Mapping Caregiving and Social Support Networks

Author: Robin Ray and Emily (known as Emma) Anderson

Setting up the project

Increasingly, families and friends are providing the support needed for people living with life-limiting illness to be cared for in their own homes and remain in their communities as they age. While this is most often the desired place of care for both the person and their family, taken-for-granted support systems to enable such care to be a reality are often sparse and inadequate.  More particularly, clinical and personal experience gained from living and working in rural and regional areas where resources to support those living with degenerative disease and/or ageing, are often limited, formed the basis choosing a method that would capture and monitor available support over time.

Here we describe two longitudinal Australian studies that have used ecomapping collect data about pertaining to the evolution of available support for 1) caregivers of people living with motor neurone disease (MND) and 2) people ageing in place in rural communities.

The MND study. Having been a family caregiver for my mother dying at home from cancer in a rural area, Robin was interested to research how family members managed with the complexities and intensity of caregiving at home. Not wanting to focus on cancer, Robin needed to find a disease context that did not involve extended years of caregiving, but required people to put their lives on hold for at least a couple of years.. The need for wider support for people living with motor neurone disease (MND) was raised in conversation at a social event and Robin knew the focus for the project had arrived. Her enthusiasm soared as she learned more about this devastating disease and began meeting people associated with MND.

An important part of setting up a project is identifying the stakeholders and deciding on the scope of their involvement. Recognising the MND Association as a stakeholder, seeking their cooperation and listening to their views and insights into working with the key informants, was vital to stepping into this new world. The initial discussions with the MND workers were like walking on egg shells. Robin was a newcomer in their domain and they were protective of their members. Yet, she needed their consent and their cooperation to gain access to participants. Listening and learning were the keys to gaining their acceptance and confidence. The researcher /stakeholder relationship developed to the point where the MND Association endorsed the project in a letter to members.

The ageing in place study also had its genesis in Emma’s earlier working life in psychiatric aged care unit in Scotland and her current experience of living in regional Australia on the other side of the world from her ageing parents, thus providing support from afar. Through discussions and interactions with older people in the local community Emma realised that many older people in rural Australia did have some level of family support, but was keen to explore how this support varied over distances and context and how older people coped with ageing in what might be resource limited locations.

Setting up the ageing in place study involved a different group of stakeholders. Given the diversity of rural locations included in the study, stakeholders in each of the three rural and remote towns had to be engaged. Research team contacts through health and social interactions were the primary link, later enhanced by Emma’s visits to each location, meeting doctor’s receptionists, managers of local clubs and leaders of faith communities who agreed to display the research promotional material.

Recruitment challenges arose for both studies. Advertising in the MND newsletter and at an information night for the newly diagnosed seemed the obvious thing to do. Not true, these only yielded one participant from each source. On reflection, several problems were inherent in these approaches. The advertisement in the newsletter was a column embedded amongst other information, was not eye catching and did not include the supplied photograph. Saying a few words at an information night when people were trying to make sense of this new disease was information overload and easily dismissed.

Emma’s ageing study used informational leaflets that were glossy and professionally printed, designed to attract attention.  She circulated these to churches, doctor’s offices and libraries. Although the resulting participants picked up the leaflets, for most participants it was the endorsement from local community members that encouraged them to contact Emma.

Personal contact emerged as the best strategy for recruitment in both studies. A letter of endorsement from the MND Association, prompted people to respond to that study, and snowballing between local residents increased participation in the ageing study,  underlining the importance of gatekeepers to the viability of a research project.

Ecomapping was a familiar tool to Robin and one that was shared with Emma. Knowing its clinical application, Robin thought it would work as a research tool to capture social support networks over time. Ecomaps are constructed in consultation with the participant and in these studies it was a shared process. In discussion with the participant the process begins by drawing a central circle. Traditionally this circle contains a genogram of the immediate family or members of the household. In the MND study, Robinwas interested mapping the support systems for the patient and their primary caregiver, so she only included the caregiving dyad in the central circle. In the ageing study, Emma was interested in support for the older person living independently at home, so that person was in the inner circle, with a partner forming part of the social network.  Next step is to identify people with whom the occupants of the central circle interact, or their social network. Each one of these is represented by their own smaller circle that forms part of a pattern surrounding the central circle. Some examples of network members might be family members, school or work connections, a community group, a friend, a sibling or parents, or in the MND project, specific health and social care workers. Each relationship now needs to be evaluated to determine the strength of that relationship. Lines are drawn between the inner circle (and in some cases particular people in the inner circle in the MND study) and each smaller circle. One line represents an acquaintance or professional relationship, two lines represent a closer relationship and three represent a very close relationship. Tension in relationships is symbolised by jaggered lines. In the MND study, one caregiver also used dotted lines to symbolise relationships with siblings that were emotionally distant.

