Literature DB >> 32368207

Sexting and other risky sexual behaviour among female students in a Nigerian academic institution.

Aboluwaji D Ayinmoro1, Endurance Uzobo2, Bodisere J Teibowei3, Joyce B Fred2.   

Abstract

OBJECTIVES: The increase in the use of social media has led to a concurrent rise in the prevalence of sexting, which has, in turn, resulted in risky sexual behaviour. This study aims to investigate the role of sexting in risky sexual behaviour among female students who own smartphones for social and educational purposes.
METHODS: A cross-sectional study was conducted on 200 undergraduate students of the Niger Delta University using a pre-tested and validated structured questionnaire. Data for the study were analysed using descriptive statistics to describe the socio-demographic characteristics and trends in sexting and risky sexual behaviour. In addition, inferential statistics (logistic regression) was used in testing the association between the dependent and independent variables. IBM SPSS version 21.0 was used for data analysis.
RESULTS: The results from the study indicated that those who had ever-sent nude pictures to their partners (OR = 2.504, p < 0.05) and the use of android phones were found to be significantly related to risky sexual behaviour of students (OR = 16.139, p < 0.05). Moreover, age (OR = 83.962, p < 0.01), ethnic group (OR = 130.612, p < 0.05), and monthly allowances (OR = 83.962, p < 0.05) were also associated with risky sexual behaviour.
CONCLUSION: This study confirmed the string influence of sexting on high-risk sexual behaviour caused by sexting. In light of this, academic institutions are advised to discourage the licentious use of smartphones.
© 2020 The Authors.

Entities:  

Keywords:  Female students; Risky sexual behaviour; Sexting; Smartphones; Social media

Year:  2020        PMID: 32368207      PMCID: PMC7184208          DOI: 10.1016/j.jtumed.2020.02.007

Source DB:  PubMed          Journal:  J Taibah Univ Med Sci        ISSN: 1658-3612


Introduction

Sexting is gradually becoming a problem for parents, educators, researchers, and society as a whole. With the advancements in communication technology, the lives of adolescents, including their sexuality, have become increasingly intertwined with digital devices. Nowadays, adolescents are not only passively exposed to sexualised media, but may also actively engage in electronically mediated sexual communication in the form of sexting. Ševčíková, Blinka, and Daneback assert that the youth tend to be very creative and use media to their advantage by downloading violent videos and sending suggestive text messages to their friends. Therefore, with increasing ubiquity of smartphones and access to the Internet, the prevalence of sexting is escalating to a devastating level, especially in the developing countries that are relatively new to the use of social media. Different studies indicate that the prevalence of sexting varies across countries., In particular, an online survey found that among the European countries, Sweden and the Czech Republic have the highest percentage of sexual messages sent or posted (12% and 10%, respectively). On the other hand, the prevalence rates in most European countries range from 1% to 4%, with the European mean being 3%. Moreover, Lee, Crofts, Salter, Milivojevic, and McGovern did a study on sexting among young people (i.e. their perceptions and practices) and found that sexting was prevalent among 13 to 15-year-olds who are particularly likely to receive sexual images. However, the study Rice, Rhoades, Winetrobe, Sanchez, Montoya, Plant, and Kordic conducted in Southern California revealed that sexting often leads to early sexual debut, which is correlated with higher rates of sexually transmitted infections and teen pregnancies. Finally, Ybarra and Mitchell New Hampshire study concluded that sexting might be linked to sexual risk behaviour. Sexting involves sending and posting sexually suggestive messages through the use of electronic devices. Klettke, Halford, and Mellor define sexting as the transmission of nude (or semi-nude) images via an electronic device. Furthermore, they added that sexting refers to the act or acts of sending, receiving, or forwarding sexually explicit messages or images from an individual's cell phone or computer to another. Sexting may cover various types of behaviour such as sending one's erotic pictures to romantic partners via the internet being the recipient of such. Currently, only a few studies have examined how these sexualised interactions in romantic relationships affect adolescent sexual behaviour. According to previous studies, sexting is associated with other health risk behaviour and environmental and personal factors such as pornography, substance use, bullying, and suicide.8, 9, 10 Furthermore, studies have also revealed that young people who sext are more likely to indulge in high-risk sexual urges and seek the fulfilment of their sexual desires shortly after exchanging sexual messages with their partners., There has been a suggestion that young people who engage in online sexual behaviour (which may include sexting) were more likely to have problematic family backgrounds. This was corroborated by Benotsch et al. who stated that adolescents who live with both parents were less likely to be involved in sexting. Young people who are involved in sexting have been reported to develop new risky sexual behaviour. Personality is a strong predictor of behaviour, and personality traits that have been associated with sexting include extraversion, neuroticism, and others. In addition, external stressors such as academic and social demands are also common at this stage of development. Nevertheless, the few studies that have looked into this phenomenon show that sexting might be associated with other factors, including health risky behaviour. Sexting could have a severely negative effect on young people because they may not be able to the handle complex emotional issues, which may sometimes accompany sexting. As previously stated, studies on sexting and sexual behaviour was primarily concentrated on both genders. For instance, Marume, Maradzika, and January studied adolescent sexting and risky sexual behaviour in Zimbabwe and found that condom use was significantly higher among girls who sext. Based on the studies that postulated that sexting could be more prevalent among females, this study explored some of the factors associated with sexting among female students and the latter's association with risky sexual behaviour. The case study sample consisted of female students from the Niger Delta University in Nigeria.

