January, 2015

Consulting Diviners For Health: The Influence Of Socio-Demographic Factors On The Use Of Divination In Health-Seeking In Northern Ghana ISSN 2319-9725 Thomas Bavo Azongo Lecturer, Department of Allied Health Sciences, School of Medicine and Health Sciences, University for Development Studies, Tamale Campus. Post Office Box 1350, Tamale, Ghana Michael Wombeogo Lecturer, Department of Allied Health Science, School of Medicine and Health Sciences, University for Development Studies, Tamale Campus. Post Office Box 1350. Tamale, Ghana. Vida N. Yakong Lecturer, Department of Allied Health Science,School of Medicine and Health Sciences, University for Development Studies, Tamale Campus. Post Office Box 1350. Tamale, Ghana. Abstract: Background: Studies have shown that health behaviour is a function of socio-demographic variables. This paper examines the effect of some socio-demographic characteristics on health seeking by the use of divination. It explores the statistical correlations between these characteristics and the resort to divination through soothsayers to seek healthcare. Methods: A questionnaire was used to obtain data form 384 adults aged between 18- 60+ years. Data coolected included the socio-demographic characteristics of respondents as well as their responses as to whether or not they resort to divination in an attempt to solve health problems they encounter. Analysis was done using descriptive statistics with the aid of frequencies and cross-tabulations. Chisquare analysis was used to determine the association between each of the socio-demographic factors and the dependent variable (whether or not they use divination in health seeking). Logistic regression was then used to estimate the effects of the socio-demographic characteristics on whether or not one had ever resorted to divination to solve a health problem. Results: Age, sex, marital status, number of children and wives, and educational level of people are strong predictors of the use of divination in health seeking. Conclusion: Polygynous males, with many children, relatively older in age, and with lower educational levels are more likely to resort to divination in health-seeking.

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1. Introduction: 1.1. The Problem Statement: In a milieu in which medical facilities cannot offer sufficient answers to health afflictions, coupled with persistent traditional beliefs and practices with pervasive reverence for ancestors, one would expect attempts by people to solicit in addition to modern medical care, divine interventions to satisfy their health needs. Several authorities have conducted studies on divination (popularly referred to as soothsaying). These studies on divinationincluding those of Fortes & Goody, 1987; Mendonsa, 1974; Mendonsa, 1982; Cardinall, 1969; Nukunya, 2003; Abotchie, 1997; Oppong, 1973 have largely focused on the general functions of divination in society rather than how the practice influences healthcare seeking behaviour. Except for a recent study by Adongo et al (1998) that involved diviners directly on issues specifically related to health seeking, there is paucity of literature on the influence of divination on health seeking behaviour. Also, quite a number of studies have shown that health behaviour is a function of sociodemographic factors, but in such studies health behaviour were studied in relation to issues such as self-reported illness and self-evaluated health status (Bourne, 2009), utilization of the health service such as health programme usage (Dagne, 2010) and usage of herbal drugs by pregnant women (Nordeng & Hawen). Survey of literature seem to suggest paucity of information on how socio-demographic factors influence divination, a practice often resorted to by patients as a means to diagnose the causes of their illnesses (supernatural or natural) before deciding on specific mode of therapy. This paper therefore attempts to augment literature on how socio-demographic characteristics influence this age-old health seeking practice. 1.2. The Study Area: The study was carried out in the Talensi and Nabdam districts in the Upper-East Region of Ghana. The population consists of 50,865 females and 50,014 males with a sex ratio of 50.4:49.6. The total number of houses is 8,839, total households is 16,375 with an average household size of 6; while the number of persons per room occupancy is 4-5. (PHC, 2000).