The use of ecomaps needed to be thought through as we wanted the the primary person in the middle circle to own the process and to have a visual representation of their own support networks. We had to think about how to accommodate participant ownership of ecomaps without increasing participant burden arising from the need to learn how to create ecomaps. Practice interviews using ecomapping to collect social network data were an important part of making ecomapping a useful research tool. Thinking about possible data collection environments, developing contingency plans for locating the ecomap so that it was shared between the researcher and the participant throughout the interview and making sure pens were available for both, were important considerations. As these studies were longitudinal involving three/two data collection points, we also had to think about how the ecomap data was going to be collected at each time point given the time it took to construct the initial ecomap in the pilot interview. Photocopying and redating ecomaps so that they could be altered rather than completely redrawn appeared to be an effective solution. It was also helpful to use a different colour pen to draw in the changes to social networks at each interview to enable the network dynamics to be easily identified and ecomaps to be grouped according to their time frame. A conscious decision was made to avoid using red pen because of its association with correcting another’s work.

The data

Collecting data in the intimate environment of a person’s home can be daunting even for a researchers with community care experience.

The first interview in the MND study was a “baptism by fire” as the interview was held in a congested, smoke filled family area and was constantly interrupted by various members of the family wandering through, being introduced, trying to have their say. Yet, to capture the uniqueness of the caregiving context, all this data was important. This was how this family lived; this was part of the social network, an object of our research.

As an aside, in subsequent interviews the family caregiver controlled the flow of people, seeing the interview as her time to be important “I’m being interviewed!” Again, this was important information, providing insight in to the social organisation of these people.

In the ageing study, ne older couple who were aware of the distance travelled to the interview invited me to arrive in time for lunch. They insisted that we had lunch first (freshly caught fish)before the interview. Throughout the lunch we chatted about families and the study. Once finished I went through the consent and cognitive screening process as part of the inclusion criteria. However,  their cognitive score precluded their participation, so I could not continue with the interview. I had not fully considered this scenario or how to manage it.  The potential participants were upset feeling that they had wasted my time. I assured them that this was not the case and that they had added to my understanding of ageing, even though I could not use their information as data for the study.

Reviewing transcripts from interviews in homes revealed an ethical dilemma arising from this context. We on occasions had inadvertently collected data from people who had not formally consented to the study. In the ageing study the partner would sit at the table interjecting comments. This was managed by gaining consent to use the data from identified members of the social network (also considered participants in our study) at the next interview and discarding data from those providing casual comments.

Initially, two interviews were scheduled on one day. However, this was a mistake because the intensity of the caregiver’s experience was emotionally draining especially when entering caregiving contexts for the first time. While debriefing measures such as journaling and collegial discussion had been instituted, these were not as available or not as effective as planned. Scheduling one interview per day increased the time needed for data collection, but improved the quality of the data because I was more focused on each interview. In the situation where two participants lived in the country, approximately two hours drive from the research base and within forty minutes drive of each other, time restrictions dictated that these interviews be held on the same day. To mitigate researcher burden, I planned an unrelated activity such as lunching with a friend or spending lunch time at a local tourist attraction. This created a complete change in cognitive and emotional space and refreshed me before the next interview.

In the ageing in place study the distances could be prohibitive so each site was interviewed in sequence allowing me to spend time in each community. I found that after 5 hours of driving I was not in the correct headspace to concentrate on an interview so scheduled interviews for the following day. Also given the small communities participants were aware of and had discussed my arrival with others taking part and would say so you are off to “Jenny’s” now.

Although, all ethical protocols were followed by the researchers in small towns news tends to travel.

