Summary of the Article
The article indicates that the Social Security Act, in section 1130, allowed the United States Department of Health and Human Services to pass projects meant for demonstrations regarding child welfare and foster care services. Such approvals were supposed to be given to titles IV-E and IV-B. The approach was a strategic method for understanding the best ways to ensure effective and innovative practices used in child welfare. Consequently, both states and tribal organizations dealing with child fostering could use federal funding to provide all the needed services. In particular, Title IV-E waivers followed the 1980s and 1990s shifts in foster care and child welfare systems. The study indicates that the initial title IV-E waivers were applied in 1995 when 23 states implemented multiple demonstrations in ten years (Graham, 2021). The projects involved using different service provisions, such as the permanence of the guardianship, payment of care services, and extended in-home and reunification.
The study used various evaluation designs, including primary research designs of waiver demonstration evaluations and safety outcomes of waiver demonstrations, in different jurisdictions. Other design methods included permanency outcomes of waiver demonstrations, wellbeing outcomes of waiver demonstrations, and focus of waiver demonstration sub-studies. The evaluation findings indicated different implementation approaches, including facilitators, challenges, fidelity, and timing of the activities. The facilitators included consistent efforts by workers to provide helpful service, using data to inform decisions, effective management, availability of services across an extended area, and well-trained personnel. Challenges included screening, communication, logistics obstacles, inadequate training among some workers, insufficient service provision in some areas, and awareness of new programs. The study also revealed that there was significant positive relation regarding child safety practices in most jurisdictions. Moreover, the evaluation reported that many jurisdictions indicated positive permanency outcomes, such as the duration of the placement and its stability. Furthermore, there was significant regard for child wellbeing in most of the jurisdictions investigated. Finally, the research found out that there were varying levels of cost studies based on each state’s efforts.
Qualitative Data Analysis Methods
There are several qualitative data analysis software used depending on the analysts’ experience and data type. The most commonly used tools include NVivo, Atlas.ti, and Excel. NVivo software supports both qualitative and mixed research designs. According to Jackson and Bazeley (2019), NVivo enables researchers to arrange, organize, and gain in-depth insights regarding unstructured studies such as interviews, web pages, social media, and articles. The NVivo software will be used by first organizing the research into different themes, identifying various nodes, and conducting the search using specific terms and phrases, which will put the themes in content. The study by Francis et al. (2017) used NVivo software to analyze themes regarding informing intervention strategies, which were meant to reduce the energy drink consumption of the youth. This reveals that the software is critical for analyzing advanced research projects.
Atlas.ti is one of the most commonly used qualitative analysis tools among researchers because of its power and ease of use. According to Friese (2019), Atlas.ti enables researchers to explore broad areas of their studies since the tool helps to reveal meaning and relationships in the different aspects of the data. Some of the studies that have used Atlas.ti include Amirzadeh and Barakpour (2019) and Park (2018). The software will be used in conjunction with current advanced technologies such as artificial intelligence and machine learning to identify key themes emerging from the text, which will be analyzed.
Lastly, Microsoft excel is also powerful software for qualitative data analysis. According to Skalidou and Oya (2018), who used the software to analyze their study’s data, excel enables researchers to import data from other word-processing software and arrange them in themes and codes. The tool will be used by copying using words in a.txt file, putting them in source cells, and creating specific nodes. This approach will be helpful since excel uses formulas that help to identify and categories text belonging to specific themes into targeted cells.
References
Amirzadeh, M., & Barakpour, N. (2019). Developing a framework for community resilience to drought in Isfahan through qualitative research method and ATLAS-ti software. Journal of Environmental Studies, 44(4), 763-781. Web.
Francis, J., Martin, K., Costa, B., Christian, H., Kaur, S., Harray, A., Barblett, A., Oddy, W. H., Ambrosini, G., Allen, K. and Trapp, G. (2017). Informing intervention strategies to reduce energy drink consumption in young people: Findings from qualitative research. Journal of Nutrition Education and Behavior, 49(9), 724-733. Web.
Friese, S. (2019). Qualitative data analysis with ATLAS. ti. Sage.
Graham, E. (2021). Title IV-E waiver demonstrations: History, findings, and implications for child welfare policy and practice. Children’s Bureau, Administration for Children and Families, U.S. Department of Health and Human Services.
Jackson, K., & Bazeley, P. (2019). Qualitative data analysis with NVivo. Sage.
Park, Y. A., Kong, E. H., & Park, Y. J. (2018). Head nurses’ experiences in clinical practice education of nursing students: A qualitative research. The Journal of Korean Academic Society of Nursing Education, 24(4), 337-346. Web.
Skalidou, D., & Oya, C. (2018). The challenges of screening and synthesizing qualitative research in a mixed-methods systematic review. The case of the impact of agricultural certification schemes. Journal of Development Effectiveness, 10(1), 39-60. Web.