Personal Profiles, Family Environment, Patterns of Smartphone Use, Nomophobia, and Smartphone Addiction across Low, Average, and High Perceived Academic Performance Levels among High School Students in the Philippines

(1) Background: Problematic smartphone use in adolescents has become a major concern among parents and educators. This study aimed to determine the factors associated with, and the predictors of, low, average, and high perceived academic performance (PAP). (2) Methods: Descriptive and comparative analyses were employed in this cross-sectional study among 3374 Filipino high school students through an online Google forms survey. (3) Results: We found that age, grade level, father’s education, time spent daily on weekends, frequency of use on weekdays, purpose of use, nomophobia (NMP), and smartphone addiction (SA) were significantly associated with low PAP, while frequency of use on weekends and type of internet access had a significant association with high PAP. Gender was a significant predictor of low, average, and high PAP. Father’s education and SA were also significant predictors for both low and average PAP. (4) Conclusions: This study shows the significant association between personal profiles, family environment, patterns of smartphone use, NMP, and SA contributing to a significant impact on Filipino high school students’ PAP. This suggests that proper guidelines for smartphone use should be provided at home and in school settings to raise awareness of the adverse effects of SA on students’ academic performance.

Studies that deal with the effects of smartphone use on academic performance have been conducted from various perspectives. Some have examined learning activities through smartphone use and found a lower grade point average (GPA) and cumulative GPA (CGPA) among students who often used their smartphones' for learning [18,19], whereas others have examined different smartphone functions' effect on academic performance [6]. Additionally, other works have determined the associations of time spent on smartphones [14], task-technology fit (TTF) [20], students' self-control [21], behavioral intention in using smartphones [22], personal traits and mobile activities [23], fear of missing out (FOMO) [16], social media use [24], nomophobia (NMP), and SA [25] with academic performance.
As such, it seems that smartphone use can be a threat to students' scholastic performance, particularly when the use of it becomes excessive [11], as this can lead to NMP and Patterns of smartphone use were found to be associated with NMP and SA, and these associations differed depending on demographics such as age, gender, and family environment. For instance, a previous study found age to be negatively associated with addictive behavior in smartphone use [42]. Furthermore, females manifested a greater likelihood of spending more time on their phones than males [43]. Additionally, people with lower education levels [3] or in lower age brackets [44] were more likely to manifest symptoms of SA.
Previous studies also claimed that NMP and SA are closely associated with each other [25,45,46], signifying that factors associated with NMP can also be factors of SA. For instance, [25] observed that adolescents with SA also showed nomophobic behaviors, and later found a positive correlation between nomophobic behaviors and social media addiction. Adolescents' family environments also play a very important role in shaping their behaviors towards smartphone use [47]. A study among Korean adolescents found that SA is significantly associated with two-parent and double-income households as well as dysfunctional families exposed to domestic violence and parental addiction [47]. Additionally, family environments where adults frequently use their mobile devices could also lead to increased smartphone use among youngsters [48].
With regards to academic performance, it was found that having a strong family background and good education facilities could help enhance students' performance [49]. Furthermore, parents' educational background was also found to be associated with students' academic performance [50], and broken families were significantly associated with lower academic achievement; these findings suggest that family structure is a significant factor in adolescents' perceived academic performance (PAP) [51]. In addition, family size was found to be associated with low academic performance among students and with parents from low income households who struggle to pay school fees [49].
In a study on high school students, [52] determined the duration of smartphone ownership to be one of the influencing factors for NMP. In addition, [53] found a significant association of NMP with age, gender, duration, and frequency of smartphone use, social network sites (SNS) use, checking smartphones for no reason, and checking smartphones directly after waking up in the morning. Similarly, [25] identified gender, parents' education levels, information and communication technology (ICT) use levels, duration and frequency of smartphone use, purpose, smartphone experience, and academic achievement as being significant predictors of both NMP and SA. Additionally, previous studies found high frequency and duration of smartphone use akin to SA severity [54,55], and the duration of SNS use and frequency of phone calls and text messages were found to be predictors of mobile phone addiction [43]. Other studies pointed out mental factors such as selfesteem, extraversion, conscientiousness, and emotional stability as significant predictors of NMP [56].
Thus, most previous studies agree with the notion that demographics (i.e., personal profiles and family environment) and patterns of smartphone use are significantly associated with NMP and SA and can negatively affect students' academic performance. However, most previous studies have examined the adverse effects of the above-mentioned variables on academic performance based on students' GPAs, while studies determining students' self-PAP in relation to these factors remain scarce. To address these gaps, this study employed a sample of Filipino adolescents (i.e., junior and senior high school students) to investigate the association and the predictive capacity of personal profiles, family environment, patterns of smartphone use, NMP, and SA on students' PAP.

