The Good Research Guide Review

The Good Research Guide Review

Table of Contents

In “The Good Research Guide: Research Methods for Small-Scale Social Research,” we’re taken on an insightful journey through the nuances of conducting effective social research on a smaller scale. This guide is essential for anyone undertaking their own investigative projects, providing clear and practical advice. Featuring up-to-date methodologies and approachable language, it empowers us with the knowledge to navigate our research challenges smoothly and precisely. Whether we’re students, professionals, or passionate enthusiasts, this book stands as a go-to resource for crafting robust and reliable social research. Have you ever felt overwhelmed by the sheer volume of research methods textbooks available and not known where to start? We were in the same boat until we stumbled upon “The Good Research Guide: Research Methods for Small-Scale Social Research Paperback – Import, 27 September 2021.” This guide quickly became our go-to resource for navigating the often complex world of social research.

The Good Research Guide: Research Methods for Small-Scale Social Research     Paperback – Import, 27 September 2021

Check out the The Good Research Guide: Research Methods for Small-Scale Social Research     Paperback – Import, 27 September 2021 here.

Overview of “The Good Research Guide”

What Makes It Stand Out?

First off, what makes “The Good Research Guide” stand out among the plethora of research method guides? We think it’s the way it simplifies complex concepts without sacrificing depth. This book is designed particularly for those embarking on small-scale social research projects, making it a perfect fit for students, early-career researchers, and anyone new to the field.

Target Audience

Who exactly is this book for? Great question! It’s primarily targeted at undergraduate and postgraduate students, but we found it equally beneficial for any beginner in social research. The author has done an excellent job tailoring the content to those who might be facing their first significant research project.

Price and Availability

We know price matters, especially when you’re on a student budget. As of its 2021 import edition, it’s reasonably priced and widely available through most online book retailers. The paperback format makes it easy to carry around, which is a bonus when you’re running between classes or fieldwork.

Table of Key Details

Here’s a quick breakdown of essential info for easy reference:

Aspect Detail
Title The Good Research Guide: Research Methods for Small-Scale Social Research
Format Paperback
Publication Date 27 September 2021
Target Audience Students, Early-Career Researchers
Price Reasonably Priced
Availability Online Retailers

The Good Research Guide: Research Methods for Small-Scale Social Research Paperback – Import, 27 September 2021

AED180.76   Only 1 left in stock (more on the way).

Content and Structure

Clear and Engaging Writing

One of the standout features for us is the clarity of the writing. The author, Martyn Denscombe, has a knack for breaking down intricate research methods into digestible chunks. This made it a lot easier for us to stay engaged, and we didn’t find ourselves rereading the same paragraphs multiple times to grasp the core concepts.

Practical Examples

Let’s talk about the practical examples. Throughout the book, the author uses real-world examples to illustrate complex ideas. This practical approach not only helps us understand the methods better but also shows us how to apply them in our own research projects.

User-Friendly Layout

Another aspect we loved was the user-friendly layout. The various chapters are logically divided and organized, which makes it easy to find the specific information we need without having to wade through irrelevant sections. This is particularly useful when we’re on tight deadlines and need to quickly get to the point.

Check out the The Good Research Guide: Research Methods for Small-Scale Social Research     Paperback – Import, 27 September 2021 here.

In-Depth Look at Key Chapters

Chapter 1: Introduction to Social Research

In the first chapter, Denscombe provides a well-rounded introduction to social research. He lays the groundwork by explaining the importance of research and the basic principles we should be aware of before delving into more complex topics. This chapter alone serves as a solid foundation for beginners.

Chapter 2: Planning a Research Project

This chapter was a game-changer for us. Planning can be one of the most daunting aspects of research, but this guide simplifies it magnificently. Denscombe walks us through setting objectives, formulating research questions, and developing a research plan—all indispensable skills for any budding researcher.

Chapter 3: Ethics in Social Research

Ethics can often seem like a minefield, but this chapter breaks it down into manageable pieces. The guide highlights the main ethical considerations we need to keep in mind, along with practical tips on how to ensure our research is conducted ethically.