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There are two predominant indigenous groups of people that inhabit the area namely the Nabdams and the Tallensis, who reside in the Nabdam and Tallensi traditional areas respectively. According to Hunter (1968) the Nabdams call themselves the Namnam (singular, Nabit), call their country Nabrug and their language Nabt . The Tallensis also call themselves Talih (singular Talin). Both the Nabdam and Tallensis belong to a number of ethnic groups speaking very closely related Oti-Volta languages and exhibiting remarkable similarities in their cultural traditions (National Commission on Culture), and also generally belonging to the Mole-Dagbani group of people. Generally they also belong to the Frafra speaking group that comprise the Bolgatanga and Bongo districts, the Tallensi of Tongo traditional area and the Nabdam of the Nangode and Sakote traditional areas. The Tallensis and Nabdams, though of two distinct ethno-linguistic groups, are in most respects a homogenous group with a common culture. Polygyny is generally prevalent where adults may marry more than one wife. The kinship and descent system is patrilineal in which an individual belongs to his father‟s descent group which is made up of persons, male and female, who are descended through the male line only from a common ancestor. In order to increase geographical access and to ensure effective health service delivery and administration, the district has been divided into six administrative sub-districts namely; Tongo Central with the capital at Tongo; Tongo West, with capital Pwalugu; NangodiKongo, capital Nangodi; Sakote-Zolba capital Pelungu; Tongo East, capital Namolgo; and Datoko with Datoko as capital. 1.3. What Is Divination: Rose (2003) defined divination as “the endeavour to obtain information about things future or otherwise removed from ordinary perception, by consulting informants other than human” , and it may be roughly classified into two kinds namely: (a) „automatic‟ divination, in which an omen is looked for and interpreted in its own right, with no thought of appeal to any supernormal power, god, or spirit; and (b) divination proper, which inquires of some sort of deity, generally by means of signs conceived of as being sent by him (p. 775). 1.4. Reasons Why People Consult Diviners: The practice of divination is often shrouded in myth and subjectivity and yet important in as much as it affects the health-seeking behaviour of a people (Azongo, 2014). This had been confirmed by Nukunya, (2003) who commented that the efficacy or otherwise of such beliefs International Journal of Innovative Research and Studies

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in society is not the important issue but the fact of how such beliefs affect people's physical, social and psychological wellbeing. Nukunya (2003) has also indicated that various kinds if divination procedures abound in Ghanaian societies, and explained that the use of divination include „trying to find the causes of sickness, or misfortunes, looking for lost property; what to do to ensure success; and in fact anything for the benefit of the client‟ (p. 62). There are many and varied reasons why people consult diviners. According to Oppong (1973), diviners are consulted upon every conceivable occasion: at succession to office, or undertaking a new enterprise; at birth to find which ancestor is returning; in misfortune to find the cause and sacrificial remedy; at marriage; at death; or after dreams to be able to interpret them. Mendonsa (1982) illustrated the social function of divination among the Sisala of Ghana and showed that the divinatory process performs a “connective function in that it permits wilful individuals to negotiate and to recreate their social order as they attempt to explain misfortune, cure illness and redress impaired social relations”, hence it deals with life crises. This is corroborated in a recent study by Azongo & Adadow (2015) which revealed that diviners play a crucial role in establishing the cause and treatment of diseases, and And that many diseases require the consultation of diviners before any intervention takes place especially diseases whose etiology is embedded in the worldview of the local people Indeed, Mbiti (1969) observed that the African is notoriously religious and that religion permeates into all departments of life so fully that it is not easy or possible always to isolate it. One would expect that this world view of supernatural causation of disease would be very much influenced by the cornucopia of Western religions and lifestyles which tend to frown upon those beliefs; but as noted by Nukunya (2003) in referring to the extent to which the introduction of Christianity influenced the lives of its converts in Ghana, that “their Christian beliefs were superficial and when they felt threatened by difficult situations had recourse to their old beliefs” (p.124). This is consistent with the observations of Mendonsa (1975) while studying the role of divination in the management of misfortune and afflictions among the Sisala of Northern Ghana several decades ago. Mendonsa wrote: “Divination is a powerful mechanism for the release of anxiety in Sisala society. In a society where illness is unchecked by modern medicine; where wells can go dry or water holes dry International Journal of Innovative Research and Studies

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up; where crop success is at the mercy of the elements; divination provides the answers in a world of questions. Even Moslems, Christians and the educated elite find it difficult, indeed, to resist the „concreteness‟ of divination when faced with affliction. More than once I have been sitting with a diviner and had an educated Christian enter the room to consult. In one case I had a conversation the previous week with this Christian about divination in which he passed it off as a mere superstition of „uneducated pagans,‟ yet when faced with the severe illness of his wife, he resorted to the ways of his forefathers.” (p. 10)