Academic Performance and Perceived Academic Performance
Academic performance is measured by evaluating how much has been achieved over a certain period of time [57]. The most common and easy way to evaluate a student's academic performance is by simply determining their GPA, whereby a higher GPA score indicates higher academic performance [58]. Previous studies note that GPA is a significant predictor of academic achievement [59,60]. However, GPA is a representation of academic achievement on a single unidimensional scale and is constructed entirely from course grade information; therefore, it is non-inclusive [61]. In contrast, PAP is a self-evaluation of academic performance that helps us understand how students view their academic achievement (i.e., high, average, low) and how they perceive themselves (i.e., positively or negatively), which relates to their self-esteem [62]. In this study, we asked participants to evaluate their academic performance based on how they perceive the effect of smartphone use on their academic grades.

Conceptual Framework
The concept of social cognitive theory is the basis of this study's framework. Social cognitive theory points out that the mutual interaction of one's personal factors, behavior, and environment influences future behavioral performance [63]. This, in turn, relates to behaviorism and the psychodynamic theory [25], in which people with smartphone use disorder believe they can escape negative emotions [25] such as loneliness and shyness [26] through smartphone use. Thus, according to [64], problematic smartphone use combines personal, cultural, environmental, and emotional factors. As the purpose of this study is to examine whether personal profiles (i.e., demographics), family environment (environmental), patterns of smartphone use, NMP, and SA (behavioral) are associated with PAP, we hypothesize that gender, age, grade level, high school level, parents' education and marital status, family income, family size, duration of time from waking up until first smartphone use, duration and frequency of smartphone use on weekdays and weekends, years of smartphone experience, type of internet access, purpose of use, survival days without a smartphone, NMP, and SA significantly predict low, average, and high PAP. Figure 1 shows the research model of this study including the variables details.
(environmental), patterns of smartphone use, NMP, and SA (behavioral) are associated with PAP, we hypothesize that gender, age, grade level, high school level, parents' education and marital status, family income, family size, duration of time from waking up until first smartphone use, duration and frequency of smartphone use on weekdays and weekends, years of smartphone experience, type of internet access, purpose of use, survival days without a smartphone, NMP, and SA significantly predict low, average, and high PAP. Figure 1 shows the research model of this study including the variables details.

Participants and Design
This cross-sectional method used convenience sampling to gather the data, which were collected from 11 schools in the Philippines. Participants were limited to Filipino high school students aged between 13 and 18 years old (i.e., from grades 7 to 12) who attended school at the time the study was conducted (during the 2019-2020 academic year, which started in July 2019 and ended in February 2020). A total of 3374 junior and senior high school students voluntarily participated in this study through an online Google Forms survey.

Procedure
Participants were provided with an informed consent form for them to sign after reading and understanding the purpose of the study, in which they were also assured that their responses would be confidential. After obtaining permission from the school administrators to use the school facility (i.e., computers in the computer rooms), the online survey was immediately launched, with simple tokens (i.e., chocolates, snacks, or candy) given immediately after the survey.

Participants and Design
This cross-sectional method used convenience sampling to gather the data, which were collected from 11 schools in the Philippines. Participants were limited to Filipino high school students aged between 13 and 18 years old (i.e., from grades 7 to 12) who attended school at the time the study was conducted (during the 2019-2020 academic year, which started in July 2019 and ended in February 2020). A total of 3374 junior and senior high school students voluntarily participated in this study through an online Google Forms survey.

Procedure
Participants were provided with an informed consent form for them to sign after reading and understanding the purpose of the study, in which they were also assured that their responses would be confidential. After obtaining permission from the school administrators to use the school facility (i.e., computers in the computer rooms), the online survey was immediately launched, with simple tokens (i.e., chocolates, snacks, or candy) given immediately after the survey. This questionnaire includes demographic information (i.e., personal profiles) such as gender, age, grade level, high school level, parents' education, family size, family income, and patterns of smartphone use (including the time gap from waking up until first smartphone use, frequency and duration of smartphone use during weekdays and weekends, years of smartphone experience, type of internet access, purpose of use, and survival days without a smartphone). Moreover, the participants were evaluated on whether they believed their smartphone use affected their academic performance by being asked whether their grades were "low," "average" or "high" because of smartphone use. Thus, the students' self-PAP was taken as the dependent variable.