Chapter 4: Data Collection Methods

Data collection is the backbone of any research project. This chapter covers various methods, such as interviews, surveys, and observations, thoroughly. Each method is discussed in terms of its strengths and weaknesses, helping us to make informed decisions about which techniques to use in our own projects.

Chapter 5: Analyzing Data

When it comes to data analysis, this chapter doesn’t disappoint. Denscombe explains both qualitative and quantitative methods, ensuring that we’re well-versed in analyzing our data, regardless of its nature. This is particularly useful for those of us who may not have a strong background in statistics.

The Book’s Strengths


What really earns this book high marks is its accessibility. It’s designed to be user-friendly for people who might not have any prior experience in research, which is an invaluable feature for beginners. The language is straightforward, and the concepts are explained in a way that anyone can grasp.

Comprehensive Coverage

Another major strength is the comprehensive coverage of topics. It’s incredibly detailed yet concise enough to serve as a go-to quick reference. Whether we’re struggling with forming research questions or grappling with data analysis, this guide has sections dedicated to it all.

Resourceful Tips and Tricks

Every chapter is brimming with useful tips and tricks that can make our research journey smoother. From planning stages to final reporting, these nuggets of wisdom help us avoid common pitfalls and stay on track.

The Good Research Guide: Research Methods for Small-Scale Social Research     Paperback – Import, 27 September 2021

Areas for Improvement

Lack of Advanced Topics

While we appreciate the book’s focus, we found ourselves wanting more advanced topics to sink our teeth into after we were more comfortable with the basics. This guide is excellent for those who are just starting out, but it might leave more advanced researchers seeking additional resources.

Minimal Visual Aids

Given the focus on clarity, adding more visual aids like diagrams and flowcharts could significantly enhance understanding. While the text itself is engaging, some concepts could benefit from visual representation.

Real-World Applications

Our Own Research Experience

When we applied the methodologies from “The Good Research Guide” to our own small-scale social research project, the results were remarkable. The planning and data collection techniques laid out in the book helped us streamline our process and focus our efforts effectively.

Academic Success

For students, this book can be a life-saver. It provides all the necessary tools to excel in coursework that requires research projects. The clear explanations and practical examples make it easier to grasp what professors are asking for in assignments.

Professional Development

If you’re an early-career researcher, this book serves as an excellent refresher and guide. It covers all the essential points and offers tips that even seasoned researchers might find useful.


Would we recommend “The Good Research Guide: Research Methods for Small-Scale Social Research Paperback – Import, 27 September 2021”? Absolutely. It’s an invaluable resource for anyone new to social research, providing clear, concise, and practical guidance. From planning and ethics to data collection and analysis, this guide covers all the bases in an accessible manner. Whether you’re a student, an early-career researcher, or just someone interested in social research, this book is definitely worth adding to your collection.

In summary, while it could benefit from more advanced topics and visual aids, its strengths far outweigh these minor drawbacks. We found it to be a thorough and accessible guide that’s easy to recommend. So, if you haven’t already, give it a try and see how it transforms your approach to social research!

Learn more about the The Good Research Guide: Research Methods for Small-Scale Social Research     Paperback – Import, 27 September 2021 here.

Disclosure: As an Amazon Associate, I earn from qualifying purchases.

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University Essentials
University Essentials

About Me

With 25 years of experience in healthcare IT implementation, Emmanuel began his career at the University of Pittsburgh Medical Center, working as an assistant manager for a billing system implementation. Over the years, he has explored various aspects of the healthcare IT domain, successfully implementing several laboratory information systems and electronic medical record (EMR) systems, such as Cerner Millennium and Epic EMR.

In 2005, Emmanuel shifted his focus to public health, working on bio-surveillance implementation for the Centers for Disease Control and Prevention (CDC). He contributed to the BioSense Data Provisioning Project and performed extensive analysis of HL7 messages in hospitals and healthcare facilities. Additionally, Emmanuel requirements analysis for the CDC BioSense Analysis, Visualization and Reporting (AVR) project and played a key role in publishing the Situational Awareness updates to the BioSense System Requirements Specification (SRS).

