- Inductive, narrative, invivo, action oriented, group and participatory characteristics
- Detailed descriptions of data collection, data management, invivo data and coding, invivo analysis and interpretation
- Quality indicators of peer research
This chapter is an overview of peer research for academics, researchers, students, patients and communities, looking to expand patient engagement in their research. It is written to explain the characteristics, methods, research quality indicators and social impact. It is based on 12 years of carefully testing the impact of specific research methods and theory on engagement research.
An integrated range of methods designed specifically to engage citizens and persons with lived experience. It is intended for qualitative researchers interested in working with citizens who are trained to conduct research or recruit, train and supervise citizen scientists. The methods meet the principles of citizen science while introducing a suite of robust qualitative methods specifically designed to engage citizens and communities in research. Professionally trained researchers who identify as a patient or person with lived experience may find this chapter useful in their personal research or in training patients as collaborators. Teams of health researchers who are interested in sponsoring patients to become trained peer researchers may find this chapter useful in exploring the types of research that has been done by trained peer researchers and the options for future engagement research. Teams may also want to embed citizens in their research agenda’s and are willing to embed training in research methods for their patient advisors. Researchers who have been asked to support or facilitate independent patient led research may be interested in research methods that have been successful in peer research projects. These methods have been used in social enterprise projects and, in Section 3: making a difference, these methods and strategies inform design thinking projects.
The majority of peer research is conducted with ethics approval and academic oversight. In section 3, making a difference, peer research is expanded to include a range of social innovation and enterprise initiatives and engagement methods are adapted to be used as part of design thinking.
This is not a curriculum or training programme but a resource to extend the current health research landscape. It is important to introduce peer research at this time when health care is facing new challenges in systemic discrimination, unprecedented medical challenges and the exponential increase in biological, physical and digital technologies that will change patient and health care provider roles. If patients and communities are not included in these changes, there are risks; they will engage with technology outside of formal healthcare and they may become more disempowered within the system.
How is Peer research practice different and how was this achieved? One can understand why people are puzzled, it is a significant social innovation and is further complicated by the fact that much of the incubation has been low key, using short term catalyst funding, social enterprise contracts, student projects and graduate research projects. We relied on early adopters who were willing to try new methods to overcome challenges. Peer research is a combination of a number of qualitative approaches designed to be done by patient researchers trained within an accepted program of studies or by researchers who train and support peer research projects. There are a number of common characteristics of peer and community research that apply to research, co design, quality improvement and health technology assessment.
The following is an example of peer research that captures the character of peer and community research. This is a community driven peer project Understanding advance care planning within the South Asian community
Four trained peer researchers from South Asian countries were contracted through PaCER to identify the readiness of South Asian communities to become part of an advanced care planning initiative with AHS. Luckily each PaCER was from a different faith community and all were women. As women they conducted a women’s focus group to identify the obstacles and opportunities in conducting this research. The researchers met with the PI and PaCER Academics to discuss the need for a culturally appropriate data collection strategy for families and for the researchers.
They had decided that any research involving death should be done within families because the traditions surrounding death were led by the head of the family but each family member would want to be involved. A modified family research method was created to meet cultural protocols. The recruitment included a careful description of the advanced care planning process and how the research method would meet cultural and language needs.
Two peer researchers, one in traditional dress, the other in western dress met the family in their home and brought along tea and treats. The lead researcher (the one from the families faith community) outlined the process with the family asking if everyone felt comfortable and in the process introduced herself and why she and her family felt that advanced care planning was important - a personal family story.
Once the head of house made any changes and set out how all members would have a chance to speak, there was a narrative conversation about the concept of advanced care planning. Confusion and conflict with traditions were also discussed. All members - from grandparents to children contributed. Other methods were not needed as the data from families in all four faith traditions created very detailed discussions about family goals, the process of dying, advanced care planning, from all generations present.
The results were compiled and analyzed after each family gathering and shared with the team to plan next steps. The PaCER academic staff and peer researchers met regularly to provide support and discuss any ethical or methodological findings. As we neared the REFLECT consultation, it became clear that the topic had generated a great deal of interest and a radio invitation was issued for a feast and a chance to be involved in the research findings.
The morning session consisted of the researchers and those who had taken part in the research to discuss the emerging ideas and plan for the afternoon session. The noon feast included faith based and community leaders, community members and health providers along with the sponsors. The results, in the form of results from the group sessions in the morning were presented to the group with active discussion and answering the main questions.
Highlights included a family head who spoke for many there, indicating his appreciation of the chance to be involved and if AHS wanted an advanced care plan done, why not leave it at the doctor’s office on a computer that they could fill out and up date if needed. An old woman spoke quietly to say that she felt that everyone was familiar with computers and they could discuss it amongst themselves. A doctor rose to say she could help and then a faith leader suggested that they could hold discussion after services to show their support.
The family method produced deep and rich information. The results contributed to the team’s implementation plans and were published, with the rest available in PRISM.
The following chart contrasts characteristics of peer research with qualitative research.
Inductive / deductive
- Inductive, cumulative data collection, analysis and interpretation with patients and communities
-Deductive process, data collected and then analysed and interpreted
-Some inductive research
- Methods for data collection, constant comparison of data and iterative cycles must be adaptable to the population and topic.
-Focus on standard questions and data collection
Use of narrative
- Narrative values and methods permeate all aspects of peer research
- Sporadic use of narrative in data collection
- In vivo data incidents are compared and lead to invivo coding of emerging categories that explain the main concern or topic of study
- Data is abstracted as soon as possible, abstract theoretical codes are compared and combined to further abstract categories
- what happened, how does it explain the problem, what action can be taken, who is the actor and who is the recipient
- what was it like, how did you feel. - Using thematic analysis to create suggestions for change
- Conversations, small working groups and focus groups
- Individual interviews dominate. Groups follow scripted questions.
- Participants who are supported to engage in data collection, analysis and interpretation
- Participants in single events of data collection. Results of the study may be shared.
Table 1 Characteristics of Peer Research and more traditional
Deductive reasoning begins with a general interest based on gaps in literature about practice, theory or a population. This general interest is stated as a hypothesis or research question that directs the method and the sample size. Data is collected using the set method. When all data is collected it is analyzed, most often with computer analysis to confirm (or not) the hypotheses and how it relates to the theory of the original question. Data analysis also includes descriptive and correlational findings. This is used mostly with evidence based medicine that follows the above sequence.
Inductive reasoning begins with observations and data about a general problem focus identified by a population. As categories emerge from systematically analyzing data as it is gathered, patterns emerge to explain the problem. This constant process of collecting, analyzing, interpreting leads to general conclusions and in some circumstances theory that explains the original focus or concern.
These two methods of reasoning have a very different “feel” to them when you’re conducting research. Inductive reasoning, by its very nature, is more open-ended and exploratory, especially at the beginning. Deductive reasoning is more controlled, testing or confirming hypotheses. Even in the most constrained experiment, the researchers may observe patterns in the data that lead them to develop new theories.
