5. ENSEÑAR LA COMUNICACIÓN NO VERBAL DEL ESPAÑOL COMO LENGUA
5.2. La experiencia integral de la comunicación no verbal a través
Chapter Overview
As noted in Chapter 4 the three research goals from applying the Andersen model to explain health care use were as follows:
1) To test the efficacy of the Anderson behavioural model in the prediction of Maori health care utilisation
2) To extend the model by considering the role of life events in the prediction of health service utilisation
3) To extend the model by considering the role of psychological distress as a predictor of health service use
In presenting the current findings with regard to these goals this Chapter is organised as follows:
1) Firstly descriptive statistics are presented for:
• sample demographics
• predisposing, enabling and need characteristics variables
• health care use variables
2) Secondly the results of six hierarchical multiple regression analyses testing the Andersen model of health service use are presented for each of the following variables:
(1) number of General Practitioner (G.P. or family physician) visits in the past 12 months;
(2) number of hospital-related health visits in the past 1 2 months;
(3) total number of days disabled (3/1 2 months) or spent in bed due to ill health in the past 3 months;
(4) number of prescription items used;
(5) number of mental health professional visits (in the past 1 2 months) (6) number of other10 health professional visits (not G.P. or hospital
related).
Within each of these regressions the role of psychological distress and life events were examined in accordance with the research goals specified above.
Demographic variables: Descriptive statistics
Sample Description
Where possible, general demo graphics for the sample are discussed here with reference to the 1 996 census findings for the Maori population (Statistics New Zealand, 1 997a) which were most relevant at the time of data collection. Descriptive demographic information of the sample is presented in Table 31 1 •
In total 502 respondents made up the sample. All but one participant were New Zealand born. Over two-thirds of the sample were female (68%, n = 34 1). The ages of respondents ranged from 1 8 to 90 years, with an average age of 40 years (SD = 14.98). In comparison to national figures, the current sample has more women and fewer respondents aged between 1 8 and 2 1 years than might have been expected. The fact that certain parts of the population are more difficult to include in the sample than others is well documented (Hill, personal communication, April 24, 1997). The unavailability and tendency to refuse to participate is higher among men and younger people which means that these groups tend to be under-represented in samples.
As indicated in the Table 3 more than 50% of the respondents: • were married or living in a de facto relationship, • living in rural settings (population < 1 000); • had no formal school qualifications ; • were not in paid employment;
• lived in their own home or the home of a family member.
10 This dependant variable refers to contact with health professionals other than G.P.'s including medical
s
p
ecialists, dentists, optometrists, physiotherapists, chiropractors, occupational therapists or naturopaths. I Unless otherwise stated untransformed variables were used in the analyses which produced the descriptive statistics reported in chapter tables.Compared to 1996 Maori population census the present sample had a lower rate of paid employment (35% were in paid employment cf 54%) and a lower level of educational qualification (58% had no school qualification cf 48%). The proportions who were married and who were living in dwellings owned by the occupants/family members were similar to census figures.
As noted in Table 3, the pattern of sample living arrangements (which were very similar to 1 996 census data) was such that:
• relatively few were living III whanaulextended family situations (Le., multi- generation households);
• most lived with their partner and children, or just their partner;
• relatively few lived alone (these were mostly respondents over the age of 60); • the majority of single parents were women.