2. Methods: 2.1. Study Survey: A community survey was conducted using a questionnaire. The questionnaire was designed to solicit among others, data on the socio-demographic characteristics and responses from the entire community on whether or not divination was used to solve health problems In calculating the sample size for the study the Daniel (1999) formula (recommended by Naing et al (2006) was used because the population was more than 50,000. A sample size of 400 was arrived at. To administer questionnaires a probability sampling technique was necessary in order to obtain a representative and unbiased sample. Therefore every effort was to be made to ensure that each member of the population had an equal chance of being selected. The step-by-step guide for conducting immunization coverage contained in the WHO document Training for Mid-level managers: the EPI Coverage Survey (WHO/EPI/91.10) was adopted and used for sampling the respondents. This method involved a two-stage cluster sampling technique in which a random sample of sub-populations was done followed by the selection of each household to select the individuals. The first stage involved identifying the clusters. To do this the study area was divided into six zones to coincide with the already existing six administrative sub-districts namely; Tongo Central, Tongo West, Nangodi-Kongo, Sakote-zolba, Tongo East and Datoko. Each of these sub-districts was made up of a number of communities which together totalled 21 communities, and therefore these were considered as the clusters. The population of each sub-district was known but those of the individual communities were not known. Each subInternational Journal of Innovative Research and Studies

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district population was divided by the number of communities in it to obtain an average population for each community. In this case it was assumed that communities in each subdistrict had equal populations. In order to systematically select clusters, a sampling interval or unit was calculated by dividing the total population by the number of clusters. By the use of random numbers the clusters were then systematically selected. The second stage involved the selection of houses and the individual respondents. Since the list of houses was not available and there were at least 100 houses in each village and therefore not feasible to list them, the households were selected in the following manner. A point judged to be the central location of the village was located. From this point a simple random method was employed by spinning a bottle on a smooth surface and determining the direction pointed by the opening of the bottle and subsequently choosing the first house in that direction (any ref)?. Then a count of the number of houses which exist along the directional line selected from the central location to the edge of the village was done. After this a random number between 1 and the total number of houses along the directional line selected was used to determine the first house to be selected. On entering the selected house a male and a female adult was selected for the administration of the questionnaires. In choosing subsequent houses it was assumed that the houses were single family dwellings. Therefore the second house visited was the one nearest to the first. The next nearest house was the one whose front door (entrance) was closest to the front door of the house just visited. The procedure was repeated till the total number of houses was obtained in each cluster chosen. In all a total of 210 houses were sampled to select 410 respondents. The sampling format showing the clusters selected, and the number of houses and individuals selected in each cluster is shown in Table 1


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Clusters

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21.

Pwalugu Awaredone Shia Yinduri Tongo Gorogo Yamiriga Namologo Kpatia Duusi Datoku Gare Yogbare Pelungu Zanlerigu Sakote Dagliga Logre Nangodi Dakio Kongo

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Population

Cumulative Population

Population + S.I

Cluster chosen

Number of Houses chosen

Num of respondents chosen

Total popu sub-district

5866 5866 5866 5866 5569 5569 5569 6354 6354 6354 3343 3343 3343 3593 3593 3593 3593 3593 4200 4200 4200

5866 11732 17597 23463 29032 34601 40170 46524 52878 59232 62575 65918 69261 72854 76447 80040 83633 87226 91426 95626 99826

5866 10620 15374 20128 24882 29636 34390 39144 43898 48652 53406 58160 62914 67668 72422 77176 81930 86684 91438 96192 100946