The process of ecomapping was introduced during the interview explanation. Before each interview began, participants were shown a copy of a simplified ecomap and the elements of the ecomap design were explained. Participants were a bit mystified at first, but willing to participate in the process. During the first interview, the ecomap was constructed as the caregiver’s/older person’s story unfolded, being careful to clarify our understandings of relationships before the lines were drawn. There was some hesitation among caregivers/older persons when it came to drawing lines that depicted the strength of a relationship. The importance of relationships was brought into sharp focus and as researchers we realised that we had to be careful to not stress the participant by our need for a value on that relationship. This could have resulted in them making a snap decision that may have under or over valued the relationship or worse still, they might have withdrawn that data.

Concern about the security of the data also had to be handled with care so that the most accurate data about the strength of the relationship could be obtained. This was overcome by drawing the circle and naming the person when the caregiver identified them, then if there was a problem, leaving relationship evaluation to a later stage in the interview. It was important to listen carefully for cues that might indicate relationship strength and then check that the correct number of lines was recorded. Consequently, ecomaps from the first round of interviews (when trust was being established), may not have truly represented all relationships.

Initially we asked direct questions to obtain ecomap data, but asour confidence increased we were able to draw data on the ecomap during the course of the interview, using the drawings as a discussion cue to gain more detailed data. Also, as some of the participants became more comfortable with the process, they began to draw in their own changes to their ecomap.

One challenge that did arise was the restriction on lines of relationship. To be methodologically sound, we needed to replicate ecomap construction as described by Hartman (1995), by drawing one, two or three lines to depict the strength of the relationship. Yet, occasionally caregivers wanted to increase the number of lines to describe a very strong relationship. One caregiver asked “Can I give her ten lines?” I thought about allowing this variation, but discarded the idea because I wanted to be able to compare ecomaps across the cases. To maintain the rigour of the data, I needed consistency of line definition across all ecomaps. Therefore, data pertaining to an extraordinary relationship could not be captured on the ecomap. By combining interviewing with ecomapping, the very strong relationship was captured in the interview data and not lost through the restriction of the ecomap. 

Working with data

Photocopying and redating ecomaps between interview rounds was a useful technique that reminded each participant of their network and also saved the time that would be needed to draw an ecomap from scratch. It was important to ensure that all changes in relationships that occurred between interviews were recorded. This meant that clarification of the ecomap data was needed at several intervals during the interview. However, it was also important to be careful not to interrupt the flow of the older person’s/caregiver’s story. Keeping your mind on gaining interview data, ecomap construction or variation and being aware of the caregiver’s needs, requires focused concentration.

While in the MND study I (Robin) wanted participants to own their maps, I had to manage my anxiety the first time a caregiver took their ecomap and made changes to their network. As Emma’s PhD supervisor, it was interesting for me to hear Emma describe a similar reaction when one of her older persons took over the ecomap. This development in data collection was both exciting (because we wanted the participant to gain something from the process of mapping their support system), but also a bit scary (as we needed to protect the usefulness of the data). From these rough maps I (Emma) used PowerPoint to replicate these relationships. Given the distances from family it was important to capture the location of network support.

caregiving mapping Debbie

Data from interviews contained the descriptors and details of the ecomaps. Recordings of the interviews were transcribed verbatim, being careful to capture the emotional content. Transcriptions were checked for accuracy by listening to each recording while reading the corresponding transcript and checking the ecomap detail. Descriptive analysis of the data was undertaken between interviews so that we could capture the issues at that time and check issues with other participants in the next round of interviews.

It became apparent that a few participants were adopting “ecomap phrases” and incorporating these into their story. For example one caregiver described a relationship in this manner: “She’s re-establishing, I think she’s making an effort to become a two line person”. The first ecomaps strictly followed the design set out by Hartman (1995), but as the caregivers’ stories became more detailed Robin found that it was valuable to expand the scope of the ecomap. Robin began writing information along the lines and making notes on the edges as seen in the example below. This increased the visual cues for both the participants and myself, enabling richer data to be collected.

Carer 13W2

The freehand drawings of the ecomaps now had to be translated into computer images, so that they could be correlated with the interview data through the computer software, and later incorporated into presentations and publications. However, this was not as easy as first thought. Several different software packages were trailed in an attempt to create a clear representation of the ecomaps drawings. Problems arose when trying to consistently create parallel lines that were both straight and jagged, together with reproducing the named circles. Reproducing each ecomap was very time-consuming and required careful checking. Eventually, the ecomaps were created in separate documents and cross referenced to the interview data. Ecomaps were printed for each case and laid out in consecutive order. It was exciting to be able to visually track the changes in relationships across each caregiver’s/older person’s case study. 

