- Pre-registration nursing students
- No definition of master’s degree in nursing described in the publication
After the search, we collated and uploaded all the identified records into EndNote v.X8 (Clarivate Analytics, Philadelphia, Pennsylvania) and removed any duplicates. Two independent reviewers (MCS and SA) screened the titles and abstracts for assessment in line with the inclusion criteria. They retrieved and assessed the full texts of the selected studies while applying the inclusion criteria. Any disagreements about the eligibility of studies were resolved by discussion or, if no consensus could be reached, by involving experienced researchers (MZ-S and RP).
The first reviewer (MCS) extracted data from the selected publications. For this purpose, an extraction tool developed by the authors was used. This tool comprised the following criteria: author(s), year of publication, country, research question, design, case definition, data sources, and methodologic and data-analysis triangulation. First, we extracted and summarized information about the case study design. Second, we narratively summarized the way in which the data and methodological triangulation were described. Finally, we summarized the information on within-case or cross-case analysis. This process was performed using Microsoft Excel. One reviewer (MCS) extracted data, whereas another reviewer (SA) cross-checked the data extraction, making suggestions for additions or edits. Any disagreements between the reviewers were resolved through discussion.
A total of 149 records were identified in 2 databases. We removed 20 duplicates and screened 129 reports by title and abstract. A total of 46 reports were assessed for eligibility. Through hand searches, we identified 117 additional records. Of these, we excluded 98 reports after title and abstract screening. A total of 17 reports were assessed for eligibility. From the 2 databases and the hand search, 63 reports were assessed for eligibility. Ultimately, we included 8 articles for data extraction. No further articles were included after the reference list screening of the included studies. A PRISMA flow diagram of the study selection and inclusion process is presented in Figure 1 . As shown in Tables 2 and and3, 3 , the articles included in this scoping review were published between 2010 and 2022 in Canada (n = 3), the United States (n = 2), Australia (n = 2), and Scotland (n = 1).
PRISMA flow diagram.
Characteristics of Articles Included.
Author | Contandriopoulos et al | Flinter | Hogan et al | Hungerford et al | O’Rourke | Roots and MacDonald | Schadewaldt et al | Strachan et al |
---|---|---|---|---|---|---|---|---|
Country | Canada | The United States | The United States | Australia | Canada | Canada | Australia | Scotland |
How or why research question | No information on the research question | Several how or why research questions | What and how research question | No information on the research question | Several how or why research questions | No information on the research question | What research question | What and why research questions |
Design and referenced author of methodological guidance | Six qualitative case studies Robert K. Yin | Multiple-case studies design Robert K. Yin | Multiple-case studies design Robert E. Stake | Case study design Robert K. Yin | Qualitative single-case study Robert K. Yin Robert E. Stake Sharan Merriam | Single-case study design Robert K. Yin Sharan Merriam | Multiple-case studies design Robert K. Yin Robert E. Stake | Multiple-case studies design |
Case definition | Team of health professionals (Small group) | Nurse practitioners (Individuals) | Primary care practices (Organization) | Community-based NP model of practice (Organization) | NP-led practice (Organization) | Primary care practices (Organization) | No information on case definition | Health board (Organization) |
Overview of Within-Method, Between/Across-Method, and Data-Analysis Triangulation.
