Research Design - Data Collection and Management

This webinar presents an overview of REDCap; the stages in developing REDCap databases and creating projects; key features; project workflow; the difference between surveys and data forms; creating and distributing surveys; allocating user rights and creating reports; and the advantages of using REDCap.

This free course is designed to help researchers better understand linked data and navigate the access and approval process. Linked data is a valuable asset in research and service evaluation. The target group for this training program is researchers new to data linkage, seeking to enhance their capabilities in planning and applying for linked data projects.

Upon completing the course, participants will be able to:

• Understand the various types of data available for linkage.
• Identify the advantages and constraints of using administrative data for research.
• Recollect the data linkage process, including different linkage methods used and an understanding of high-level data linkage flow.
• Describe the steps involved in designing a data linkage project, including cohort and control group selection.
• Describe techniques to measure linkage accuracy and report on the quality of data linkage.
• Explain the regulatory framework governing data linkage and understand the essential governance roles and responsibilities researchers must uphold.
• Understand factors that influence project timeframes and costs, enabling more efficient project planning and resource allocation.

By the end of this project, you will learn how to create an Excel Spreadsheet by using a free version of Microsoft Office Excel.

Excel is a spreadsheet that works like a database. It consists of individual cells that can be used to build functions, formulas, tables, and graphs that easily organize and analyze large amounts of information and data. Excel is organized into rows (represented by numbers) and columns (represented by letters) that contain your information. This format allows you to present large amounts of information and data in a concise and easy to follow format. You will learn what an Excel Spreadsheet is, why we use it and the most important keyboard shortcuts, functions, and basic formulas.

Online qualitative surveys—those surveys that prioritise qualitative questions and interpretivist values—have rich potential for researchers, particularly in new or emerging areas of public health. However, there is limited discussion about the practical development and methodological implications of such surveys, particularly for public health researchers. This poses challenges for researchers, funders, ethics committees, and peer reviewers in assessing the rigour and robustness of such research, and in deciding the appropriateness of the method for answering different research questions. Drawing and extending on the work of other researchers, as well as our own experiences of conducting online qualitative surveys with young people and adults, we describe the processes associated with developing and implementing online qualitative surveys and writing up online qualitative survey data. We provide practical examples and lessons learned about question development, the importance of rigorous piloting strategies, use of novel techniques to prompt detailed responses from participants, and decisions that are made about data preparation and interpretation. We consider reviewer comments, and some ethical considerations of this type of qualitative research for both participants and researchers. We provide a range of practical strategies to improve trustworthiness in decision-making and data interpretation—including the importance of using theory. Rigorous online qualitative surveys that are grounded in qualitative interpretivist values offer a range of unique benefits for public health researchers, knowledge users, and research participants.

23 (research data) things is self-directed learning for anybody who wants to know more about research data.

Good data practices mean researchers and institutions can meet obligations to funders, improve the efficiency of research, and ensure data is findable, accessible, interoperable, and reusable (FAIR). Doing data right is a joint responsibility between researchers and institutions. The ARDC has collated the following best-practice guidance to help you manage your research data in the most effective way possible.

An introduction to research data, including types of data, data ownership, data management planning, documentation, storage, access and security.

This seminar explains why we need good data management practices, outlines researcher responsibilities, and provides practical data management planning strategies, including database design and development, data entry, cleaning and storage to ensure the most robust and safe data possible.

Comprehensive introduction to data collection for quanititative and qualitative approaches, includes step by step instructions, examples and templates.

In this presentation, the ARDC’s Dr Robin Burgess highlights the importance of having a governance framework in place. It supports the management, handling and sharing of the data created by a project. It also ensures that any data that has been created is of good quality, supporting sharing and future reuse of the data.

A data management plan (DMP) is a living document for a research project, which outlines data creation, data policies, access and ownership rules, management practices, management facilities and equipment, and who will be responsible for what.

This video outlines how to create a Data Management Plan.

A guide to developing a data sharing agreement (DSA), which brings clarity to what can and cannot be done with the data you are sharing as the owner or accessing as the requester.

This module covers some of the key features of Microsoft Excel through the simple example of using an Excel workbook to plan for a party. The idea is that you can then apply these same concepts to any workbooks of your own, including much larger ones. Where possible, the instructions provided are general so they can apply to whatever version of the software you have; however these instructions and screenshots specifically apply to Excel 2016 on a Windows 10 operating system. If you find that the instructions differ from your version of Excel, you can use the Help box in Excel to search for the option you need. For detailed instructions on any of the topics covered (or anything else not covered), remember Google is your friend and other guides can usually be found online.

