Research results
Participants’ profile
In the selected sample, a striking 84 per cent of women aged twenty to eighty years reported undergoing some form of FGM/C, while the remaining 16 per cent did not. Most participants were residents of the Bahari area, classified as urban (17.7 per cent), followed by a smaller proportion living in Ammarat, also classified as urban (2.3 per cent). Among rural respondents, Ombadda and Karari represented significant locations, accounting for 11.7 per cent and 13.3 per cent, respectively. In terms of gender distribution, there were 178 male participants (29.7 per cent) and 422 female participants (70.3 per cent). Age distribution revealed that the majority of respondents (66.3 per cent) fell within the forty to sixty age group, while 33.7 per cent belonged to the older age bracket. A significant proportion of respondents had completed primary school, accounting for 21.0 per cent of the sample, while 12.7 per cent of respondents were illiterate. Furthermore, 10.0 per cent of participants had university and postgraduate degrees. Ethnically, the largest group represented in the sample was from the Nubian North (46.7 per cent), closely followed by the Arab Central group (44.7 per cent). The Mapan-Angassana and Nubian Central Kordofan ethnicities accounted for only 5.0 per cent and 3.7 per cent respectively.
Lastly, in terms of income levels, the majority of respondents (43.0 per cent) identified as low income, with 31.7 per cent classified within the middle-income bracket and 25.3 per cent categorised as high-income earners. These demographic measures collectively promote ethical research practices and significantly enhance the credibility of the study’s findings.
The analysis of the model instrument was conducted through a comprehensive two-step process. Initially, the measurement model was evaluated, followed by a detailed examination of the hypotheses using a structural model. This assessment focused on key aspects of variables’ reliability, convergent validity, and discriminant validity for the various variables involved.
The average responses from participants provided a nuanced understanding of their perceptions and behaviours regarding FGM/C. The data revealed a moderate level of abandonment, reflecting a delicate balance between acceptance and resistance. This suggested that, while some individuals appeared open to the idea of discontinuing the practice, others remained more hesitant, influenced perhaps by deep-seated cultural or social factors. Similarly, when participants were asked about their behavioural intentions toward abandonment, the results were telling. There was a slight, but noticeable, inclination toward supporting abandonment, hinting at a shift in mindset, even if the transformation was not yet widespread. The survey also explored how participants perceived the ease and usefulness of abandoning FGM/C, with responses indicating that, for many, the process could be perceived as challenging yet ultimately beneficial.
Further insights were gained by considering the role of social norms and peer pressure. It was evident that these factors played a significant role in shaping attitudes, with many respondents acknowledging the weight of community influence on their views and actions regarding FGM/C. The discussion around the facilitating conditions for programmes aimed at eliminating the practice revealed a wide spectrum of opinions. While some participants expressed concerns that these programmes were difficult to understand, unavailable, or lacking in permanence, others offered a more cautious endorsement, acknowledging some support for these initiatives. However, the majority of respondents shared a negative view regarding the quality and effectiveness of these programmes, particularly in terms of how well they communicated their messages. Many felt that the programmes fell short, leaving room for significant improvement in both content and delivery.
Taken together, these responses painted a picture of a society at a crossroads, where the path toward abandoning FGM/C is neither clear-cut nor universally embraced, but where there is also an undercurrent of possibility for change. The data served as a powerful reminder of the deep-rooted cultural dynamics at play and the need for thoughtful, contextually-aware strategies to foster progress.
Reliability and validity of the model instruments
The results of the reliability and validity tests showed that the questionnaire was consistent and dependable. Each tool used in the study met the required standards for measuring relationships between items. The study also checked the accuracy of the measurements and found that the variables were both reliable and valid, meaning they were closely linked where expected but clearly different where needed. Overall, the model proved to be both trustworthy and meaningful, with strong evidence that the different factors were related in the right ways while remaining distinct from each other.
Using Structural Equation Modelling in studying FGM/C abandonment
Structural Equation Modelling (SEM) is a robust statistical method used to uncover the key drivers of behavioural change, particularly in areas such as gender harmful practices. By leveraging SEM, researchers are able to identify and quantify the underlying relationships between various factors and their influence on target behaviours. The coefficients derived from the model provide insightful information on the strength and direction of these relationships, allowing for a deeper understanding of the dynamics at play (Byrne 2016).
For instance, a coefficient with a significant positive value indicates the strong influence of a specific factor on the target behaviour, whereas a negative coefficient reveals a suppressive or deterrent effect. These coefficients are crucial in determining which variables have the greatest impact on behaviour change. By examining the magnitude of these coefficients, researchers can effectively prioritise interventions that are most likely to bring about significant change.
In addition to coefficients, the model’s loadings offer a clear indication of the importance of each indicator within a latent construct. This information is invaluable for practitioners, guiding them in focusing on the most relevant variables that can drive change. Furthermore, a comprehensive understanding of these relationships aids the efficient allocation of resources, ensuring that interventions are targeted where they are most likely to have the greatest impact. This approach helps optimise intervention costs, maximising effectiveness while minimising wasted resources.
Before developing the model, a comprehensive assessment of its overall fit was conducted, focusing on several fit indices that evaluate how well the model matches the observed data (Table 7.1). These indices are essential for gauging the model’s robustness and its capacity to accurately capture the relationships between the constructs. The analysis showed a strong fit, suggesting that the model offers a reliable framework for understanding the underlying dynamics.
Table 7.1. Model goodness-of-fit results.
Fit Index | Recommended Value (Hair 2006) | Measurement Model |
χ 2 | Non-significant at p <0.05 | 2568.096 |
Degrees of Freedom | n/a | 569 |
χ 2 /df | <5 preferable <3 | 4.513 |
Goodness-of-Fit Index | >0.90 | .963 |
Adjusted Goodness-of-Fit Index | >0.80 | .857 |
Comparative Fit Index | >0.90 | .963 |
Root Means Square Residuals | <0.10 | .145 |
Root Means Square Error of Approximation | <0.08 | .075 |
Normed Fit Index | >0.90 | .953 |
Parsimony Normed Fit Index | >0.60 | .857 |
Source: The author.
After carefully analysing the model’s components and ensuring their reliability, an SEM was developed. This model reflects the relationships between the key variables in the study, offering valuable insights into how they influence one another. Figure 7.2 presents the model that best represents the data, visually showing how the different factors are interconnected. These findings are crucial for uncovering the key behavioural drivers behind the decision to abandon FGM/C, giving us a clearer picture of the factors at play.