Author | Contandriopoulos et al | Flinter | Hogan et al | Hungerford et al | O’Rourke | Roots and MacDonald | Schadewaldt et al | Strachan et al |
---|---|---|---|---|---|---|---|---|
Within-method triangulation (using within-method triangulation use at least 2 data-collection procedures from the same design approach) | ||||||||
: | ||||||||
Interviews | X | x | x | x | x | |||
Observations | x | x | ||||||
Public documents | x | x | x | |||||
Electronic health records | x | |||||||
Between/across-method (using both qualitative and quantitative data-collection procedures in the same study) | ||||||||
: | ||||||||
: | ||||||||
Interviews | x | x | x | |||||
Observations | x | x | ||||||
Public documents | x | x | ||||||
Electronic health records | x | |||||||
: | ||||||||
Self-assessment | x | |||||||
Service records | x | |||||||
Questionnaires | x | |||||||
Data-analysis triangulation (combination of 2 or more methods of analyzing data) | ||||||||
: | ||||||||
: | ||||||||
Deductive | x | x | x | |||||
Inductive | x | x | ||||||
Thematic | x | x | ||||||
Content | ||||||||
: | ||||||||
Descriptive analysis | x | x | x | |||||
: | ||||||||
: | ||||||||
Deductive | x | x | x | x | ||||
Inductive | x | x | ||||||
Thematic | x | |||||||
Content | x |
The following sections describe the research question, case definition, and case study design. Case studies are most appropriate when asking “how” or “why” questions. 1 According to Yin, 1 how and why questions are explanatory and lead to the use of case studies, histories, and experiments as the preferred research methods. In 1 study from Canada, eg, the following research question was presented: “How and why did stakeholders participate in the system change process that led to the introduction of the first nurse practitioner-led Clinic in Ontario?” (p7) 19 Once the research question has been formulated, the case should be defined and, subsequently, the case study design chosen. 1 In typical case studies with mixed methods, the 2 types of data are gathered concurrently in a convergent design and the results merged to examine a case and/or compare multiple cases. 10
“How” or “why” questions were found in 4 studies. 16 , 17 , 19 , 22 Two studies additionally asked “what” questions. Three studies described an exploratory approach, and 1 study presented an explanatory approach. Of these 4 studies, 3 studies chose a qualitative approach 17 , 19 , 22 and 1 opted for mixed methods with a convergent design. 16
In the remaining studies, either the research questions were not clearly stated or no “how” or “why” questions were formulated. For example, “what” questions were found in 1 study. 21 No information was provided on exploratory, descriptive, and explanatory approaches. Schadewaldt et al 21 chose mixed methods with a convergent design.
A total of 5 studies defined the case as an organizational unit. 17 , 18 - 20 , 22 Of the 8 articles, 4 reported multiple-case studies. 16 , 17 , 22 , 23 Another 2 publications involved single-case studies. 19 , 20 Moreover, 2 publications did not state the case study design explicitly.
This section describes within-method triangulation, which involves employing at least 2 data-collection procedures within the same design approach. 6 , 7 This can also be called data source triangulation. 8 Next, we present the single data-collection procedures in detail. In 5 studies, information on within-method triangulation was found. 15 , 17 - 19 , 22 Studies describing a quantitative approach and the triangulation of 2 or more quantitative data-collection procedures could not be included in this scoping review.
Five studies used qualitative data-collection procedures. Two studies combined face-to-face interviews and documents. 15 , 19 One study mixed in-depth interviews with observations, 18 and 1 study combined face-to-face interviews and documentation. 22 One study contained face-to-face interviews, observations, and documentation. 17 The combination of different qualitative data-collection procedures was used to present the case context in an authentic and complex way, to elicit the perspectives of the participants, and to obtain a holistic description and explanation of the cases under study.
All 5 studies used qualitative interviews as the primary data-collection procedure. 15 , 17 - 19 , 22 Face-to-face, in-depth, and semi-structured interviews were conducted. The topics covered in the interviews included processes in the introduction of new care services and experiences of barriers and facilitators to collaborative work in general practices. Two studies did not specify the type of interviews conducted and did not report sample questions. 15 , 18
In 2 studies, qualitative observations were carried out. 17 , 18 During the observations, the physical design of the clinical patients’ rooms and office spaces was examined. 17 Hungerford et al 18 did not explain what information was collected during the observations. In both studies, the type of observation was not specified. Observations were generally recorded as field notes.
In 3 studies, various qualitative public documents were studied. 15 , 19 , 22 These documents included role description, education curriculum, governance frameworks, websites, and newspapers with information about the implementation of the role and general practice. Only 1 study failed to specify the type of document and the collected data. 15
In 1 study, qualitative documentation was investigated. 17 This included a review of dashboards (eg, provider productivity reports or provider quality dashboards in the electronic health record) and quality performance reports (eg, practice-wide or co-management team-wide performance reports).
This section describes the between/across methods, which involve employing both qualitative and quantitative data-collection procedures in the same study. 6 , 7 This procedure can also be denoted “methodologic triangulation.” 8 Subsequently, we present the individual data-collection procedures. In 3 studies, information on between/across triangulation was found. 16 , 20 , 21
Three studies used qualitative and quantitative data-collection procedures. One study combined face-to-face interviews, documentation, and self-assessments. 16 One study employed semi-structured interviews, direct observation, documents, and service records, 20 and another study combined face-to-face interviews, non-participant observation, documents, and questionnaires. 23
All 3 studies used qualitative interviews as the primary data-collection procedure. 16 , 20 , 23 Face-to-face and semi-structured interviews were conducted. In the interviews, data were collected on the introduction of new care services and experiences of barriers to and facilitators of collaborative work in general practices.