Table 3
Summary of Participant Socio-demographic Information12 No. of participants Gender Age (years) Male Female 1 8-29 30-39 40-49 50-59 60-69 70-99 Relationship status MarriedJDe Facto Never Married SeparatedJDi vorced Widowed Household composition Area of residence Living alone Living with partner Single parent Partner and children
Youth (over 1 8) living with parents Extended family situation
Living with other adults (e.g., flatting) 'Other'
Rural Urban
Highest educational qualification No school qualification
Secondary school qualification 13 Uni. bursary or scholarship Trade or professional qualification University degree or diploma
Primary work role
Paid employment (full- or part-time) Unemployed Retired Student Beneficiary Home-maker, parent 1 6 1 3 4 1 1 30 1 70 76 59 39 27 257 1 4 1 50 50 54 77 95 1 37 33 41 37 26 27 1 23 1 286 1 4 1 7 42 10 1 74 1 0 1 67 1 6 1 08 32 Percentage of participants 32% 68% 26% 34% 15% 1 2% 8% 5% 52% 28% 10% 10% 1 1 % 15% 19% 28% 7% 8% 7% 5% 54% 46% 58% 29% 1 % 9% 2% 35% 20% 1 4% 3% 22% 6%
12 Adapted from Flett, Millar, Long & MacDonald, 1 998.
The demographic data from the present sample are further elaborated in the following sections in terms of the predisposing, enabling and need distinctions proposed by Andersen.
Predisposing variables described statistically
Means, standard deviations and coding algorithms for predisposing variables investigated are presented in Table 4 below.
Table 4
Means, Standard Deviations and Coding Algorithms for Predisposing Variables14 Variable Characteristics Age Gender Married/de facto Area (rural/urban) Educational Qualifications Telephone Access Vehic1e Access Life events Social contacts Drinks Alcohol Health Worries Health Control Mean 40. 10 1 .68 1 .49 1 .54 1 .92 1 .29 1 .23 3.41 1 . 1 1 1 .34 2.86 1 .75 SD 14.98 .48 .50 .50 1 .47 . 45 . 42 2.30 . 3 1 . 47 . 95 . 74 Coding Algorithm
Actual number of years 1 = male, 2 = female (68 %) 1 = yes, 2 = no (49%) 1 = urban, 2 = rural (54%) 1 = no school qualification 2 = 1 + S .C subject
3 = 1 + 6th form cert./U.E subject
4 = bursary/scholarship 5 = trade/professional 6 = university degree/diploma 7 = university post-grad . 1 = yes, 2 = no (29%) 1 = yes, 2 = no (23%)
total life events experienced (range=O-l l)
1 - yes, 2 = no (1 1 %) 1 = yes, 2 = no (34%) 1 = great deal, 2 = some, 3 = hardly any, 4 = none
1 = great deal, 2 = some, 3 = hardly any, 4 = none
The demographic characteristics of the sample have been reviewed in the previous section. This section describes some additional variables which were classified according to the Andersen model as predisposing characteristics - factors which make an individual more or less inclined ("predisposed") to use health services.
The age distribution of the sample is such that 87% were under the age of 60. The sub sample over the age of 60 is important in that this is often considered to be the time one assumes status as a Maori elder (i.e., kaumatua or kuia). The characteristics of this sub sample have been described in some detail elsewhere (e.g., Hirini, Flett, Kazantzis, Long, Miller & MacDonald, 1 999).
Access factors
In replicating the work of Gribben (1 992) and Wolinsky & Iohnson ( 1 99 1 ) a variety of access variables thought to influence health care use were investigated. In order to utilise health services there needs to be mechanisms available to the individual that might "predispose" them to initiate contact with those services. Seventy one percent (n = 357) of
respondents had a working telephone in their homes. The large majority of respondents
(77%, n = 388) had access to a motor vehicle for their own regular private use, which
accounted for the observation that most (75%, n = 374) travelled by private vehicle to visit
a doctor. The remainder of the sample either walked to the doctor ( 1 8 %), took a bus or taxi (5 %) or travelled by some other means (e.g., bicycle or motor bike).
Social contact
Nearly all (99.4%) of the respondents had living siblings or children, with most either
having spoken over the phone (8 1 %), or having got together in some way (89%) with
relatives and friends over the previous two weeks. Previous authors such as Nelson ( 1 993)
and Wolinsky & Iohnson (199 1) have found that social contact (measured in a variety of
Health worry and health control
Following on from the recommendation of Wolinsky & Johnson (199 1 ; 1 992), due to uneven distributions the health worry and health control variables were dichotomised into those expressing ' a great deal' or 'some' health worries versus those expressing 'hardly any' or 'no' such worries. Similarly, health control became 'a great deal' and ' some' versus 'hardly any' and 'none' .
