessions requires focussed and meaningful interpretation with the objective of retrieving the perspectives advocated by the participants. Thematic conversion of interview findings might require the utilization of software like NVivo (Austin, 2014). Manual conversion of large datasets into grounded themes is not recommended in the context of reducing the scope of errors in the interpretation of study findings. Research professiona ls require systematic documentation of various coding paradigms in accordance with the inclusion and exclusion criteria (Austin, 2014). Thematic conversion of the depression data in the presented clinical scenario will assist in generating a hypothesis that might require further testing and evaluation through prospective quantitative research interventions (Austin, 2014). However, the quantitative data analysis approach advocates the determination of variables and establishing the same while incorporating a set of values with each variable requiring evaluation (Simpson, 2015). These variables require assimilation in accordance with the measurement level and attributes requiring assessment in accordance with the pre-defined parameters of the research study. In the presented case scenario, these variables might include the low severity and high severity depression episodes and the values could indicate the clinical manifestations experiences by the depressed adolescents across the com munity environment. The categorical evaluation of variables and associated values assists in their meaningful sequencing that evidentially predicts the outcomes of the quantitative research intervention. The dependent as well as independent variables require objective statistical interpretation for generating the research findings. The statistical approaches including ANOVA, Binomial test, Chi-square (2) test and Kendall tau () alternative requires utilization in the quantitative analysis for the systematic theorization of the outcome data (Simpson, 2015). Findings and Generalization The qualitative research intervention leads to weaker findings in comparison to the findings obtained through quantitative study (Anderson, 2010). The qualitative findings are categorized while structuring the responses provided by the participants. The baseline of the qualitative findings includes the evidence-based literature containing previously recorded data on the same subject of study. The generalizability of the qualitative research findings is achieved through the process of meta-synthesis, multidimensional analysis, documentation and audit of the recorded data, consistent comparison of the datasets, triangulation as well as systematic sampling (Leung, 2015). Therefore, the findings of the presented case scenario could acquire generalization with the systematic analysis and audit of the recorded patient experiences in terms of depressive complications. Contrarily, the pattern of generalizability retrieved through quantitative approaches varies reciprocally with the statistic al power of the study variables (Kukull Ganguli, 2012). The quantitative study findings acquire generalization in accordance with the research setting, sample selection methodology, level of selection bias as well as study limitations. The pattern of generalizability of quantitative research findings results in the generation of a hypothesis on a wider scale (Kukull Ganguli, 2012). However, the generalizability of findings in a quantitative intervention might reduce their sensitivity as well as internal under the influence of confounding variables (Kukull Ganguli, 2012). Therefore, healthcare professionals require undertaking evidence-based measures with the objective of reducing the scope of occurrence of bias in the study findings while excluding the confounding dataset from the research analysis. Grounded Theory Approach and Qualitative Research The acquisition of the grounded theory approach assists in the justification and design of the qualitative research methods in the context of generating findings of elevated quality (Sbaraini, Carter, Evans, Blinkhorn, 2011). These high-quality findings will require consistent utilization in the prospective research interventions with the objective of enhancing patient care outcomes in the clinical settings. The grounded theory approach in the context of qualitative analysis advocates the utilization of inductive assessment without waiting for the complete collection of the required data (Sbaraini, Carter, Evans, Blinkhorn, 2011). The data collection process runs in parallel with data analysis while facilitating the process of theoretical sampling. The grounded theory intervention further advocates the process of coding and comparison of the recorded data in the context of identifying the pattern of variation in the extracted data. The interrelation of codes results in the generati on of concepts. The data analysis is facilitated by memo-writing (Sbaraini, Carter, Evans, Blinkhorn, 2011). The concomitant execution of memo-writing, data comparison and coding leads to the process of theoretical sampling that evidentially assists in the development of emerging theory. The grounded theory approach advocates the acquisition of theoretical saturation in the context of substantiating the study results from the data analysis (Sbaraini, Carter, Evans, Blinkhorn, 2011). Substantive extraction of results under the direction of grounded theory approach leads to the development of substantive theory that revolves around the interrelated concepts and never considered as final by the research professionals (Sbaraini, Carter, Evans, Blinkhorn, 2011). Two grounded theory approaches include the evaluation of the dental treatment knowledge of the dental practitioners identified through interview sessions and theoretical sampling, and the willingness of the treated patients in terms of receiving the recommended dental approaches (evaluated through interview sessions and memo-writing) (Sbaraini, Carter, Evans, Blinkhorn, 2011). References Amini , K., Negarandeh , R., Cheraghi , M. A., Eftekhar , M. (2013). Major depressive disorder: a qualitative study on the experiences of Iranian patients. Issues in Mental Health Nursing, 34(9). doi:10.3109/01612840.2013.789942 Anderson, C. (2010). Presenting and Evaluating Qualitative Research. American Journal of Pharmaceutical Education, 74(8). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2987281/ Austin, Z. (2014). Qualitative Research: Getting Started. The Canadian Journal of Hospital Pharmacy, 67(6), 436-440. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4275140/#__sec10title Kukull, W. A., Ganguli, M. (2012). Generalizability - The trees, the forest, and the low-hanging fruit. Neurology, 78(23), 1886-1891. doi:10.1212/WNL.0b013e318258f812 Leung, L. (2015). Validity, reliability, and generalizability in qualitative research. Journal of Family Medicine and Primary Care, 4(3), 324-327. doi:10.4103/2249-4863.161306 Mendez-Luck, C. A., Trejo, L., Miranda, J., Jimenez, E., Quiter, E. S., Mangione, C. M. (2011). Recruitment Strategies and Costs Associated With Community-Based Research in a Mexican-Origin Population. The Gerontologist, 51(1), S94S105. doi:10.1093/geront/gnq076 Overend, K., Bosanquet, K., Bailey, D., Foster, D., Gascoyne, S., Lewis, H., . . . Chew-Graham, C. (2015). Revealing hidden depression in older people: a qualitative study within a randomised controlled trial. BMC Family Practice. doi:10.1186/s12875-015-0362-2 Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health, 533-544. doi:10.1007/s10488-013-0528-y Ponto, J. (2015). Understanding and Evaluating Survey Research. JADPRO, 6(2), 168-171. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4601897/ Sbaraini, A., Carter, S. M., Evans, R. W., Blinkhorn, A. (2011). How to do a grounded theory study: a worked example of a study of dental practices. BMC Medical ResearchMethodology. doi:10.1186/1471-2288-11-128 Simpson, S. H. (2015). Creating a Data Analysis Plan: What to Consider When Choosing Statistics for a Study. CJHP, 68(4), 311-317. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552232/ Sutton, J. (2015). Qualitative Research: Data Collection, Analysis, and Management. CJHP, 68(3), 226-231. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4485510/ Teixeira , N. J., Fernandes , d.-C., Llonch , S. A. (2013). A quantitative, cross-sectional study of depression and self-esteem in teenage and young adult burn victims in rehabilitation. Ostomy/Wound Management, 59(9), 22-29. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/24018389