Análisis e interpretación de resultados de la observación

travel for wellbeing 68 33.3

Total 204 100.0

Each group was directed to a different survey to ensure relevant questions were asked. Those who had never travelled for wellbeing (Group 1 and 2) were asked a series of questions explore their opinions about wellbeing travel and their non-travel status:

Q26. When considering a holiday or short break, have you ever thought about travelling somewhere to improve your well-being (i.e. well-being travel)? Q30. When you think of well-being travel, what images come to your mind? Q33. Would you travel to a destination which focused upon well-being if it was an affordable holiday? Please explain why or why not.

Q34. If you were to travel for well-being, please indicate which type of well-being travel you would be likely to take part in, Religious Tourism; Spiritual tourism; Spa Tourism; or Lifestyle Retreat.

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Of the total sample 12.3% reported that they had not travelled in the past year. The No Wellbeing group included the majority of non-travellers, 66%, while the Wellbeing Travellers had the least of those who did not travel, 12%, and Wellbeing Non-Travellers 24%. This travel rate cannot be compared with past research in Australia because no other research had been conducted on this topic at the time this research took place (van den Eynde, 2009). Table 9 provides a snapshot profile of the three survey sample groups assembled from key findings of the socio-economic characteristics of the total sample including gender; age; employment type; highest education level; religion; and engagement with wellbeing activities.

Table 9: Socio-economic characteristics of survey groups. No-Wellbeing Wellbeing Non-Traveller Wellbeing Traveller Male 67.1% 56.5% 52.9% Female 32.9% 43.5% 47.1% Age Median 45-54 55-64 45-54 Income Median $36,000-51,999 $52,000-79,999 $52,000-79,000 Higher Education Median

TAFE TAFE Diploma

Religious Affiliation 18.1% 24.7% 30.8%

Primary

Employment Type

Full Time Pension/Benefit/ Retired Full Time Secondary Employment Type Pension/Benefit/ Retired

Full Time Pension/ Benefit/Retired The following provides a profile of the three survey groups representing key findings of the socio-economic characteristics of the total sample including gender; age; employment type; highest education level; religion; and engagement with wellbeing activities.

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Group 1: Low Wellbeing Engagement, No Wellbeing Travel. This group comprised of 74 participants, or 35.8% of the total sample. They were defined as people who do not participate in a wellbeing activity at least once every fortnight, and have not travelled for wellbeing in the past two years. It

comprised of a substantial amount of males (67.1%) and was the highest proportion of males to females of all three groups. This group also had the highest proportion of those were the ‘Full Time Employed’.

Group 1had the lowest education level (with TAFE certificate as a median highest education level) and had the lowest median income of all three groups, 36.1% of this group with an income between $36,000 and $51,999. The anomaly of this group was that it included the largest proportion of people in the highest income bracket, with 5.6% earning $100,000 or more per year.

Not only did they not participate in wellbeing regularly, they were also the least religious, with 18.1% reporting a religious affiliation. In addition to not travelling for wellbeing, this group also comprised the majority of the survey sample who identified as non-travellers (66%).

Group 2: Regular Wellbeing Engagement, No Wellbeing Travel. Group 2 comprised of 62 participants and were 30.4% of the total sample. They were defined as a group of people who do participate in a wellbeing activity every fortnight, but have not travelled for wellbeing in the past two years.

Group 2 had the most balanced gender ratio and the oldest age cohort n of all three groups (55-64). However, they also included the highest proportion of people in the youngest age category, 17.9% in the 18 to 25 age group.

The median income for this group was above the average Australian income, $52,000 to $77,000. Particularly characterising this group was employment, 40.3% had pension/benefits as their employment type. Along with not travelling for wellbeing, 24.0% of this group were non-travellers.

Group 3: Regular Wellbeing Engagement, Travel for Wellbeing. This group comprised of 68 participants, or 33.0% of the sample. They were defined as people who participate in at least one wellbeing activity every fortnight.

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They have travelled for wellbeing in the past two years to either a spa, lifestyle, religious retreat or ‘other’ interpretation of wellbeing travel.

Similar to the other two groups, their median age is between 45 and 54. Group 3 had the highest female sample (47.1%), and the highest amount of those who were unemployed and part time employed. They were also the group with the highest level of those who had completed a Bachelor (29.0%) or Postgraduate degree (11.0%).

Group 3 comprised the lowest rate of non-travellers, recording 12.0% who had not travelled in the past year.

Procedure

The survey was designed after the analysis was completed for Phase 1 (interviews) and Phase 2 (focus group). The resultant survey was significantly informed by the first two phases and included similar themes and a number of additional themes that emerged from this data analysis.