Most participants (62%) reported having 'hardly any' or 'no' concerns or worries about their health, while 30% had 'some' and 8% had a 'great deal'. In their seminal study of Maori women, the Maori Women's Welfare League found more than half of their sample to worry at least a little about their health, degree of worry was highest among young urban women and kuia (Murchie, 1 984). Unlike the Murchie findings no signiflcant differences were observed between age or gender groups for the health worry variable in the current study.
Participants in the present study largely felt that they had a fair degree of control over their future health, with 87% (n = 430) feeling they had 'some' or a 'great deal' of health control. Ten percent felt they had 'very little control' and 2% felt they had no such control. Comparable figures were found between the gender groups with respect to levels of self perceived control over their personal health status. However, significant differences in health control were observed between age groups. The younger age groups were more likely to feel that they had 'some' or 'a great deal' of control over their future health.
Life events
As described earlier in Chapter 3 a number of previous writers have emphasised the importance of the experience of life events (e.g., Cheng, 1 992). Rubio and Lubin (1 986), for example, found that a number of life events were predictive of subsequent health care use in a U.S. college sample. As an extension to the Andersen model, these events among
others are conceptualised within the Andersen framework as a predisposing characteristic, in the sense that they are experiences that may in part reflect an individual' s position or circumstances in the social structure and the commensurate lifestyles to which people in those positions become socialised. A. "total number of life events experienced in the last 1 2 months" was calculated and is reported in Table 5. The possible individual life events assessed for each participant are listed below:
• You had an operation, injury or major illness (newly diagnosed or ongoing)
• A close family member had an operation, injury or major illness (newly diagnosed
or ongoing)
• You married
• You separated or divorced
• You reconciled after a period of separation
• Your partner or spouse died
• A close family member, other than your partner or spouse, died • You, or your partner, became pregnant
• You, or your partner, had a baby or adopted a child
• A new person, other than a new baby, came to live in your household
• A child or other close relative left home (other than separation)
• You retired
• You started a new job or changed jobs • You lost your job or business
• You were unemployed and seeking work for one month or more • You moved house
• You had major financial difficulties • Your finances improved considerably
• You had serious legal problems with the police or authorities
• A close family member had serious legal problems with the police or authorities
Thirty-six respondents (7%) reported experiencing none of the life events measured. Yet most of the sample had experienced at least one such life event, with one individual
experiencing a total of eleven events in the previous year (M = 3.4 1 , SD = 2.3). The most
commonly reported events were:
• "A close family member had an operation, injury or major illness" (34%);
• "Your finances improved considerably" (33%);
• "A close family member, other than your partner or spouse died" (33%); • "You had major fmancial difficulties"(29%);
• "You moved house" (26%);
• "You were unemployed and seeking work for one month or more"(25% ) and; • "You had an operation, injury or major illness" (22%).
The total overall experience of life events was not significantly associated with gender, education or income levels andlor whether a respondent was in paid employment. Although at the individual item level, women were significantly more likely to say yes to the item "A new person, other than a baby, came to live in your household", whilst men were significantly more likely to say yes to "You were unemployed and seeking work for one month or more".
Alcohol use
In the last national health survey (Ministry of Health, 1 999a) Maori adults were found to be most likely to indicate a hazardous drinking pattern. Of the 502 participants, 335 (67%) reported drinking alcohol. This is somewhat lower than other estimates of New Zealand alcohol consumption. Field and Casswell, for example, reported that 86% of New Zealanders surveyed (a general population sample, n = 5,475) had consumed alcohol in the
last 1 2 months (1999).