Over the past 11 years, Emmanuel has worked in the Middle East, implementing the Epic EMR system at Cleveland Clinic Abu Dhabi. As a multidisciplinary team member, he has taken on various roles, including SCRUM Master, Project Manager, Integration Engineer, and Platform Engineer. Concurrently working as an adjunct university faculty member, teaching graduate-level courses in Systems Life Cycle and undergraduate courses in Health Information Systems

From a technological standpoint, Emmanuel has designed, installed, and implemented complete hospital integration systems using Rhapsody Integration Engine, MS SQL Server, and Public Health Information Networks Messaging System (PHINMS). He has also developed over 10,000 interfaces some of which coded in Java and JavaScript.

In 2019, Emmanuel expanded his skill set and entered the field of digital marketing, quickly becoming a proficient Digital Marketing Strategist. He has since helped numerous clients develop robust digital marketing strategies for their businesses. His expertise encompasses Social Media Marketing, On-page and Off-page SEO, Google Ads, and Google Analytics. Additionally, he and a team have managed clients’ website development projects, ensuring that each site is optimized for SEO, further enhancing their online presence and performance.

Alongside their digital marketing expertise, Emmanuel has delved into the world of Affiliate Marketing, where Emmanuel and his team successfully managed and executed campaigns for a variety of clients. By identifying the right products and services to promote, Emmanuel and his team helped clients generate passive income streams and increase their overall revenue.

Their approach to Affiliate Marketing involves creating valuable content that educates and engages the target audience, while strategically incorporating affiliate links. Emmanuel and his team have experience working with multiple affiliate networks and platforms, ensuring optimal tracking and reporting of performance metrics. By staying up to date with the latest trends and best practices, Emmanuel and his team have been able to optimize affiliate campaigns for maximum results, fostering long-term partnerships and sustainable growth for their clients.

As an accomplished professional, Emmanuel holds dual Bachelor of Arts degrees in Linguistics and English, a Master of Science in Health Information Systems from the University of Pittsburgh, and a Ph.D. in Information Systems from Nova Southeastern University.

My Teaching History

Professor Bazile is a dedicated technology instructor and Adjunct Faculty professor, who began his teaching career in April 2000 at the Business Career Institute in Las Vegas, Nevada.

In 2001, he expanded his expertise by training nurses in the use of Electronic Medical Records (EMR) systems. His experience in both technology and healthcare led to his appointment as an Adjunct Faculty professor at the University of Phoenix in May 2008, where he has taught several graduate-level information technology and healthcare information systems courses.

Dr. Bazile has also developed an HL7 course, which he has taught at various healthcare facilities, drawing from his own book, “HL7: Introductory and Advanced Concepts,” currently available on Amazon. With a passion for teaching and a commitment to ensuring students get the most out of each course he teaches, Dr. Bazile is a valuable asset to both his students and the institutions he serves.

My Teaching Philosophy

My teaching philosophy as an Information Systems professor in healthcare is built on the concept that education should equip students to be confident and capable problem solvers who are prepared to traverse the complicated and ever-changing landscape of Healthcare IT.

In order to accomplish this, I prioritize the creation of a dynamic and engaging learning environment that encourages students to engage with course material and with one another. This involves employing a range of teaching approaches, such as lectures, seminars, and hands-on activities, to ensure that students learn in the manner that best matches their learning style.

I believe the reason we have Information Systems as a discipline is to allow students to apply technology to solve real world problems. If that is the case, both undergraduate and graduate students have to be challenged to incorporate their core academic courses with their matriculated subjects. As such, it is important that students enter their Junior and Senior years with a strong command of the core courses such as Programming, databases, networks, hardware and software, as they serve as the foundation upon which real-world solutions will be built.

I also believe in the importance of incorporating real-world examples and case studies into my courses, as this helps to connect abstract concepts to practical applications. Additionally, I encourage students to apply what they are learning to their own personal and professional goals, as this helps to make the material more meaningful and relevant to their lives.

I strive to foster a positive and supportive learning environment where all students feel comfortable asking questions and participating in class discussions. I believe that this is key to fostering a sense of community and ensuring that all students have the opportunity to succeed.

I have also taught online courses. I have found in an asynchronous learning environment it can be difficult to apply the Peer Teaching or Experiential Learning Pedagogical Approaches. However, I have found the Discovery Learning approach to works quite well. Along with a boost to students’ self-confidence, Discovery Learning in an online environment allows students to synthesize information, expand on existing concepts on their own, while experiencing a positive outcome through trial and error.