1 2 3 4 5 6, 7 8, 9 10, 11 12 13, 14 15 16 17 18 19 20 21 -

10 10 10 10 10 20 20 20 10 20 10 10 10 10 10 10 10 210

20 20 20 20 20 40 40 40 20 40 20 20 20 20 20 20 20 420

23462

16706

19062

10030

17969

12602

99832

S. I. = Sampling Interval = Total population divided by number of clusters = 4754

Table 1: Cluster identification and sampling format 2.2. Data Analyses: Basic statistical analyses of variables of interest were done by performing tabulations and cross-tabulations. The relevant tabulations yielded frequencies which were used to describe the basic summaries of the variables. The cross tabulations allowed for comparison between variables and so Chi-squares and P-values were obtained for testing the associations between variables. For this study the significance level was 0.05. See Table 2 and Table 3. Logistic regression, the method most commonly used for the analysis of binary outcome variables (Kirkwood & Sterne, 2003) was used to analyse the data as it was obtained from a cross-sectional survey. It was used specifically to address one of the study questions that aimed at determining the extent to which people resort to divination to solve their health problems. To estimate this we made use of a key question in the questionnaire that solicited a categorical dichotomous response from respondents as to whether they utilized divination for the solution of their health problems or not. This response, which was a binary outcome (Yes=1, No=0) constituted the dependent variable. The independent variables (the covariates) were the socio-demographic characteristics – age, sex, marital status, and number of wives possessed by men, number of children, formal education level, religious affiliation, occupation, and income level. Results from the logistic regression were reported as odds International Journal of Innovative Research and Studies

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ratios with corresponding 95% confidence intervals. The odds ratios between two groups was interpreted as the odds of utilising divination for one group divided by the odds of utilising divination for the other group. A test for the overall association of a variable was done using the Wald test. The aim of the analysis was to estimate the effects of these socio-demographic characteristics on the outcome i.e. the dependent variable (whether or not one has ever utilized divination to solve health problems). It was however noted that odds ratios when assumed to be equivalent to relative risks tend to overestimate real effects, because odds ratios approximate relative risk if the outcome of interest i.e. use of divination, is rare. In this study the use of divination was estimated to be high. But rather than using only bivariate analysis, logistic regression enables a fair prediction of whether a person will use divination based on the socio-demographic characteristics The effect of each of these sociodemographic characteristics could also be measured. See Table 4

3. Results: 3.1. Age. The ages of respondents ranged from 18-60+ years out of which 258 were male and 126 females. Age groups ranged from 18-30 to 60+ at 12year intervals. The modal age group was found to be 31-45 years constituting 34.1% of the sample. The use of divination followed a trend: the higher the age the more likely to use divination. However, the last age group 60+ years had a slightly lower proportion (83.1%) using divination than the preceding group. A possible explanation could be because those on the 60+ age are probably too elderly and weaker to be able to visit diviners and would probably delegate to those less elderly adults. Age accounted for2.1 times the odds of using divination. On controlling for the different age strata, those on the 31-45 years old group were found to be 2.9 times more likely to use divination, while those in the 46-60 group were 6.9 more likely to use divination (using the 18-30 years age group as referent. However those on the 60+ age group were 5.4 times more likely to use divination (using same referent). 3.2. Sex: There were a total of258 male and 126 females. Sex accounted for 47% the odds of using divination. Approximately 90% were aware of the practice of diviners in the community. Majority (53.3%) of the total respondents indicated that only 25 % of females consulted diviners, while a further 38% indicated only family or clan heads could consult diviners. Thus divination by women was generally low since family or clan heads were invariably men.


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3.3. Marital Status: Those married constituted about 69.3% of the sample. Being married accounted for 64% odds of using divination while the proportion of those married who used divination was 78.6%. Those not married, i.e. single, the divorced and widows/widowers, were 27%, 14% and 62% respectively less likely to use divination (using the married group as referent). 3.4. Number Of Children: In combining both males and females 21.9% had only one wife while 77.9% had at least two children. However by considering the males alone (since in the cultural context it is men who own children, and not women) 21.7% of the men had only one wife and 78,2% of them had at least two children while the majority of them (28.3%) had more than four children. The trend of use of divination increased with increasing number of children one had. Though number of children a person had accounted for only 14% of the odds of using divination, those with three or more children were 1.2 times more likely to use divination than those with no child at all. 3.5. Education: Though educational level accounted for 60% odds of using divination, the proportion of those using it decreased with increasing levels of education. For example tertiary level education was 14% less likely than those with no education at all.Religion: About 90.4% of those belonging to African Traditional religion indicated they resort to divination in cases of illhealth as compared to Christians (42.0%), Muslims (38.5%) and other religions (40.%) all of which are found to be significant proportionsEven though religious affiliation was significantly associated with the use of divination, Christians and Muslims did not vary in their tendency to use divination. 3.6. Occupation: About 50.0% of the sample were engaged in farming as their major occupation, and 85.8% of then indicated they engage in divination in ill-health all others, including the unemployed had significant proportions engaged in divination. Thus it appeared that no matter the occupation all were equally likely to engage diviners in times of ill-health. 3.7. Income Levels: It was found that income levels per say had no significant correlation with the use of divination in health seeking. However, all respondents belonging to the various income levels had significant and higher proportions engaged in divination for health. **

See Table 2, Table 3 and Table 4below.


