CHINWE Onyemaechi,1 and Okafor, Juliet Onyinyechukwu2
1&2Department of Psychology, Chukwuemeka Odumegwu Ojukwu University, Igbariam
ci.onyemaechi@coou.edu.ng, jayokafor@yahoo.com
Abstract
The study examined social media addiction and perceived attractiveness as correlates of healthy social interaction among university students of Nnamdi Azikiwe University, Awka. The participants comprised 123 students drawn from Nnamdi Azikiwe University, Awka, Anambra State. The participants comprised 66 (53.7%) males, and 57 (46.3%) females. The participants’ age ranged from 17 to 27. The mean age was 23.44, and standard deviation was 1.87. Accidental sampling technique was used to select the participants because the students that participated in the study were sampled via availability, accessibility, and willingness. Three instruments were used: Interaction Rating Scale Advanced- Brief, Social Media Addiction Scale, and Perceived Attractiveness Scale. The study adopted cross-sectional and correlational design and Pearson Product Moment Coefficient analysis were used as appropriate design and statistics. Results indicated that social media addiction dimensions such as conflict at -.17, p>.05 and mood modification at .15, p>.05 had no correlation with healthy social interaction. More so, social media addiction dimension like occupation at .35** p<.05 had positive correlation with healthy social interaction, while relapse dimension at -.31** p<.05, had negative correlation with healthy social interaction. These findings suggested that psychological intervention is needed among the students since, social media addiction, and perceived attractiveness impacted healthy social interaction. This will help the students to know and manage their social media addiction, and perceived attractiveness in order to adapt very well in their relationship and thereby experience healthy social interaction.
Keywords: Social media addiction, Perceived attractiveness, Healthy social interaction.
INTRODUCTION
For students studying in university, social interaction with peers and lecturers can often be an
exercise in frustration. If such frustration is to be minimized, much thought needs to be given to the methods of interaction that will be utilized, so that the university environment fulfils the human desire for social interaction. Asynchronous interaction may not give the immediacy that is required for successful social interaction. The lapsed time that can occur between question and answer may not assuage the tyrannies of distance, time zones, and isolation from which learners may suffer. The inability to interact freely with other students may exacerbate feelings of aloneness, and provide a less-than-ideal environment for successful study.
Hence, social interaction is any dynamic sequence of social actions between individuals (or groups) that modify their actions and reactions by their interaction partner(s) (Cristiani, et al. 2011). Social interactions the writer intends are the acts, actions, or practices of two or more people mutually oriented towards each other’s selves, that is, any behavior that tries to affect or take account of each other’s subjective experiences or intentions. For instance, talking is the most common kind of social interaction. Studying together, playing chess, eating at a table and offering a cup of water are social interactions too. In other words, the writer can conclude in social interactions term is a reciprocal relationship between the individual and the individual, individuals and groups, or groups and groups in the community.
However, there are several ways in which interaction are important. For instance, close interactions are a basis for attachment and social support (Berkman et al. 2018; Gifford-Smith & Brownell 2019). Interactions are a source of social influence, and are central for identity formation, role modeling, sense of belonging, and social comparisons (Berkman et al. 2018). Since social interaction plays an essential role in the student learning process and off-learning environment. According to Hurst et al. (2013) social interaction enhances students’ literacy, knowledge, critical thinking, problem-solving skills, and ability to communicate and network. It allows students to fit in with society in contributing effectively and meaningfully. In the learning environment, students benefit more when they are allowed to read, write, participate, listen, and speak in the learning process via social interaction. Socially, students can participate well when they are allowed to contribute, share ideas, and get involved in the social discourse. According to Okita (2012), students’ ability to develop cognitive reasoning lies in their social interaction, culture, and values. Hence, students can build virtual interaction and connection, which at some point can lead to physical contact and social media use that often result into addiction. However, social media’s long hours lead to private content exposers to the public (Saravanakumar & Deepa, 2016; Blasbalg et al., 2012).
Demirtepe-Saygili (2020) defined social media addiction as “a subtype of internet addiction, including the behaviour of checking and updating”. Individuals with social media addiction are often overly concerned about social media and are driven by an uncontrollable urge to log on to and use social media (Andreassen & Pallesen, 2014). Studies have shown that the symptoms of social media addiction can be manifested in mood, cognition, physical and emotional reactions, and interpersonal and psychological problems (Balakrishnan & Shamim, 2013; Błachnio, Przepiorka, Senol-Durak, Durak, & Sherstyuk, 2017, Anazonwu, .Onyemaechi & Uzuh, 2019).