Analysis process

The validity of the analysis process and the reliability of the findings were contingent on discussion with research colleagues and other people working with motor neurone disease. In this section, the use of the pronoun “we” is essential for effective, trustworthy data analysis. Prof Annette Street was an integral part of the “we” in this project. Her insight and ability to interpret the data were invaluable.

The interview data and field notes were loaded into NVivo, a soft ware package designed to manage qualitative data and enable line-by-line analysis.  Ecomaps were linked to their corresponding transcripts using the databite function so that relationship detail in the transcript could be connected with the relevant ecomap. Transcripts were read several times to get a sense of their meaning, before codes were assigned to the relevant passages. Writing an explanation of each code was a laborious task and it was tempting to just go on with the analysis thinking that we would remember what we meant by each code. However, this step was invaluable because as the analysis continued we found that our understandings of descriptors changed. At times we needed to go back and revisit an explanation and look at where we had previously applied that code. This process lead to one of two outcomes: either the name of the code had to be modified and previous work reanalysed, or a new code was created for the new material. We applied the words and phrases used by the participants to label each code. As the list of codes grew, it became increasingly difficult to keep track of each one, so we began grouping them to themes, this time using concepts to label each theme.

Our next problem was how to get the ecomap data into a form so that comparisons could be made and the patterns of social change identified. We counted the number of relationship lines in each ecomap, then drawing on interview data, we made statements about the strength and usefulness of relationships as they evolved in specific cases across the data collection period. These statements also contributed to theme development.

This is an extract from our themes list that relates specifically to ecomap data. Note the code occurring

The validity of the analysis process and the reliability of the findings were contingent on discussion with research colleagues and experts in motor neurone disease or gerontics. In this section, the use of the pronoun “we” is essential for effective, trustworthy data analysis.

The interview data and field notes were uploaded to NVivo, a software package designed to manage qualitative data and enable line-by-line analysis.  Ecomaps were linked to their corresponding transcripts using the databite function so that relationship detail in the transcript could be connected with the relevant ecomap. Transcripts were read several times to get a sense of their meaning, before codes were assigned to the relevant passages. Writing an explanation of each code was a laborious task and it was tempting to just go on with the analysis thinking that we would remember what we meant by each code. However, this step was invaluable because as the analysis continued we found that our understandings of descriptors changed. At times we needed to go back and revisit an explanation and look at where we had previously applied that code. This process lead to one of two outcomes: either the name of the code had to be modified and previous work reanalysed, or a new code was created for the new material. We applied the words and phrases used by the participants to label each code. As the list of codes grew, it became increasingly difficult to keep track of each one, so we began grouping them to themes, this time using concepts to label each theme.

Our next problem was how to get the ecomap data into a form so that comparisons could be made and the patterns of social change identified. In the MND study, we counted the number of relationship lines in each ecomap, then drawing on interview data, we made statements about the strength and usefulness of relationships as they evolved in specific cases across the data collection period. These statements also contributed to theme development.

This is an extract from our themes list that relates specifically to ecomap data. Note the code occurring after the hyphen.

MND Study

  • Network - considered our needs                                       
  • Network - died or relocated                                             
  • Network - drifted away                                          
  • Network - emotional support
  • Extended family - emotional support
  • Extended family - invited in
  • Extended family - not seen
  • Extended family - practical support

Ageing in place study

  • Network – family focused
  • Network – friend focused
  • Network – family distant
  • Network - local

Tabulating the data from the ecomaps seemed like a good idea. Yet, trying to capture the strength of relationships across time periods and case studies resulted in large unwieldy tables.. We went through several versions of tables and consulted a statistics expert before settling on a useable format. In the MND Study, we found that dividing up the support networks (as depicted by the ecomaps) into health care workers, family, and community, enabled us to achieve tables that were easier to read while still capturing the relationship detail.

It became obvious that social networks declined over time, but we wanted to see if there was a correlation between network decline and stage of disease. As motor neurone disease is a degenerative illness we wondered if social networks declined as the person became more disabled and needed more care.  We went back to the literature to search the trajectories of the various forms of the disease and used this information together with caregivers’ stories about the type of care they were providing, to develop a care need indicator. This was added to the table to provide a point of comparison, recognising that it was not a tested tool.