Ultimately, my mission as an educator, and a Healthcare IT Information Systems professor is to provide students with the knowledge, skills, and confidence they need to thrive and succeed in their careers and to be technological leaders. By creating a positive and supportive learning environment, incorporating real-world examples and case studies, and encouraging students to apply what they are learning to their own objectives; my hope is to inspire and empower all students to achieve their full potential.

Population Size:

A total of 310 responses were originally received. Any response containing missing data due to unclicked radio buttons or unchecked checkboxes were first reviewed, and, if justified, were omitted from analysis. For surveys with missing data, a total of 18 responses were removed. In order to address any issues with response-set, the data was downloaded into Microsoft Access and queries ran to identify responses that contained the same values for each question. A total of 16 responses were found to be qualified for removal. Another 18 were identified as outliers and removed leaving a total of 258 responses for the study analysis.

In order to assess multivariate outliers, the Mahalanobis distances were calculated and plotted against their corresponding Chi-Square distribution percentiles (Schmidt & Hunter, 2003). The resulting scatterplot is similar to a univariate normal Q-Q plot, where deviations from a straight line show evidence of non-normality. The data showed indications of moderate deviations from multivariate normality, as indicated by the concavity of the data points. There were no additional multivariate outliers or missing values in the data after the removal of 52 responses.

Descriptive Statistics

Frequencies and percentages were conducted for the demographics indicators, while means and standard deviations were calculated for the continuous indicators. For gender, there were 151 females (59%) and 107 males (41%) in the sample. For ethnicity, most participants were Caucasian (119, 46%), followed by African American (56, 22%). The two most populous education levels were Bachelor’s (90, 35%) and Master’s (62, 22%). The biggest proportion of the sample by age group was the 35-44 age group (101, 39%) followed by the 45-54 age group (59, 23%).


Confirmatory Factor Analysis and Composite Reliability

A CFA was conducted along with a reliability analysis to assess construct validity. Examination of modification indices and factor loadings indicated that CSE1, CSE5, CSE7, PC5, ATE1, ATE6, ATE8, PP5, and PP6 were all causing significant problems with the model parameters. The results of the last iteration of the CFA performed in R showed significantly improved fit, although still poor overall (χ2(545) = 2125.61, p < .001, CFI = 0.82, TLI = 0.81, RMSEA = 0.11). The high degrees of freedom indicate that a very large number of parameters are being estimated in this model.

Composite Reliability

For the full model, each construct had excellent reliability. The ATE latent construct had a composite reliability value of 0.89. The ORC construct had a composite reliability value of 0.94. The CSE latent construct had a composite reliability value of 0.85 and PC had a composite reliability value of 0.95. For PP and RES, the composite reliability scores were 0.80 and 0.96 respectively. These values indicate that the loadings for each construct were all directionally similar, and that the items in each construct show a high degree of consistency.

Cronbach’s Alpha

Cronbach’s alpha values were calculated for the items in each construct. The alphas for PC (α = 0.90), AXY (α = 0.94), and RES (α = 0.94) indicated excellent reliability. The alphas for CSE (α = 0.80), ATE (α = 0.88), and PP (α = 0.83) all showed good reliability. These values confirm the results of the composite reliability tests, and reiterate the high degree of reliability within each latent construct.

Partial Least Squares – Structural Equation Modeling

A partial least squares- structural equation modeling (PLS-SEM) was conducted to determine how well the data fit the proposed model, and discern whether significant relationships existed between the independent and dependent constructs. The full model showed AVE values of 0.53 for ATE, 0.69 for AXY, 0.44 for CSE, .72 for PC, .35 for PP, and 0.81 for RES. The high values for AXY, PC, and RES indicate that the amount of variance accounted for in the manifest variables is sufficiently high. The values for ATE, CSE, and PP indicate that some of the variance in the manifest variables is left unexplained.