Perceived attractiveness is traditionally defined in social psychology as a positive attitude or evaluation regarding a particular person, including the three components conventionally ascribed to attitudes: behavioral (tendency to approach the person), cognitive (positive beliefs about the person), and affective (positive feelings for the person). Within the study of social psychology, attractiveness is related to how much one likes or dislikes another person (Ranjbartabar, Richards, Bilgin, & Kutay, 2019). It can be viewed as force acting between two people that tends to draw them together and to resist their separation. When thinking about attractiveness, one must refer to the qualities of the attracted and those of the attractor to achieve predictive accuracy. It is suggested that to determine attractiveness, both the personalities and the situation must be taken into account (Mohammadi, Gregory, Thelwall, & Barahmand, 2020). The outcome of this paper will establish the healthy social interaction among students and its link with social media addiction, and perceived attractiveness. Its findings will help the students to know the importance of healthy social interaction in their lives and academic orientation. It will encourage parents and lecturers to promote favourable healthy social interaction with students. It will also motivate the students to healthy social interaction as something universal and not as an obstacle or a stumbling block to their social life. The study is also hoped to benefit universities management, especially those that are interest in its students’ healthy social interaction, with this they will know how to organize programmes that will train the students on how to relate with people around. The study is hoped to benefit the society by promoting good ethical conduct among students and to assist in disseminating durable, sustainable and moral values that foster meaningful models for students.
This paper investigated social media addiction and perceived attraction as correlates of healthy social interaction among university students. The results of the study indicated that social media addiction factors like conflict, mood modification had no correlation with healthy social interaction, occupation factor indicated positive significant correlation with healthy social interaction, and relapse factor had negative significant correlation with healthy social interaction. Perceived attractiveness factor like social attraction did not correlate with healthy social interaction. Conversely, physical attractions of perceived attractiveness significantly correlate with healthy social interaction. Further, task attraction showed negative correlation with healthy social interaction.
Empirical review
Social Media addiction and Healthy Social Interaction
Ciacchini et al. (2023) explored the psychological correlates of social media and internet problematic use in Pisa, Italy. A cross-sectional study was conducted in a sample of secondary school students (N = 258); participants were asked to complete an online survey, investigating social media addiction (BSMAS), self-esteem (RSES), feelings of isolation (CSIQ-A) and anxiety (STAI-Y). Data analysis (descriptive statistics, correlational and regression analyses) was conducted through XLSTAT software ©. An additional ad hoc questionnaire was administrated. Findings showed that the 11% of the participants were significantly addicted to social media, mostly females (59%). Gender represented an exposure factor for the hours spent on social media and the checking activity while performing other daily activities. Significant correlations emerged between the self-report measure of social media addiction and self-esteem and anxiety. Low scores at RSES corresponded to higher checking activity, hours spent on social networks, and playing videogames that were investigated as supplementary indicators of addiction with ad hoc questionnaire. The regression analysis showed just two predictors of social media addiction, gender (female) and trait anxiety.
Kolhar, Kazi, and Alameen (2021) investigated the purposes for which social networking sites are used and their effects on learning, social interaction, and sleep duration. A cross-sectional study was conducted among 300, 17–29-year-old female students at Prince Sattam bin Abdul Aziz University. A questionnaire was used to collect data. Chi-squared (Fisher’s exact test) test was used to analyze the data. The results showed that 97% of the students used social media applications. Only 1% of them used social media for academic purposes. Whereas 35% of them used these platforms to chat with others, 43% of them browsed these sites to pass time. Moreover, 57% of them were addicted to social media. Additionally, 52% of them reported that social media use had affected their learning activities, 66% of them felt more drawn toward social media than toward academic activities, and 74% of them spent their free time on social media platforms. The most popular applications (i.e., based on usage) were Snapchat (45%), Instagram (22%), Twitter (18%), and WhatsApp (7%). Further, 46% and 39% of them reported going to bed between 11 pm and 12 am and between 1 am and 2 am, respectively. Finally, 68% of them attributed their delayed bedtime to social media use, and 59% of them reported that social media had affected their social interactions.