There were no significant differences between gender groups on whether participants drank alcohol at all, with 70% of men and 65% of women drinking alcohol. However, men drank significantly more often than did women, a finding consistent with those of the 1 996/97 national health survey (Ministry of Health, 1999a). Younger Maori in the present sample (72%) were significantly more likely to drink alcohol than middle-aged (62%) and older Maori (50%).
Enabling variables described statistically
Table 5 presents means, standard deviations and coding algorithms for enabling variables.
Table 5
Means, Standard Deviations and Coding Algorithms for Enabling Variables
Variable Mean
Characteristics
G.P.'s Genderl5 1 . 1 6
Time with Same G.P. 4.04
G.P. Waiting Times 25 .77
G.P. Fees 1 .8 3
Paid employment 1.63
Income 15,475.24
Grouped income brackets 3.55
Adequacy of Income 2.3 1
Satisfaction in Standard of Living 2.99
Private Health Insurance 1 . 83 Community Services Card 1 .28
SD . 37 1 .24 2 1 .73 1 .07 . 48 1 4,678.038 2. 1 7 . 82 . 77 . 37 . 44 Coding Algorithm 1 = male, 2 = female (1 6%), 1 = 0-3 months, 2 = 4 - 12 months 3 = 1-2 years, 4 = 3 - 5 years 5 = 5+ years number of minutes
1 = not at all, 2 = occasi onally, 3 = some of time, 4 = often 1 = yes 2 = no annual income ($NZ) 1 = 0-5,999 ($NZ) 2 = 6,000-9,999 3 = 10,000- 1 4,999 4 = 15 ,000- 19,999 5 = 20,000-25,999 6 = 25 ,000-29,999 7 = 30,000-34,999 8 = 35,000-39,999 9 = 40,000-44,999 10 = 45,000-49,000 1 1 = 50,000+ 1 = can't manage,
2 = just enough, 3 = little over, 4 = always extra 1 = very dissatisfied, 2 = dissatisfied 3 = satisfied 4 = very satisfied 1 = yes, 2 = no (83%)
1 = yes, 2 = no or have applied,
15 A total of 69 people did not respond to this question (possibly because they had no regular G.P.). There were 7 respondents who said they attended a 'joint practice' (i.e., both women and men served as a respondent' s G.P.).
Doctor gender and length of time visiting a regular Doctor
Drawing from the previous work by Aday & Andersen (1 975) and Aday, Andersen & Fleming ( 1 980), Gribben ( 1992) and Lewin-Epstein (1991) respondents were asked if they had a regular doctor. Lloyd, Lupton & Donaldson (199 1 ) argue that continuity of health care is an imperative in order to attain equity in health status and health care access within modem industrialised societies. Eighty six percent of the sample had a regular G.P. (i.e., they usually saw the same physician), with two-thirds of the sample having consulted their regular doctor for a period exceeding three years (67%).
A total of 82% (n = 356) of respondents reported having a male doctor. The New Zealand Health Information Service data available when the data were being analysed, indicated that of the 3 , 1 66 G.P.' s practicing in New Zealand, the majority (63 %) were male (n = 2,002), considerably more than female G.P' s (n = 1 , 1 64), (New Zealand Health
Information Service, personal communication, 200 1 ).
Dr fees
When asked if Dr's fees ever stopped respondents from seeking a consultation when they felt they should (see Gribben, 1992), over half of the present sample (57%, n = 282) responded 'not at all'; fifteen percent (n = 75) replied 'occasionally' ; while 1 7 % (n = 86) said 'some of the time' and 1 1 % (n = 55) said ' often' in response to this question. Thus 45% of the sample reported that Dr's fees at least 'occasionally' impeded their access to care when they felt they needed it. The relatively low income levels of the current sample (reported earlier), and the lack of health insurance (83 % had none) meant that doctor fees were, not surprisingly, sometimes seen as a barrier to accessing health services.
