Sampling Method

There are probability and non-probability sampling methods for selecting a portion of the population for research purposes. In probability sampling, every element of the population of interest has an equal chance of being selected in the sample (Whitley, 2002). This may be through simplified random sampling, stratified random sampling, and cluster sampling. In all these methods, random assignment of participants enhances the validity of findings. The downside of such methods is that, it may not be practical due to the costs associated with the process or other reasons.

Non-probability sampling methods, on the other hand, do not guarantee all elements of the population an equal chance of being selected to be part of the sample. Selection is based on some non-objective criteria of what is essential, practical, or convenient to the researcher in most of the cases (Field, 2009). Such methods include convenience sampling, snowballing and personal judgement sampling. The main advantage of such methods is that they are cheap and convenient in terms of both cost and money. The significant disadvantage is that the findings may have limited generalisability.

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In this study, a non-probability method of convenience sampling was used for both aid organisation and respondent selection. In convenience sampling, all employees currently working for NGOs in Zimbabwe as aid workers, be it from a relief or development side, and were taken aboard as potential candidates. This included both local and international staff. These may be occupying low to high levels in the NGOs, from both INGO and local NGOs. They were based in offices or out in the field. The convenience method was chosen to guarantee convenience and participants availability.

From over 2,000 registered NGOs in the country, both local NGOs and INGO, the researcher narrowed the list to a convenience sample of 30 NGOs which included the largest NGOs in the country, being made up of 10 local and 20 INGOs. The choice of the 30 was driven by the convenience as well as need to consider meaningful organisations with structures and systems and which were largely recognized for their efforts by authorities (NANGO, 2006). The researcher once chaired a network of around 50 human resources heads of the NGOs operating in the country covering international and local NGOs. To be selected, the NGOs were supposed to have been in existence for at least five (5) years and had to have more than ten (10) employees, a Zimbabwean country office as well as involvement in meaningful relief or development work. The criteria were chosen to enable representation and generalisation of results. Most advocacy-type NGOs were dropped given the fact that they could not meet the minimum employee numbers set. As such, it is these 30 organisations that were approached for research. The researcher obtained permission in writing, or otherwise in 20 of these organisations and was invited by some of these NGOs to some of their workshops. In this group, the most prominent five NGOs in the country were included. The other seven (7) asked the researcher to approach their staff on his own, “if they are interested.” The remaining three (3) were dropped due to access and protocol issues. They took longer to respond, and all the three dropped were mid-size international NGOs, employing less than 20 people locally.

Of these organisations, the majority are involved in relief, development, and some advocacy, which is specific to certain rights, especially those of children, women, and the disabled, but excluding political rights. Most of the largest NGOs in the country had their employees participating. Some specfic organisations requested a copy of results, and if possible, those results isolated to their respective organisations.

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Probability sampling methods have the likelihood of being complicated in the humanitarian sector given sensitivities associated with lists of such employees. Such issues include reasons of security or confidentiality, given the many security protocols in most NGOs, owing to the dangers posed to aid workers in various settings. For some NGOs, the researcher had to wait for months to get permission from their international head offices to participate. The researcher relied on his prior experience in the sector and his networks in the NGO Human Resources Network. The Network assisted the researcher in getting permissions and support from most NGOs. A convenience sample in choosing both the organisations and the participants made it easier for the researcher to gain access to the NGOs and employees as well as the resultant high response rate.

The section above summarises the sampling method and procedure as well as the characteristics of the ultimate sample of aid workers drawn from the population. These biographical characteristics of the sample will be revisited in inferential statistics to answer hypotheses testing questions.

The next section describes the instruments used to answer the research question. 4.3. INSTRUMENTATION

To answer the research questions and test the research hypotheses, it is essential to establish how each of the variables of SI, EI, and CA is related to burnout. As such, these variables must be operationally defined, and measured before they are related to burnout. This section deals with the operational definitions of the variables and the instruments used to measure burnout, spiritual intelligence, emotional intelligence, and coping ability. The description of the measurement instruments, psychometric properties, and justification for the choice of instrument is discussed in turn.