Cao, Gong, Yu, and Dai (2020) explored the formation of social media addiction considering the perspectives of users and social media per se on the basis of extended motivational framework and attachment theory. The study investigated the formation of social media addiction with particular focus on WeChat. A field survey with 505 subjects of WeChat users was conducted to investigate the research model. Results demonstrated that social media addiction was determined by individuals’ emotional and functional attachment to the platform. These attachments are in turn influenced by motivational (perceived enjoyment and social interaction) and technical (informational support, system quality and personalization) factors.
Abd-Rahman, and Abdul Razak (.2019) examined if the young adult addicted to social media, analyses if social media addiction will affect their emotion and identify their social media level of addiction. The study was conducted in Universiti Teknologi MARA main campus in Shah Alam. The respondents were 380 students from different type of background, education level and faculty in the university. The study used Google Forms as the form of online questionnaires. The study revealed that the student level of addiction was mild and not severe. Majority of the student have more than three social media accounts. The most popular social media that they use was Instagram. They spent more than five hours on their social media a day. Although majority of them said that they are addicted to the internet, but there are no signs they have been addicted. The main reason they use social media was for entertainment. The relationship result between social media usage and social media addiction was not significant. But the result between addiction of social media and effect on emotion was significance.
Robinsonet et at., (2019) identified specific social media behaviors related to major depressive disorder (MDD). Millennials (N = 504) who actively use Facebook, Twitter, Instagram, and/or Snapchat participated in an online survey assessing major depression and specific social media behaviors. Univariate and multivariate analyses were conducted to identify specific social media behaviors associated with the presence of MDD. The results identified five key social media factors associated with MDD. Individuals who were more likely to compare themselves to others better off than they were (p = 0.005), those who indicated that they would be more bothered by being tagged in unflattering pictures (p = 0.011), and those less likely to post pictures of themselves along with other people (p = 0.015) were more likely to meet the criteria for MDD. Participants following 300 + Twitter accounts were less likely to have MDD (p = 0.041), and those with higher scores on the Social Media Addiction scale were significantly more likely to meet the criteria for MDD (p = 0.031). Participating in negative social media behaviors was associated with a higher likelihood of having MDD.
Perceived Attractiveness and Healthy Social Interaction
Hill, Nelson and Perlman (2023) explored influences judgments of physical attractiveness as a comprehensive perspective with implications for mental health in a selective review of previous research, plus new analyses of data from three previously published studies: The Boston Couples Study, the Multiple Identities Questionnaire, and the Intimate Relationships Across Cultures Study, with implications for mental health. Self-ratings of attractiveness are inflated by self-esteem and confidence in self-halo effects. Partner-ratings are inflated by love and relationship satisfaction in partner-halo effects. Positive responses from others influence attractiveness-enhancing cycles, while negative responses influence attractiveness-deprecating cycles, with impacts on well-being. These influences are represented in a comprehensive Attractiveness Halo Model, which identifies Ten Components of Attractiveness that were inter-related, including physical, emotional, sexual, sensory, intellectual, behavioural, observer, situation, reciprocity, and time.
Kim, and Yang (2021) explored the mediating effect of life satisfaction on the relation between perceived physical attractiveness and lifestyle of health, making an effort to reach an optimal state in physical, emotional, social, spiritual, and intellectual domains in Korean adults. Four hundred fifty-nine adults in a community setting participated in this cross-sectional study. The results showed positive associations among physical attractiveness, life satisfaction, and health-promoting lifestyle after adjusting for age, gender, marital status, education, and job status. Life satisfaction partially mediated the relationship between perceived physical attractiveness and a higher lifestyle of health (z = 2.80, p = 0.005).
Ames (2020) investigated how physical attractiveness and similarity cues lead to a higher perceived attractiveness in an online dating environment. The data was collected from a total of 150 participants. A Factorial ANOVA showed that the perceived attractiveness was higher when profile owners were highly physically attractive. Also, profiles that contained similarity cues were perceived as higher physically and socially attractive but did not affect the intention to like a profile. Moreover, there was no interaction effect between the physical attractiveness of a profile owner and similarity cues on perceived attractiveness. Thus, average attractiveness does not trigger additional impression formation processes in order to reduce uncertainty about profile owners. Instead, people seem to form separate impressions based on physical and social cues in an online dating profile.