In 2 studies, direct and non-participant qualitative observations were conducted. 20 , 23 During the observations, the interaction between health professionals or the organization and the clinical context was observed. Observations were generally recorded as field notes.
In 2 studies, various qualitative public documents were examined. 20 , 23 These documents included role description, newspapers, websites, and practice documents (eg, flyers). In the documents, information on the role implementation and role description of NPs was collected.
In 1 study, qualitative individual journals were studied. 16 These included reflective journals from NPs, who performed the role in primary health care.
Only 1 study involved quantitative service records. 20 These service records were obtained from the primary care practices and the respective health authorities. They were collected before and after the implementation of an NP role to identify changes in patients’ access to health care, the volume of patients served, and patients’ use of acute care services.
In 2 studies, quantitative questionnaires were used to gather information about the teams’ satisfaction with collaboration. 16 , 21 In 1 study, 3 validated scales were used. The scales measured experience, satisfaction, and belief in the benefits of collaboration. 21 Psychometric performance indicators of these scales were provided. However, the time points of data collection were not specified; similarly, whether the questionnaires were completed online or by hand was not mentioned. A competency self-assessment tool was used in another study. 16 The assessment comprised 70 items and included topics such as health promotion, protection, disease prevention and treatment, the NP-patient relationship, the teaching-coaching function, the professional role, managing and negotiating health care delivery systems, monitoring and ensuring the quality of health care practice, and cultural competence. Psychometric performance indicators were provided. The assessment was completed online with 2 measurement time points (pre self-assessment and post self-assessment).
This section describes data-analysis triangulation, which involves the combination of 2 or more methods of analyzing data. 6 Subsequently, we present within-case analysis and cross-case analysis.
Three studies combined qualitative and quantitative methods of analysis. 16 , 20 , 21 Two studies involved deductive and inductive qualitative analysis, and qualitative data were analyzed thematically. 20 , 21 One used deductive qualitative analysis. 16 The method of analysis was not specified in the studies. Quantitative data were analyzed using descriptive statistics in 3 studies. 16 , 20 , 23 The descriptive statistics comprised the calculation of the mean, median, and frequencies.
Two studies combined deductive and inductive qualitative analysis, 19 , 22 and 2 studies only used deductive qualitative analysis. 15 , 18 Qualitative data were analyzed thematically in 1 study, 22 and data were treated with content analysis in the other. 19 The method of analysis was not specified in the 2 studies.
In 7 studies, a within-case analysis was performed. 15 - 20 , 22 Six studies used qualitative data for the within-case analysis, and 1 study employed qualitative and quantitative data. Data were analyzed separately, consecutively, or in parallel. The themes generated from qualitative data were compared and then summarized. The individual cases were presented mostly as a narrative description. Quantitative data were integrated into the qualitative description with tables and graphs. Qualitative and quantitative data were also presented as a narrative description.
Of the multiple-case studies, 5 carried out cross-case analyses. 15 - 17 , 20 , 22 Three studies described the cross-case analysis using qualitative data. Two studies reported a combination of qualitative and quantitative data for the cross-case analysis. In each multiple-case study, the individual cases were contrasted to identify the differences and similarities between the cases. One study did not specify whether a within-case or a cross-case analysis was conducted. 23
This section describes confirmation or contradiction through qualitative and quantitative data. 1 , 4 Qualitative and quantitative data were reported separately, with little connection between them. As a result, the conclusions on neither the comparisons nor the contradictions could be clearly determined.
In 3 studies, the consistency of the results of different types of qualitative data was highlighted. 16 , 19 , 21 In particular, documentation and interviews or interviews and observations were contrasted:
Both types of data showed that NPs and general practitioners wanted to have more time in common to discuss patient cases and engage in personal exchanges. 21 In addition, the qualitative and quantitative data confirmed the individual progression of NPs from less competent to more competent. 16 One study pointed out that qualitative and quantitative data obtained similar results for the cases. 20 For example, integrating NPs improved patient access by increasing appointment availability.
