Abstract
Background:
Contraceptive use remains low to moderate in most African countries. Ideation or the ideas and views that people hold has been advanced as a possible explanation for differences in contraceptive use within and across countries.
Objectives:
In this paper, we sought to identify the relevant dimensions of ideation and assessed how these dimensions relate to contraceptive use intentions in two illustrative countries – Kenya and Nigeria.
Methods:
Using factor analysis, we first identified the relevant dimensions of ideation from a set of cognitive, emotional and social interactions items. Subsequently, we examined the relationships of these dimensions with intention to use contraceptives.
Results:
The data revealed four dimensions of contraceptive ideation in both countries: perceived self-efficacy, myths and rumors related to contraceptives, social interactions and influence, and contraceptive awareness. All four dimensions of ideation are strongly associated with contraceptive use intention in Nigeria. Both perceived self-efficacy and myths and rumors dimensions were significantly associated with contraceptive use intention in Kenya. In contrast, social interaction dimension and contraceptive awareness were not strongly associated with intention in Kenya.
Conclusion:
The ideation model is relevant for contraceptive use research and programing. Programs seeking to increase contraceptive use and help women to attain their desired family size should promote contraceptive self-efficacy and identify ways to correct prevailing myths and rumors.
Keywords: Ideation, contraceptive use, contraceptive intention, urban women, Kenya, Nigeria
1. Introduction
Contraceptive use is a key factor in preventing unwanted pregnancies, reducing maternal and child mortality, and improving the lives of women and their families (Kavanaugh and Anderson 2013; Sonfield et al. 2013; Tsui, McDonald-Mosley and Burke 2010). A recent study estimated that contraceptive use could avert more than two fifths of maternal deaths (Ahmed et al. 2012). Increased access to contraceptive services has been established as a cost-effective strategy for countries to reduce maternal and child mortality (Moreland and Talbird 2006). The benefits of contraceptive use go beyond the health sector. Providing unrestricted access to contraceptives will help ensure a reduction in unwanted pregnancies and thereby contribute to increased female education, women’s empowerment, poverty reduction, and even environmental sustainability (Moreland and Talbird 2006; Smith et al. 2009; Sonfield et al. 2013).
Regrettably, levels of contraceptive use remain low in many African countries, unintended pregnancies are common, and unmet need is high. In Nigeria, for example, the results of the 2013 Demographic and Health Survey indicate that only 15.1% of married women were using any contraceptive method, while only 9.8% were using a modern method (NPC/ICF 2014). These numbers have not changed meaningfully since 2003 (NPC/ICF 2009). Partly as a result of low contraceptive use, in 2013, fertility remains high in Nigeria at 5.5 children per women, on average. Underlying the low contraceptive use and high fertility rate in Nigeria are fertility preferences that favor a large family size. Only 19% of currently married women desired no more children while 33% desired another child within the next two years (NPC/ICF 2014). Furthermore, the mean ideal family size was 7.1 children per women while unmet need stood at 16% among currently married women. Thus, it appears that in Nigeria, the problem has more to do with desires for high fertility than with unmet need. Kenya’s reproductive health context is different from the situation in Nigeria. The total fertility rate was 4.6 children per woman in 2008 (KNBS/ICF 2008). In 2008, 39% of married Kenyan women were using modern contraceptive methods, a noticeable increase from 32% in 2003 (KNBS/ICF 2008). In addition, in 2008, 49% of married women in Kenya desired no more children while 27% would want to wait at least two years for another child (KNBS/ICF 2008). The mean ideal number of children among married women in Kenya, 4.0 children per woman, was lower than the actual fertility rate while 26% had an unmet need for family planning. In other words, compared with Nigeria, the problem in Kenya has more to do with unmet need than with continued desire for high fertility.
In this paper, we examine differences and commonalities in the determinants of contraceptive use intentions in these two contexts with a special focus on ideational variables. Ideation can be defined as “views and ideas that people hold individually” (van de Kaa 1996: 423). These views and ideas reflect ways of thinking of individuals; the media and social interactions contribute to shaping these views and ideas (Kincaid 2000a). The suggestion that ideational change or changes in the way people think is a key factor in fertility decline is not new; more than a century ago, Leroy-Beaulieu attributed fertility decline to changing moral values (Leroy-Beaulieu 1896). Nonetheless, it was not until the 1980’s that ideational change gained prominence in demographic literature as an explanation for fertility decline and to nuance the classical demographic transition theory (Bongaarts and Watkins 1996; Cleland 1985; Cleland and Wilson 1987; Lesthaeghe 1983; Lesthaeghe and Surkyn 1988; van de Kaa 1996). Some studies have posited ideational change to be a key factor in the second demographic transition in Europe (van de Kaa 2002; Lesthaeghe 2010; Sobotka, Zeman and Kantorova 2003) and in recent fertility declines in some less industrialized countries (e.g., Abbasi-Shavazi, McDonald and Hosseini-Chavoshi 2009 for Iran).