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SOCIO-DEMOGRAPHIC

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MALES

FEMALES

CHARACTERISTICS

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TOTAL

TOTAL

FREQ

PERCENTAGE (ROW)

Age 18 30

72 (27.91)

41 (32.52)

113

29.43

31-45

86 (33.33)

45 (35.71)

131

34.11

46-60

63 (24.42)

28 (22.22)

91

23.70

60+

37 (14.34)

12 (9.52)

49

12,76

Total

258

126

384

100

Married

188

78 (61.91)

266

69.27

Single

(72.87)

28 (22.22)

86

22.40

Divorced

58 (22.48)

4 (3.17)

9

2.34

Widowed/widowed

5 (1.94)

16 (12.70)

23

5.99

126

384

100

Marital status

7 (2.71) Total 258 Number of wives (for males) None

58 (22.48)

-

58

22.48

One

145 (56.2)

-

145

56.20

Two

40 (15.50)

-

40

15.50

Three

6 (2.33)

-

6

2.33

Four

6 (2.33)

-

6

2.33

>four

3 (1.16)

-

3

1.16

258

100

Total

258

Number of children none

0 (0.00)

1 (0.79)

1

0.26

One

56 (21.71)

28 (22.22)

84

21.87

Two

48 (18.60)

26 (20.63)

74

19.27

Three

42 (16.28)

21 (16.67)

63

16.41


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Four

39 (15.12)

26 (20.63)

65

16.93

>four

73 (28.29)

24 (19.05)

97

25.26

Total

258

126

384

100

No formal education

130

67 (53.17)

197

51.30

Primary

(50.39)

10 (7.94)

33

8.59

JSS/Mid School

23 (8.91)

22 (17.46)

57

14.84

SSS/GCE/Technical

35 (13.57)

13 (10.32)

37

9.64

Tertiary

24 (9.30)

14 (11.11)

60

15.63

126

384

100

Educational level

46 (17.83) Total 258 Religious affiliation Traditional

173

56 (44.44)

229

59.64

Christian

(67.05)

58 (46.03)

124

32.29

Moslem

66 (25.58)

11 (8.73)

26

6.77

Other

15 (5.81)

1 (0.79)

5

1.30

126

384

100

4 (1.55) Total 258 Occupation Farming

174

37 (29.39)

211

54.95

Housewife

(67.44)

29 (100.00)

29

7.55

Self employed

0 (0.00)

24 (19.05)

49

12.76

Salaried worker

25 (9.69)

19 (15.08)

66

17.19

Unemployed

47 (18.22)

17 (13.49)

29

7.55

126

384

100

49 (38.89)

136

35.42

12 (4.65) Total 258 Annual income Less than Ghc 100

87 (33.72)


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Ghc 100-200

78 (30.27)

43 (34.14)

121

31.51

Ghc 250-500

49 (18.99)

22 (17.46)

71

18.49

More than Ghc 500

44 (17.05)

12 (9.52)

56

14.58

Total

258

126

384

100

Percentage

67.19

32.81

Table 2: Distribution of socio-demographic characteristics of survey respondents by sex

Socio-

Number

Proportion

Chi square

P- value

demographic

Degree

of

freedom

characteristic Age 18 – 30

55

48.67

31 – 45

96

73.28

46 – 60

79

86.81

60+

41

83.67

Sex Male

196

75.97

Female

75

59.52

Marital status Married

209

78.57

Single

43

50.00

Divorced

3

33.33

Widow/widower

16

69.57

Number of wives None

29

50.00

One

116

80.00

Two

36

90.00

Three

6

100.0

Four

6

100.0

>four

3

100.0

Number

of

42.17

0.000

3

11.02

0.001

1

31.74

0.000

3

31.77

0.000

5

50.64

0.000

5

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0

0

One

36

42.86

Two

51

68.92

Three

46

73.02

Four

54

83.08

>four

84

86.60

Educational level No education

168

85.28

Primary

25

75.76

JSS/Mid.

