Phase 1 Data management

Stage 1. Familiarisation

The purpose of familiarisation was for the researcher to immerse themselves in the data, garner an overview of the substantive content, and identify topics and subjects of interest. Data analysis began during the data collection; the audio-recorded group meetings and interviews were transcribed verbatim to minimise important omissions (Ward et al. 2013). The transcribed data were then compared with the reflective journal memos and notes to identify similarities and differences between the researcher’s observations of processes and the audio-recorded information.

Transcription

Transcription of the whole data set was the responsibility of and performed solely by the researcher. This ensured that there was no ambiguity in transcription style or formatting and reduced the time taken to become fully familiar with the data. The data were transcribed into individual word processordocuments within one week of

being audio-recorded. The group meeting data was aggregated per group to include

understandings not limited to one partner. To avoid the potential for biased interpretations the partners approved their interview transcripts and the groups approved their group transcripts, comparing the researcher’s account with those of the partner or the group.

Immersion in the data

Once all partners and groups had approved the transcripts, the researcher became immersed in the detail of each transcript. The researcher read and re-read each transcript, where necessary listening again to the audio recording and marking initial thoughts. This assisted in gaining a sense of the whole interview before indexing and labelling began. The process continued until the diversity within the data was understood (Rabiee 2004).

Srivastava and Hopwood (2009) state that where large volumes of qualitative research data are collected, not every piece of material may be reviewed during familiarisation. However, although the process was time consuming, the researcher considered that the research sample size allowed for all transcripts to be included at this stage. This was considered necessary for a complete process that ensured all data from each group and each partner were considered, and that data not commonly

repeated were not overlooked. This resulted in full inclusion and understanding of the data (Ward et al. 2013). Through continually organising and reviewing ideas in the context of the research objectives, questions, and guides, the researcher had, by the end of stage one, noted recurrent and non-recurrent ideas present in the data.

Stage 2 Identifying a thematic framework

Having developed a list of possible topics for inclusion during Stage 1, the purpose of Stage 2 was to identify an initial thematic framework and commence organising the data by identifying headings and subheadings, leading toward the creation of meaningful analysis.

Developing an initial framework

The large amount of data was managed by creating an initial framework. This was developed a priori from the research objectives, design, group (Appendix G) and

interview guides (Appendix H), and emergent questions and topics. The initial framework comprised a list of possible topics that was sorted into a set of headings and subheadings. It was not considered permanent; it could be altered and refined at any time. An example of the initial framework is provided in Table 14; the complete initial analytical framework is presented in Appendix I.

Table 14. Example of initial thematic framework

Data collection phase one pre-experience of and engagement with MyHR

Ro1. To clarify what people living with complex chronic conditions in a rural community require from MyHR Q3 Partner personal journey

Q3.1 Tell me about your family Q3.2 Tell me about yourself Q3.3 Who is involved in your healthcare provision?

Q3.2.1 Tell me about your health Emergent questions and topics Health practitioners?

Health goals?

Stage 3 Indexing to labels and charting to categories

The purpose of Stage 3 was to bring order, understanding and meaning to the words, phrases, or paragraphs of the research community. This required indexing data to labels; the data was scrutinised, highlighted, and sorted; words, phrases, or paragraphs were compared within and between partners and groups.

From a practical perspective, handling the large amounts of transcribed data became overwhelming, despite using the facilities of a word processor and spreadsheets. To manage the data better and enhance transparency and rigour, the whole data set was transferred into the Computer Assisted Qualitative Data Analysis Software

(CAQDAS) package Quirkos©. Quirkos©was considered appropriate for this research

because it provides a variety of search and retrieval tools and the facility to perform comparisons within groups or partners and across groups or partners, and to compare labels, categories, and themes.

It is important to mention that no software, word processor, spreadsheet, or CAQDAS can provide understanding or give meaning to the text; that is the task and skill of the researcher. Any computer program is an instrument that simply manages the data and makes handling of them easier (Burnard 1994; Burnard et al. 2008; Pope, Ziebland & Mays 2000).

The complete data set was transferred from the individual word processordocuments

into Quirkos© as individual _{source files}. This assisted with the continuation of orderly

and accessible retrieval of data (Houghton et al. 2015; Ritchie & Lewis 2003). The demographic, health, and medical characteristics of each partner were imported into Quirkos© as _{source properties,} whichlinked directly to the _{source files}, allowing the

researcher to explore the data in multiple ways, e.g., by gender, age, education, number of CCCs, health professional involvement, and carer status. The initial framework, previously indexed in spreadsheet format (Appendix I) was transferred to Quirkos© as a _Quirk (label), and an example is depicted in Figure 9.