We draw on a model proposed by Lawrence Kincaid linking individual ideation with behavior: the Ideation Model of Strategic Communication and Behavior Change (Figure 1; Kincaid 2000a). Kincaid (2000a) pointed out that the inferences made by demographers on the role of ideation in fertility decline have been indirect and have mostly relied on spatial patterns of fertility decline. To correct for this weakness, he proposed an ideational model that can be measured and tested at the individual level by elucidating the psychological and social interaction pathways of behavior change. Such a conceptualization broadens understanding of the micro-level decision-making processes that affect contraceptive use behaviors and facilitate fertility change (Kincaid 2000a). Kincaid posits that ideation is an intermediate construct between behavior and contextual factors. He argues that ideation comprises three domains: cognitive, emotional and elements of social interactions. The cognitive dimension includes the following psychosocial concepts: attitudes, knowledge, perceived risk, subjective norms and self-image. The emotional domain includes preferences and self-efficacy. Lastly, the social elements of ideation include social support, social influence, interpersonal communication (e.g., spousal communication) and personal advocacy (Babalola and Kincaid 2009; Kincaid 2000a, 2000b). Individually, these ideational variables have been widely recognized to influence behaviors and are key components of several behavior change models (Fishbein et al. 2001).
Research has shown that, on their own, these ideational elements affect contraceptive intention and use. For example, several studies have found a strong link between spousal communication and increased contraceptive use (Agha and Van Rossem 2002; Gayen and Raeside 2010; Link 2011; Tumlinson et al. 2013). Some studies have also found a positive and strong link between personal or perceived spousal approval of family planning and use of contraceptive methods (Kaggwa, Diop and Storey 2008; Rahayu, Utomo and McDonald 2009; Samandari, Speizer, and O’Connell 2010; Teye 2013). Moreover, research has shown that perceived normative support and perceived peer behavior are strong determinants of intention to use and actual use of contraceptives (Gayen, and Raeside 2010; Ryan, Franzetta and Manlove 2007; Samandari, Speizer, and O’Connell 2010). Other studies have found that positive attitudes towards contraception increase the likelihood of using a method (Bryant 2009; Khumsaen and Gary 2009; Potard et al 2012). In contrast, negative attitudes such as fear of side effects or perceived disadvantages of contraceptive use have been linked with lack of intention to use and lower use (Bajwa et al. 2012; Bosompra 2001). A high level of perceived self-efficacy (or confidence in one’s ability to act) for contraceptive use has been positively associated with intention to use, increased likelihood of contraceptive adoption, and sustained use (Agha 2010; Bogale, Boer and Seydel 2010; Khumsaen and Gary 2009; Ryan, Franzetta and Manlove 2007; Taffa et al. 2002). In analyses that have created an index of ideation, it has been found that higher levels of ideation have been shown to be associated with increased contraceptive use in the literature (Amouzou and Becker 2009; Babalola and Vondrasek 2005; Kincaid 2000a, b).
2. Objectives
With the theoretical background described above in mind and using Kenya and Nigeria as illustrative countries, the objectives of this paper are twofold. First, we will identify the relevant dimensions of contraceptive ideation in urban Kenya and Nigeria to determine similarities and differences in these two contexts. Second, we will explore the association of the identified dimensions of ideation with intention to use contraceptives among married or in union women in these settings. Two reasons informed the decision to focus on contraceptive intention. First, intention has been posited in many theories of behavior change as the most proximate determinant of actual behavior (e.g., Fishbein et al. 2001). Also, many studies have found intention to be a very strong determinant of behavior (Curtis and Westoff 1996; Bankole and Westoff 1998; Roy et al. 2003). Second, in the absence of longitudinal data, the focus on the association of ideation with intention to use as opposed to actual contraceptive use allows us to better address possible reverse causality inherent in cross-sectional data. Ideation relates to people’s perceptions now, whereas behavioral intentions relate to how people see themselves in the future. It is therefore reasonable to argue that ideation affects contraceptive intentions rather than the other way around.
3. Methods
3.1. Participants
The results presented in this manuscript are based on cross-sectional household surveys conducted by the Measurement, Learning & Evaluation project as part of a comprehensive strategy to evaluate the effects of the Nigeria Urban Reproductive Health Initiative (NURHI) and the Tupange, the Urban Reproductive Health Project in Kenya. Funded by the Bill & Melinda Gates Foundation, both NURHI and Tupange seek to generate demand for family planning services and increase the contraceptive prevalence rate in selected cities with a special focus on the urban poor. The data analyzed were derived from the 2010 baseline surveys that targeted women aged 15 – 49 years in six large cities in Nigeria (Abuja, Benin City, Ibadan, Ilorin, Kaduna, and Zaria), and in five cities in Kenya (Nairobi, Kisumu, Mombasa, Kakamega, and Machakos). Survey participants included 16,144 respondents in Nigeria and 8,932 in Kenya. A two-stage sample selection process was used to select the participants. First, fieldworkers selected clusters in each survey city, with the number selected proportional to the size of the city. All households and dwelling units within the selected clusters were listed and a random sample of 41 households (Nigeria) or 30 households (Kenya) was selected for the women’s interview. The women’s questionnaire was administered to all eligible women (ages 15–49) in the selected households who consented to be interviewed. We limited the analyses to women married or in union who reported awareness of at least one contraceptive method and were not currently using a modern contraceptive method. This consisted of a sample of 2362 women in Kenya and 7235 women in Nigeria.