Although questionnaire results indicated that NPs and general practitioners experienced high levels of collaboration and satisfaction with the collaborative relationship, the qualitative results drew a more ambivalent picture of NPs’ and general practitioners’ experiences with collaboration. 21
The studies included in this scoping review evidenced various research questions. The recommended formats (ie, how or why questions) were not applied consistently. Therefore, no case study design should be applied because the research question is the major guide for determining the research design. 2 Furthermore, case definitions and designs were applied variably. The lack of standardization is reflected in differences in the reporting of these case studies. Generally, case study research is viewed as allowing much more freedom and flexibility. 5 , 24 However, this flexibility and the lack of uniform specifications lead to confusion.
Methodologic triangulation, as described in the literature, can be somewhat confusing as it can refer to either data-collection methods or research designs. 6 , 8 For example, methodologic triangulation can allude to qualitative and quantitative methods, indicating a paradigmatic connection. Methodologic triangulation can also point to qualitative and quantitative data-collection methods, analysis, and interpretation without specific philosophical stances. 6 , 8 Regarding “data-collection methods with no philosophical stances,” we would recommend using the wording “data source triangulation” instead. Thus, the demarcation between the method and the data-collection procedures will be clearer.
Yin 1 advocated the use of multiple sources of evidence so that a case or cases can be investigated more comprehensively and accurately. Most studies included multiple data-collection procedures. Five studies employed a variety of qualitative data-collection procedures, and 3 studies used qualitative and quantitative data-collection procedures (mixed methods). In contrast, no study contained 2 or more quantitative data-collection procedures. In particular, quantitative data-collection procedures—such as validated, reliable questionnaires, scales, or assessments—were not used exhaustively. The prerequisites for using multiple data-collection procedures are availability, the knowledge and skill of the researcher, and sufficient financial funds. 1 To meet these prerequisites, research teams consisting of members with different levels of training and experience are necessary. Multidisciplinary research teams need to be aware of the strengths and weaknesses of different data sources and collection procedures. 1
When using multiple data sources and analysis methods, it is necessary to present the results in a coherent manner. Although the importance of multiple data sources and analysis has been emphasized, 1 , 5 the description of triangulation has tended to be brief. Thus, traceability of the research process is not always ensured. The sparse description of the data-analysis triangulation procedure may be due to the limited number of words in publications or the complexity involved in merging the different data sources.
Only a few concrete recommendations regarding the operationalization of the data-analysis triangulation with the qualitative data process were found. 25 A total of 3 approaches have been proposed 25 : (1) the intuitive approach, in which researchers intuitively connect information from different data sources; (2) the procedural approach, in which each comparative or contrasting step in triangulation is documented to ensure transparency and replicability; and (3) the intersubjective approach, which necessitates a group of researchers agreeing on the steps in the triangulation process. For each case study, one of these 3 approaches needs to be selected, carefully carried out, and documented. Thus, in-depth examination of the data can take place. Farmer et al 25 concluded that most researchers take the intuitive approach; therefore, triangulation is not clearly articulated. This trend is also evident in our scoping review.
Few studies in this scoping review used a combination of qualitative and quantitative analysis. However, creating a comprehensive stand-alone picture of a case from both qualitative and quantitative methods is challenging. Findings derived from different data types may not automatically coalesce into a coherent whole. 4 O’Cathain et al 26 described 3 techniques for combining the results of qualitative and quantitative methods: (1) developing a triangulation protocol; (2) following a thread by selecting a theme from 1 component and following it across the other components; and (3) developing a mixed-methods matrix.
The most detailed description of the conducting of triangulation is the triangulation protocol. The triangulation protocol takes place at the interpretation stage of the research process. 26 This protocol was developed for multiple qualitative data but can also be applied to a combination of qualitative and quantitative data. 25 , 26 It is possible to determine agreement, partial agreement, “silence,” or dissonance between the results of qualitative and quantitative data. The protocol is intended to bring together the various themes from the qualitative and quantitative results and identify overarching meta-themes. 25 , 26
The “following a thread” technique is used in the analysis stage of the research process. To begin, each data source is analyzed to identify the most important themes that need further investigation. Subsequently, the research team selects 1 theme from 1 data source and follows it up in the other data source, thereby creating a thread. The individual steps of this technique are not specified. 26 , 27
A mixed-methods matrix is used at the end of the analysis. 26 All the data collected on a defined case are examined together in 1 large matrix, paying attention to cases rather than variables or themes. In a mixed-methods matrix (eg, a table), the rows represent the cases for which both qualitative and quantitative data exist. The columns show the findings for each case. This technique allows the research team to look for congruency, surprises, and paradoxes among the findings as well as patterns across multiple cases. In our review, we identified only one of these 3 approaches in the study by Roots and MacDonald. 20 These authors mentioned that a causal network analysis was performed using a matrix. However, no further details were given, and reference was made to a later publication. We could not find this publication.