Waiting time
Waiting time (i.e., the waiting period in a Dr' s clinic) was measured in minutes, and responses ranged from less than a minute (2%, n = 9) up to two hours (1 %, n = 4). The mean waiting time for the entire sample was just over 25 minutes. Gribben (1992) found a median waiting time of 20 minutes among a South Auckland sample, he also found the
waiting time variable to be one of only three significant predictor variables for G.P. utilisation.
Health subsidies/insurance
With respect to private insurance schemes or government subsidies for meeting health care costs of the present sample, 83% of respondents reported that they did not belong to a current health insurance scheme, 9% had a high user health card while 72% had a community services card (which, as noted elsewhere, subsidises health care use). These findings are not particularly surprising given the observed income level distribution within the sample (see below under income).
Although the New Zealand government subsidises costs for G.P. services and prescription item use through a targeted benefit system, a fee-for-service system operates for those using primary health care services. At the last 1 996/1997 national health survey 40% of the general population were covered by a health or medical insurance scheme. When comparisons are made between groups, considerably fewer Maori (25%) were covered by health insurance plans than Pakeha (cf 44%), (Scort, personal communication, June 27, 2001 ).
Employment status
Two questions were asked regarding employment: "Are you engaged in any paid employment" and "what is your main work-related role (e.g. employed, unemployed, retired etc).
As noted in Table 5, 63 % (n = 3 1 8) of respondents were not in paid employment (thus n =
1 84 were in paid work). This is incongruent with the figures reported in Table 3 where
65% reported not being in paid work. A total of 35% (n = 1 7 8), (174 + 4 were seasonal
workers) said yes to their main work role being full-time/part-time or seasonal work.
These two totals should be identical but of the n = 1 84 who said yes to paid employment, n
= 9 of those reported something other than full-time/part-time or seasonal work as their
main work role (i.e., they were students or beneficiaries). Therefore, these nine
1 84-9 = 175 (which still doesn't match the n = 1 78). B ut, of the n = 1 84 who reported not being in paid employment, n = 3 of these defined full-, part-time or seasonal work as their main work role. So within the paid employment question these might be considered to be ' false negatives' , thus the actual number in paid employment should be 175+3 = 178. At closer inspection then, the paid employment figures reported in Tables 3 and 5 do reconcile.
Main job
At the 1 996 census M aori in employment were concentrated in three main industry groups:
( 1 ) community, social and personal services (27.3%); (2) wholesale, retail and hospitality trades (20.4%) and; (3) manufacturing j obs (1 8.9%).-
Among the present male sub sample in paid employment, over a third (36%, n = 24) described their main j ob as being operators and assembly-line workers. From 1 996 census figures Maori men were heavily concentrated as plant and machine operators and assemblers (22.8%). In the present study the next largest male group in paid e mployment were those working in the agriculture and fishery industries (25%, n = 1 7), followed by those working in ' elementary' vocations (13%, n = 9). Among the women in paid employment, 24% (n = 27) were working in the service and sales fields, another 23% (n =
26) were employed as clerks. Eleven percent (n = 12) of women sampled worked in the agriculture and fishery industries.
Fifteen percent (n = 1 7) of women within the sample were working as professionals, in contrast to less than 5% (n = 3) of men. In contrast more men ( 14%, n = 22) t han women (6%, n = 20) held trade or professional qualifications.
Income
Reported annual incomes (for those in paid employment) ranged from $ 1 ,040 t o $200,000 p.a., the mean income being $22,087.84 (SD = $ 19,699.74). The average income for males in paid work was M = $29,463.52, SD = $26,400.68, and for females M = $ 1 7,000.39, SD
= $ 1 0,701 .38. The two main points to note are the skewed income distribution within the sample (Le., more than 50% of both genders earned less than the mean income for their respective groups), and the disparity between male and female incomes. An income disparity between genders was recorded at the 1 996 census; Milori men had a higher