Peer methods tend to use inductive and iterative processes because these allow co research participants to become very involved in the research process. The analysis is done by the peer researchers and participants. Every time data is collected it is analysed by asking questions such as
- ‘what is happening here?’ (the action focus) that produce action notes called incidents that summarize what has happened such as ‘I was lost in the mall and asked an adult to help me ’ or
- ‘what was it like?’ (a qualitative focus) that produces descriptive incidents such as ‘I was so worried when I was lost in the mall but a nice lady helped me so I was not afraid’ ’
In inductive research, the researcher is immersed in the process, carefully trained to listen for and record data in short notes called incidents or stories focused on the topic. These short notes are then used during constant comparison, to create categories that are coded to reflect the nature and meaning of the incidents and stories within the category, such as rescued, or lost in the mall
As inductive research, the researcher is able to use these general category codes as subtle prompts to confirm or test categories in subsequent data collection. For example, were there other times when you got lost, or, where there times when you felt rescued by someone. As the categories are compared and tested, the process of data collection becomes more focused to look for dominant themes of the topic (descriptive) or categories that explain the main concern (action). This leads to rich interpretation in a short period of time because data collection and analysis is so focused.
The inductive process is iterative, data and analysis inform the next step of data collection and analysis and these steps lead to explanations. The deductive process begins with a consistent data collection process and the results are analyzed when enough data has been collected to justify the confirmation or negation of the original question.
Peer research, at the heart of its mandate is the ability to reach out to populations that are not being heard because they have either given up or, more likely, because they are considered outside of the scope of standardized studies. Look at the time and effort expended by advocates to include women in clinical trials even though it was apparent that women often manifest conditions in different ways. Both Grey Matters and PaCER were grounded in a teaching method that was experiential and based on the need to adapt all aspects of research, from co design, eligibility criteria, recruitment and conducting and analyzing data to find solutions that would include the population in implementation and evaluation of results.
This is perhaps the most difficult aspect of peer research to understand and to teach given the dominant learning practice in health research that is about consistent protocols. However, we have seen the first feature of peer research is an inductive stance that supports iterative data/analysis and planning next steps in response to findings. This alone requires a method that adapts as the findings are emerging.
The learning approach for such inductive and adaptable research requires that students begin to learn by doing research, noting obstacles to engagement and carefully planning and evaluating adaptations. The curriculum for PaCER was designed using an active learning cycle based on Participatory Action Research. During the first iteration of the curriculum, students were part of a year long internship that introduced theory, methods and competencies as part of designing and conducting a research process. Each group of students worked with their target group and each ethics proposal and research project reflected the culture and conditions of the target populations.
As the methods became more clearly defined (the blending of narrative foundations, inductive process and grounded theory analysis) the internship was developed into three courses that defined competencies for getting ready for research (foundations), basic data collection and analysis as part of co design of an ethics proposal (particum). The practicum enabled students to demonstrate learning in real life consultation with participants and community resources, in person and online. Students learned by doing and discussing how to use what they learned. The final internship enabled the student teams to conduct the research they had developed after ethics approval. This too required adaptation in recruitment and methods. When the program was approved and moved to continuing education, the initial push was to adopt adult learning that was more based on assignments and discussion. This approach to teach in more standardized ways may reduce the ability to teach basic adaptation.
As peer research is adopted by innovation teams, there will be a return to a focus on adaptation, especially in the prototype development and testing. Good design thinking is about learning about the potential diversity and being able to adapt to new populations.
Narrative data collection is a natural process for peer research where peers engage in conversations that share and explore stories. It is natural to share concerns and it is also natural to use shared stories to explore potential solutions to the problems. The use of a story template helps peers and participant co researchers to work with stories as legitimate forms of knowledge and as these stories are used to explore how things might be different, they open the door to narrative futures or forecasting solutions. Design thinking uses story formats throughout to produce rich and flexible data.
Because co-research participants have been prepared ahead of time to expect that stories are important, they have time to think about stories that are related to the topic. They are ready to engage not only in telling stories but exploring them with others to find meaning.
This power of narrative to engage produces rich data. Stories include other narrative forms such as metaphors, properties, styles, context, and consequences which help clarify why stories are grouped into categories These narrative properties help define differences in categories during interpretation.
For example in the mall example above you could use properties such as where the child got lost, who - the gender, age, of the rescuer, what metaphors were used, what were the outcomes.
These properties of narratives are extremely useful when selecting the core category and finding relationships between categories and the main concern or topics during interpretation with co research participants.
Finally, when planning implementation strategies, Marketing research tells us clearly that Implementation strategies that include a vision conveyed through story resonate and increase uptake. https://www.nature.com/articles/palcomms201793. When stories types, their titles (the titles of stories in narrative research act as codes or names for types of stories.
Because the co-research social innovation study (chapter 2) set out to involve social innovators throughout the research process, we soon faced the so-called glass ceiling of analysis. The ceiling of co-analysis occurred as I used the concepts, language, philosophy and theories of my basic discipline to name the emerging categories. I had not realized that I was doing this but it soon became apparent that the co researchers felt sidelined because they did not share my academic language. It seemed to suggest they, the co-researchers, were not equivalent to academically certified researchers.
When we used the titles of stories as category names we were able to re engage in analysis. During the first course in the PaCER program of studies we introduce students to using a story template to capture interviewing. The title of the stories are hotly debated because they are in effect the category name or code that holds the meaning and intent of the story.
I later realized that categorizing data held insidious assumptions that separated participants from academics. Early in PaCER, we often heard that unless peer researchers can conceptualize or create theory, they can’t be considered researchers. We had to find a way to validate the knowledge of those most impacted to be included in health research. Luckily my background in community and social innovation had built my trust in the wisdom and competence of those who rely on services, all we needed to do was to find an alternative to conceptualizing using academic theory based concepts.
We began with classical grounded theory to find ways around this criticism levelled against peer research. Step by step, study by study, we have studied alternatives, using the iterative cycles of data collection and analysis to test new approaches that could compensate for this lack of academic theory. Community Based Participatory Research (CBPR), and Participatory Action Research (PAR) use plain or invivo language of everyday life to contextualize experience within local culture and organizational structures. This works well within local contexts but we were looking to increase the evidence of peer research to gain recognition among health researchers.
While each discipline creates its own language of codes and conceptual models, we set out to create a body of research about the experience of being a patient in a health context. Patient experience can be coded according to the narrative questions asked of stories. The language of peer research may not be conceptual from a disciplinary or theoretical foundation, but it does lead to deep, action oriented categories of real life experience. The following titles of peer research are examples of invivo theories.