3.2. Variables
The key dependent variable assessed in this study is reported intention to use a modern contraceptive method within 12 months of the survey. The key independent variables were dimensions of contraceptive ideation derived from thirty-four ideational items measured similarly in each of the two study countries. The items included awareness (spontaneous or probed) of various modern methods of contraception ranging from sterilization to emergency contraception (9 items; used as proxy for knowledge and classified under the cognitive dimension of ideation). The items also included a set of eight items that measured myths and rumors about contraceptives using Likert-scale questions that assessed the respondents’ level of disagreement with statements such as “who use contraception end up with health problems” (attitudes; classified under the cognitive dimension of ideation). The individual items were coded such that higher scores reflect rejection of myths and rumors. Perceived self-efficacy to take action regarding contraceptive use consisted of seven items measured on a Likert-scale that assessed the respondent’s confidence in their ability to take specific actions, including start a conversation on family planning with their partner and obtain a method if they decided to use (emotional dimension of ideation). In addition, we also measured spousal communication about family size (1 item; social interaction dimension of ideation), discussion of FP with significant others, including mother, mother-in-law, sister-in-law, and religious leader (4 items; social interaction dimension of ideation) and perceived approval of significant others for the respondent’s use of contraceptives (5 items; social interaction dimension of ideation). In preliminary factor analysis models, we had included other variables but the final model only retained the variables that loaded significantly on any factor in either of the two study countries.
In addition to ideation, we controlled for education level, age, square of age, parity, city of residence, religion, religiosity, husband’s education, age gap between spouses, women’s autonomy measured as whether or not the woman needed permission from the husband or anyone else before using contraceptives (this potential ideational item did not load on any ideational factor in either of the two study countries so is only included as a control variable), prior use of contraceptives, and household wealth. Summary statistics for these variables can be found in Table 1.
Table 1:
Kenya (n=2049) | Nigeria (n=6265) | |
---|---|---|
Education Level | ||
None | 5.2 | 17.2 |
Primary | 46.6 | 20.6 |
Secondary | 35.4 | 41.1 |
Post-secondary | 12.8 | 21.1 |
Current age in years | 29.4 | 32.4 |
Parity | 2.0 | 3.4 |
City of residence | n/a | |
Nairobi | 65.2 | |
Mombasa | 25.9 | |
Kisumu | 5.9 | |
Machakos | 1.2 | |
Kakamega | 1.8 | |
City of residence | n/a | |
Abuja | 11.8 | |
Benin City | 11.5 | |
Ibadan | 20.2 | |
Ilorin | 17.2 | |
Kaduna | 20.8 | |
Zaria | 18.5 | |
Religion | ||
Non-Muslim | 86.2 | 43.6 |
Moslem | 13.8 | 56.4 |
Religiosity | ||
Not very religious | 36.7 | 24.3 |
Very religious | 63.3 | 75.7 |
Husband’s education | ||
None | 2.1 | 11.8 |
Primary | 27.0 | 15.4 |
Secondary | 57.1 | 39.5 |
Post-secondary | 19.8 | 33.3 |
Age gap between spouses in years | 5.7 | 9.3 |
Fertility desires | ||
Desire an additional child | 65.7 | 75.6 |
Does not desire additional child | 34.3 | 24.4 |
Prior use of contraceptives | ||
No | ||
Yes | ||
Woman’s autonomy | ||
Does not need permission for FP | 53.7 | 21.0 |
Needs permission for FP | 46.3 | 79.0 |
Household wealth quintile | ||
Lowest | 21.3 | 19.5 |
Second | 20.0 | 21.1 |
Middle | 20.9 | 21.2 |
Fourth | 21.5 | 19.9 |
Highest | 16.3 | 18.3 |
Notes: n/a= Not applicable
3.3. Analysis
We employed two analytic methods in this study. First, we used factor analysis to determine the relevant dimensions of ideation. We relied on scree plots and the interpretability of the factors to determine the appropriate number of factors. Following Hair et al. (1998: p 112) and considering our large sample sizes, we chose a cut-off point of 0.30 for factor loadings to determine the significance of items for each factor. We scored the respondents on each of the derived orthogonal factors.
Second, we used the derived factor scores as a continuous variable along with other independent variables in multivariable logistic regression models to predict contraceptive use intention. We estimated two models for each country: one that included only the socio-demographic and household variables (Model 1), and the second that included the independent variables from Model 1 as well as dimensions of ideation (Model 2). We reported the odds ratio associated with each correlate (Models 1 and 2) and the X-standardized beta coefficients to enable us to see the relative importance of the independent variables (Model 2 only). All results adjust for the complex sampling design and use weights to adjust for non-response and sample selection.