Tables gave us information about the strength of relationships and numbers of persons in a network, but reduced our ability to actually visualise the changes in networks over time. Graphs enabled us to represent the stability or decline of a social network and to see which elements of the network were disengaging or were lost.

Data analysis requires many hours of reading, thinking and discussing to go beyond description and discover what the data is really saying. We began to notice that some themes occurred repeatedly across cases.

In the Ageing in place study, ecomaps were used to visualise the types of social networks and classify the locus of support. Reviewing the relationships and the strength of these relationships allowed for classification of network type using Wenger’s typology of social networks (Wenger, 1997).

table

Each ecomap remained as a whole throughout this study with any changes noted at the next visit. In this study networks remained similar between interviews with any changes overlayed on the original ecomap. There was less variation the networks over time. Where losses occurred these were mostly due to death.

In both studies, it was clear that further tools were needed for this analysis and we decided that social theory would be helpful. Thus, themes that had already been identified in the analysis were examined using social theory lenses. Applying theories of social capital (Coleman, 1999; Cox & Caldwell, 2000; Putnam, 2000; Putnam, Leonardi, & Nanetti, 1993) enabled us to clarify the connectedness in family, community and health care relationships. Anthony Giddens (1984; Giddens, 1990; Giddens & Pierson, 1998) theories concerning changing social structure and interactions with expert systems provided insight into the society of the older person, the caregiver and the social dynamics that impact on support networks.

Using Charmaz’s constructivist approach to data analysis, the Ageing in place study applied open and topic coding, breaking the data down to ensure that the codes arose from participant’s voice and not from an pre-conceived labels. Fracturing continued until themes emerged which were then conceptualised as categories informed by Giddens’ Theory of Structuration. Within each network was the interaction between trust and risk which then became the pivotal concept of my thesis.

table

The MND study used constant comparative analysis of data through descriptive coding and conceptual ordering resulting in 21 major themes. These themes were conceptually ordered as the caregiver, their interactions with expert systems, their social relationships and caregiving. This process was helpful in identifying the central concepts arising from the study as presented in the following table.

   Caregiver

Expert System

Social Network

     Caregiving

Caregiver

Relationships

Control

Getting a diagnosis

Information

Formal care

Government

Financial issues

Network

Extended family

Community

Reciprocity

Asking for help

Person living with MND

Care role

Symptoms

Quality of life

Future

Conceptual theorising about the data increased the validity of our findings and situated them in the social context being examined by this study.

Wenger, C. (1997). Social networks and the prediction of elderly people at risk. Aging and Mental Health, 1(4), 311-320. 

Reporting the project

The first part of the MND project to be reported was the use of ecomaps as a data gathering tool. As ecomapping had not been used as a research tool in chronic illness research, it was easy to decide that a journal article describing the use of this method could be published. We constructed the paper to describe the origins and applications of ecomaps, our use of ecomaps in this study and the type of results we achieved. It was important to provide some examples of the data generated so that readers could gain a clear understanding of the usefulness of ecomaps in research. We decided to submit the paper (Ray & Street, 2005a) to a nursing journal, so that nurses could learn about using ecomapping in nursing research. We also thought that ecomaps would be useful for identifying support service needs for people being cared for at home.

Dissemination of data from both studies originated from working with the themes and categories that had been generated through the data analysis. We found it helpful to use cognitive concept mapping to gather like themes together, identify the links between repeated themes and develop a central concept that became the focus of a paper. This process generated several topics for journal articles and conference presentations. The next step was to go back to the literature and review work that had been done around the central focus for each paper. This was a time consuming task, but it enabled us to connect our findings to the literature and choose the most appropriate findings to publish. It was important to carefully select findings and to avoid the temptation to “dump data”. Being excited about your findings does not make them publishable. We needed to select findings that illustrated the new information gained for the project and then identify the most appropriate journal in which to publish them. Remember to check the journal’s audience to make sure you have a good fit between your outcomes and the needs and interests of the journal readership.

We targeted a social health journal to publish the ecomap material concerning the dynamic nature of support networks in degenerative illness and a geriatrics journal to publish the type of support for ageing in rural areas.  We thought that given the  range of health and social care workers involved in care and support across both lots of study participants, readers of these journals would be interested in this information.