Yeh et al., (2020) explored the factors determining social interaction and loyalty to real estate agents. Based on the past literature regarding the factors of loyalty, the study considers physical attractiveness and intellectual competence combined with a traditional loyalty model in proposing its conceptual framework. It then estimates the relevant parameters using a linear structural equation model (SEM). The subjects of the study consist of consumers in Kaohsiung City, Taiwan, aged at least 20 years’ old who have experience in engaging the services of real estate companies during housing transactions. A total of 300 questionnaires were distributed, with 268 valid ones being returned, for a valid return rate of 89.33%. According to the empirical results, physical attractiveness indirectly influences satisfaction through trust and intellectual competence, with satisfaction in turn affecting loyalty. The effect of physical attractiveness on satisfaction through trust was more significant than its effect on satisfaction through intellectual competence. These findings show that the relationship among physical attractiveness, intellectual competence, and trust plays an important role in determining satisfaction and loyalty
Shafiq, and Arshad (2020) investigated the role of physical attractiveness and personal connection during the service encounter in Punjab. The survey strategy was exercised in data collection of 180 responses for hypotheses testing. Results show that physical attractiveness and personal connection have an absolute influence on consumer response. Social interaction and gratification motivation played successful mediating roles between them. Service expertise bound the influence of physical attractiveness on social interaction.
Summary of Literature Reviewed
Conceptually, the study factors (social media addiction, perceived attraction, and healthy social interaction) were explained in the following order: definition, components, and possible impact on the factors. Theoretically, four theories were reviewed first, self-expansion theory by Aron and Aron (1986) that suggests that people form and maintain social relationships because they are motivated to expand their sense of self (Aron & Aron, 1986). Aron and Aron (1986) claim that expanding the sense of self through new experiences is a fundamental human motivation and the basic reason for entering relationships. Second, uses and gratifications theory that states that people are motivated to seek out forms of media to satisfy their psychological and social needs (West & Turner, 2007, Onyemaechi, 2025). Third, media dependency theory by Sandra BallRokeach and Melvin Defleur outlines three relationships that lay the framework for media dependency; these include society vs. media, media vs. audience and society vs. audience. Users must engage in each of these model relationships to meet their needs. Fourth, balance theory by Heider (1958) that proposed that in order to understand attraction, it is necessary to focus on the individual’s perception of a relationship rather than the objective realities. Empirically, studies reviewed, but none was able to link the study variables together.
METHOD
Participants
The participants comprised 123 students drawn Nnamdi Azikiwe University, Awka, Anambra State. The participants comprised 66(53.7%) males, and 57(46.3%) females. The participants’ age ranged from 17 to 27. The mean age was 23.44, and standard deviation was 1.87. Department data revealed that 61(49.6%) were drawn from Psychology, 38(30.9%) were drawn from Sociology, 16(13.0%) were drawn from Political Science, and 8(6.5%) were drawn from Economics. Level data revealed that 2(1.6%) were Year One, 33(26.8%) were Year Two, 33(26.8%) were Year Three, and 55(44.7%) were Year Four. Accident sampling technique was used to select the participants because the students that participated in the study were sampled via availability, accessibility, and willingness.
Instruments
Three instruments were used: Interaction Rating Scale Advanced- Brief, Social Media Addiction Scale, and Perceived Attractiveness Scale.
Interaction Rating Scale Advanced- Brief by Anme et al. (2013)
The IRSA-Brief scale 39 items designed to measure self-control,” “expressivity,” “sensitivity,” “assertiveness,” “responsiveness,” and “regulation”. The scale has three subscales: cooperation, self-control and assertion. The total score range was from 0 to 39 scores for the impression items and the overall impression item were on a five-point scale: 1 = not evident at all, 2 = not clearly evident, 3 = neutral, 4 = evident, 5 = evident at high level. The scale has internal consistency, Cronbach’s alpha of 0.84 for the overall scale, for the subscales 0.66 for cooperation, 0.67 for self-control, and 0.75 for assertion. Inter-observer reliability was found to be 90%.The researcher conducted a pilot test with 74 university students and reported Cronbach alpha of 0.79.