3.4. Hypotheses Tested
The two hypotheses tested in this manuscript include the following:
The socio-demographic and household variables that are associated with contraceptive intention differ between Kenya and Nigeria; and
All the dimensions of ideation are significant predictors of contraceptive intention in both Kenya and Nigeria.
4. Findings
Table 1 presents the socio-demographic characteristics of the study population: married women not currently using a contraceptive method with awareness of at least one contraceptive method. In Kenya, the mean age of the women is 29.4 years. About half of the women have post-primary education, while most reside in Nairobi city, are non-Muslim, and are very religious. A little over one third of the women desire no more children. The mean age gap between these women and their husbands is 5.7 years and many of these husbands (70.9%) have post-primary education. Less than half of the women reported needing permission before using family planning.
In Nigeria, the mean age is 32.4 years. Very few women reside in the capital city. Many of the women have post-primary education, are Muslim, and are very religious. About three-quarters of the women desire to have an additional child at some point in the future. The mean spousal age gap is 9.3 years and 72.8% of the husbands have post-primary education. About four-fifths of the women need permission before using family planning.
4.1. Dimensions of ideation
4.1.1. Kenya
Results of the scree plot suggested that a four-factor solution was ideal. One item (discussion of number of children with spouse) did not load significantly on any of the four factors (Table 2). Nonetheless, the four factors explained 91.5% of the variance in the data.
Table 2:
Kenya | Nigeria | ||
---|---|---|---|
Factor 1: Perceived self-efficacy (Variance explained=34.4%) | Factor 1: Perceived self-efficacy (Variance explained=37.0%) | ||
Perceived self-efficacy for starting a conversation with partner about FP | 0.698 | Perceived self-efficacy for starting a conversation with partner about FP | 0.804 |
Perceived self-efficacy for convincing partner that they should use a FP method | 0.723 | Perceived self-efficacy for convincing partner that they should use a FP method | 0.814 |
Perceived self-efficacy for obtaining a FP method if decided to use one | 0.803 | Perceived self-efficacy for obtaining a FP method if decided to use one | 0.799 |
Perceived self-efficacy for using a FP method even if partner doesn’t want you to | 0.448 | Perceived self-efficacy for using a FP method even if partner doesn’t want her to | 0.492 |
Perceived self-efficacy for using a FP method even if no friend or neighbor uses | 0.729 | Perceived self-efficacy for using a FP method even if no friend or neighbor uses | 0.739 |
Perceived self-efficacy for using a FP method even if religious leader did not think she should | 0.680 | Perceived self-efficacy for using a FP method even if religious leader did not think she should | 0.621 |
Perceived self-efficacy for getting to a place where contraceptives are provided if needed | 0.754 | Perceived self-efficacy for getting to a place where contraceptives are provided if needed | 0.835 |
Ever discussed number of children with spouse | 0.349 | ||
Factor 2: Myths and rumors (Variance explained=24.4%) | Factor 2: Myths and rumors (Variance explained=25.9%) | ||
Level of disagreement that use of contraceptive injection can make a woman sterile | 0.566 | Disagreed that use of contraceptive injection can make a woman sterile | 0.672 |
Level of disagreement that people who use contraception end up with health problems | 0.699 | Disagreed that people who use contraception end up with health problems | 0.696 |
Level of disagreement that contraceptives can harm your womb | 0.703 | Disagreed that contraceptives can harm your womb | 0.749 |
Level of disagreement that contraceptives reduce women’s sexual urge | 0.446 | Disagreed that contraceptives reduce women’s sexual urge | 0.564 |
Level of disagreement that contraceptives can cause cancer | 0.615 | Disagreed that contraceptives can cause cancer | 0.668 |
Level of disagreement that contraceptives can give you deformed babies | 0.656 | Disagreed that contraceptives can give you deformed babies | 0.697 |
Level of disagreement that contraceptives are dangerous to your health | 0.737 | Disagreed that contraceptives are dangerous to your health | 0.683 |
Level of disagreement that women who use FP may become promiscuous | 0.318 | Disagreed that women who use FP may become promiscuous | 0.443 |
Factor 3: Social interactions and influence (Variance explained= 14.8%) | Factor 3: Social interactions and influence Variance explained=l 6.0%) | ||
Discussed FP with mother | 0.391 | Discussed FP with mother | 0.359 |
Discussed FP with mother-in-law | 0.404 | Discussed FP with mother-in-law | 0.368 |
Discussed FP with sister-in-law | 0.458 | Discussed FP with sister-in-law | 0.379 |