Nomophobia (NMP-Q Scale)
Developed in 2015, the NMP-Q scale consists of 20 questions pertaining to the following four dimensions: not being able to communicate (6 items), not being able to access information (4 items), losing connectedness (5 items), and giving up convenience (5 items). Responses to each item were recorded on a 7-point Likert scale that ranged from 1 (strongly disagree) to 7 (strongly agree) [29]. Total scores were computed and classified as follows: absence of NMP (20), mild level of NMP , moderate level of NMP (60-99), and severe level of NMP (100-140). In this study, Cronbach's alpha was 0.916, and the following coefficients emerged for its subscales: not being able to communicate = 0.857, losing connectedness = 0.838, not being able to access information = 0.697, and giving up convenience = 0.743.

Smartphone Addiction Scale-Short Version
The short version of the SA scale (SAS-SV) [3,65] was used to measure participants' SA. Measured on a 6-point Likert scale, the answers of this 10-item questionnaire ranged from 1 (strongly disagree) to 6 (strongly agree) [3,65]; the cut-off scores were 31 and 33 for boys and girls, respectively [65]. The reliability score for this scale was a Cronbach's alpha of 0.831.

Statistical Analyses
All analyses in this study were conducted using SPSS version 23 (SPSS Inc., Chicago, IL, USA) for Windows [66]. The main statistical method used in this study was a multiple linear regression analysis in which the PAP groups (i.e., low, average, and high) were the dependent variables, and the variables for personal profiles (i.e., age, gender, grade level, and high school level), family environment (i.e., parents' education and marital status, family income type, and family size), and patterns of smartphone use (i.e., the time gap from waking up until first smartphone use, frequency and duration of smartphone use on weekdays and weekends, years of smartphone experience, type of internet access, purpose of use, and survival days without a smartphone) were the covariates. Additionally, a Pearson correlation analysis was used to explore the relationships between the variables, and a chi-square and one-way ANOVA were used to explore the differences between students across low, average, and high PAP groups.

General Characteristics of Variables
This study also reported that 42.1% (n = 1422) of participants had been using smartphones for the last 3 to 6 years, with an average of 4.90 years of smartphone experience. The largest portion of time gap from waking up until the first smartphone use was within 5 min, as reported by 40.5% of participants (n = 1367). Furthermore, participants spent an average of 8.87 and 9.91 h a day on their smartphones during the week and weekends, respectively. Concerning the frequency of use, participants used their smartphones 20 times or less at an average frequency of 8.98 and 10.24 times a day on weekdays and weekends, respectively. With regard to the type of internet access, 54.4% of participants reported having "Wi-Fi," while 27.5% indicated using a "prepaid internet card." The top three purposes of smartphone use were accessing social network sites (SNS) (n = 1700, 50.4%), online chatting (n = 562, 16.7%), and playing games (n = 382, 11.3%). When asked how many days they could survive without a smartphone, 59.7% (n = 2105) of participants indicated "three days or less." Lastly, when participants were asked how their smartphone use affected their academic grades, 60% (n = 2023) indicated that their grades were "average," while 23% (n = 777) and 17% (n = 574) answered "high" and "low," respectively.