- Losing our stories
- Out in the cold without a clue
- Hiding undiagnosed arthritic pain
In PaCER, the use of narrative and plain language has been well received in collaborative publications that have been accepted by professional journals. When the reason for experience based concepts is explained, most academics felt it was appropriate. It is important to note that peer research has been analyzed by professional and academic researchers who use different labels and may combine findings in different structures. It is a strength that invivo incidents and coding support and encourages re analysis, this adds an additional level of understanding and reinforces the importance of partnership in health research. Both peer research and academic needs can be met within a story based analysis.
An action orientation is the hallmark of emancipatory social science. Research that engages people in experience research tends to focus on people’s concerns. Sharing concerns naturally lead to suggesting ways to deal with concerns. All emancipatory social science, no matter the population has focused on systemic discrimination in order to inform collective action.
Throughout the 30 years of collaborative research with social innovators, seniors, students, peer support groups, and finally patients and communities, the common question of participants was, ‘Will this make a difference?’ This concern aligns with action research such as CBPR, PAR and Classical grounded theory, that deliberately set out to address common concerns in ways that will explain, resolve or reframe the concern. That was why I initially selected classical grounded theory for my PhD, and why it has informed all of the stages of innovation since that first co research study.
Regardless of the stated method, it is the engagement strategy that promotes a clear focus through the SET co design process, iterative COLLECT data collection and analysis cycles that focuses on resolving, explaining or describing the topic or concern and a REFLECT process that reinforced the explanation or resolution of the main concern or topic. This process leads to suggestions for Implementation and innovation. The engagement strategy can be applied with a wide range of research, co design, quality improvement and technology assessment approaches along with support for peer support and community engagement.
Group research was first proposed by Seniors in the Grey Matters research. Seniors wanted to create a focus group method that provided time to understand the topic, share stories and discuss common concerns. The resulting peer research takes more time, promotes cross talk and creates shared meaning. These group sessions create common goals and ownership of the findings. It is perhaps the most effective peer method, producing not only data but shared meaning and in depth collective stories and interpretation
Group research is used to set priorities, collect a broad range of stories to inform the development of categories, reflect and contribute to findings that suggest actions based on the findings.
The nature of the group process augments the power of engagement strategy SET COLLECT REFLECT, allowing groups to make key decisions about setting or co designing the research, collecting and analyzing information, and co-creating the findings and suggestions for action. SET and REFLECT are actually consulting workshops that ground the research process with opportunities for direct input in choosing the topic of research during the SET co design process and in consolidating the explanations of the topic or main concern during REFLECT.
The distinguishing characteristics of Peer research groups include. The length of time, the preparation of the participants who are consultants, the lack of set questions and open conversations where participants are encouraged to contribute ideas to emerging stories. These groups seem to rely on the freedom and cross talk that builds trust and a common mission of making sense of concerns to find ways to make a difference.
A one hour focus group with questions is likely not a peer research experience.
Each SET COLLECT REFLECT focus group has a distinct purpose and method. While they work as a cohesive unit, they can also be used separately and with other research methods that enable peer research.
Co research is at the heart of Peer research. On one hand, peer research enables academic researchers and research teams to train or hire trained peer researchers to conduct research with other patients. On the other hand, peer research means that participants take on new roles as part of co research.
Through careful preparation, clearly defined roles, analyzing their own data, summarizing findings and shared analysis in groups with other patients, participants learn about research by participating as co researchers. Most citizens who take part in peer research leave with confidence in the findings, new personal insight and renewed sense of agency when interacting with healthcare professionals or research teams.
Co research participants can take part in one research event or can choose to be involved throughout the research strategy. They are considered consultants during the SET and REFLECT stages to reinforce their important role as experts. They can also choose to be interviewed, take part in a research focus group or help out as a research assistant recruiting and preparing participants.
People involved in the research feel they are part of it, they commit to using the information, and supporting uptake. In the future, the preparation to become a co research participant might include some basic online stories about research using peer research. The other aspect to be researched is encouraging participants to be part of dissemination, implementation and uptake.
Data collection consists of cycles that include data collection, analysis, memoing and shared analysis that lead to planning the next cycle.
The first table describes the four basic ways to collect data in peer research: Individual interviews, Group research, Field work and Mining public and unstructured data along with Citizen Science. This table summarizes the data sources, the use of stories, and how to track data collected using basic field notes. This is done to lead into the next section that locates and describes these methods within the engagement strategies.
4 WAYS TO COLLECT DATA IN RESEARCH
Community level field work
Open interviews that invite stories of experience
Creating common experiences and strategies
Observing interactions and actions within social situations. Visiting and noting community resources and visiting people
Online searching and analysis of publicly available data is not subject to ethics restriction.
Notes taken during interview
Flip charted notes
Notes about Conversations
Words, phrases or sentences, that capture action or incidents, stories
Flip chart notes of incidents (what happened)
Incidents as actions, behaviours, interactions, environment details, can be stories
Analysis of descriptions and data provided on line
Stories as unit of analysis
Notes can be taken within a story template
Can listen to audio tape and transcribe segments
Note individual stories around emerging common category or theme
Observations can be compared and observations told and recorded into a story format
User comments as stories, as are slogans, accessibility and goals of programs and policies and role descriptions.
Field notes as data
Notes taken to capture the nature and findings of the interview
Notes take capturing the incidents that can be combined as stories
Notes about the social environment, place, people, interactions, outcomes
Online data is considered observation. Discourse analysis can be used to identify power differentials.
Table 2: Data collection options in Peer Research
The following table extends the above table across the SET COLLECT REFLECT and IMPLEMENT of the Peer Research Engagement Strategy.
- Consulting with individuals knowledgeable about the topic or concerns
- Narrative interviewing and analysis
Consulting with individuals knowledgeable about the topic or concerns
- Individuals from the research who can act as champions in implementation
Focus Group Methods
- Consultation team of patients and community
-Priority setting to identify focus of topic or social problem for grant or study
- Research groups
- Rapid development of shared stories, themes and categories
- Confirmation and refining findings
evaluation of engagement
- Suggestions for implementation and social innovation
- Follow up with KT team and groups interested in quality improvement and social change
Field work/ Participant Observation
- Direct experience (observing and participating to identify needs and context of topic)
- Understanding organizations, roles and relationships
- Follow up with those observed for their input of findings
- Observing other related situations using study findings
- Study of implicated social organizations and health systems
Gathering unstructured and social media
- Data publicly available on the internet and other social media platforms
- Quick data and analysis of health systems and programs involved in potential topics and concern
- Quick survey of patient experience research and grey literature on topics
- Data available on health chatlines, patient experience websites and program details
- Data can be subjected to discourse analysis
- Good linkage to social innovation first steps of understanding existing barriers to equality
Table 3: Methods and purpose within the Peer research engagement strategy.
This following section follows up with some specific details about the data collection methods summarized above.
The initial study of interviewing for peer research took place with seniors who were taught open ended, semi structured and standardized questionnaires related to community development and service needs (see Grey Matters). While seniors felt secure with structured and standardized interviews, they were disappointed with the results that were difficult to apply. The scope provided by open interviewing was more difficult to analyse but provided useful information that could be applied to their research.