Discussed FP with religious leader | 0.334 | Discussed FP with religious leader | 0.304 |
Perceived that mother would support her use of contraceptives | 0.522 | Perceived that mother would support her use of contraceptives | 0.541 |
Perceived that mother-in-law would support her use of contraceptives | 0.652 | Perceived that mother-in-law would support her use of contraceptives | 0.665 |
Perceived that sister-in-law would support her use of contraceptives | 0.615 | Perceived that sister-in-law would support her use of contraceptives | 0.618 |
Perceived that father-in-law would support her use of contraceptives | 0.436 | Perceived that father-in-law would support her use of contraceptives | 0.527 |
Perceived that religious leader would support her use of contraceptives | 0.484 | Perceived that religious leader would support her use of contraceptives | 0.554 |
Factor 4: Contraceptive awareness (Variance explained= 14.0%) | Factor 4: Contraceptive awareness (Variance explained=13.9%) | ||
Aware of female sterilization | 0.606 | Aware of female sterilization | 0.535 |
Aware of male sterilization | 0.581 | Aware of male sterilization | 0.567 |
Aware of oral pill | 0.413 | Aware of oral pill | 0.444 |
Aware of IUD | 0.579 | Aware of IUD | 0.510 |
Aware of implants | 0.354 | Aware of injectables | 0.426 |
Aware of injectables | 0.559 | Aware of implants | 0.531 |
Aware of female condoms | 0.406 | Aware of female condoms | 0.472 |
Aware of LAM | 0.311 | Aware of LAM | 0.410 |
Aware of emergency contraception | 0.364 | Aware of emergency contraceptives | 0.422 |
Not significantly related to any factor: 1. Ever discussed number of children with spouse |
The first factor measured perceived self-efficacy to take actions in favor of contraceptive use under specific conditions (see Table 2). The seven items that loaded most significantly on this factor had a Cronbach’s alpha score of 0.866. The second factor represented myths and rumors about contraceptives. The eight items that loaded most significantly on this factor were related to beliefs about the dangerous health and social consequences of contraceptives on the woman and her unborn child. These eight items had a Cronbach’s alpha score of 0.813. The third factor reflected social interactions and social influence; nine items related to discussion of FP with significant others and their perceived support of the respondent’s use of contraceptives loaded most significantly on this factor. The Cronbach’s alpha for these nine variables was 0.730. The nine items that loaded most significantly on the fourth factor measured awareness about specific contraceptive methods. These items had a Cronbach’s alpha of 0.728.
4.1.2. Nigeria
Based on the scree plot and for interpretability of the results, we determined that a four-factor solution was ideal. Each of the 34 items loaded significantly on one of the four factors. As we observed for Kenya, the first factor measured perceived self-efficacy for taking actions in favor of contraceptive use. Curiously, discussion of the number of children also loaded significantly on this factor. This first factor explained 37.0% of the variance in the data. The eight items that load significantly on this factor had a Cronbach alpha of 0.874. The second factor was related to myths and rumors about contraceptives. The proportion of the variance explained by this factor was 25.9%. Eight factors loaded most significantly on this factor; the Cronbach’s alpha was 0.852. The third factor can be labeled social interactions and social influence; it explained 16.0% of the variance in the data. The nine items that loaded most significantly on this factor had a Cronbach’s alpha of 0.732. The fourth factor measured aspects of contraceptive awareness and explained 13.9% of the variance in the data; nine items loaded significantly on this factor with a Cronbach’s alpha of 0.738.
4.2. Association of dimensions of ideation with intention to use contraceptive
4.2.1. Kenya
Among the women in the sample that are not currently using a contraceptive method, 27.7% (95% CI: 23.6%, 31.8%) reported an intention to use a modern method in the next 12 months. Intention to use a modern method varied between 18.1% in Mombasa and 36.7% in Kisumu (Table not shown).
The results of Model 1 (Table 3) reveal a positive relationship with parity such that every additional child increases the odds of contraceptive use intention by 21%. Compared to the women resident in Nairobi, the women from Kakamega are 59% more likely to report intention to use. The results of this model further show that the odds of intention to use contraceptives are about 56% lower for Muslims than for non-Muslims. Religiosity, education, prior contraceptive use, household wealth, women’s autonomy, fertility desires, and husband’s education are not significantly related to intention to use contraception.