Because it focused on the implementation of NPs in primary health care, the setting of this scoping review was narrow. However, triangulation is essential for research in this area. This type of research was found to provide a good basis for understanding methodologic and data-analysis triangulation. Despite the lack of traceability in the description of the data and methodological triangulation, we believe that case studies are an appropriate design for exploring new nursing roles in existing health care systems. This is evidenced by the fact that case study research is widely used in many social science disciplines as well as in professional practice. 1 To strengthen this research method and increase the traceability in the research process, we recommend using the reporting guideline and reporting checklist by Rodgers et al. 9 This reporting checklist needs to be complemented with methodologic and data-analysis triangulation. A procedural approach needs to be followed in which each comparative step of the triangulation is documented. 25 A triangulation protocol or a mixed-methods matrix can be used for this purpose. 26 If there is a word limit in a publication, the triangulation protocol or mixed-methods matrix needs to be identified. A schematic representation of methodologic and data-analysis triangulation in case studies can be found in Figure 2 .
Schematic representation of methodologic and data-analysis triangulation in case studies (own work).
This study suffered from several limitations that must be acknowledged. Given the nature of scoping reviews, we did not analyze the evidence reported in the studies. However, 2 reviewers independently reviewed all the full-text reports with respect to the inclusion criteria. The focus on the primary care setting with NPs (master’s degree) was very narrow, and only a few studies qualified. Thus, possible important methodological aspects that would have contributed to answering the questions were omitted. Studies describing the triangulation of 2 or more quantitative data-collection procedures could not be included in this scoping review due to the inclusion and exclusion criteria.
Given the various processes described for methodologic and data-analysis triangulation, we can conclude that triangulation in case studies is poorly standardized. Consequently, the traceability of the research process is not always given. Triangulation is complicated by the confusion of terminology. To advance case study research in nursing, we encourage authors to reflect critically on methodologic and data-analysis triangulation and use existing tools, such as the triangulation protocol or mixed-methods matrix and the reporting guideline checklist by Rodgers et al, 9 to ensure more transparent reporting.
Acknowledgments.
The authors thank Simona Aeschlimann for her support during the screening process.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
Supplemental Material: Supplemental material for this article is available online.
Ai generator.
In today’s dynamic business environment, organizations must constantly evaluate new opportunities and projects to stay competitive. To make informed decisions, it’s essential to create a robust business case that outlines the potential benefits, risks, and costs of a proposed initiative. In this article, we’ll provide an overview of what a business case is, how to create one, and answer some common questions about the process.
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A business case is a detailed document that outlines the rationale for initiating a new project or opportunity, along with the potential benefits, costs, and risks. It typically includes an analysis of the current situation, a proposed solution, a cost-benefit analysis, and an evaluation of the feasibility of the initiative.
Step 1:Â identify the problem or opportunity.
Start by identifying the problem or opportunity that your business case will address. Clearly define the issue and explain why it’s important to your organization.
Next, develop a proposed solution to the problem or opportunity. Explain how this solution will address the issue and provide specific details on how it will work.
Perform a cost-benefit analysis to determine the financial impact of the proposed initiative. Estimate the costs and benefits of the project over its lifespan, and compare them to determine the net value.
Evaluate the feasibility of the initiative, taking into account factors like technical requirements, organizational capabilities, and legal considerations.
Finally, present your findings in a clear and concise manner, using visual aids like graphs and charts to help convey your message.
Some examples of business case analyses include market research, feasibility studies, cost-benefit analyses, and SWOT analyses.
Successful business case examples include Netflix’s decision to shift from DVD rentals to streaming, Amazon’s development of its Prime service, and Apple’s creation of the iPhone.
Project cost estimate examples include direct costs (like labor and materials), indirect costs (like administrative expenses and marketing), and contingency costs (like unexpected expenses).
A well-crafted business case can help organizations make informed decisions about new opportunities and projects. By following the steps outlined above and incorporating best practices from successful case study examples, businesses can create a comprehensive and compelling case that drives strategic action planning and ensures success.
