Medical Subject Headings (MeSH) by the U.S. National Library of Medicine defines, Gender discrimination, or sexism, as “Prejudice or discrimination based on gender or behavior or attitudes that foster stereotyped social roles based on gender.” (1). While the word stereotyping is defined according MeSH as “An oversimplified perception or conception especially of persons, social groups, etc.”(2). While ‘Gender stereotyping’ is a broad category that reflects our impression and beliefs about females and males, they originate from gender roles that define the responsibilities of females and males and remarkably difficult to abandon. Classically, roles such as taking care of children and cooking are attached to females, while males are identified with roles such as engaging in paid employment (3). Even in the current scenario urban women tend to be more interested in humanitarian, educational, and medical fields; while males are more attracted to defense, sports, and technical fields (4).
There is apathy towards involving women in important roles in society and huge bias against the existing (5). The Equal Opportunities Commission (EOC) (2005) states that not only society but also females themselves avoid getting into various skilled jobs due to rampant prejudices (6). Mapfumo, Chireshe & Munhuweyi (2002) from Zimbabwe observed that both males and females choose their careers under stereotyping perception (7). The study conducted by McQuaid and Bond (2004) shows that many girls in Scotland had negative attitudes to work in jobs perceived to be masculine (8). In Egypt and other countries with traditional cultures, females have fewer opportunities to reach higher positions at workplaces (9). Furthermore, the role of gender stereotyping on career choices was also observed in the UK (10).
Violence and aggression are enforced by men towards women. The issue is deemed as a shadow pandemic (11). Basar and Demirci (2018) conducted a study among Turkish women and observed that 41.3% of the study participants had experienced domestic violence (12). A survey conducted in the USA estimated that 19.3%, 15.3%, and 43.9% of women have experienced rape, stalking, and other forms of sexual violence respectively during their lifetimes (13). Many consider ‘Violence Against Women’ (VAW) as an important challenge to the overall health and social development in India (14). The roots of this psyche can be traced to the bringing up of the boys in the families and societies stressing gender-specific roles in society and also gender-specific freedom even in trivial issues like clothes (15).
Adolescence (10–19 years) is a critical period of rapid physical and psychosocial changes (16). Global data indicate that gender norms are commonly reflected in adolescents’ gender attitudes. For example, population-based surveys in low- and middle-income countries (LMICs) indicate that over half of late adolescents justify wife-beating (17). There is an increase in the crimes against women committed by juveniles, including rape. Many juveniles blame women’s behaviour for getting raped (18). Law cannot provide much deterrence as the punishments for juvenile criminals are understandably not the most severe (19). It is important to address gender attitudes in early adolescences before their beliefs become more solidified (20, 21). It is observed that diminishing gender inequality in a community results in reduced violence against women (22). Involving adolescents along with adults in gender-sensitive training and in developing response against violence is considered by experts as need of the hour (23).
Very few studies have assessed the attitude of Indian males towards females and studies concerning adolescents are further rare. As today’s adolescents are tomorrow’s adults, it is essential to cultivate a positive gender attitude in them as it will go a long way in the development of gender tolerance in our society. The aim of the current research was to understand the attitude towards women, gender stereotyping, and gender biases among adolescent boys and girls from a rural area of Maharashtra, India.
Methods
It was a cross-sectional study conducted using multi-stage sampling among the adolescents studying in private and government schools in the rural area of Sangli district, Western Maharashtra. The study was questionnaire-based and was conducted for a period of 12 months, i.e., Sept. 2016 to Aug. 2017. World Health Organization defines the phase of adolescence between 10 years to 19 years. Considering the schooling pattern in India generally, the school-going children from 5^th standard to 12^th standard belong to this age. However, most of the institutions' 11^th and 12^th standards are separate and not attached to a school. Therefore, it was decided to consider students from 5^th to 10^th standards for the study. However, considering the cultural background, general maturity, and sensibilities of people it was decided to include students from the 8^th, 9^th, and 10^th standards only. Hence, the study population was adolescents studying in 8^th, 9^th, and 10^th standard from the schools in Sangli district.
It was further decided to include the schools from the field practice area of Rural Health Training Center, Turchi, belonging to Bharati Vidyapeeth (Deemed to be University) Medical College & Hospital, Sangli (MH), India. This decision was taken for better follow-up, cooperation, and feasibility. After the requisite for ethical clearance from the institutional ethical committee and permissions from school authorities, and all the students getting the written consent from their parents were included in the study. In a similar study conducted, the observed percentage of positive attitude among adolescent males was 88.3% (24). Hence, the calculated minimum sample size was 360 (prevalence of positive attitude = 88.3% i.e., p = 0.883, hence q = 0.117, level of significance = 1%, α = 0.05 i.e., Zα= 2.58, allowable error is 5%, d= 0.05. The sample size, n= Zα²pq / d²p² = [(2.58)²×0.883×0.117]/ (0.05)²×(0.883)² = 352.8 ≅ 360). Considering 30 students in each class and correction for drop-out, it was decided to include five schools in the study selected randomly from the schools in the field practice area. Out of the selected schools, two were co-education and three schools were for females only. All the available participants from these schools were included in the study, hence the actual samples included in the final analysis (after the rejection of incomplete questionnaires) were 826 (297 males and 529 females).