The size of ecomaps as well as their complexity created a challenge when preparing journal articles and conference presentations. We had to think carefully about how to choose the most representative ecomaps and tabulated data to support our findings. The community table and some of the graphs were published by Health and Social Care in the Community (Ray & Street, 2005a) while an extensive discussion of networks and ecomapping in rural ageing has been published in Geriatrics (Anderson, Larkins, Beaney & Ray, 2018)

When presenting ecomap data at conferences or seminars, it is important to allow time to explain how the ecomaps are constructed and to clearly interpret the chosen ecomaps so that the decision trail is transparent and findings are easily understood. Audiences are interested in the process of developing ecomaps and fascinated by the data they produce, so be prepared for questions.

References

Anderson, E. M., Larkins, S., Beaney, S., & Ray, R. A. (2018). Should I Stay or Go: Rural Ageing, a Time for Reflection. Geriatrics (Basel, Switzerland), 3(3), 49.

Carpenter-Aeby, T., Aeby, V. G., & Boyd, S. (2007) Ecomaps as Visual Tools for Deconstructing Reciprocal Influences: Triage with Disruptive Students at an Alternative School. School Community Journal, 17(2), 45.

Early, B. P., Smith, E. D., Todd, L., & Beem, T. (2000) The needs and supportive networks of the dying: An assessment instrument and mapping procedure for hospice patients. American Journal of Hospice & Palliative Care, 17(2), 87-96.

Hanson, S. M. H. (2001) Family assessment and intervention. In S. M. H. Hanson (Ed.), Family health care nursing: theory, practice and research. Philadelphia: F.A. Davis Publishers.

Hartman, A. (1995) Diagrammatic assessment of family relationships. Families in Society, 76(2), 111.

Hodge, D. R. (2000) Spiritual ecomaps: A new diagrammatic tool for assessing marital and family spirituality. Journal of Marital and Family Therapy, 26(2), 217-228.

Ray, R. A., & Street, A. F. (2005) Ecomapping: an innovative research tool for nurses. Journal of Advanced Nursing, 50(5), 545-552.

Ray, R. A., & Street, A. F. (2005a) Who's there and who cares: age as an indicator of social support networks for caregivers among people living with motor neurone disease. Health and Social Care in the Community, 13(6), 542-552.

Rempel, G. R., Neufeld, A., & Kushner, K. E. (2007) Interactive Use of Genograms and Ecomaps in Family Caregiving Research. Journal of Family Nursing, 13(4), 403-419.

Ross, B. R. (2001) Nursing process and family health care. In S. M. H. Hanson (Ed.), Family health care nursing: theory, practice and research (second ed., pp. 147-169). Philadelphia: F.A. Davis Publishers.

Tracy, E. M., Whittaker, J. K., Pugh, A., Kapp, S. N., & Overstreet, E. J. (1994) Support networks of primary caregivers receiving family preservation services: An exploratory study. Families in Society, 75(8), 481-489.

Wright, L. M., & Leahey, M. (2000) Nurses and families: a guide to family assessment and intervention (third ed.). Philadelphia: F.A. Davis Company.

Looking back

  1. Three years on: research developments

While I have not used ecomaps in my recent research (my focus has changed from support networks to challenges for patients and caregivers such as coping with degeneration and end of life issues); research concerning social support for patients and families continues to appear sporadically in the literature. The work is predominantly in aged care with a smattering from disability and cancer care.

Four studies have used mapping as a technique for identifying support.  Rempel, Neufeld and Kushner  (2007) drew on my work and effectively used ecomapping as part of an ethnographic study to identify supportive and non-supportive relationships for male caregivers of people with various dementias.  In a study of children with disabilities, Washington (2009) constructed ecomaps with participants in conjunction with a questionnaire and interview to triangulate data collection in a phenomenological study. Ecomaps served to identify the superficial nature of community relationships and the lack of real support offered by these connections. These replicated my use of ecomaps and their findings are consistent with my previous work. Visualization of relationships as depicted in ecomaps gives family caregivers insight into the real nature of the relationships in their caregiving context as well as adding richness to the interview data. Two other studies used social network mapping techniques to identify relationship connections for family caregivers (Carpentier & Grenier, 2012)  and patients (Price, 2011) in the context of their social networks. However, in these studies, the maps were constructed from narrative data as part of the analysis.  While they exhibited some of the properties of ecomaps such as lines of relationship connection and circles, they did not replicate ecomaps and were not shared with the participants. As a researcher, I think it is important to be able to give something back to our participants. Constructing ecomaps with participants enables them to have ownership of the data and to learn from seeing and evaluating their own social relationships. Collectively these studies support the value of using mapping as a tool to identify support systems available to patients and families whether as a clinical tool for discharge planning or to research the experiences of people living with chronic disease.