Materials and Methods

Study area

The study was conducted in the Niger Delta University, located in the Wilberforce Island of Bayelsa State, Nigeria, from September to October 2019. The university is made up of three campuses: Gloryland Campus (main campus), College of Health Sciences, and the temporary campus of the Faculty of Law in Yenagoa. It also has its own teaching hospital in the suburban area of Okolobiri known as the Niger Delta University Teaching Hospital (NDUTH). It has 12 faculties and offers bachelor's, master's, and doctoral degrees.

Study design and population

The study has a cross-sectional quantitative design; it seeks to explore sexting and risky sexual behaviour among smartphone-using female students. The population of the study comprised of female students who use smartphones. However, the inclusion criteria strictly required female students who possess smartphones, they could readily use for sending or receiving pictures and videos online.

Data collection/study instruments

The data collection instrument came in the form of a pre-tested and validated structured questionnaire designed by the researcher based on the revised pilot study and recommendations from experts in measurements and evaluation. The questionnaire was divided into three main parts: Section A, which focused on the socio-demographic characteristics of the respondents (e.g. age, religion, academic level, ethnic group, income, and mode of residence); Section B, which focused on sexting behaviour and included questions such as: Have you ever received or sent a nude or semi-nude picture or video before? (Chronbach's alpha coefficient of α = 0.89); and Section C focused on risky sexual behaviour with questions such as: Have you ever had sex, sex without a condom, sex when drunk, etc.? (Chronbach's alpha coefficient of α = 0.89).

Sample size estimation and sampling technique

The sample size for this study was determined using Cochran's formula. The estimated sample size required for the study was calculated as follows:where n = Required Sample size; Z1-α/2 = the value of standard normal variables at 95% confidence interval = 1.96; P = Expected prevalence or proportion of undergraduate students who sext = 80% (0.05); d = marginal error at 5% (standard value of 0.05). The total estimated sample size required for the study was 200 respondents. This study mainly adopted the simple random sampling technique to recruit female students who owned a smartphone that they could access online information with. In cases were female students had no access to the internet, the next respondents with internet access were selected until the required sample size was reached.

Data analysis

Data collected for this study were manually checked for errors before inputing them into the IBM SPSS software for analysis. The variables in the study were then described through frequencies and percentages, bar charts, and logistic regression. The logistic regression model was used to assess the strength of association between the dependent and independent variables. In all analyses, the base for rejection was set at a p-value of 0.05.

Dependent variable

The dependent variable for this study is risky sexual behaviour. The risky sexual behaviour comprised the following: having had sex, sex without a condom, sex while intoxicated, sex with someone you've known for less than two days, cheating on your partner, taking pills for sex, and having sex during menstruation. These items were coded (yes = 1 and no = 0) and re-grouped to form a dichotomous variable of low risky sexual behaviour (0–3 = 0) and high risky behaviour (4–7 = 1).

Independent variables

The independent variables revolved around sexting behaviour with items like: knowledge of sexting, liking for sexting, having received/sent a sexually explicit text message to a friend, last time of sexting, having sent nude picture to partner, having a partner who enjoys sexting, using smartphones to encourage sexting, and being forced by partner to sext. The variables also included socio-demographic characteristics such as age, ethnicity, religion, academic level, income, and mode of residence.

Results

Socio-demographic characteristics of the respondents

Table 1 shows the socio-demographic characteristics of the respondents, which include their age, religion, ethnic groups, academic level, income/allowances, and mode of residence. As the illustrated in the table, majority of the respondents (50.5%) were between the ages of 23–30 years old and were Christian (99.0%). Additionally, more than half of the respondents were from the Ijaw/Epie ethnic group (55.5%). In terms of academic level, majority of the respondents were first-year students (20%) (see Table 2, Table 3).
Table 1

Socio-demographic characteristics of the respondents.