Text prompt
10 Examples of Public speaking
20 Examples of Gas lighting
Genomic selection (GS) is becoming increasingly widespread and applied due to the promising results obtained, cost savings in generating single nucleotide polymorphism (SNP) markers, and the development of statistical models that allow to improve the analysis robustness and accuracy. The composition and size of the training population have a major influence on GS, which poses challenges for interspecific biparental populations. Another factor is the use of different reference genomes from other species to perform SNP calling, which could make it possible to explore variability in interspecific crosses comprehensively. Late leaf rust is a disease caused by the pathogen Acculeastrum americanum, and there are reports on genetic resistance in Rubus occidentalis, which leads to the need for interspecific hybridizations, aiming to combine the fruit quality of R. idaeus with the resistance of R. occidentalis . The present study was carried out with a population of 94 interspecific raspberry hybrids. We evaluated the effect of different reference genomes on the SNP markers discovery, as well as training population optimization strategies on the accuracy of genomic predictions, namely the CV-α, leaving-one-family-out (LOFO), pairwise families, and stratified k-fold. The average predictive accuracies ranged from ââ0.33 to 0.44 and We demonstrated higher prediction accuracy and more precise estimates when we combined stratified sampling to compose the training set (CV-α and k-fold stratified CV) and the panel of Unique markers. These results corroborate that genomic prediction aligned with SNP calling and training population optimization strategies can significantly increase genetic gains in interspecific biparental crosses.
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Abbreviations.
Analysis of variance
Cross-validation
Genomic best linear unbiased predictor
Genotyping by sequencing
Linkage disequilibrium
Leave-one-family-out
Pairwise family
Single nucleotide polymorphism
Sum of squares
Training population
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Department of Genetics, Luiz de Queirozâ College of Agriculture, University of SĂŁo Paulo (USP), Piracicaba, SĂŁo Paulo, Brazil
Allison Vieira da Silva, Melina Prado, Gabriela RomĂȘro Campos & Gustavo Husein
Rice Research Station, Louisiana State University AgCenter, Rayne, USA
Karina Lima Reis Borges, José Crossa & Roberto Fritsche-Neto
GDM Seeds, Campinas, SĂŁo Paulo, Brazil
Rafael Massahiro Yassue
Crop Science Department, Luiz de Queiroz College of Agriculture, University of SĂŁo Paulo, Piracicaba, SP, 13418-900, Brazil
Marcel Bellato Sposito
Department of Plant Pathology and Nematology, Luiz de Queiroz College of Agriculture (ESALQ), University of SĂŁo Paulo (USP), Piracicaba, SĂŁo Paulo, Brazil
Lilian Amorim
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AVS, JC and RFN elaborated on the hypothesis, conducted the analyses, helped to interpret the results, and contributed to the writing. LA and MBS funding and elaborated on the hypothesis. MP, GRC, RMY, GH, and KLRB contributed to the panel evaluation and characterization, helped to interpret the results, writing, and discussion. All authors read and approved the final manuscript.
Correspondence to Allison Vieira da Silva .
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da Silva, A.V., Prado, M., Campos, G.R. et al. Comparing strategies for genomic predictions in interspecific biparental populations: a case study with the Rubus genus. Euphytica 220 , 146 (2024). https://doi.org/10.1007/s10681-024-03406-2
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DOI : https://doi.org/10.1007/s10681-024-03406-2
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Identify the key problems and issues in the case study. Formulate and include a thesis statement, summarizing the outcome of your analysis in 1-2 sentences. Background. Set the scene: background information, relevant facts, and the most important issues. Demonstrate that you have researched the problems in this case study. Evaluation of the Case
To avoid any confusion, here are twelve characteristics that delineate the differences between writing a paper using the case study research method and writing a case analysis paper: Case study is a method of in-depth research and rigorous inquiry; case analysis is a reliable method of teaching and learning. A case study is a modality of ...
In contrast, case studies examine a subject in depth, offer detailed information, and help develop critical thinking skills. Types of Case Studies. When it comes to writing case study analysis, there are five types you must learn to differentiate. That is important because whether you get such an assignment, you will have to understand the task ...
Case study examples. While templates are helpful, seeing a case study in action can also be a great way to learn. Here are some examples of how Adobe customers have experienced success. Juniper Networks. One example is the Adobe and Juniper Networks case study, which puts the reader in the customer's shoes.
Briefly introduce the problems and issues found in the case study. Discuss the theory you will be using in the analysis; Present the key points of the study and present any assumptions made during the analysis. Findings. This is where you present in more detail the specific problems you discovered in the case study.