In Peer research interviews are narrative conversations about specific experiences. While a peer researcher can use their personal stories that enable the participant to feel comfortable sharing stories, this is difficult for someone who does not share experience. In peer to peer interviews you prepare participants ahead of time, letting them know that the topic was chosen by patients and the researcher has experience with it. The purpose is to collect stories about what happened to them and what could or should have happened.
You begin with an open and curious stance, inviting them to share their experience of the topic or main concern. You learn to listen for and capture stories through short notes called incidents, collect data using the story templates, or wait until later to take notes from audio and video recordings.
The nature of narrative conversations increases memory about situations, the whole story and exploring meaning. The skill lies in creating a conversation of equals, interested in exploring experiences about a common concern or topic. You show interest in learning more about what happened, and as in conversation, prompt to hear more.
The peer researcher is curious and interested but avoids any reinforcements such as ‘good’, ‘oh my’, or ‘me too’. These reinforcing statements lead the participant to think that they are answering a question and they will search for the right answer or struggle to figure out what is expected in an answer. Learn to allow time for people to think. If you feel you need to provide support, a gentle prompt related to the story often works.
However, the use of questions is often reinforced by ethics committees who see questions as a way of ensuring that research stays within safe boundaries. In medicine patients are so socialized to being asked questions by professionals that the response is automatic, strong and visceral: What is the right answer? What will happen if I don’t answer correctly? Why is this being asked? What will happen if I answer the wrong way? How do I answer without criticizing my health care provider? Who will find out what I have said? ...and on it goes. These are not idle concerns. Patients spend a great deal of time and energy anticipating questions about their health and how to answer them and they bring these expectations with them when they come to research.
At the end of a narrative interview you celebrate the stories as important knowledge about the research topic. In summary, a narrative interview is not a series of questions but an integrated and meaningful conversation that leaves participants engaged and acknowledged.
Group research is the magic ingredient in peer research, because participants and peer research teams are engaged in all aspects of the engagement strategy. Groups ground engagement because they are used to consolidate and interpret findings before and after data is collected and analyzed.
Groups are blended, with patient and community members as consultants who work with a team of peer researchers who are considered part of the group. They provide research support and guidance as follows:
- Facilitation is done ‘sitting down’ to be seen as a group member. Facilitation starts conversation and supports, or redirects conversation. This is not a leadership position, it follows PAR principles that state all group members are equal and bring differing but valued contributions.
- Flip charts are created by the flip chart recorder who stands up so that everyone can see as the data is recorded when the group is in person. The recorder records using a visible chat function when working online. Either way the pages become the group data record. The flip chart person records conversation in small incident units. The names of contributing members are not included unless the group requests that they be noted. The flip chart person is responsible for the integrity of the data, checking to make sure that the incident notes on the flip chart are accurate. This person also identifies when incident notes are turning into stories. These stories may be recorded on separate flip charts to allow groups to think in stories. The flip charts of stories are used for group analysis.
- Process recording is done by a team member trained in recording what is happening in short incident notes. This is not a recording of content but the nature of the conversation, ideas that resonate or separate the group, and the emotional connections that grow as part of the process. This provides the context and relationships within the group.
Peer group research uses a different protocol for each stage of engagement: SET, COLLECT and REFLECT but there is a general format to build familiarity for those who are involved in more than one group. The sessions are planned to meet the needs of the participants, and generally begin with refreshments and time to meet and talk about why people have chosen to come. People share stories and mingle over flip chart data, discussing ideas during a lunch break and in the afternoon, co research participants focus on analysis of the morning’s work. Groups are often involved in preliminary sorting incidents and stories and suggesting category names. The afternoon ends with a summary and reflections on what they have learned about themselves and the topic and what they think might be needed next - and how they can help. The day ends with a short evaluation of the day and the process with invitations for next steps.
Focus groups not only create good data and personal knowledge, they create motivation to continue to be involved in other peer research and often an interest in becoming a peer researcher.
Observing and taking notes is an essential skill, not only for field work but for any data collection process because it identifies personal interest in what is considered important and also identifies bias in observing. These skills are essential for interviewing and group work - or any situation where information is collected by observers.
Participant observation generally means that one person participates and observes at the same time. In peer research observation is taught in pairs to teach about the impact of personal values on what people look for and record. To teach the concept of inter rater reliability which is achieved when observers are aware of their personal bias and expectations you need to work in pairs or small groups. This takes time to achieve but is easier when one person observes and records as the event unfolds and the other person participates in the event and records after the session. This allows the participant and observer to compare their observations from two perspectives. This exercise teaches about research and the need to be open and to not be drawn into looking at action through biased eyes.
Participant observation is also the most difficult process to get approved in health care settings. Staff are often uneasy about patients watching healthcare being delivered. While it may be difficult to gain access, observations in clinical and community settings come with the expectation that the write up of the observation are shared with the staff field contact to discuss findings with any who are interested.
This type of data collection has been called shadowing, when observers accompany patients and families through healthcare processes, it can produce startling results.
There is an explosion of publicly accessible information, personal beliefs, opinions and experiences through the internet and related social media platforms. It opens new meaning to the Grounded Theory contention that ‘All’ is Data. These new and widely available data sources are unorganized and require careful attention to ensure data quality, especially reliability. Data mining is not new in marketing, public opinion and values research and with more interest in citizen science, these new forms of data will become more a part of more formal co design and research.
Some of the public sources of information include:
- Interactive news publications, customer generated online comments
- Social media platforms such as facebook, twitter, linkedin, Reddit
- Websites, Youtube, photo sharing, instagram, Flickr
- Medical records, health chat rooms such as https://www.healthfulchat.org/, https://www.patientslikeme.com/ https://www.phc.ox.ac.uk/research/research-themes/patient-experience and https://healthtalk.org/ along with an increasing array of professionally led open chat discussions provide insight into patient experience like never before.
These data sources require the use of peer researchers familiar with internet practices because they have more expertise in assessing data quality, reliability and relevance. Accessing these data sources may also require the assistance of those familiar with using online resources.
While accessing existing resources may be a good place to begin co-design, the use of media platforms for data collection is a growing field. The use of crowdsourcing has been used to access simple, low-tech, inexpensive solutions to fight Covid 19 (https://hbr.org/2020/10/global-crowdsourcing-can-help-the-u-s-beat-the-pandemic). The use of online technology and citizen science is evident throughout the research community, informing all levels from individual protein folding online competitions to artificial intelligence networks that are informing national covid 19 planning teams.
All data collected needs to be managed and protected. The following is a short summary of some of the options that have been proven successful in peer research. Each management approach requires training and oversight to ensure that data is held in secure storage according to ethical standards. Each of the data management options have assets and obstacles in peer research and some adaptations are included
Audio and Video recordings
- A permanent record of the data collection event as a reference for all other data management tools
- These records must be secure at all times which makes it difficult for teams to share the recorded data
- Audio and video recordings can be held temporarily while transcripts or incident lists are being prepared.