The data toolkit covers topics including; Introduction to data, Data Ethics, Data Governance, Data Management, Data Standards, Data Stewardship, Data Storage, Open Data, Policy, Privacy, security and confidentiality, Data capability.

In this self-paced workshop you will learn steps to build data sets: find where and how to gather textual data for your corpus or data set, Prepare data for analysis: explore useful processes and tools to prepare and clean textual data for analysis, analyse data: identify different types of analysis used to interrogate content and uncover new insights.

Key data collection and analysis guidance, with templates in development.

The resource provides basic information and practical tips to help you design and implement simple survey questionnaires for your program evaluation activities. These resources are intended for people who are considering writing a survey questionnaire to collect data for program evaluation but have limited experience or training in writing survey questions.

This practice guide is for people who are considering using a survey method to collect data for program evaluation but have limited experience or training in using surveys. The resource provides general guidance about using surveys as well as tips on when and how you might use a survey and what steps are involved in conducting surveys. The resource also briefly outlines the different methods of data collection that can be used to evaluate a program.

Surveys are commonly used as a way to gather the information. Finding the resources to process and analyse all that data can feel overwhelming and sometimes you may not be sure where to begin. These tips are designed to reduce the burden of managing surveys and to make the most of the data you collect.

What do you need to think about when developing a questionnaire? This workshop looks at the information being sought, understanding respondents, wording of questions and responses, question sequence, and revising the questionnaire.

Practical help for planning and conducting surveys, includes good survey design, approval pathways, sampling and admin mehtods, writing high quality questionnaires and data collection instruments, maximising response rates and reducing data errors.

This presentation covers how to access REDCap, basic REDCap functionality, and where to go for further assistance and resources.

This video is a beginners guide to designing online surveys in SurveyMonkey.

This module provides an introduction to creating and distributing a survey using the online tool Qualtrics.

Learn how to use Covidence, an online tool that streamlines parts of the systematic review process. These videos go through what is Covidence, getting started, importing references, screening, data extraction, quality assessment and PRISMA.

This introduction to Endnote video covers: What is Endnote, Endnote 20, Setting up an Endnote library, Adding references, Endote and Word and how to get help.

Learn how to : Get started with Endnote, downloading and installing, adding records, managing records, backing up your Endnote library, Endnote online, Endnote and Word, FAQs.

This presentation provides a practical approach to extracting, analysing, and presenting data within scoping reviews, with step-by-step examples.

List of translations and cultural validations for patient-reported outcomes measures (PROMs) that are currently used in cancer clinical trials.

Describes potential solutions to reduce research waste while maximising patient-related outcome (PRO) data. Considers research waste in research design and conduct; publication and reporting; usability of results.

The EORTC QLQ and FACIT measurement suites provide the most widely used cancer-specific questionnaires for patient reported outcomes (PROs) in clinical research. This site provides a summary comparison of each measurement suite.

Three links to Quality of Life – Technical Service (QOL-TS) checklist; Participant Fact Sheet: Understanding Quality of Life Assessments in Cancer Research; Administering Quality of Life Questionnaires in Cancer Trials (For Trial Staff).

A range of resources to assist in incorporating health economic and pharmacoeconomic analyses into trial protocols and research. Provides factsheets, checklists, and excel workbook on collecting administrative data. Access also provided to 3 videos on undertanding health economics in cancer research, and a consumers’ guide.

Learn about the Health Studies Australian National Data Asset (HeSANDA) program and how it is building national infrastructure to allow researchers to access and share data from health studies, including clinical trials, cohort studies and other data valuable for research.

The Victorian Cancer Registry (VCR) Data Explorer can be accessed on the Cancer Council Victoria website. You are able to download statistics about cancer incidence in Victoria, including per tumour stream, and under the headings of diagnoses, deaths, and survival. For more detailed data, you can request aggregated (non-identifiable) data via the data request form. There are also provisions for identifiable data and accessing your own cancer data. Future developments plan to provide data by geographical prevalence and more detailed data for haematological cancers. There is a cost for accessing data, see the webpage for details.

For the Barwon South West of Victoria only. The registry was developed to capture outcomes, patterns of care and quality of care delivered to patients diagnosed with cancer in the Barwon South Western region. Data includes stage at diagnosis, first-line treatments, and subsequent outcomes. The dataset provides comprehensive information to inform clinical and population health decision-making for all residents of the region.