4.3.1 Burnout

4.3.1.1 Operationalisation of Burnout

Burnout has been defined in this study as a kind of job strain that emanates from accumulated work-related stress and consisting of three dimensions of emotional exhaustion, depersonalisation, and feelings of reduced personal accomplishment occurring in people who work with other people (Maslach & Jackson, 1986). Such a conceptualisation stems directly from Maslach and Jackson’s theoretical conceptualisation as a psychological syndrome of

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emotional exhaustion, depersonalisation and reduced personal accomplishment that occur among individuals who work with other people in some capacity. Given the theoretical base of the operational definition, it is therefore pertinent to use Maslach’s Burnout Inventory, which stems from the same theoretical conceptualisation to measure burnout among aid workers.

4.3.1.2 Burnout Measurement-Maslach Burnout Inventory-HSS

The Maslach Burnout Inventory-Human Services Survey (MBI-HSS) was used to assess burnout. The tool was developed by Maslach and Jackson (1986) to measure the psychological syndrome of emotional exhaustion (EA), depersonalisation (DP) and personal accomplishment (PA) that occurs among people who work with other people in some capacity (Maslach & Jackson, 1986).

4.3.1.3 Development of the MBI-HSS

The MBI-HSS was initially constructed by Maslach from 47 items administered to 605 people from several health services occupations (Maslach & Leiter, 1997). Through factor analysis, the items were reduced from 47 to 25. These were further reduced to 22 when administered to a new sample of 420 people. The outcome was three factors with Cronbach Alphas of .90 (Emotional Exhaustion), .79 (Depersonalisation) and .80 (Personal Accomplishment) and all at p=.001 (Maslach, Jackson, & Leiter, 1996). The three factors have been confirmed by several researchers (Jackson et al., 1986; Maslach et al., 1996).

4.3.1.4 Dimensions of the MBI-HSS

The questionnaire is based on three sub-scales emotional exhaustion, depersonalisation, and personal accomplishment. The scale has 22 items on a six-point scale with ‘0’ for never and ‘6’ for every day.

Emotional exhaustion is the key sub-scale of burnout. It refers to a situation where the emotional resources of human services employees are depleted, and they feel incapable of psychologically engaging in their work. The nine (9) items assess the feelings of being emotionally overextended and exhausted by one’s work (Maslach & Jackson, 1986). Emotional exhaustion has been identified as the core of burnout by many researchers (Maslach & Jackson, 1986; Schaufeli & Enzmann, 1998; Maslach & Leiter, 2016). Below is a table with the Cronbach Alpha for emotional exhaustion for this study. The dimension has nine items: 1,

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2, 3, 6, 8, 13, 14, 16, and 20. Table 4.1 below portrays the Cronbach Alpha for Emotional Exhaustion.

Table 4.1

Cronbach’s Alpha for Emotional Exhaustion

Cronbach’s Alpha Cronbach’s Alpha Based on Standardised Items

No of Items

.818 .820 9

Depersonalisation is one of the two dimensions, which indicate burnout with emotional exhaustion. It refers to the negative, cynical acts and feelings about one’s clients, and core to this dimension is the cynical and dehumanising perception that clients deserve their trouble (Maslach & Jackson, 1986). The depersonalisation scale measures a callous response towards recipients of the human service (Maslach et al., 1997). The subscale has five (5) items: 5,10,11, 15, and 22. Its Cronbach’s Alpha in this study is represented Table 4.2 below.

Table 4.2

Cronbach’s Alpha for Depersonalisation

Cronbach’s Alpha Cronbach’s Alpha Based on Standardised Items

No of Items

.709 .714 5

Personal accomplishment is the opposite of the other two sub-scales above. If it is reduced, it is the tendency to assess oneself negatively regarding one’s work. It is somehow linked to efficacy if taken positively. Personal accomplishment measures feelings of competence and achievement in one’s work with recipients (Maslach et al., 1996). It has eight items (4, 7, 9, 12, 17, 18, 19 and 21). This subscale should be reversed in scoring or treated in such a way that low PA scores indicate high burnout, with the reverse also being true. Its Cronbach’s Alpha for this study is represented in Table 4.3 below.