- Some sponsors request audio recordings but this can prove dangerous as the participants can be recognized. Avoid it if possible.
- Quotes can be accessed and depersonalized as needed.
- Most qualitative research like full transcripts for quotes.
-peer research tends not to use full transcripts except in training. .
- Time consuming
- computer transcription needs careful editing.
- participants are often uncomfortable with full transcripts.
- Use audio and flip chart notes to Take short notes and identify those areas most related to the topic,
- use full transcripts of sections that may be used for quotes
- Connection to participant
- speech rhythm reinforces memory
- Novel approach may be foreign to qualitative researchers
- Use for sections of transcripts to bracket stories
- Use as text backup of audio tapes
Short incident notes of ‘what's happening’ or ‘what’s it like’
- Consistent format for all data collection methods
- Including unstructured and social media data
- Qualitative researchers may still require transcripts
- Begin using short incident notes as part of SET focus groups to build competence in using short incident notes in other data collection methods.
Story template that includes: the context of the research, the steps in the plot and the consequences of the story.
- Template can be used in all data collection,
- Templates are used for both incident analysis and story analysis
- provides common format for data management
- Shifting templates as individual stories become group stories
Templates can be used during data collection
Story templates can be used with participants when sharing stories and when analyzing stories at the end of Collect interviews.
- Each team member can enter their data directly from recordings into a case/concept framework template
- This is a way of managing consultation data quickly without detailed analysis
- When the basic framework is known, it helps identify options for co design topics and main concerns
Table 4. Ways of managing data for sorting and categorizing.
Whenever possible, students and new researchers should ensure that there are audio recordings of their work so that they can refer to them as they learn to use short incident notes or story templates. At this data management stage, audio tapes are useful to begin the process of collecting quotes that are attached to short incident notes or to story templates.
The speech transcript is used throughout this boo because it is a way of capturing the patient voice with the rhythm of speech. This was introduced in chapter 2 where speech transcripts produced natural speech rhythm which improves memory and connection. Reading speech transcripts produces a feeling of hearing the person tell the story. This method is useful in reports developed for patients and communities and has been accepted in peer reviewed journals.
Short incident notes and stories are the preferred method of managing data in grounded theory research and other participatory and inductive research methods. They are collected or produced on cards to increase the ability to sort and compare incident notes during constant comparison. It is easy to take pictures of the cards in a category for data tracking. Concept notes can also be added on the back of cards.
Narrative data collection benefits from the use of story templates that can be produced during data collection or when listening to audio recordings. When seniors found it difficult to transcribe data or take short notes, they suggested using the story templates to manage data. It was easier to use the story templates, then fill in the spaces as they listened to the tape. It also has the benefit of identifying gaps in data collection. It is common that the story teller misses important information in the initial context or in the consequence of the story. Many participants enjoy seeing the story being recorded on the temples as it takes shape and have commented that it makes the story real and valued.
The Framework tool for data management framework creates a structure at the beginning of data collection to enable researchers to enter their data early and to compare entries quickly in order to build analysis structures. There are computer software options to move through the stages from initial categorizations to final reporting. The following research note by Jane Ritchie and Liz Spencer is an excellent source of Framework analysis in policy research. Research Note
As a tool in peer research, Framework tools provide a means of organizing and managing data into a consistent matrix consisting of columns organized by basic themes that can be redefined. The rows represent cases in Framework analysis. The cases are organized according to the structure of the research such as: different researchers in a team, different disciplines in a team, programs according to focus, stage in treatment, funding formats, etc. The resulting matrix reflects the unique needs of the research. The framework can be used in analysis during
- SET or co design team of patient researchers can enter preliminary data about the potential topics or problems for research. These can be entered by the team members according as possible topics or social problems for study become identified. This framework matrix could replace the current use of posters of possible topics for research for a SET co design team to prioritize. The matrix could be used in rating each topic or problem during the SET focus group.
- COLLECT, during content or thematic analysis, the framework template could initially be used to record data at each iteration and then it could be used to redefine cells according to the level of theme and subthemes. In action research, the template could be used to identify various ways that data inform or explain the social problem of the research.
- REFLECT or co design team of patient consultants could use a framework template to summarize categories related to the topic, or to portray the explanation of the main concern based on the core category and properties based on sequence, actors, location, funding, etc.
It would be interesting to test the acceptability of framework analysis beyond the ability to organize and present data and findings. While it is effective in identifying similarities and differences in an easy to understand format for shared discussions, the eventual quality of the interpretation or theory is yet to be tested.
Data Analysis is the process of taking data apart into pieces that can be questioned and sorted into categories that are similar, recombining these pieces of data to capture new meaning about the topic. Constant comparison of incidents leads to coding or naming the categories which represent the collective meaning of the incidents. In peer research categories are actions or descriptions of what is happening or, if focusing on qualitative research what it was like. Analysis remains grounded in invivo language and codes for categories to ensure that the research remains in a patient voice and captures patient experience. The use of invivo language throughout a qualitative analysis is demonstrated in the following example from a study related to teaching new research students to use abstracted invivo codes.
The following is an example an analysis process using invivo codes in a study about a patients experience in emergency care.
Fig. 3: Earlingson, 2017: https://www.sciencedirect.com/science/article/pii/S2211419X17300423
The following is a peer research example of a similar process of abstraction. Note that peer research is generally simplified to include fewer steps
- Direct quote - transcribed with natural breaks.
- As I noticed changes in the way people reacted to me,
- it became important to be more like everyone else
- being normal is impossible
- It always leaves me feeling alone
- always expecting to fail.
- I feel alone and expecting to fail when I try to be normal
- Category codes
- I Don’t belong (a category code)
- Trying to fit in (a category code)
- Expecting to fail (a category code)
In raw data, the units chosen and the codes of potential categories all use the same language. Peer research draws on emancipatory and narrative theory using plain english to inform the naming of categories where appropriate.
The following table includes analysis techniques that have been used in qualitative peer research. Note that statistical analysis is not included in the list of peer research options although patients and communities have been successfully engaged in scoping reviews (McCarron, 2020).
Content and Thematic analysis
- Comparing data to sort into descriptive or emotion category codes
- Challenges with food for patients with Inflammatory Bowel Disease.