Figure 9. Example of a label

As the analysis continued, the researcher highlighted significant words, parts of sentences, or whole paragraphs from the partner and group transcripts in the source text, by dragging and dropping the highlighted piece into the Quirk (label) that best

reflected the content of each passage, or by generating an emergent Quirk (label).

Each label reflected the group, the partner, their lived illness, their experience of and

Mother was born around Mole Creek somewhere. She live to be 96, old age got her in the end. 2 brothers one died at 16 months he got burnt and they reckon it was shock that killed him. The other brother nearly reached 40 he was killed by a truck on the train he was on, which went into the drink. I’ve got four sisters they’re all still alive. 2 children 2 boys one nearly 57 and one 53 they’re pretty good, one beautiful grandson 21 next month (CH21).

engagement with MyHR, and how this might be useful for addressing the research questions.

One of the most important aspects of the data analysis was the flexibility and transparency of data reduction, achieved by comparing and contrasting data and highlighting and grouping similar quotes together. Using a hierarchical arrangement the researcher could distinguish the overall structure, rather than becoming overwhelmed by the abundance of Quirks (labels) (Rabiee 2004). The Quirks (labels)

were further sorted, refined, and charted to categories as depicted in Figure 10.

Figure 10. The category ‘Family’ charted from the labels

To assist in indexing labels and charting labels to categories, each label and category required a research-specific description. The descriptions assisted in demonstrating a research-focused understanding of: the word, part sentence, or paragraph that was indexed to a label, why each label had been charted to a particular category, and later, why the category was mapped to a theme. Table 15 demonstrates labels charted to a category and their individual descriptions.

Table 15. Example of label and category descriptions

Category Description

Family Those individuals who are in some way important to the person calling them their family.

Label

Family

background Family and the lives of family members have a significant impact on life experiences Family health One part of the entire history of a person

Carer status Anyone who cares, paid or unpaid, for a friend or family member who because of CCCs, struggles to cope without their support.

As the researcher became further immersed in the data, the labels were charted to categories. To ensure appropriate context, the researcher repeatedly checked progress

against the original transcripts, audio recordings, and reflective journal memos and notes. Where some labels initially belonged in more than one category, adjustment of the category was necessary to reflect more accurately the emerging data. This ensured that the data fit in only one category and was not repeated in several. Table 16 displays the narrative indexed to a label then charted to the category Family, one

partner per row, one label per column.

Table 16. Example of Family category

Category-Family Label

Family background Label Family health Label Carer status

C H. 6

We've two children. A boy and a girl, they are doing very well they've left school I'm not a grandma yet. They're both working, one's in Queensland and (daughter's) down at Huonville. Mum's parents were from here (Tasmania) and both born here in Tasmania of Irish ancestry and Dad’s parents were both born in Yorkshire and came out here after the war. Dad was evacuated out here during the war and him and his sister refused to go back when the war finished and so his parents came out here.

My mother is deceased at 82 years she had MS and dementia. Dad's health is good, other than legally blind, he's got a pacemaker, had double bypass

I'm not a registered carer but I do care for my father, who lives on his own.

C H. 13

We live on a mixed farm our grandchildren our 8th generation. Our grandparents were Scottish. We were the first farm to milk sheep, niche veg and poppies. It financially supports one family and one workman. We're currently doing succession planning; produce goes to mainland and Hobart. We also have a mill (flour) ...

My mother sits all day she's developed diabetes and now she has macular and cannot see the bottom of letters and her feet are numb. My dad has macular as well Informally for my father and mother in-law (and) sister is coming from Japan to help with mum. C H. 14

Lost both parents in Switzerland due to an accident. Bought back here to the Snowy Mountain scheme by my father’s best friends who thought they couldn't have children then went on to have 3 children naturally. They brought me up.... I have a son and daughter living (twins) and an older daughter who died at 43, 2 years ago ... Oh and 4 Grandchildren

and (granddaughter) is a Lymphoblastic Leukaemia survivor. Strong family history of Type 1 diabetes and Hashimoto’s My son is my carer he lives in Fern Tree C H. 19

Never knew grandparents I'm 4th or 5th gen Aus. Dad died 10 yrs. ago. Ca stomach and secondary in his 80's. Had a heart attack in his 40's. Mum has lumps on her breast she’s alive at 94 yrs. [In] 2014 [son] was diagnosed with Type 2 diabetes

No, I was for my 2nd wife. My wife is now my carer