Social Media Addiction Scale by Tutgun-Ünal, and Deniz (2015)
The scale contain 41 items designed to measure internet addiction and social media use. The scale has four subscales: Conflict (19 items), Occupation (12 items), Mood Modification (5 items), and Relapse (5 items). SMAS is a five point likert scale graded with the frequency expressions in the range of “Always” “Often”, “Sometimes”, “Rarely”, and “Never” and the highest point to be taken from the whole of the scale is 205 and the lowest point is 41. In order to help the interpretation of the points taken from SMAS, the range of the points to be taken from the scale were detected and range coefficients were calculated in accordance with five point likert scale. Accordingly, from 41to 73 means “No Addiction”, from 74 to 106 means “Less Addicted”, from 107 to 139 means “Moderate Addicted”, 140 to 172 means “High Addicted” and from 173 to 205 means “Very High Addicted”. The scale has Cronbach alpha of 0.96 for Conflict0.93 for Occupation,0.89 for Mood Modification, and 0.91 for Relapse, while 0.97 for the SMAS. The researcher conducted a pilot test with 74 university students and reported Cronbach alphas of 0.863 for Conflict, 0.827 for Occupation, 0.93 for Mood Modification, and 0.92 for Relapse.
Perceived Attractiveness Scale developed by Mccroskey, and Mccain (1972)
The scale contain 18 items designed to assess how people are attracted to one another, the more they will communicate with each other; and how they are attracted to another person, the more influence that person has on us in interpersonal communication. The scale has three subscales: Task, social, and physical attraction. The instrument offered a five point strongly agree-strongly disagree response field. The Cronbach alphas are as follows: 0.86 for social attraction, 0.81 for physical attraction, and 0.84 for task attraction. The researcher conducted a pilot test with 74 university students and reported Cronbach alphas of 0.79 for Social attraction, 0.65 for Physical Attraction, 0.95 for Task.
Procedure
The researcher conducted a pilot test to before adopting the instruments for the study. The participants for the study were recruited through assistants of the class representative that enable him to distribute the questionnaires. These class representatives were debriefed on how to administer and guide the participants to respond to the questionnaires. After the debriefing, the researcher and the assistants approach the students, and explain the purpose of the study, before administering the copies of the questionnaire. On the whole 130 copies of questionnaire were administered, but 123 were properly answered. Ethically, the participants were appropriately debriefed about the study and the right they have to withdraw from the study. Participants were allowed to participate in the study after they have signed informed consent form indicating their approval to participate in the study. And those who signed the form were allowed to be part of the study participants were assured of confidentiality and anonymity of their names, age, and information they provided at the course of the study.
Design and Statistics
The study adopted cross-sectional and correlational design for the study because the objective of the study is to establish the relationship that exists between social media addiction and perceived attraction as correlates of healthy social interaction. Pearson Product Moment Coefficient analysis was used in testing the correlation of the variables in the study (social media addiction, and perceived attraction as correlates of healthy social interaction).
RESULT
Descriptive and Pearson Product Moment Coefficient Statistics Table of Social Media Addiction, Perceived Attractiveness, and Healthy Social Interaction
| Sources | Mean | Std.D | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| 1. Social Interaction | 86.53 | 11.60 | 1 | |||||||
| 2. Conflict, SMA | 30.79 | 2.95 | -.17 | 1 | ||||||
| 3. Occupation, SMA | 21.21 | 2.39 | .35** | .48** | 1 | |||||
| 4. Mood modificat., SMA | 8.98 | .94 | .15 | -.39** | -.06 | 1 | ||||
| 5. Relapse, SMA | 9.27 | 1.61 | -.31** | -.53** | -.35** | .85** | 1 | |||
| 6. Social Attraction | 8.23 | 1.73 | .02 | .87** | .42** | -.48** | -.69** | 1 | ||
| 7. Physical Attraction | 9.85 | 1.63 | .35** | .02 | .31** | -.79** | -.80** | .20* | 1 | |
| 8. Task Attraction | 10.00 | 1.38 | -.87** | -.22* | -.65** | -.20* | .32** | -.32** | -.20* | 1 |
Results from the table above indicated that social media addiction dimensions such as conflict at -.17(M: 30.79, Std.D: 2.95) and mood modification at .15(M: 8.98, Std.D: .94) had no correlation with healthy social interaction. More so, social media addiction dimension like occupation at .35** (M: 21.21, Std.D: 2.39) had positive correlation with healthy social interaction, while relapse dimension at -.31** (M: 9.27, Std.D: 1.61) had negative correlation with healthy social interaction.