-many computer options available, -variety of coding schemes
- Academic traditions use theoretical codes that may not be meaningful to patients
-when thematic analysis is used in peer research real life codes are used throughout
- Identifying and explaining main concerns of populations
- Theory is generated directly from data
- Peer resources in community based support programs
- Rigorous, structured process of
- Focus on conceptual categories
- Use of story as ‘incident’ or unit of analysis
- Use of invovo, real life codes for categories
- How people form and share meaning through stories
- Losing our stories when diagnosed in a mental health system
- Common unit of analysis for all data collection
- Properties of stories inform interpretation
- Not widely accepted in academic journals
- Common story template and analysis format makes it easy to teach and share
Discourse and Systems analysis
- The use of language to find meaning and power in relationships and systems
- Analysis of online program descriptions to identify the role of patients and their agency related to their health
- Focus for systems analysis at all levels
- Easy to teach and access through social media, ideal first step in social innovation research
- Can be threatening to systems
- Use of analysis of language at all levels from policy to the patient/provider interaction
- Organize and manage early findings of team members
- Contrasts themes across specific programs in an organization
- Rows (cases) and themes enable early and summative data to be analyzed quickly
- Mostly use in descriptive categories,
and requires oversight to ensure common reporting
- Excellent for shared analysis of peer research teams, where each member follows analyzes a theme.
Table 5: Summary of analyses used in Peer Research
The majority of qualitative health research uses content and thematic computer analysis that sort data using preestablished category codes created by the researcher. Most current computer analyses allow for the emergence of other categories. Computer content analysis of social media has become popular in quantifying patterns and categories of values, preferences and expectations. There is a broad range of content analysis software solutions for public, unstructured text data in chats, comment sections, news, blogs and twitter.
Peer research methods are based on the use of patient and community language throughout analysis. Because data collection is based on narrative ways of knowing through interviews, videos, pictures and documents, incidents and stories are employed in analysis based on the properties of stories.
Regardless of the process or the type of data, content or thematic analysis bridges between talk and meaning. Whether that meaning is presented in descriptions of experience, stories, strategies or new ways of doing things, the goal is to use data to confirm or uncover meaning.
Current approaches to Classical Grounded Theory analysis (Holton, 2018) have been adopted widely as a part of Qualitative research analysis to increase rigor and concept development. The most widely used analysis tools are the open coding and constant comparison of data. Grounded theory methods rely on the ability to use iterative cycles of data collection and analysis. This not only focuses data collection it increases the potential for unplanned concepts and theory to emerge. It is a trade off: the efficiency of computer analysis to test hypotheses or the creative potential of iterative analysis to develop new interpretations.
Analysis consists of creating short incident notes from whatever data collection method is being used. That said, in narrative analysis the entire story or the representation of a story (metaphor, strategy, actors in the story, consequence or step in the plot ) can also be considered as a story incident. Whatever the data, the first analysis question is ‘What is happening here?’ A more traditional question if you are focusing on early abstraction of concepts would be ‘If this is my data, what was my question?’.
This question guides a constant comparison of the incidents or stories with other storied incidents in emerging categories. These categories are named or coded according to the shared meanings of the incidents included in the sorted categories. If the new stories or incidents don’t find a home in any of the categories, a new category is created and named. Categories are expected to divide or combine through this process to refine their relevance to the main concern of the study. Throughout this process the definition of the main concern or topic is being refined and one category is often emerging as the category that best explains the underlying structure of the main concern or topic.
Grounded theory analysis is ideal in new areas of research, in conflicted or confused social organizations or in tracking social innovation because it adapts easily to unexpected information. Grounded theory is particularly effective within organizations and the roles and relationships they produce.
Stories are the currency of social communication, in the form of autobiographies, life stories, video and film, social media and stories of life experience. As such they are the foundation of data collection and analysis.
Narrative focuses on the ways in which people create and use stories to interpret and explain daily life and world views. As such, narrative analysis includes a wide range of options depending on the profession or discipline. Anthropology and Ethnography gravitated early to use story to capture knowledge about people, their culture, and adaptations. Sociology and nursing produced ways to analyze the content of stories and Psychology specialized in ways to understand how people form meaning in their lives through narratives. In general, narrative analysis helps make sense of past experience. It organizes our current experiences and uncovers the values, expectations and structures that lead us to share stories with others to create common stories and narratives. Narratives of change and forecasting narratives focus on the anticipated futures that emerge from story analysis.
The narrative analysis as part of peer research is based on collecting data within story units that are analyzed initially using story templates. These templates organize data according to the context of the story, applying the questions about story properties - the who, what, where, when and how. The steps or plot of the story provides the strategy or expected process of the story. The consequence includes the expectations and outcomes, the impact of the story. In addition to the story per se, a range of narrative functions are identified including metaphors, mottos and slogans, roles and values.
Discourse analysis focuses on analyzing language from any form of data collection that includes direct access to speech acts that identify pronouns, verbs, metaphors and role descriptions. There is an example of Discourse analysis of Stories in autobiographies in the appendix. Discourse has been particularly useful in emancipatory research because language and the structures of language uncover systemic discrimination. Specifically the use of language to consolidate power and wealth or privilege is used to confront power.
Discourse analysis is particularly useful in the study of policy and health systems because of public access to social media documents, program and policy statements and advertising. Critical theory research uses discourse analysis to detect power imbalance and systemic obstacles. Discourse analysis also identifies personal roles in organizations, professional relationships and business practices which protect power through structures and policy. It can also be employed as a secondary analysis after the initial analysis is complete.
Discourse becomes a method of analysis in section 3 which includes systems analysis and emancipatory patient standpoint theory.
This has been covered under data management but is also considered an early stage of analysis and is increasing in the scope of analysis. (retrieve link)
Interpretation is the act of explaining, reframing or otherwise understanding the meaning of the main concern, phenomenon, or practice. It uncovers the underlying structure in what people do and say. Interpretation in Peer Research is the result of combined attention to analysis, memoing, shared analysis and consistent testing of emerging categories. The term interpretation is used to include both explanatory theory and thematic concepts. Because inductive analysis consists of constant comparison of incidents to create categories there is an aspect of interpretation throughout the peer research process.
Interpretation is practiced by peer researchers and participant co researchers at the end of each data event, by individual peer researchers, by the peer research team, by the REFLECT team that consists of peer researchers and consultants from SET or COLLECT. In most research, interpretation takes place with the sponsor or liaison team. Meaning in peer research is focused by the topic or main concern and meaning emerges as the core category or theme takes shape to explain or describe the topic or main concern.
From a classical grounded theory perspective, interpretation is a process of selecting a core category or theme that best describes or explains the topic or the main concern. That core category provides the foundation for a coherent pattern of categories related to the initial topic or concern. For peer research this connection- from co design proposal through to the end - provides the security of a focus that structures and guides the research process. While grounded theory is inductive, it is not a free for all, the focus of the main concern deepens the interpretation while welcoming unexpected directions.
This continuous thread of interpretation occurs through memoing, memoing about what you are noticing, the patterns, the questions. This trail of meaning becomes the thread of interpretation as you develop a sensitivity to concepts that are emerging. In peer research, memoing is considered a personal and private chance to create your own conceptualizing style. This personal memoing occurs prior to sharing analysis with the peer research team so that each person has prepared their thinking and is more confident in planning next steps. You finish by sorting and resorting memos to find the many meanings underneath. Many find that their research report is basically written already when they sort their accumulated memos.