Table 3:
Variable | Kenya (n=2362) | Nigeria (n=7235) | ||||
---|---|---|---|---|---|---|
Model 1 | Model 2 | Model 1 | Model 2 | |||
OR | OR | Std. β coef. | OR | OR | Std. β coef. | |
Socio-demographic and household variables | ||||||
Education Level | ||||||
None (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Primary | 1.149 | 0.940 | −0.031 | 1.398* | 1.348† | 0.122† |
Secondary | 0.958 | 0.744 | −0.142 | 1.560* | 1.343† | 0.145 |
Post-secondary | 0.832 | 0.584 | −0.179 | 1.611* | 1.114 | 0.043 |
Current age in years | 1.107 | 1.118 | 0.896 | 1 347*** | 1.303*** | 2.080*** |
Square of age | 0.996* | 0.996* | −2.039* | 0 994*** | 0 994*** | −2 999*** |
Parity | 1.213*** | 1.256*** | 0.421*** | 1.169*** | 1.176*** | 0.427*** |
City of residence (Kenya) | ||||||
Nairobi (RC) | 1.00 | 1.00 | 0.00 | |||
Mombasa | 0.732 | 0.766 | −0.117 | |||
Kisumu | 1.118 | 1.088 | −0.020 | |||
Machakos | 1.376 | 1.227 | −0.022 | |||
Kakamega | 1.592* | 1.474* | 0.051* | |||
City of residence (Nigeria) | ||||||
Abuja | 1.00 | 1.00 | 0.00 | |||
Benin City | 1.107 | 1.003 | 0.001 | |||
Ibadan | 0.522*** | 0 517*** | −0.257*** | |||
Ilorin | 0.827 | 0.825 | −0.073 | |||
Kaduna | 0.644† | 0.617* | −0.198* | |||
Zaria | 0.685† | 0.747 | −0.119 | |||
Religion | ||||||
Non-Muslim (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Moslem | 0.442* | 0.466* | −0.263* | 1.275† | 1.682*** | 0.255*** |
Religiosity | ||||||
Not very religious (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Very religious | 0.999 | 0.998 | −0.001 | 0.792† | 0.766* | −0.115* |
Fertility desires | ||||||
Desire an additional child (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Does not desire additional child | 1.307 | 1.197 | 0.085 | 3.248*** | 2.835*** | 0.432*** |
Husband’s education | ||||||
None (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Primary | 1.709 | 1.184 | 0.075 | 1.671* | 1.561* | 0.163** |
Secondary | 1.925 | 1.411 | 0.182 | 1.624* | 1.508† | 0.200* |
Post-secondary | 1.387 | 1.108 | 0.041 | 1.836** | 1.744** | 0.260** |
Age gap between spouses in years | 0.965† | 0.970 | −0.147 | 0.991 | 0.995 | −0.033 |
Woman’s autonomy | ||||||
Does not need permission for FP (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Needs permission for FP | 1.219 | 1.287 | 0.126 | 1.487** | 1.312 | 0.113 |
Prior contraceptive use | ||||||
No (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Yes | 0.808 | 0.678 | −0.175 | 3.085*** | 2.093*** | 0.361*** |
Household wealth quintile | ||||||
Lowest (RC) | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.00 |
Second | 1.391 | 1.474 | 0.155 | 0.843 | 0.801 | −0.091 |
Middle | 1.169 | 1.202 | 0.075 | 0.735* | 0.683* | −0.154* |
Fourth | 0.934 | 0.898 | −0.044 | 0.786 | 0.743† | −0.117† |
Highest | 1.241 | 1.155 | 0.053 | 0.567** | 0.466*** | −0.290*** |
Dimensions of Ideation | ||||||
Self-efficacy dimension | --- | 1.625*** | 0.435*** | --- | 2.278*** | 0 755*** |
Myths and rumors dimension | --- | 1 319*** | 0.253*** | --- | 1.370*** | 0.296*** |
Social interactions and influence dimension | --- | 1.152 | 0.125 | --- | 1.338*** | 0.273*** |
Contraceptive awareness dimension | --- | 0.979 | −0.018 | --- | 1.292*** | 0.221*** |
Notes: RC= Reference Category. --- = Not applicable. Statistical significance:
p<0.1
p<0.05
p<0.01
p<0.01.
The introduction of the dimensions of ideation into the estimated model (Model 2) reveals no noticeable differences in the strength of the relationship of intention with socio-demographic and household variables compared to those of Model 1. The results of Model 2 further show that only two of the four dimensions of ideation are significantly and positively associated with contraceptive use intention: perceived self-efficacy and myths and rumors dimensions. In particular, those with higher self-efficacy are more likely to intend to use a method and those who reject more rumors are also more likely to use than those who accept more rumors. Judging from the standardized beta coefficients, the self-efficacy dimension contributes more to explaining contraceptive use intention than any of the other three dimensions.
4.3.2. Nigeria
Only 9.1% (95% CI: 8.2%, 9.9%) of married or cohabiting women not currently using a modern method reported the intention to do so in the next 12 months. Contraceptive intention varied by city: from 7.5% in Ibadan to 12.2% in Ilorin (Table not shown).
The results of Model 1 (Table 3) indicate a positive albeit non-graduated relationship with education and a strong concave relationship with age. Prior use of contraceptives increased the odds of intention to use more than threefold. Parity was positively associated with intention to use, with each additional child increasing the odds of intention to use by 17%. The odds of intention to use contraception also varied by city of residence. Specifically, the women resident in Ibadan, Kaduna or Zaria were less likely than their counterparts from Abuja to report an intention to use in the next 12 months. Desires for no additional child increased the odds of contraceptive intention more than threefold. The model also revealed a strong positive association with husband’s education and a negative, albeit weak, relationship with religiosity. The relationship with women’s autonomy was not as expected as the women who reported that they needed permission to use contraceptives were more likely than others to report an intention to use contraception. The relationship with household wealth was unexpectedly negative.
With the introduction of ideational factors into the estimated model (see Model 2) the pattern of relationships with most of the socio-demographic and household variables is similar to what we observed in Model 1. However, a few variables become either less significant or non-significant, including education and women’s autonomy. In contrast, being Muslim is now significantly associated with greater intention to use. All four dimensions of ideation are significantly associated with contraceptive use intention. The effects for self-efficacy and myths and rumors are similar to Kenya. We also find that women who have higher scores on the social interactions and influence dimension and women with higher contraceptive awareness are significantly more likely to intend to use than their counterparts with lower scores. A comparison of the standardized beta coefficients revealed that self-efficacy was, by far, the most important dimension of ideation affecting contraceptive use intention in Nigeria.