The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case ...
How to Write Case Study Analysis. 1. Analyzing the Data Collected. Examine the data to identify patterns, trends, and key findings. Use qualitative and quantitative methods to ensure a comprehensive analysis. Validate the data's accuracy and relevance to the subject.
While, as its name implies, this section comes at the beginning of your case study, write it last. First, craft the rest of your document, then pick the most important bits and compile them into the introductory overview. 2. Explain the problem in question. "Adam caught a flat tire.
A poor layout can deter readers even if you have an outstanding case study. To create an engaging case study, follow these steps: Craft a compelling title. Just like you wouldn't read a newspaper article without an eye-catching headline, the same goes for case studies. Start with a title that grabs attention. Organize your content.
1. Make it as easy as possible for the client. Just like when asking for reviews, it's important to make the process as clear and easy as possible for the client. When you reach out, ask if you can use their story of achievement as a case study for your business. Make the details as clear as possible, including:
For example, the case study quotes the social media manager and project manager's insights regarding team-wide communication and access before explaining in greater detail. Takeaway: Highlight pain points your business solves for its client, and explore that influence in greater detail. 3. EndeavourX and Figma.
The five case studies listed below are well-written, well-designed, and incorporate a time-tested structure. 1. Lane Terralever and Pinnacle at Promontory. This case study example from Lane Terralever incorporates images to support the content and effectively uses subheadings to make the piece scannable. 2.
Case Study Analysis is a widely used research method that examines in-depth information about a particular individual, group, organization, or event. It is a comprehensive investigative approach that aims to understand the intricacies and complexities of the subject under study. Through the analysis of real-life scenarios and inquiry into ...
A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research. ... by using textual analysis or discourse analysis). In all cases, though, make sure to give contextual details about the case ...
8. Review and revise. The process of writing a case study doesn't actually end when the report is written; you also need to review your writing for coherence, clarity, and correctness. Don't underestimate the importance of this step! Make sure the information flows logically and that your arguments are well-supported.
1. Draft Structure. đïž Your draft should contain at least 4 sections: an introduction; a body where you should include background information, an explanation of why you decided to do this case study, and a presentation of your main findings; a conclusion where you present data; and references. 2. Introduction.
10 steps to develop a case study. Creating a comprehensive case study involves a systematic process of investigation, analysis, and presentation. Below are the key steps to follow when developing a case study: 1. Define the objective. The first step in developing a case study is to clearly define its objective. What are you trying to achieve ...
6 parts of a case analysis. Explore these parts of a case analysis to understand the process of performing one a little better: 1. Preparation. Just like with any study, it's important to first prepare to conduct the case analysis. To begin, review the details of the case you're analyzing to make sure you understand it thoroughly.
Step 1: Investigate the Company's History and Growth. A company's past can greatly affect the present and future state of the organization. To begin, investigate the company's founding, critical incidents, structure, and growth. Create a timeline of events, issues, and achievements. This timeline will come in handy for the next step.
The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case. It is unique given one characteristic: case studies draw from more than one data source. Case studies are inherently multimodal or mixed ...
To save you time and effort, I have curated a list of 5 versatile case study presentation templates, each designed for specific needs and audiences. Here are some best case study presentation examples that showcase effective strategies for engaging your audience and conveying complex information clearly. 1. Lab report case study template.
For instance, include a screenshot of the increased conversions and quotes from your client. 4. Make Your Case Study Easy to Read. No one wants to read one huge chunk of text, no matter how interesting and informative it might be. Case studies, like blog posts, should be scannable and easy to read.
Within-case analysis . In 7 studies, a within-case analysis was performed. 15-20,22 Six studies used qualitative data for the within-case analysis, and 1 study employed qualitative and quantitative data. Data were analyzed separately, consecutively, or in parallel. The themes generated from qualitative data were compared and then summarized.
It typically includes an analysis of the current situation, a proposed solution, a cost-benefit analysis, and an evaluation of the feasibility of the initiative. How to Create a Business Case Step 1: Identify the problem or opportunity. Start by identifying the problem or opportunity that your business case will address.
Genomic selection (GS) is becoming increasingly widespread and applied due to the promising results obtained, cost savings in generating single nucleotide polymorphism (SNP) markers, and the development of statistical models that allow to improve the analysis robustness and accuracy. The composition and size of the training population have a major influence on GS, which poses challenges for ...