The study tool was a pre-designed, self-administered questionnaire. The questionnaire had five sections with Section-I had socio-demographic variables like age, residence, etc. Sections II, III, and IV consisted of a locally pre-validated gender stereotyping scale, Attitudes toward Women Scale for Adolescents (AWSA), and attitude towards crime against women respectively (24, 25, 26). These scales had been previously used in a similar study, in the same geographical area and shown to have a good internal consistency and test-retest reliability.
Section V had questions regarding attitude towards men (male bias). It was developed with the help of field experts and published literature. Each question in the 17- items scale could be answered with a five-point Likert scale. For most of the questions, points considered were from 1 to 5 for an answer starting from strongly disagree to strongly agree respectively. The questions consisted of statements showing male bias, such as “males are better drivers”, “males should not cook”, “women should look after children”. Total points were between 0 to 85 and scores of ≤ 42 were considered as ‘Minimal Male Bias’ and scores ≥ 43 were considered as ‘Strong Male Bias’. The scale had a good internal consistency (Cronbach’s α, r = 0.62) and test‑retest reliability (Spearman correlation coefficient, r = 0.71).
An evaluation was done based on the answers given by the students. Statistical Analysis was done using descriptive statistics, chi-square test, and Mann-Whitney U test. The data entry and analysis were performed using MS Excel 2016 and SPSS-22.
Results
The mean (SD) age of participants was 13.99 (0.98) and 297 (36%) were males. Seven hundred sixty-three (92.4%) were Hindu/Jain and 63 (7.6%) were Muslim. Seven hundred forty-five (90.2%) resided in the rural areas, whereas 81 (9.8%) correspondents resided in urban areas. Four hundred and nine (49.5%) participants lived in a joint family and 417 (50.5%) had a nuclear family.
Considering the occupation of the father of each participant, the majority 550 (66.6%) were farmers, followed by 232 service/businessmen (28.1%), and 44 (5.3%) were labourers. Mothers of the majority of the participants were homemakers 709 (85.8%), followed by 68 (8.2%) farmers and 49 (5.9%) servicewomen. While fathers of 617 (74.7%) participants were highschool educated, 146 (17.7%) were college-educated, and 63 (7.6%) were primary educated. It was reported that mothers of majority students, i.e. 673 (81.5%) had a high school education, whereas mothers of 73 (8.8%) participants had studied in a college and 80 (9.7%) had studied only up to the primary stage. It was reported that mothers of 800 (96.9%) participants were involved in decision making whereas mothers of 26 (3.1%) participants had no say in decision making.
Out of the 826 participants, 124 (15%) had a strong positive attitude towards women and 569 (68.9%) had a positive attitude, while 133 (16.1%) had a negative attitude. A negative attitude towards women was observed in 93 (31.3%) males as compared to only 40 (7.6%) female participants. Overall, a positive attitude had an increasing trend with age.
We observed minimal to no stereotyping in 375 (45.4%), moderate stereotyping in 357 (43.2%), and severe stereotyping in 94 (11.4%) participants. A higher percentage of females had minimal to no stereotyping 261 (49.3%) as compared to males 114 (38.4%). Considering religion, minimal to no stereotyping was higher in Hindu/Jain participants as well as residents of rural areas.
Considering crime against women, 653 (79.1%) had a positive attitude and 173 (20.9%) had a negative attitude. As far as gender difference was considered, positive attitude was more common among females 456 (86.2%) than males 197 (66.3%). A strong positive attitude towards crime against women was observed in a higher percentage of rural residents as compared to urban (80.3% vs 67.9%). A negative attitude was the highest among participants with labourer fathers 11 (25%).
Strong male bias was observed in 484 (58.6%) participants, while minimal male bias was noted in 342 (41.4%) participants. The majority of males i.e., 226 (76.1%) displayed strong male bias as compared to 258 (48.8%). A higher percentage of females disagreed with each of the 17 questions as compared to males. More than 60% of male participants agreed that males are generally more knowledgeable than females, and more than 50% agreed that males are better drivers, better athletes, more truthful, and decisive than females. The majority of female participants did not agree to any of the statements. Contrarily, less than 20% agreed to the statements like men were stronger and wiser. The remaining statements were agreed by 20 to 40% of female participants. Overall, a higher percentage of respondents from joint families had strong male bias as compared to those from nuclear families (63.6% vs 53.7%).
All four scores were statistically associated with gender.

 

Stereotyping score and attitude towards crime against women score were associated with residence (Table 2).
The association of interpretation of all the scores with various parameters was calculated using the chi-square test. We observed a statistically significant association of the attitude towards females with gender, age group, and father’s education. Similarly, there was an association between the gender stereotyping scale with gender, religion, and residence. Attitude towards crime against women was statistically associated with gender, residence, and father’s occupation.
We observed a statistically significant association of attitude towards males with gender and type of family.