Analysis of the focus group discussion stimulated ideas for new topics of investigation. The focus group discussed wellbeing in terms of gender. They spoke of actively seeking to improve wellbeing as a predominately female pursuit and as the opposite to masculinity. This was personalized in stories about their husbands or brothers who would not consider doing wellbeing travel, going to a naturopath, or going to a doctor. This discussion prompted the addition of a theme and set of questions about gender in the survey.

The in-depth interviews with service providers also promoted the addition of the gender theme for the survey because all indicated their customers were

predominately female.

When the focus group were asked to discuss a definition of wellbeing, and if Australian people are well today, a discussion formed which equated technology as an anti-thesis to wellbeing because 1) technology keeps people inside on their screens and 2) technology means we are more connected to other people, and this was perceived as suffocating and contributing to a decrease of feeling well. This discussion prompted the addition of a theme about technology in the survey.

The focus group and the in-depth interviews with service providers also stimulated a theme about how the concept of wellbeing and associated products are

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increasing in Australia currently. This data prompted the addition of a set of questions about a collective/society representation of wellbeing in Australia.

Theme 1 In your opinion what is wellbeing?

Theme 2 Have you heard of wellbeing travel? What do you know?

Theme 3 Have you noticed an increase in Australians becoming conscious of their wellbeing?

Theme 4 What are your regular wellbeing activities and what experiences have you had with wellbeing travel?

Theme 5 Can you identify the barriers and constraints of wellbeing? (Please see Appendix J for a breakdown of themes and rationale for themes). Theme 6 What is relationship does wellbeing and gender?

Theme 7 What is the relationship between wellbeing and technology? The researcher designed, uploaded and monitored the online survey using ‘Qualtrics’, a widely used software for online surveys. Pre-testing (p. 155) occurred in the form of a pilot study before the Qualtrics survey was available to participants. Five participants (friends, family and colleagues) read or completed the trial survey to assist with picking up any editing or content issues.

The process of recruitment for the survey began when the researcher first contacted Research Now in 2009. The researcher requested a panel that would be representative of the Australian population. Research Now confirmed they would provide a sample that was benchmarked of the Australian Bureau of Statistics (please see Appendix I for benchmarking information). The conditions of the contract with Research Now (to provide the panel sample) was finalised in June 2012 and the project commenced. Over a period of two weeks, Research Now contacted potential participants from their panel by sending small batches of email invitations. The amount of invitations was closely monitored to not exceed the target amount of surveys (200). Attached to the email was a link to the survey hosted by online survey software ‘Qualtrics’.

A total of 244 participants began the survey, however 204 participants

completed the survey. Although all those invited were eligible to participate, the total sample (n=204) were filtered into one of three groups.

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Consent to participate was presented in the first screen of the survey. On this first screen participants were welcomed to the survey, introduced to the research and informed of their confidentiality if consenting to participate in the research.

Participants were asked to tick the ‘yes’ box to consent to being a part of the research If they did not consent they were re-directed to an end of survey screen.

Survey Data Analysis

The quantitative survey data was analysed with SPSS. Following completion of the survey, the raw quantitative data was exported from Qualtrics to an SPSS file and data clean-up was undertaken. Analysis of quantitative data largely comprised of applying the descriptive and frequency functions to summarise the data, for instance, sample sizes of the three survey groups; the presentation of demographic data concerning the survey sample groups, and measures of central tendency for selected demographic variables, age and income (see the section above titled ‘Participants’). The descriptive data provided an initial analysis of the relationship between variables of interest.

The limited quantitative data analysis also included chi-square tests to assist in examining research question two ‘What are the drivers and constraints of travelling for wellbeing in Australia?’. As stated in the literature review, past and current research resoundingly finds wellbeing and health is determined by socio-economics, therefore, the student researcher systematically applied chi-square tests with all categorical demographic data to determine if there was a relationship between wellbeing, survey groups, and demographic information. The chi-square test - a non- parametric test - is a common choice to examine differences and relationships with categorical data (Morgan, Reichert, Harrison, 2016, 35).

The systematic application of chi-square tests was undertaken with the following survey questions:

- Q10. Please rate your level of well-being on a scale of 1 to 5 (1= not well, 5=very well).

- Q11. Have you reached your own ideal state of well-being at any point in your life? When and why?

- Q12. If yes, are unwell people not willing to put in this time and effort?

- Q15. Do you think over the past few years the Australian people have become more conscious of their health and well-being?

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Qualitative data was analysed with QSR Nvivo 9 and 10. Consistent with analysis of Phase 1 and 2 data, coding for phase 3 was conducted with thematic network analysis as a method to examine the themes that can identify an overarching discourse of wellbeing and wellbeing travel.

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Chapter 7: Results and Discussion. The Organisation and Construction of