Demographic variablesFrequency (n = 200)Percentage (%)
Age
Less than 18 years old4623.0
18–22 years old5326.5
23–30 years old10150.5
Religion
Christian19899.0
Muslim21.0
Ethnic group
Ijaw/Epie11155.5
Urhobo4522.5
Igbo3718.5
Hausa21.0
Yoruba52.5
Academic Level
100 L4422.0
200 L4020.0
300 L4120.5
400 L3316.5
500 L4221.0
Income/monthly allowance (N)
5,000 – 10,9998040.0
11,000 – 16,9997537.5
17,000 – 20,0004522.5
Mode of residence at school
Off-campus11959.5
On-campus8140.5
Table 2

Distribution of respondents by sexting behaviour.

Sexting behaviour variablesYes (%)No (%)
Knowledge of sexting152 (76.0)48 (24.0)
Received a sext94 (47.0)106 (53.0)
Enjoys sexting89 (44.5)111 (55.5)
Sent a nude picture73 (36.5)127 (63.5)
Partner enjoys receiving nude pictures76 (38.0)124 (62.0)
Uses smartphones to encourage sexting144 (72.0)56 (28.0)
Forced by partner to sext30 (15.0)170 (85.0)
Table 3

Association between sexting, socio-demographic characteristics, and risky sexual behaviour among respondents using binary logistic regression.

Predictor variablesLow risky behaviour (%)High risky sexual behaviour (%)Model 1
Model 2
OR [95% CI]OR [95% CI]
Knowledge of sexting73 (48.0)79 (52.0)1.636 [.790–3.389]3.069 [.529–17.820]
Enjoyment of sexting49 (55.1)40 (44.9)0.639 [.333–1.224]0.745 [.130 - .443]
Ever received/sent a sext to a friend49 (52.1)45 (47.9)0.706 [.368–1.355]0.076 [.013 - .443]
Last time of sexting36 (52.9)32 (47.1)0.539 [2.56–1.135]1.389 [.272–7.095]
Ever sent a nude picture to her partner29 (39.7)44 (60.3)2.504∗ [1.102–5.690]2.957 [.513–17.036]
Partner enjoys sexting32 (42.1)44 (57.9)1.702 [.776–3.733]2.006 [.312–12.891]
Use of smartphones to encourage sexting63 (43.8)81 (56.2)2.068 [.956–4.474]16.139∗ [2.374–109.696]
Forced by partner to sext22 (73.3)8 (26.7)0.300 [.118 - .768]2.469 [.251–24.290]
Socio-demographic variables
Age
Less than 18 years old (Ref)35 (76.1)11 (23.9)1.000
18–22 years old10 (18.9)43 (81.1)83.962∗∗ [7.046–1000.537]
23–30 years old54 (53.5)47 (46.5)10.656 [1.275–82.542]
Religion
Christian (Ref)99 (50.0)99 (50.0)
Muslim2 (100.0)
Ethnic group
Yoruba (Ref)2 (40.0)3 (60.0)1.000
Urhobo2 (4.4)43 (95.6)130.612∗ [1.090–15657.333]
Igbo6 (16.2)31 (83.8)10.953 [.138–870.740]
Hausa2 (100.0)
Ijaw/Epie89 (80.2)22 (19.8)0.186 [.003–13.089]
Academic level
100 Level (Ref)16 (36.4)28 (63.6)1.000
200 Level27 (67.5)13 (32.5)0.293 [.018–4.812]
300 Level17 (41.5)24 (58.5)1.338 [.096–18.578]
400 Level15 (45.5)18 (54.5)8.299 [.552–124.726]
500 Level24 (57.1)18 (42.9)2.554 [.143–45.545]
Income/monthly allowance (N)
5,000 – 10,99923 (28.8)57 (71.2)1.000
11,000 – 16,99954 (72.0)21 (28.0)0.017∗ [.002 - .139]
17,000 – 20,00022 (48.9)23 (51.1)0.072∗ [.007 - .722]
Mode of residence at school
Off-campus (Ref)66 (55.5)53 (44.5)1.000
On-campus33 (40.7)48 (59.3)3.604 [.552–23.520]

Significant at P < 0.01∗∗ or P < 0.05∗; Ref = reference category.

Socio-demographic characteristics of the respondents. Distribution of respondents by sexting behaviour. Association between sexting, socio-demographic characteristics, and risky sexual behaviour among respondents using binary logistic regression. Significant at P < 0.01∗∗ or P < 0.05∗; Ref = reference category. Most of the respondents (40.0%) had a very low monthly income, which ranged between 5,000 to 10,999; and more than half of the respondents (59.5%), resided outside the school campus.