Once there is an initial plan for how the categories work with the main concern or topic, a REFLECT focus group is convened. This consultation includes mainly patients and community members who were involved in the SET research to work with the findings from a patient perspective. They challenge categories and their relationship to find a coherent presentation that explains, resolves or describes the findings. The Reflect group then discusses the potential impact and suggestions for implementation or innovation. These lead to discussions about how to present the findings, potential audiences and opportunities to try out the findings. The session ends with an evaluation of the research process.
Because interpretation is not a separate process, we come back to the analysis frameworks that were used throughout the study to describe the process and expected outcomes.
The final stages of thematic analysis is a process of consolidating main themes and the hierarchies of sub themes. Quotes are generally incorporated into the structure to capture patient voices. This generally leads to discussion of each thematic hierarchy.
Grounded theory as action based research arrives at the end stage as part of the iterative cycles that support analysis and memoing of the emerging explanation or resolution of the main concern. The focus on the main concern and individual memoing that supports shared analysis builds momentum toward a consolidated picture of what is happening. The essence is a simple and actionable pattern that leads to specific recommendations for action backed by evidence.
Narrative interpretation provides a way of conceptualizing findings within a story framework. Because narrative supports all data collection and analysis, it can augment any stage of the interpretation processes. One of the interpretation tools identified during narrative analysis of autobiographies and the use of stories throughout research is presented below. Autobiographies are eventually analyzed using an abstracted script that captures the context, plot and consequence of a category. The context is abstracted using the property of “When”. The plot is abstracted to the fundamental action that describes the property of ‘How’. The plot begins with the key pronoun “I or We”. The consequence is how the person's personal life story changes, beginning with the “And Then” property.
I you look at the earlier of a situation where a person was trying to fit in
- Direct quote - transcribed with natural breaks.
- As I noticed changes in the way people reacted to me,
- it became important to be more like everyone else
- being normal is impossible
- It left me feeling alone
- always expecting to fail.
one of the scripts or interpretation might be:
- When my condition is changing
- I try to fit in
- And when it doesn’t work, I feel more alone and a failure
While the concept of script arose in an extended study of autobiographies, it can easily be applied to any number of health issues such as breast removal gone wrong or changing genders. The benefit of these simple scripts is that they are easily understood, These scripts are action based and focus recommendations.
Discourse analysis is a secondary analysis used when trying to identify the roles, relationships and systems involved to understand the influence of power in meaning. It opens a powerful debate about why actions occur the way they do. The narrative script above can be a useful tool to understanding power dynamics. A power interpretation can be applied at all stages of analysis and interpretation depending on systemic factors.
You are searching for agency, both internal and external that brings meaning to why actions happen and why people take up the roles they do. The major advantage is that it also suggests actions that would balance power differentials, such as changing patient roles, changing the access process for service.
Like Discourse interpretation, Framework Analysis is a secondary analytic tool that opens avenues for discussing interpretations. It makes no claim to interpretation but is an effective tool when doing team based research.
Peer researchers develop a finely tuned sense when working consistently with inductive research. Through becoming immersed in the data and analysis they become tuned to underlying concepts and potential directions for sampling. Sampling means choosing the next data collection event based on the emerging findings. . It is important that each peer researcher develop their personal analytic skills. However it is also important to share these individual findings with the team.
The iterative structure of peer research has been designed to develop personal conceptualizing skills. The following is an example of a team approach to promote individual conceptualizing.
A large team of student interns held a day long focus group and each person analyzed a portion of the flip charts. Each intern wrote memos about the categories that were emerging and what interested them most. Memoing is considered a personal and private process until the REFLECT stage and is therefore not shared. Memoing prepares each intern to take part in shared analysis.
During shared analysis, the first intern presented a category they had identified with a sample of incidents and why this category was of interest to them. The intern then facilitated a group discussion about the category and invited other team members to contribute data to that category. Each team member has a chance to present a new category or a change to an existing category.
In a peer research team, each intern can adopt or share categories to build skills related to abstracting and revising a category. This version of shared analysis to inform sampling or next stage of data collection, provides a learning process in both personal conceptualizing and shared decision making. It is made possible because of the use of invivo and real life coding.
Quality indicators can be considered from a number of perspectives. The peer research method adopted a classical grounded theory analysis to provide a consistent, focused and robust method of analysis and interpretation as identified above. The key to quality lies in the concurrent data collection, analysis through constant comparison, memoing, planning next steps based on emerging theory to ensure that measuring and testing theory is built into the research fabric.
The quality indicators for Grounded theory research include four practical criteria, a fifth category Engagement is added for peer research
- Fit: The final theory fits with the original main concern and the data
- Work: The theory does what it is intended to do, in other words, it works to inform the underlying structure in what people do and say.
- Relevant: It is useful for those who share the same concern and it makes sense to them
- Modifiability: The theory can be applied and modified for different populations and different concerns.
- Engagement : This category was added for Peer and Community Research to identify how patients and community members were engaged in the research and how the results are useful in engaging other groups and communities.
It is also possible to use quality indicators were developed to identify the features of effective peer research endeavours. These criteria were developed at the end of the Grey Matters project to formalize what they had learned.
- Real life language. Proposals, interactions, meetings with stakeholders and media, research methods and protocols, and reports and articles should demonstrate language that is understood by all. Concepts may become abstracted but retain real life experience codes.
- Representation. The various voices in your project are clearly recognized and documented. Representation is a negotiated process. The methods for achieving partnership at each stage of the research – from creating the research agenda to presenting findings – are negotiated through a process of mutual agreement (cf. chapter 3 social contract)
- Relevance: The process and results should signal a change in the practices of research. Begin by reviewing the following principles of collaborative research with each person who joins your team. These set the expectations of how all researchers and participants will be included in the process:
- Equal but different: The thoughts and beliefs of all participants about the shared questions and issues are equally valid. Everyone from the grant holders, project coordinators, peer researchers, co research participants, and volunteers need to accept that each person will have a say.
- Trust: Trust is hard to earn and is quickly lost. Actively acknowledging the contributions of participants leads to greater understanding and an openness to hear and learn from the voice of others.
- Shared power: Nobody decides for somebody else. Sharing power starts with the expectation to listen and the freedom to express opinion. Each person learns from others and grows in his or her own confidence and capacity. The team lead and committees need to ensure that there is a consensus process in place for meetings and a process to make decisions between meetings.
It is not feasible to make all decisions in committee, but it is also not acceptable to make decisions without consultation. This requires a strong team lead that summarizes information and data for discussion, sets meetings, writes minutes and e-mails and maintains open logs of progress. If the participants are going to own the results, they must feel they own the process.