32

56.14

SSS/GCE/Technical 19

51.35

Tertiary

45.00

27

Religious

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52.14

0.000

4

107.44

0.000

3

55.76

0.000

4

3.50

0.320

3

affiliation Traditional

207

90.39

Christian

52

41.94

Muslim

10

38.46

Other

2

40.00

Occupation Farming

181

85.78

Housewife

18

62.07

Self-employed

28

57.14

Salaried

30

45.45

unemployed

14

48.28

Income level < 100

103

75.74

101 – 200

80

66.12

201 – 500

51

71.83

500+

37

66.07

Table 3: Proportions of respondents who use divination for health


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Logistic

demographic

(without Interaction)

interaction)

Characteristics

OR

OR

P-

regression Logistic

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C.I

value 2.12

Age

0.000

18 – 30

regression

P-

(with Wald Test

C.I.

value 1.62

–

2.76

0.000 Ref

31 – 45

2.90

0.000

1.70 – 4.94

46 – 60

6.94

0.000

3.41 – 14.13

60+

5.40

0.000

2.33 – 12.55

0.47

Sex

0.001

Male

0.29

–

0.73

0.001 Ref

Female

0.47 0.64

Marital status

0.001

Married

0.50

0.000

0.29 – 0.73

–

0.83

0.000 Ref

Single

0.27

0.000

0.16 – 0.45

Divorced

0.14

0.006

0.03 – 0.56

Widow/widower

0.62

0.322

0.24 – 1.59

Number of wives

3.52

0.000

None

2.12

–

5.85

0.000 Ref

One

4.00

0.000

2.08 – 7.71

Two or more

9.00

0.000

2.83 – 28.54

Number

of 0.14

0.000

1.45

–

2.02

children

𝑷 > 𝛘𝟐

0.000 Ref

None

0.12

0.000

0.06 – 0.24

One

0.34

0.006

0.16 – 0.74

Two

1.18

0.034

0.19 – 0.94

Three or more

Educational level No education Primary

0.60

0.000

0.52 0.69

–

0.000 Ref 0.54


0.173

0.22 – 1.31 Page 188

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JSS/Mid.

0.22

0.000

0.11 – 0.43

SSS/GCE/Technic

0.18

0.000

0.09 – 0.39

al

0.14

0.000

0.07 – 0.27

Tertiary Religious

0.19

0.000

0.13

–

0.28

affiliation

0.000 Ref

Traditional

0.08

0.000

0.04 – 0.14

Christian

0.07

0.000

0.03 – 0.16

Muslim

0.07

0.005

0.01 - 0.45

Other Occupation Farming

0.57

0.000

0.49 0.67

–

0.000 Ref

Housewife

0.27

0.000

0.12 – 0.63

Self-employed

0.22

0.000

0.11 – 0.44

Salaried

0.14

0.000

0.07 – 0.26

unemployed

0.15

0.000

0.07 – 0.35

Table 4: Logistic regression of socio-demographic characteristics on use of divination OR = Odds Ratio, CI = Confidence Intervals

4. Discussion: The sample selected were aged between18-60+. This was with the assumption (based on common known knowledge) that children do not usually consult diviners. This assumption was confirmed as statistical analysis of the proportions of the various age groups that use divination indicated that the patronage of divination increases with increasing age; thus the older generations are more engaged in the practice than the younger ones. These findings are consistent with customary and cultural practice that pertain in the area that in matters regarding critical decision-making the older generations have more power as household headship and clan headship is normally associated with the more elderly. The decision for the inclusion of women in the survey was quite challenging. Initial community entry discussions and observations, as well as a rapid assessment of pre-test of the questionnaires suggested the exclusion of women from the study. Reasons were that it was not a normal practice of women to consult diviners in the area, thus making this practice a gendered issue. However it was thought wise to recruit women since it was not against any traditional norm to interview women about their beliefs in divination. Interestingly results of International Journal of Innovative Research and Studies