As a positive outcome of my research, mapping of support systems for family caregivers has been taught to community groups as a method of identifying and engaging the support available to families. Increasingly, people with chronic and/or life limiting are being cared for at home. There is an almost unspoken expectation that family members will be available and capable of providing care. In many places, particularly in rural and remote areas, the availability of community services support is limited or non-existent.  Discussing the need for social support among community groups particularly in rural towns including teaching ecomapping, enables people to see the need to support others and to identify the supports that are possibly available to them personally.

  1. In hindsight

In designing the project again, I would still use ecomapping in a similar way, perhaps taking advantage of digital media if there was a user friendly program that would enable ecomap construction on a tablet. Creating the ecomaps in digital format has benefits for the researcher. It would reduce possible transcription errors and the time taken to transcribe the drawings into digital format, as well as facilitating easier publication. However, using a tablet might inhibit the participant’s ownership and interaction with their ecomap as well as increasing the interview burden.  Learning to use the program would be time consuming and may be a barrier for participants who are not used to using technology, limiting access to useful data. The current method of free drawing ecomaps involves adapting a life skill that is common across prospective participants and thus may continue to be more conducive to collecting rich data. 

Despite the digital possibilities, I would still like to be able to offer caregivers the option of a hard copy to enable them to continue to evaluate and perhaps better utilize their sources of support between data collection visits. The hard copy would enhance the cooperative nature of data generation and provide a useful tool that participants could utilize beyond the timeframe of the research project.

It would still be important to undertake the research in the home where the caregiving is taking place. The location itself is a rich source of data as the researcher is privileged to be immersed in the physical and emotional caregiving environment. This experience enriches field notes and adds to further information to ecomaps.

Additionally, if I had the time and resources, I would follow the family caregiver’s networks into the post caregiving phase. Incidentally, I was able to capture small amounts of interesting data from a few participants who agreed to be interviewed after the person had died (within the time frame set by my study). While some studies have addressed the after effects of caregiving, bereavement and adaption,  changes in social support are not well documented.  Mapping the redevelopment of family caregivers’ social support systems adds another dimension to understanding social support over time. However the researcher has to be very sensitive to the caregiver’s needs concerning grief and loss when entering this phase of the caregiving trajectory.

  1. Software tools

I’m sure I could have used NVivo more effectively as I did not use all the functions available to me. The time between undertaking the NVivo course (including an update) and using the software was too long and I did not have the resources to gain extra tuition along the way. While I continue to use NVivo, I do so sporadically as research is not my only occupation. Therefore, I have not expanded my exploration of available software.

In correspondence with Robin Ray, I asked her if she would be interested in a conversation with someone expert in the current versions of software. She welcomed this, and the following comment was provided by Dr. Leonie Daws, of Kihi Consultancies.

I was interested to read your case study, Mapping Caregiving, on the SAGE companion website for Lyn’s book, Handling Qualitative Data. The process of ecomapping appears to have suited the study well but clearly presented challenges when it came to creating a digital record of each ecomap. I note that you used NVivo to assist in a line-by-line analysis of the interview transcripts, but that you looked elsewhere for mapping software.

It may not provide the perfect solution but perhaps you could explore how NVivo’s Relationship Nodes might work for you. The program enables you to create Relationship Types, which can be used to parallel your ecomapping connections. For example, you could create Relationship Types for ‘is an acquaintance of’, ‘has a professional relationship with’ etc.

You create Relationship Nodes by linking a patient’s case node with their caregiver’s node and so on, making as many nodes as are needed to represent each connection and selecting the appropriate Relationship Type to describe the connection. This then provides you with a place to store relevant passages from the transcripts to illustrate the character of that particular relationship – by coding passages at the node.