5. Discussion
Recognizing the role of ideation in contraceptive use and intention to use, this study identified the relevant dimensions of contraceptive ideation in urban areas of Kenya (a country with a moderate level of contraceptive prevalence and considerable unmet need) and Nigeria (a country where contraceptive prevalence and unmet need remain low, and fertility desires are high). We also explored the association of the various dimensions of ideation with contraceptive use intentions. To the best of our knowledge, this is the first study that explicitly examined the dimensionality of ideation in relation to contraceptive use intentions.
In spite of the differences in contraceptive prevalence and reproductive health outcomes between Kenya and Nigeria, there are striking similarities in the dimensions of ideation and in the relationship between ideation and contraceptive use intentions in the two countries. Our findings reveal that ideation is not necessarily a one-dimensional construct. We identified four dimensions of contraceptive ideation in both countries: perceived self-efficacy, myths and rumors related to contraceptives, social interactions and influence, and awareness about contraceptive methods.
There are commonalities and differences in the association of these dimensions of ideation with contraceptive use intention in Kenya and Nigeria. All the four dimensions of ideation turned out to be very strong predictors in Nigeria whereas in Kenya, only the self-efficacy and myths and rumors dimensions were significant. Nonetheless, in both countries, the self-efficacy dimension was by far the most significant ideational predictor of intention to use contraception. The importance of self-efficacy for contraceptive use intention in both countries is consistent with evidence from prior research (Agha 2010; Bogale, Boer and Seydel 2010; Taffa et al. 2002; Khumsaen and Gary 2009; Ryan, Franzetta and Manlove 2007).
This study identified other important correlates of intention to use contraception; some of these correlates are common to both countries whereas others are only relevant for either country. For example, parity is consistently associated with intention to use contraception in both countries. The finding that the odds of contraceptive use intention increase with parity may suggest that women in both countries tend to wait until they have a specific number of children before considering contraception. This relationship is understandable in a context where many people believe that contraceptives may hinder the attainment of future fertility goals.
Nigeria and Kenya differ in some noticeable ways in terms of the key socio-demographic correlates of contraceptive intentions. For example, in Nigeria, after controlling for ideation, age of the woman was a significant, albeit concave, predictor of intention to use contraceptives. In contrast in Kenya, there was no strong relationship between age and contraceptive intention. In other words, in Nigeria where contraceptive use is generally low and desires for large family sizes widespread, the non-contracepting women most likely to intend to use a method are those in the middle childbearing ages. In contrast, in Kenya where contraceptive prevalence is much higher but with a relatively high level of unmet need, intention to use a method no longer appears to be so much a function of the woman’s age. Another striking difference between Nigeria and Kenya has to do with the role of fertility desires. In Nigeria, women who do not want any(more) children were significantly more likely to intend to use than women wanting more children; this relationship was absent in Kenya. In addition, Kenya and Nigeria differ regarding the significance of husband/partner’s education. This variable is a strong predictor in Nigeria but is not associated with the outcome in Kenya. Contrary to evidence from some prior studies, this study did not a strong association between education of the woman and contraceptive use intention in Kenya or Nigeria after controlling for ideation (Meskele and Mekonnen 2014; Dibaba 2009; Adegbola and Okunowo 2007). Whereas the lack of a significant association between education and intention to use contraception is unexpected, it is consistent with what a few studies have found (Agha 2010; Gebremariam and Addissie 2014).
Prior studies have documented the positive association between women’s decision-making autonomy and contraceptive use or intention (Callahan and Becker 2012; Hogan, Berhanu and Hailemariam 1999; Saleem and Bobak 2005). In general, these studies have found that greater decision-making autonomy is associated with higher odds of contraceptive use and intention. In contrast to these studies, there is no evidence of a strong relationship between women’s autonomy and contraceptive use intention in Kenya. In Nigeria, the surprising positive relationship between lack of autonomy and intention to use contraceptive disappeared after controlling for ideation. The reason for this finding is unclear although it is possible that any relationship between women’s autonomy and contraceptive intentions operates through its (women’s autonomy) link with ideation.