On the other hand, social attraction of perceived attractiveness at .02 (M: 8.23, Std. D: 1.73) had no correlation with healthy social interaction, while physical attraction of perceived attractiveness at .35** (M: 9.85, Std.D: 1.63) had positive correlation with healthy social interaction, and task attraction of perceived attractiveness at -.87** (M: 10.00, Std.D: 1.38) had negative correlation with healthy social interaction.
Summary of Findings
- Social media addiction factors like conflict, mood modification had no correlation with healthy social interaction, occupation factor indicated positive significant correlation with healthy social interaction, and relapse factor had negative significant correlation with healthy social interaction.
- Perceived attractiveness factor like social attraction did not correlate with healthy social interaction. Conversely, physical attractions of perceived attractiveness significantly correlate with healthy social interaction. Further, task attraction showed negative correlation with healthy social interaction.
DISCUSSION
The first hypothesis which stated that social media addiction will significantly correlate with healthy social interaction among students was accepted partly because social media addiction factors like conflict, mood modification had no correlation with healthy social interaction, occupation factor indicated positive significant correlation with healthy social interaction, and relapse factor had negative significant correlation with healthy social interaction. This means that increase in occupation means increase in healthy social interaction, while decrease in relapse means increase in healthy social interaction. This affirmed Cao, Gong, Yu, and Dai (2020) study that demonstrated that social media addiction was determined by individuals’ emotional and functional attachment to the platform. These attachments are in turn influenced by motivational (perceived enjoyment and social interaction) and technical (informational support, system quality and personalization) factors. This indicates that students who are more bothered by being tagged in unflattering pictures, and those less likely to post pictures of themselves along with other people were more likely to meet the criteria for healthy social interaction. Hence, students following 300 + Twitter accounts were less likely to have healthy social interaction, and those with higher scores on the Social Media Addiction were significantly more likely to meet the criteria for healthy social interaction (Onyemaechi,, Okpaleke & Nwankwo 2023; Okonkwo et. al 2023). This means that students in negative social media behaviors were associated with a higher likelihood of having less healthy social interaction (Robinsonet et at., 2019; Onyemaechi, et al., 2022). Theoretically, these demonstrate the power of agenda-setting through trending stories and tweets, etc. However, an increasing amount of people seem to be relying on social media as a news source, giving social media platforms and the people they follow the power to set the agenda. Since attitude formation is a large part of celebrity interaction on social media; people form opinions on products and services, etc. when they are more widely displayed on social media or posted about by a celebrity figure. Therefore, applying media dependency theory suggests that the more dependent a student is on social media, the greater number of opinions they will form about products and services that appear on their feed more often (Onyemaechi, Unnadike, Izuchukwu, Onwusobalu, Umenweke, 2022).
Second hypothesis which stated that perceived attractiveness will significantly correlate with healthy social interaction among students was confirmed because perceived attractiveness factor like social attraction did not correlate with healthy social interaction. Conversely, physical attractions of perceived attractiveness significantly correlate with healthy social interaction. Further, task attraction showed negative correlation with healthy social interaction. This shows that in physical attraction means increase healthy social interaction, whereas decrease in task attraction means increase healthy social interaction. This is in line with the notion that physical attractiveness indirectly influences interaction through trust and intellectual competence, with satisfaction in turn affecting loyalty. However, the effect of physical attractiveness on healthy social interaction through trust was more significant than its effect on satisfaction through intellectual competence (Yeh et al., 2020; Onyemaechi, Okere, Chukwuemeka, & Nnaemeka, 2017). By implication this denotes that positive responses from others influence attractiveness-enhancing cycles, while negative responses influence attractiveness-deprecating cycles, with impacts on healthy social interaction (Hill, Nelson & Perlman, 2023). Theoretically, this supported Aron and Aron (1986) claims that expanding the sense of self through new experiences is a fundamental human motivation and the basic reason for entering into healthy social interaction. By including others’ knowledge, skills, perspectives, and resources in the self, people can expand their sense of efficacy in the world. Since people enter interaction because they want to expand the self by incorporating new knowledge, skills, ideas, attractiveness, and so forth.
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