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the study vindicated Ngom et al (2003) assertion thatin a patriarchal society (like this) one would expect that women and children voices to be heard only through the sanctioned hierarchy of communication. Gaining permission to seek health care from a gate keeper – either husband or compound head – was an accepted cultural norm. In such a polygynous society the desire of almost every male adult to have children, and more especially to have male children, makes marriage a very important social obligation. However, the presence of a spouse brings more responsibility to the man as he has to take care of the wife as well as the children. It is therefore not surprising that married persons are 64% more likely to patronise divination than those not married, since in this areaconsulting diviners constitutes an important responsibility towards the health of the family. We posit that the number of wives possessed by a man invariably imposes more responsibility as more wives could also bring along more children. Thus the men with more wives would consult diviners more especially as they have to consult on behalf of their children and wives. This is consistent with the above analysis on spousal status It is interesting to note that while the overall community patronage for divination is as high as 71%, those with formal education are 60% less likely to patronise divination. It therefore appears that the use of divination for health is predominantly a practice of low-education level persons who are traditional religious believers. Plausible explanations of this lie the fact that higher educated persons tend to be Christians who preach against the use of supernatural means of dealing with human afflictions. Also, higher educational levels are associated with the use of Westernised (biomedical) means of dealing with problems. Results of the current study also indicate that, age, sex, marital status, number of wives and children that a man has, educational level and religious affiliation, are significant predictors of the use of divination in health-seeking. This means that generally, the aged non-educated polygynous males who are traditional believers have higher odds of using divination for health. This has implications for clinical care of patients, particularly the non-literate aged males who believe in traditional religion. In clinical medical care situations providing comprehensive care for such patients, and indeed for all patients, would therefore require cultural competence skills from medical staff that would enable them provide care that is effective, understandable and respectful in a manner compatible with the patient‟s cultural health beliefs and practices. It is also worth noting that patients do not necessarily leave behind their cultural believes when attending hospital and this can have implications for health care seeking and healing


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Results indicated that 90.4% of traditional religion believers use divination as compared to Christians (42%) and Muslims and other religion believers (42% and (38.5% respectively). Even though religious affiliation was significantly associated with the use of divination, Christians and Muslims and other believers did not vary significantly in their tendency to use divination. Indeed, Mbiti (1969) observed that the African is notoriously religious and that religion permeates into all departments of life so fully that it is not easy or possible always to isolate it.

5. Conclusions/Recommendations: The results indicate that there is a high tendency for people to resort to divination as a means of tackling their health problems, and that this tendency increases with age, number of wives and children one possessed and decreases with higher formal educational level attained. Thus uneducated polygynous adults who have more children tend to utilize divination for health. The belief in supernatural and spiritual causes and consequences of ill-health is a widespread phenomenon that cannot be explained away with modern scientific knowledge and theories. In as much as people would believe in supernatural causes, they would always seek supernatural means of treatment. Compliance to treatment regime is of paramount importance especially in the clinical care of patients. It is therefore recommended that in offering health care services to people especially the uneducated adult males, modern medical practitioners should be mindful of the fact that while receiving medical care these people would also not only receive other treatment emanating from the prescriptions of diviners, but would if not hospitalized but their family members, consult diviners and clandestinely administer prescriptions emanating from such consultations.


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14. Ngom, P., Debpuur, C., Akweongo, P., Adongo, P., & , F. N. (2003). Gate keeping and women‟s health seeking behaviour in Navrongo, Northern Ghana. African, Journal of Reproductive Health. 7(1), 17–26. 15. Nordeng, H., & Havnen, G. (2005). Impact of Socio-demographic factors, knowledge and attitude on the use of herbal drugs in pregnancy. Acta obstetrica et gynecologica, 84(1): 26-33. 16. Nukunya, G. (2003). Tradition and Change in Ghana: An Introduction to Sociology (2nd Edition ed.). Accra: Ghana Universities Press. 17. Oppong, C., (1973). Growing up in Dagbon. Accra, Tema. Ghana Publishing Corporation. 18. Population and Housing Census of Ghana, 2000. 19. Rose, H. J. (1994, 2003). Divination (Introductory and Primitive). In J. H. Selbie, Encyclopaedia of Religion and Ethics (pp. 775-780). London, New York: T & T Clark. 20. TNDA (2005). Talensi-Nabdam District Assembly annual action plan. Tongo, Ghana:


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