Findings from this study have implications for family planning promotional efforts. The important role of ideation in contraceptive use intention identified in this study indicates that an ideation framework is relevant in developing strategies for generating demand for family planning services and increasing contraceptive prevalence. More specifically and in relation to the two study countries, communication programs should focus on increasing self-efficacy for contraceptive use and addressing prevailing myths and rumors that hinder the uptake of contraceptives. The literature on self-efficacy is rich with suggestions for strengthening this construct. Bandura (1977) specified four channels through which self-efficacy can be learned and strengthened: (1) successful performance of the behavior (enactive source); (2) modeling or vicarious experience (vicarious source); (3) persuasion or encouragement from others (exhortative source); and (4) emotional arousal (emotive source). Substantively, consistent with the enactive source of self-efficacy, strategies for strengthening self-efficacy for contraceptive use should include encouraging clients to use contraceptives for the first time and develop mastery of the practice. In this respect, it is critical to identify and address psychological, logistic and structural barriers to contraceptive access. Also, based on the self-efficacy items explored in this study, it is important to provide opportunities for women to learn and practice how to communicate with their spouses on contraceptive use. In line with the vicarious source of self-efficacy, relevant strategies should include opportunities for the audience to learn from a satisfied contraceptive user similar in other respects to the non-using audience. According to Bandura, observing relevant behaviors in others allows one to form “a conception of how new behavior patterns are performed, and on later occasions the symbolic construction serves as a guide for action” (Bandura 1977: 192). Modeling relevant behaviors can be implemented in small groups or through the mass media. Strategies reflecting the exhortative source of self-efficacy could include promoting discussion about contraceptive use with significant others and encouraging personal advocacy in favor of contraceptive use among the intended audience. Finally, consistent with the emotive source of self-efficacy, programs should include strategies for reducing audience anxiety about contraceptives by addressing fears and misconceptions.
The need for addressing fears and misinformation about contraceptives is further supported by our study finding that the myths and rumors dimension of ideation is a very strong predictor of contraceptive use intention in both countries. Effectively correcting myths and rumors about contraceptives will require strategically designed messages that provide factual information on contraceptives and debunk rumors. The mass media can be used to convey such messages. However, it is important to include the use of small group interventions that allow participants to discuss the prevailing myths about contraceptives in their community and critically examine their personal beliefs about contraceptives.
Our finding that shows that women who do not want any(more) children in Nigeria are more likely to intend to use suggests that efforts that focus on promoting the small family as the norm are relevant in Nigeria. Such efforts might be redundant in Kenya.
This study has demonstrated the importance of ideation in helping individuals form the intention to use modern contraceptives. The Kincaid model is particularly relevant in this context although our study suggests that the cognitive domain is not necessarily a one-dimensional construct. In our analysis, contraceptive awareness (knowledge) and myths and rumors (attitudes) load on separate factors in both countries.
One of the reasons we decided to focus on contraceptive intentions in this study is because there is considerable evidence that contraceptive intentions strongly predict contraceptive use (Curtis and Westoff 1996; Bankole and Westoff 1998; Roy et al. 2003). Nonetheless, it is also true that intention does not always translate into behavioral performance. For example, a study in Bali, Indonesia, found that almost 30% of the women who reported intention not to have any more children had a child during the four-year study period (Withers, Tavrow and Abe 2012). In a meta-analysis of existing meta-analytic reviews, Sheeran (2002) found that although the effects of intention on behavior are relatively large, only 28% of the variance in behavior is explained by intention. So, for non-contracepting women, developing the intention to use contraceptives is not a guarantee that these women will eventually adopt a method. Efforts will still need to be geared towards helping these women translate their contraceptive intentions into reality. Fortunately, there is guidance from extant literature regarding how to maximize the likelihood that intentions will be translated into behavior. Research has shown that the consistency of intention and behavior depends on the type of intention formed (goal intention versus implementation intention) (Fennis et al. 2011; Gollwitzer and Sheeran 2006; Sheeran 2002). Whereas goal intention relates to what people plan to do sometime in the future, implementation intention is more specific in terms of the time and context of implementation of the behavior (Sheeran 2002). Literature has shown that implementation intentions are more likely to be translated to behavior than goal intentions. Other studies have highlighted the role of self-efficacy in bridging the intention-behavior gap (Lippke et al., 2009; Schwarzer, 2008; Sniehotta, Scholz and Schwarzer 2005). In sum, strategies for bridging the intention-behavior gap should include the use of persuasive messages that encourage the audience to form specific time-bound intentions to use contraceptives, and efforts to strengthen self-efficacy for action.
This study has some limitations that warrant mention. First, the data analyzed are self-reported. There is therefore the possibility that the responses might have been affected by recall and social desirability biases. During data collection, the field-workers took appropriate steps to minimize subjectivity and the influence of social desirability, including interviewing participants in a private location in the absence of a third party, assuring the respondent of confidentiality and minimizing social distance between the interviewer and the interviewee. The second limitation has to do with the variable derived from the questions on perceived need for permission and perceived social support. It is possible that women misperceive whether they actually need permission from their husbands, or whether they actually have the support that they think they have regarding contraceptive use. Third, the study relies on cross-sectional data, thereby making causal inference problematic. Nonetheless, the consistency and strength of the association of ideation with contraceptive intention lend support to the argument that the observed relationships are not trivial. The implications of the findings for programming should therefore be taken seriously.
6. Conclusion
This study provides strong evidence of the relevance of the ideation model in contraceptive use research and programing in urban areas of two African countries with different levels of contraceptive prevalence, unmet need and fertility desires. Two dimensions of ideation were particularly influential in predicting intention to use: self-efficacy and myths and rumors dimensions. Programs seeking to increase contraceptive use and help women and couples to attain their desired family size should promote contraceptive self-efficacy and identify ways to correct prevailing myths and rumors.
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