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Table 4.3

Cronbach’s Alpha for Personal Accomplishment

Cronbach’s Alpha Cronbach’s Alpha Based on Standardised Items

No of Items

.766 .769 8

When considering an overall burnout score, one should find high EE and DP as the significant indicators of high burnout coupled with low PA scores. The Cronbach’s Alpha for total burnout for this study is given below, when PA is reverse scored.

Table 4.4 presents the Cronbach’s Alpha of the MBI-HSS overall score.

Table 4.4

Cronbach’s Alpha for Burnout

Cronbach’s Alpha Cronbach’s Alpha Based on Standardised Items

No of Items

.866 .870 22

4.3.1.5 Scoring, Reliability and Validity

Maslach and Jackson (1986) advised against using the overall score of MBI but using subscales to estimate burnout in line with the cut-off points. The Cronbach’s Alpha for emotional exhaustion was .81, for depersonalisation, .71 and personal accomplishment it was .71. When the researcher attempted to combine the scales for an overall burnout score, a Cronbach’s Alpha level of .87 was obtained. This was from subtracting overall PA scores from the total of EA and DP overall scores. The researcher decided to follow Maslach and Jackson’s (1986) advice of avoiding the use of a composite score, but scores on the three individual dimensions of burnout. In the scale, bubrnout cut-off scores are indicated in Table 4.5 below:

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Table 4.5

MBI-HSS Cut-off Points

Emotional Exhaustion Depersonalisation Personal Accomplishment

High 27+ 13+ 39+

Moderate 17-26 7-12 32-38

Low 0-16 0-6 0-31

The table above shows the norms for the cut-off scores for burnout. Cut-off scores have been a debatable issue in burnout research (Schaufeli & Enzmann, 1998). Maslach and Jackson (1986) recommended that for research purposes using the MBI-HSS, researchers usually report on the average score rather than the total. This average is determined by dividing the total score for each subscale with the number of items responded to in the sub-scale. It is the approach adopted by this researcher for scoring the individual dimensions of burnout.

This multi-dimensional model, however, has implications for research and intervention as practitioners would want to deal with a composite score. From Maslach’s advice, differential responses may reflect the differential impact of situational factors, and intervention should target the specific component of burnout that needs to be addressed (Maslach et al., 1997). It seems that this approach allows for focused response in dealing with burnout. The main limitation of the MBI is on cut-off points for clinical diagnosis, as well as not having a total burnout score.

4.3.1.6 Administration of the MBI-HSS

The MBI-HSS is administered to individuals or in groups. The instructions are simple and straightforward. While there is no time limit to complete the questionnaire, an average person will take about five to seven minutes for the 22 questions.

This license to use the instrument was bought from Mind and Garden, who are the holders of the licence. Permission was granted to copy only 350 questionnaires, and to use only for 12 months. The commercial aspect of the MBI has been cited as one of disadvantage of the MBI as it limits academic freedom in exploring and validating the tool for research purposes because of costs associated with the instrument. Despite this concern, the instrument is still the most widely used burnout tool.

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4.3.1.7 Justification for its use

This instrument was chosen because of its extensive use in helping professions in a variety of settings, and for its validity and reliability, which are widely quoted in different environments with Cronbach Alphas above .70 (Schaufeli & Enzmann, 1998). Schepman and Zarate (2008) reported that an average Cronbach Alpha around .83 was found consistently in different contexts. This supports the idea that the MBI-HSS is an internally consistent scale. Reliability coefficients of .90, .79 and .71 were reported for subscales of emotional exhaustion, depersonalisation and personal accomplishment, respectively (Maslach et al., 1997). Test- retest reliability coefficients confirm the stability of the MBI-HSS scales over time. Leiter et al., (1996) found test-retest reliability coefficients ranging from .50 to .82 for time spans of three to 12 months. Research evidence also confirmed the multi-dimensional nature of burnout (Jackson, et al., 1986). Such strong psychometric properties were important in the decision to use the MBI-HSS as a tool to measure burnout in this study. No modification was done as English is one of the official languages in Zimbabwe, and NGOs employ people with at least five ‘O’ Level subjects including, English language.