- Shared work: To share expertise there needs to be a willingness to use common language, to model and mentor unfamiliar activities. Learning to share requires time for reflection on the process and joint ownership of successes and failures. Working together includes the glamorous tasks of planning and committee work but also the tasks of clearing up, making tea, and taking the heat for missing deadlines. It may be just as hard for an academic to learn to chat with a potential participant over tea, as it is for a senior to analyze data. Neither task is exclusive in collaborative research.
We end this long and detailed chapter with final words from the Grey Matters project.
It may be easy to learn how to do the research but how do we know if we are doing it right or if it is any good? (JW, 2005). JW has a good point, wanting to do research isn’t enough, it is necessary to know the standards used to judge good research so that there is confidence in the quality of the work. The standards for judging quantitative or experimental research (experiments with numbers) are widely accepted. Reliability in quantitative research means that the findings can be replicated by others who use the same procedures. The following are commonly accepted standards for qualitative (describing life experiences) research.
Are the results believable from the perspective of the participants in the research? Would a patient or a member of a marginalized group who was cruising the Internet have faith in what you are presenting? This includes faith in the question, the methods, and the findings. This is where peer research has the edge over most academic researchers. If the research is designed and conducted by patient, the results should speak to patients
. In the example of the seniors researching the impact of cervical cancer, we can see this standard of credibility in play. The desire to do research arose from a curiosity about shared experiences and the results emerged from the discussions of the cancer support group. The results should therefore resonate with or speak to others in the same situation. The study reporting the standardized questionnaire results may not have as much credibility among seniors (women, cancer survivors) since the language and the categories in the test speak to a theory constructed by academic or professional researchers. Seniors need to capitalize on the standard of credibility and the researchers must be careful not to lose touch with their participants lest their results lose credibility.
When a researcher talks about findings or writes an article, they must think about how other people relate the findings to their own situation. To accomplish transferability, the researcher starts by carefully describing the “who, where, how, what, and when”, of the research so that the reader can understand the research and how it relate it to his or her own situation. In the cancer situation the young doctor may assume that the findings apply to all older women with cervical cancer experience because he used a standardized questionnaire, but it may only be relevant to women willing to answer questions posed by a young doctor. The observations made by researchers who were part of a women’s support group might transfer well to other support groups, older women who are alone in their healing, other women with different types of cancer and illness, and even younger men with prostate cancer. Because the research evolved from the lived experience of women with cancer, there are many points of connection or transfer.
This is a confirmation of how carefully the research was done, what problems arose, and how the changes made affected the study and the results. Dependable research is transparent, meaning that nothing is hidden. Sometimes standardizing the process increases dependability but can decrease credibility. As one of our researchers commented when administering their standardized questions: We felt good that we had a standardized questionnaire and that we were doing the questionnaire the right way but the answers were boring and left a lot of questions unanswered. (DW, 2004)
Academics are most likely to use this objectivity standard against research done by patients and communities. They may feel that peer researchers are biased and tempted to distort the information to reflect what they want to find. Research is not about proving the researchers’ thoughts and knowledge, but about looking at every event or piece of information as if it were happening for the first time. Objectivity means that every observation is open to question. Every researcher, regardless of age, has to struggle to avoid having their biases affect their observations. Research can range from a very simple observation to a very complex investigation, but regardless of the size or complexity, all research is a process of discovery.
In this chapter we have attempted to provide a broad overview of how health researchers and health care providers can understand and support peer research. The following quote is from two of the authors of Grey Matters in their field notes.
It would have been so easy to take the data and to write it up as an academic, the data spoke to the theories that we were interested in. It was a hard decision. In the end perhaps there is a place for both, research that speaks to theory and research that speaks to everyday life. The ideal would be to have both goals possible in the same method; at least it’s something to work toward. (NJM and CE, 2006) in Grey Matters, 2010.
This chapter provides the bridge between narrative methods and advanced methods particular to Peer Research as conducted within the boundaries of academic health research. It was developed for those interested in using peer research methods in a variety of health and health related research to extend patient engagement. Those wishing to become peer researchers will hopefully find this a way to understand how peer research is different than other forms of qualitative research.
In the end, this chapter completes the second section combining the findings of a number of research projects to create a peer research method specifically to be used by patients and community members. As such it provides the background for PaCER training, for Health researchers wanting to include patients in their research plans and research teams thinking about hiring trained patients to augment existing or proposed grants.
In the future researchers who identify with a patient population may use this chapter to hone their personal research skills and teams who are working with peer researchers, may consider new ventures to create new models of peer research.
The next section, Making a difference uses the methods and theories already covered to extend peer research into a support for social innovation and social enterprise to bring patients and communities into the transformation in health that is ‘just over the hill’
- Have you used methods similar to these as part of your research? If so how have peer research methods differed, if at all?
- What methods seem to capture your ideas about peer and community research?
- What obstacles do you see in adapting these peer methods to your patient engagement practice?
- How might you incorporate peer research into your future plans?
Competencies in Peer Research for Qualitative Research
Collect your data
Prepare to listen and look for incidents in the data you are about to collect. Incidents are actions (stories) and indicators of actions (metaphors, strategies). Coding occurs at the category level as incidents refine, challenge or support the category code.
Question, Code and Constantly Compare incidents,
· Question each incident in turn, to learn how it relates to your main concerns and what ideas it brings to your analysis. Based on your questioning, refine each incident to reflect the answers to your questions.
‘Rehearsing children’ might change to incident codes ‘rehearsing children for the social worker visit’, ‘rehearsing children- vulnerability’, ‘rehearsing children to be allies’,
· Constantly compare each incident to the incidents within categories of other incident codes and from this sorting process you form categories that share the same meanings and/or properties.
· As categories form, you compare new incidents to the emerging categories. You continue to ask questions of the contents of each category to test its strength in making sense of the main concern and how the category could be used to resolve or find solutions to the main concern. Categories are flexible and combine and divide as new incident codes are added.
· When the core category, that best is identified, you compare each remaining category to the core category and to each other to find the pattern of categories that make up your working theory
Memo about emerging categories
· Memo as questions arise about connections and ideas about emerging theory
If you are sharing analysis with your team mates, you might follow one category throughout the analysis to learn about how categories evolve or dissolve.
· As you come close to the core category, focus on which category seems to stand out and how your category might relate to or challenge that emerging category as theory.
· Continue to memo selectively about which category best seems to explain the main concern and is the foundation of your theory
With the researcher team and the PI.
This is an opportunity for each team member to present and be questioned about one of her/his categories
· Initially each person presents and works with the team to collect and consolidate any incidents or concepts that fit with his or her category. Each person has at least one category to work with.
· When you are selecting the core category, each person presents what they consider to be the best category until consensus is reached
· Each persons then presents how their personal category relates to the core category
· During this shared analysis, the team also divides up the remaining categories and each team member works with that category to prepare a poster for REFLECT
Next steps to be ready for interviews
Next steps allow the team and the PI to decide how to use analysis you strategize what each person will be analyzing, who they could see, the focus of their research as part of the goal for the next stage.