Structural Model

Once the measurement model had been tested for model specification, the structural model was tested to determine if ATE, AXY, CSE, PC, and PP had a significant effect on RES. A path weighted model was calculated using 10,000 bootstrap samples in R. The results showed a pseudo R-squared value of 0.78. This indicates that approximately 78% of the variance in RES is explainable by the collective effects of CSE, PC, ATE, PP, and AXY.

Further examination of the effects indicated that AXY had a highly significant effect on RES (= 0.87, < .001). This indicates that a standard deviation increase in AXY increases the expected value of RES by 0.87 standard deviations. CSE did not have a significant effect on RES (= 0.02, = .423). Additionally, CSE (= 0.02, = .423), PC (= 0.05, = .334), ATE (= 0.00, = .983), and PP (= 0.03, = .407) did not have significant effects on RES. Table 11 outlines the results of the path estimates.

Correlation Analyses

Both Pearson and Spearman correlations were calculated on the composite scores. The results of the Pearson correlations indicated that CSE was significantly correlated AXY (= 0.22, < .001) and RES (= 0.21, < .001). The results also indicated that PC was significantly correlated with ATE (= -0.79, < .001), AXY (= 0.18, < .001), and RES (= 0.20, < .001). ATE was significantly correlated with AXY (= -0.19, < .001) and RES (= -0.19, < .001). AXY was significantly correlated with RES (= 0.85, < .001).

ANCOVA Analyses

An analysis of covariance (ANCOVA) was conducted to determine if a significant relationship existed between the AXY, PP, CSE, PC, ATE scores and RES controlling for Gender, Age, Ethnicity, Education, and Specialty. The overall model was found to be significant (F(63,194) = 53.39, < .001), with an R2 value of .95, indicating that 95% of the variance in RES was explained by the collective effect of the independent variables and covariates.

Since the overall model was found to be significant, the model’s covariates were assessed. The AXY (F(10,194) = 262.20, < .001), ATE (F(7,194) = 2.20, = .036), Years computers (F(1,194) = 5.71, = .018), and PC (F(12,194) = 2.00, = .026) scores were found to be significant, indicating that a significant amount of variance in RES is explained by AXY, ATE, and PC.

A path diagram depicting the results of the structural model.


This research investigated Computer Self-Efficacy (CSE), Perceived Complexity (PC), Attitudes toward EMR Systems (ATE), Peer Pressure (PP), and Anxiety (AXY) to determine whether these constructs as individuals, or as a group, or coupled together with some other factors could significantly explain resistance to EMR systems. Quantitative examination of self-reported survey results was performed to understand the strength and significance of the relationships, while these relationships were investigated to test the strength of model fit.

the regression paths of the structural model were examined to test the hypotheses. Significance was determined using an alpha level of .05. The model had an overall R2 value of 0.78. This indicates that approximately 78% of the variability in RES can be accounted for by CSE, PC, ATE, PP, and AXY. Since the overall model was significant, the individual coefficients can be interpreted. Some of the hypotheses were supported by the results of this study, and some were rejected. The construction of a data model of the relationships in this study could not meet thresholds that would be evidence of a good fit of the relationships identified in the study.

The fifth hypotheses tested the influence of AXY on resistance to EMR systems. AXY was expressed to be significantly related to resistance (r=.87, p<.001). This finding supports the hypothesis that anxiety with the EMR system will lead to medical care professionals rejecting use of the system. Unlike the findings of the first four hypotheses, the findings of the current study support previous research. Angst and Agarwal (2009) indicated that AXY is a factor which is significantly related to the problem of EMR system resistance. Based on the empirical findings of previous research, the present research and conceptual propositions and conclusions in previously written scholarly articles, there is a great deal of support for the finding that AXY is significantly influenced by EMR resistance.

The findings of this research do not support all findings by previous researchers, and there are multiple relationships which had been established as being significant that were identified as being insignificant in the current research. Generally, because of the inconsistency of previous findings and the current study there may be elements related to the sample examined or other contextual factors which may contribute to the inconsistency that exists. Ultimately, it is suggested that there be further research done on the problem of resistance to EMR system use.

Ultimately the findings support a new take on the problem of EMR system resistance that may contribute to the ways in which scholars investigate the problem of EMR resistance in general. This may also help with the way practitioners approach EMR systems, and articulate value of the systems to medical professionals investing record-keeping systems in the workplace.