Discussion
The purpose of this study was three-fold. First, it aimed to determine the factors that are associated with PAP. Second, it explored the differences between students across low, average, and high PAPs with regard to their personal profiles, family environment, patterns of smartphone use, NMP, and SA. Finally, this study examined the predictive factors of low, average, and high PAP.
We found that low and high PAP scores were significantly associated with gender, high school level, mother's education, and years of smartphone experience. Age, grade level, father's education, daily time spent using smartphones on weekends, frequency of use of smartphones on weekdays, purpose of use of smartphones, NMP, and SA were significantly associated with low PAP, whereas frequency of use on weekends and type of internet access were revealed to have a significant association with high PAP. The results suggest that PAP scores are influenced by these variables. A previous study found that more mature university students (i.e., those aged 23 and over) scored higher in Revised Approaches to Studying Inventory (RASI) orientation than those in lower age groups [70], thereby suggesting an increase in academic performance with an increase in age. Our finding of a significant association between age, grade level, and low PAP coincides with other papers' findings that high school students' age has a significant effect on their academic performance [71]. Moreover, our study supports previous findings that parents' educational backgrounds are correlated with students' academic performance [50], which can be positively influenced by both family income (i.e., father's income) and parents' education levels [49].
It is interesting to note that this study found that there was a significant negative association between daily time spent on smartphones on weekends (i.e., 10 h on average), the frequency of use on weekdays (i.e., 20 times or less each day), and low PAP. Moreover, high PAP was significantly and positively associated with frequency of use on weekends (i.e., 20 times or less per day). These results indicate that the likelihood of having low PAP decreases as the duration of smartphone use on weekends and frequency of smartphone use on weekdays and weekends increase, which also signify that participants with high duration and frequency of smartphone use and longer experience with smartphone use are more likely to have better perceptions about their academic achievement; this is inconsistent with findings from a recent study on Chinese adolescents' poor academic performance due to prolonged smartphone use [72].
It seems that for Filipino high school students, smartphone use gives them the confidence to perform well in their studies. For example, perhaps they used smartphone apps for learning, which could effectively enhance productivity and academic performance [73], as well as increase the likelihood of positively perceiving their academic improvement [22]. Applying the same logic, Singaporean university students who used smartphones for learning purposes reported having higher GPA scores [74]. In this study, accessing SNS or social media was the most common purpose of smartphone use. According to studies on SNSs [75,76], Twitter gave students more freedom to ask questions and have discussions that are helpful for enhancing students' engagement and academic achievement [75]. Similarly, Facebook use helped promote co-curricular activities, which can lead to academic success and boost individual well-being [76].
Our findings also suggested that having more years of smartphone experience (i.e., 5 years on average) was positively associated with high PAP. This indicates the possibility of students with more years of smartphone experience or ownership having more positive perceptions about their academic performance. To the best of our knowledge, no study has examined this relationship so far. However, a study among Turkish high school students found a positive correlation between duration of smartphone ownership and FOMO [77]. As mentioned earlier, students these days use smartphones for academic learning purpose [73], thus the longer they own a smartphone, the more academic learning enhancement they benefit from; this, in turn, goes some way to explaining why they feel anxious when smartphones are inaccessible. Furthermore, we found that the purpose of use (i.e., SNS) was associated with low PAP. This suggests that the use of SNS as the purpose of smartphone use is associated with students' poor perceptions of academic performance. This is in line with previous findings stating that the addictive use of social media leads to low self-esteem or negative self-evaluation [78]. Additionally, studies in the past noted that SNS use distracts students' cognition and affects academic performance [79,80].
Furthermore, NMP and SA were found to be positively associated with low PAP, thereby suggesting that students perceive their academic performance to be poorer as their levels of NMP and SA increase. These findings are consistent with the results of a systematic review about the adverse effects of NMP on academic performance [81] and a study among nomophobic university students that demonstrated weak academic performance [82]; similarly, a study among Turkish undergraduate students and other selected university students found that there was a negative relationship between academic performance and SA [1,16], as well as between students' in-class smartphone use and academic grades [83]. As for adolescents and children, a study of screen-based activities (i.e., social media use) also found it to be negatively associated with academic performance [84].
We also found a significant difference between low, average, and high PAP in terms of gender, age, grade level, high school level, mother's education, father's education, time spent daily using smartphones on weekdays, frequency of use of smartphones on weekdays, years of smartphone experience, type of internet access, survival days without a smartphone, and SA. Surprisingly, participants in the high PAP group spent a significantly longer time using their smartphones during weekdays, and had higher frequency of smartphone use on weekdays, and longer years of smartphone use experience than those in the average and low PAP groups. Again, these findings indicate a better PAP when high school students consistently use smartphones for learning purposes, as discussed earlier [22,[72][73][74][75][76]. In addition, participants in the low PAP group had significantly higher levels of smartphone addiction, which again confirms the positive association between SA and low PAP [1,16,83].
Participants in the high PAP group reported significantly lower survival days without a smartphone than those in low and average groups. The majority (60%) of the participants in this study indicated being able to survive for up to 3 days without their smartphones. This supports a recent survey in the Philippines, which reported that one out of three Filipinos could not survive without a smartphone [40]; Similar results were also found in the Australian context [85], which indicated that not being able to use a smartphone may lead to NMP [26][27][28][29] and FOMO [86].
Furthermore, we found that gender was a significant predictor of low, average, and high PAP, which is in line with previous findings that suggested that gender is an important factor in academic grades (whereby women are more motivated in terms of academic achievements than men) [87]. The education level of fathers and SA were also significant predictors for both low and average PAP. These are consistent with previous studies that found a significant relationship between parental educational levels and academic performance of students [88], as well as the possibility of fathers' academic efficacy enhancing academic performance, especially for girls [89]. Other studies have also concluded that SA is a predictive factor for academic performance [16], and there is a significant association between problematic smartphone use and lower GPAs or worse academic performances [12].
In addition, family size and type of internet access were significant predictors of average and high PAP levels. This indicates that family size (i.e., average size of 5.53) and the way students access the internet influence their PAP. A study among Nigerian students found a significant relationship between family size and academic performance [88]. A study conducted among postsecondary level students also found that those who have access to websites at school (regardless of the type of access) and made use of the tools for e-learning performed better in their examinations [90]. Furthermore, age, grade, frequency of smartphone use on weekdays, and purpose of use were significant predictors of low PAP. In other words, high school students' (who were at an average age and grade level of 14.76 and 9.16, respectively) perceptions of academic performance are significantly impacted when they use their smartphones at least 20 times a day on weekdays and primarily for SNS.
Another study was conducted examining the effect of TTF of smartphones on PAP and smartphone use among Korean college students [20], and it was found that the TTF of smartphones directly influenced the impact of students' PAP and indirectly influenced their attitude toward smartphone use [20]. To the best of our knowledge, no studies have examined the impact of frequency and purpose of smartphone use on students' PAP. Nonetheless, in a study among Turkish adolescents, school achievement was found to be a significant factor for problematic smartphone use or SA [25], suggesting that smartphone use impacts students' academic performance. This confirms previous findings that there are significant associations between smartphone use and students' exam results [9], frequency of smartphone use and academic success [7], and higher smartphone use and poor academic performance [14].
The purpose of smartphone use (i.e., SNS) significantly predicted low PAP in the sense that they were positively associated with each other, which is again consistent with previous findings that there was a negative association between social media use and academic performance [24,84]. Moreover, in a study among undergraduate students in Singapore, mobile phone activity (i.e., improper use of smartphones) was found to be a critical predictive factor that mediated the relationship between smartphone dependency and GPA scores [23]. However, [23] pointed out that the effect of social media use on students' GPAs was not as bad as the effect of playing video games. Thus, personal traits (i.e., self-control and self-efficacy) help students to effectively handle smartphone use in order to achieve better academic performance [21] and to enhance their positive perceptions of their own academic performance [22].