Sexting behaviour among respondents

This study examined the respondents' sexual behaviour through exploring their knowledge of sexting, receipt of sext messages, feelings about sexting, frequency of sending nude pictures, partner's willingness to send nude pictures, use of smartphones to encourage sexting, and being forced by their partner to sexting. When the respondents were asked whether they knew about sexting, majority of them (76.0%) indicated that they did and almost half of them (47.0%) indicated that they have received a sext. Most of the respondents (72%) indicated that they have used their smartphones to encourage sexting.

Sexting and risky sexual behaviour

In order to determine the predictive influence of sexting on risky sexual behaviour among the respondents, binary logistic regression was used in Model 1 and 2, respectively. In Model 1, only the respondents who had ever sent nude pictures to their partner were associated with risky sexual behaviour (OR = 2.504, p < 0.05) at a statistically significant level. Therefore, those who send nude pictures to their partners are 2.5 times more likely to engage in high-risk sexual behaviour. Among the predictor variables in Model 2, the ‘use of smartphones to encourage sexting’ was found to have the most statistically significant association with risky sexual behaviour (OR = 16.139, p < 0.05). Among the socio-demographic characteristics of the respondents, age was found to have the most statistically significant association with risky sexual behaviour. In particular, those in the age range of 18–22 years old are 84 times more likely to engage in high-risk sexual behaviour than those who are less than 18 years old. Among the ethnic groups, those who were from the Urhobo ethnic group are 130.6 times more likely to engage in risky sexual behaviour than those from Yoruba. The respondents' monthly allowance was also found to have a statistically significant association with risky sexual behaviour. In particular, those who earned 11,000 – 16,000 and 17,000 – 20,000 are 1.7 and 7.2 times less likely to engage in high-risk sexual behaviour compared to those who earned 5,000 – 10,000, respectively.

Discussion

The discussion of this study's findings was done in line with existing literature. Findings on the respondents' sexual behaviour confirm that majority of them have used smartphones to send nude pictures and this could influence their sexual behaviour to a large extent. It corroborates the works of Lenhart and Ybarra and Mitchel define sexting as the exchange of sexually suggestive pictures or messages, including nude or semi-nude photographs through mobile phones to the opposite sex as well as sharing sexual photos via online text messaging. Marume et al. argued that sexting was correlated with both safe and risky sexual practices. This study found a similar trend of risky sexual behaviour among respondents who engaged in sexting, namely those who engaged in sexting were more likely to engage in early sexual activity without protection than those who do not. This suggests that sexting can influence or promote sex among students to a large extent; further confirming the belief of Marume et al. that sexting is linked to sexual behaviour. Moreover, it supports the latter's stance regarding the significant correlation between sexting and risky sexual practices among adolescents in Zimbabwe, which was recommended to be indicated in reproductive health programmes to result in higher impact intervention. Among the factors that affect sexting and risky sexual behaviour, this study found that those who engaged in sexting did so primarily because the use of smartphones did not only affect sexting, but was also greatly influenced by friends and relatives, which, in turn, encouraged sexting—and consequently, risky sexual behaviour—among students. This study indicated that sexting significantly influences sexual behaviour; thus, sending sexts to their romantic partners positively predicted subsequent high-risk sexual behaviour among the respondents. This assertion has also been previously confirmed by two cross-sectional studies, which provided more insight into the possible causal links between sexting and high-risk offline sexual behaviour., Another study by Temple and Choi, 19 further corroborates this by stating that actively sending sexts may activate sexual behaviour among adolescents. However, this study found that of all the predictor variables, only ‘sending nude pictures to one's partner’ and ‘use of smartphones to sext’ were significantly related to high-risk sexual behaviour. Furthermore, just as this study found certain socio-demographic data that were significantly correlated to high-risk sexual behaviour, previous studies have also noted this position. In particular, Ševčíková, Blinka, and Daneback and Rice et al. arrived at the same conclusion that age and sensation-seeking behaviour were found to have effects on the intercept of offline sexual behaviour. In other words, older adolescents and high prevention-seekers were more likely to be sexually experienced at baseline. Also, Rice et al. found the race of the smartphone user (e.g. black/African American) to be significantly associated with high-risk sexual behaviour, a position that is also held by this study. Additionally, the findings from this study slightly differ from other studies with respect to the prevalence of sexting behaviour. This study found the prevalence of sexting as indicated by the various measures of sexting behaviour to be high, whereas other studies put the prevalence of sexting between 2.5% and 27.6%., In particular, Ybarra and Mitchell's study puts the prevalence rate of sexting at just 7% while another study in Nigeria had similar prevalence rate of sexting with this study at 33.2%.

