Using the Internet has become one of the most popular leisure activities among postsecondary students in China. Concern about the large number of students using the Internet has led to an increase in research on the influencing factors of Internet addiction and the negative consequences caused by it. This short-term longitudinal study examined the associations among three dimensions of social support [objective support (OS), subjective support (SS), and support utilization (SU)], loneliness, and the four dimensions of Internet addiction (compulsive Internet use [CIU] & withdrawal from Internet addiction [WIA], tolerance of Internet addiction [TIA], time-management problems [TMPs], and interpersonal and health problems [IHPs]) in a Chinese sample. A total of 169 postsecondary first-year students (88 girls and 81 boys; mean age = 18.31 years) participated in the study. The questionnaire measurements were taken at the beginning of the school year (T1), 6 months later (T2), and 1 year later (T3). Cross-lagged and structural equation modeling analyses indicated that (a) OS (T1) and SU (T1) negatively predicted loneliness (T2); and loneliness (T2) negatively predicted OS (T3) and SU(T3); (b) CIU & WIA (T1) and TMPs (T1) positively predicted loneliness (T2); and loneliness (T2) positively predicted CIU & WIA (T3), TIA (T3), TMP (T3), and IHP (T3); (c) SS (T1) directly affected TIA (T3) and TMP (T3); and (d) loneliness (T2) played a mediating role in the relationships between OS (T1) and CIU (T3), OS (T1) and TMP (T3), OS (T1) and IHP (T3), and SU (T1) and IHP (T3). Finally, interventions for Internet addiction and implications for future studies were discussed.
This short‐term longitudinal study examined the reciprocal associations among shyness, interpersonal relationships, and loneliness in a sample of 361 Chinese college freshmen (138 male students, mean age = 18.57 years). A fully cross‐lagged panel design was used in which shyness, interpersonal relationships, and loneliness were assessed at three time points separated by 8 months. The results indicated that the associations among shyness, interpersonal relationships, and loneliness were dynamic and bidirectional. The self‐report scores and the pattern of cross‐lagged associations among shyness, interpersonal relationships, and loneliness were the same for male and female students at all three times. Implications for loneliness interventions and future research directions are provided.
Recently, combined quantitative and qualitative analysis has become popular for research. In studying careers, subjective and objective information are ideal for assessing individual career development and are relevant in career counseling. This paper measures career adaptability by combining text mining and item response theory (IRT), with college students' self-reported career adaptability as a subjective measure and responses to questionnaire items as an objective measure. The two are combined under a Bayesian framework. Additionally, the validity of text categorization and IRT, combined with model measurement, were explored; text categorization results were used as prior information when estimating IRT capability parameters to test whether adding prior information can improve accuracy. This study draws the following conclusions: (1) The text classification method had the highest sensitivity in 300-person samples; however, the text-IRT method had the best predictive effect, high reliability, and unique advantages in accuracy. (2) In 600-person samples, the text classification method had the best predictive effect. The effect was relatively good, with unique advantages in identifying low career adaptability. However, this must be selected according to actual needs. If the accuracy requirement is high and sensitivity can be sacrificed, the text-IRT method is more appropriate. (3) The text-IRT method is more suitable for 900 subjects when accuracy, sensitivity, and specificity need to be considered, and text classification is best when identifying low career adaptability. (4) Sample size influenced accuracy, specificity, and the negative predictive values of text classification, as well as the sensitivity of IRT and text-IRT methods.INDEX TERMS Career adaptability, item response theory, text mining.
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