Conclusions
This study clearly revealed the significant association between personal profiles, family environment, patterns of smartphone use, NMP, and SA, and students' low and high PAP. Our findings suggest that Filipino high school students with high smartphone use perceived their academic performance to be better. However, given that frequency of smartphone use on weekdays, purpose of use, and SA significantly predict low PAP, we conclude that problematic use of smartphones impacts how Filipino high school students perceived their academic performance.

Implications
This study found a high percentage of NMP and SA rates among participants, which indicate a high level of smartphone dependence. Despite the likelihood of high PAP when smartphone use increases, proper guidelines on smartphone use should be provided at home and in school to raise awareness of the adverse effects of SA on students' academic performance.

Limitations and Future Directions
Despite its contributions, this study has some limitations: first, as this is a crosssectional study, it is difficult to determine the cause and effect relationship. To address this issue, it is recommended that a longitudinal research design should be employed. Second, this study uses a non-probability convenience sampling method in which we cannot generalize the results to the entire population. To ensure that the sample is representative of the overall population, a probability sampling method should be used. Third, our participants consisted of high school students. Future research should include a comparative study between NMP, SA, and PAP among participants with different levels of education (i.e., elementary, undergraduate, and graduate school students). Furthermore, data on patterns of smartphone use, such as duration and frequency of smartphone use on weekdays and weekends, were collected through self-reports. This raises the issue of sincerity and accuracy of the reported hours and frequency. To avoid this in future studies, a smartphone app should be used to keep record of the actual daily duration and frequency of smartphone use in order to obtain accurate smartphone usage data. Finally, PAP focuses more on how the participants evaluate their scholastic performance, which also paves the way for examining their self-esteem, and thus results cannot be compared with previous studies which used GPA to evaluate participants' academic performance. Thus, in future studies it is recommended to use both PAP and overall GPA to evaluate the impact of demographics, patterns of smartphone use, NMP, and SA on students' academic performance.  Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to confidentiality.