Limitations

To the best of the researchers' knowledge, a study investigating sexting and risky sexual behaviour among female smartphone users has not yet been carried out, especially in Nigeria. However, the limitation of this study is based on its cross-sectional design, which restricts the level of inferences that can be made. Furthermore, since the study concentrated on just one institution in Nigeria, its generalisability is limited to the said study locale. Finally, the research's questionnaire-based format allows for the possibility of response bias given the nature of the study.

Conclusion

Based on the study, it is evident that sexting is significantly associated with risky sexual behaviour among female university students in Nigeria. As such, there is need for all stakeholders in the university system to promote moral values and standards that will regulate the students' and the youth's use of smartphones while still upholding the moral values of society. Hence, it is suggested that programmes that promote moral values when using smartphones should be organised by university authorities across the country, especially among university students. This can be done in collaboration with the National Orientation Agency (NOA) and other higher-educational institutions in Nigeria.

Source of funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflict of interest

There is no conflict of interest.

Ethical approval

All of the research procedures performed in this study adhere to the ethical standards of the Niger Delta University, which is also in line with the national code of conducting research in Nigeria. The research process is also in accordance with the Helsinki 1964 declaration and its later amendments or other comparable ethical standards.

Authors contributions

EU and JBF conceptualised and designed the study. ADA, EU, and BJT drafted the questionnaire. EU, BJT, and JBF ensured face validity and administered the questionnaires to the respondents. EU and ADA analysed and interpreted the data. ADA, EU, JBF, and BJT wrote the manuscript. All authors have critically reviewed and approved the final draft and are responsible for the content and similarity index of the manuscript.
  10 in total

1.  Prevalence and characteristics of youth sexting: a national study.

Authors:  Kimberly J Mitchell; David Finkelhor; Lisa M Jones; Janis Wolak
Journal:  Pediatrics       Date:  2011-12-05       Impact factor: 7.124

Review 2.  Sexting prevalence and correlates: a systematic literature review.

Authors:  Bianca Klettke; David J Hallford; David J Mellor
Journal:  Clin Psychol Rev       Date:  2013-11-05

3.  "Sexting" and its relation to sexual activity and sexual risk behavior in a national survey of adolescents.

Authors:  Michele L Ybarra; Kimberly J Mitchell
Journal:  J Adolesc Health       Date:  2014-09-27       Impact factor: 5.012

4.  Sexting and sexual behavior among middle school students.

Authors:  Eric Rice; Jeremy Gibbs; Hailey Winetrobe; Harmony Rhoades; Aaron Plant; Jorge Montoya; Timothy Kordic
Journal:  Pediatrics       Date:  2014-07       Impact factor: 7.124

5.  Online sexual behaviours among Swedish youth: associations to background factors, behaviours and abuse.

Authors:  Linda S Jonsson; Marie Bladh; Gisela Priebe; Carl Göran Svedin
Journal:  Eur Child Adolesc Psychiatry       Date:  2015-01-15       Impact factor: 4.785

6.  Sexually explicit cell phone messaging associated with sexual risk among adolescents.

Authors:  Eric Rice; Harmony Rhoades; Hailey Winetrobe; Monica Sanchez; Jorge Montoya; Aaron Plant; Timothy Kordic
Journal:  Pediatrics       Date:  2012-09-17       Impact factor: 7.124

7.  Sexting among young adults.

Authors:  Deborah Gordon-Messer; Jose Arturo Bauermeister; Alison Grodzinski; Marc Zimmerman
Journal:  J Adolesc Health       Date:  2012-07-23       Impact factor: 5.012

8.  Sexting, substance use, and sexual risk behavior in young adults.

Authors:  Eric G Benotsch; Daniel J Snipes; Aaron M Martin; Sheana S Bull
Journal:  J Adolesc Health       Date:  2012-08-14       Impact factor: 5.012

9.  Longitudinal association between teen sexting and sexual behavior.

Authors:  Jeff R Temple; HyeJeong Choi
Journal:  Pediatrics       Date:  2014-10-06       Impact factor: 7.124

10.  Sexting: Prevalence, Predictors, and Associated Sexual Risk Behaviors among Postsecondary School Young People in Ibadan, Nigeria.

Authors:  Oluwatoyin Olatunde; Folusho Balogun
Journal:  Front Public Health       Date:  2017-05-08
  10 in total

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