Once all the required relationships have been created, you can use Models to map the connections for each patient or caregiver by inserting the patient or caregiver’s case node into a new model and then asking for all associated relationships. This will automatically generate a map of that person’s support network and has the added capability of providing access to supporting text simply by clicking on the Relationship icon and asking to open the node it represents.

The Relationship Type can store information about the direction of a relationship – unspecified, one-way or reciprocal. There’s no capacity to characterise the Relationship Type through the use of lines indicating strength of the relationship or associated tensions, although this can be achieved to some extent at a later stage in the Model. Here you set up styles including line thickness and colour or font appearance, which can be used in a standardised way to symbolise relative, strength, tension or trustworthiness.

The end result would not recreate the appearance of your present ecomaps but would have the advantage of providing direct access to your evidence.

Response from Robin

It sounds like relationship node would be helpful for some of the data as they could be worked alongside the ecomaps. However, given that the patient or caregiver may only refer to a person in their network in a few words rather than having a script from that person we may lose the context of the data. The ability to draw the relationships and use these drawings to prompt the participant in follow up interviews is still something I am grappling with. Any thoughts on this would be helpful.

I will need to explore relationship nodes in more detail. Thanks for the tip.

References

Carpentier, N., & Grenier, A. (2012). Successful linkage between formal and informal care systems: The mobilization of outside help by caregivers of persons with Alzheimer's Disease. Qualitative Health Research, 22(10), 1330-1344.

Price, B. (2011). How to map a patient's social support network. Nursing older people, 23(2), 28-35.

Rempel, G. R., Neufeld, A., & Kushner, K. E. (2007). Interactive Use of Genograms and Ecomaps in Family Caregiving Research. Journal of Family Nursing, 13(4), 403-419. doi: 10.1177/1074840707307917

Washington, L. (2009). A Contextual Analysis of Caregivers of Children With Disabilities. Journal of Human Behavior in the Social Environment, 19(5), 554-571. doi: 10.1080/10911350902983093

 

 

Author profile: Robin Ray

My involvement in qualitative research began when I was thinking about how to undertake my Master of Health Science. As a mature aged student, I sought opportunities to do project work in my undergraduate degrees and this together with some helpful advice set me on the track to a masters by research. I was interested in why people made particular health decisions and more particularly how their daily context and life experience that influenced their health decision making. Qualitative methodology gave me the scope to explore the dynamics of these experiences for each person. Changes in life led me to into new research arenas and I moved my research focus to the increasing numbers of family caregivers who put their lives on hold to care for loved ones with life-limiting illness, especially when they have little or no real idea about what fulltime caregiving requires of them. I began using ecomaps to help people identify avenues of support. This translated into the idea that ecomaps could be a helpful data gathering tool. At national and international conferences, I have enjoyed lively discussions with people about the availability of social support and the use of ecomaps in research and in health and social care. My current academic position in the College of Medicine and Dentistry at James Cook University enables me to continue to enjoy encouraging others to develop their research skills through teaching research methodologies, as well as supporting and advising Masters and PhD candidates like Emma Anderson,  my co-author on this site.

For further information about my research and contact details, visit: https://research.jcu.edu.au/portfolio/robin.ray/

 

Robin Ray

Author profile: Emma Anderson

My research career started when I left University and worked as a research biochemist for eight years. I started and abandoned a PhD after eventually discovering that laboratory research was not for me. I then moved into research management and aided others in their research endeavours. In this role I was introduced to social research; why people made decisions and how their everyday experiences influenced their life journey. I realised that I had not lost my desire to undertake research, but rather I had not chosen a subject that engaged me. After immigrating to Australia and away from my ageing parents I began thinking about social support for ageing and how this would be navigated in a changing society. At this point, Robin Ray had joined the College of Medicine and Dentistry and I now had a project that I was passionate about, with her agreement and input I started my PhD. Over the past six years, I have travelled north Queensland engaging with older people and members of their social networks in their homes and communities using ecomaps to visualize and discuss these relationships. It has been a pleasure to be invited into their homes to discuss how they view their ageing self, how they plan to cope with ageing and the support they received from family and friends. I have presented my work both nationally and internationally and plan to submit my thesis in a few weeks.

emma.anderson2@my.jcu.edu.au