Early and Dynamic Socio-Academic Variables Related to Dropout Intention: A Predictive Model Made during the Pandemic

Social and academic integration variables have been shown to be relevant for the understanding of university dropout. However, there is less evidence regarding the influence of these variables on dropout intention, as well as the predictive models that explain their relationships. Improvements in this topic become relevant considering that dropout intention stands as a useful measure to anticipate and intervene this phenomenon. The objective of the present study was to evaluate a predictive model for university dropout intention that considers the relationships between social and academic variables during the first university semester of 2020. The research was conducted using a cross-sectional associative-predictive design, with a convenience sampling (n = 711) due to the restrictions of the pandemic period. The results showed a good fit of the proposed hypothetical model that explained 38.7% of dropout intention. Both social support and perceived social isolation predicted the sense of belonging and, through it, engagement. Previous academic performance predicted early academic performance and, through it, engagement. The set of variables predicted the intention to quit through engagement. These results are a contribution both to the understanding of the phenomenon and to guide potential interventions in the early stages of the university experience.

The Association between Oral Health-Related Quality of Life, Loneliness, Perceived and Objective Social Isolation—Results of a Nationally Representative Survey

The aim was to examine the association between oral health-related quality of life and loneliness and perceived as well as objective social isolation. Data were used from a nationally representative survey with n = 3075 (late Summer 2021). The established Oral Health Impact Profile (OHIP-G5) was used to quantify oral health-related quality of life. Moreover, established tools were used to quantify the outcome measures (De Jong Gierveld loneliness scale, Bude/Lantermann scale and Lubben Social Network Scale). It was adjusted for several covariates in regression analysis. Linear regressions showed that low oral health-related quality of life is associated with higher loneliness (B = 0.03, p < 0.001), higher perceived social isolation (B = 0.06, p < 0.001) and higher objective social isolation (B = 0.07, p < 0.05). Further regressions were performed (e.g., stratified by denture usage). Our study stressed the importance of low oral health-related quality of life for loneliness and social isolation (both perceived and objective). This knowledge is important to address individuals at risk. Future studies should clarify the underlying mechanisms.

Early and Dynamic Socio-Academic Variables Related to Dropout Intention: A Predictive Model Made During Pandemic

Social and academic integration variables have shown to be relevant for the understanding of university dropout. However, there is less evidence regarding the influence of these variables on dropout intention, as well as predictive models that explain their relationships. Improvements in this topic become relevant considering that dropout intention stands as a useful measure to anticipate and intervene on this phenomenon. The objective of the present study was to evaluate a predictive model for the university dropout intention that considers the relationships between social and academic variables, during the first university semester of 2020. The research was carried out using a cross-sectional associative-predictive design, with a convenience sampling (n=711) due the restrictions of pandemic period. The results showed a good fit of the proposed hypothetical model that explains 38.7% of dropout intention. Both social support and perceived social isolation predicted the sense of belonging, and through it, engagement. Previous academic performance predicted early academic performance, and through it, engagement. The set of variables predicted the intention to quit, through engagement. These results are a contribution both to the understanding of the phenomenon and to guide potential interventions in the early stages of the university experience.

Predictors of Mental Health During the COVID Pandemic

Health professionals have been concerned about mental health of older adults during the COVID pandemic. To explore their experiences, we conducted an online survey of community-dwelling older people to examine their mental health related to stress, based on Pearlin’s Stress Process Model. A snowball approach was used; we sent recruitment e-mails through senior organizations and contacts with e-mail lists of potential participants; there were 504 respondents. We used regression analysis to explore predictors of mental health based on Pearlin’s model. Background characteristics included age (m = 75.7, SD 4.95), gender (77.4% female) and race (White = 93.4%). The CESD-10 provided a measure of mental health. Scores indicated 62.3% of the sample scored in the low range for depressive symptoms and 37.7% in the moderate to high range. Stressors were measured using the Perceived Stress Scale that includes subscales of perceived helplessness and perceived self-efficacy. We also measured perceived social Isolation, and current life space as predictor variables. Results of regressing the CESD-10 onto the set of theoretical predictors revealed that the inclusion both subscales of the Perceived Stress Scale, social isolation, and current life space jointly accounted for approximately 63.0% of the variability in the outcome beyond the baseline model (FChange[4, 449] = 211.15, p &lt; .01), which included age, race, and gender. The model overall, accounted for approximately 66.5% (R2adjusted = 66.0%) of the variability in CESD-10 scores, (F[7, 449] = 127.473, p &lt; .01). Addressing stress among older adults is important to help them maintain positive mental health.

Remote Relaxation and Acceptance Training for the Management of Stress in Cancer Patients: A Study Protocol

Background: Cancer patients are now facing a double distinctive challenge of survival against both the disease and fear of contracting COVID-19. This challenge has resulted in the forced adoption of social distancing measures and reorganization of the delivery of medical and psychological treatments. The perceived loneliness and uncertainty increased distress and symptoms burden. In the current period, eHealth interventions might provide valuable benefits in the field of cancer care.Objective: The overall goal of the study protocol will be to provide an innovative intervention for cancer patients based on an online platform, to help them manage and prevent psychological problems related to social isolation. Specifically, the efficacy of two web-based interventions aimed at lowering stress in cancer patients will be tested and compared.Methods: One hundred and fifty participants (75 per group) will be enrolled in a two-group randomized trial. The two interventions will be composed either by exercises on relaxation and meditation practices, presented in both automated online content and interactive group sessions or by fixed psychoeducational online content. Stress, anxiety, and depressive symptoms, distress, resilience, and perceived social isolation will be measured before the start of the interventions (T0), 2 weeks (T1), 4 weeks (T2), and 2 months (T3) after the beginning of the interventions in both groups. A repeated measures ANOVA will be performed to test differences in the questionnaires' scores between groups across the four-time points.Expected Results: We hypothesized greater improvement in the specific domain of stress symptoms (IES-R) assessed in the group receiving the interactive intervention, compared to the group which will receive only fully automated psychoeducational content. Secondarily, we expect the same trend of improvement across all the psychological variables in the blended intervention group.Conclusions: Implementing these practices on people who are forced into mandatory social isolation may help them become more aware of their mind-body condition and reduce negative effects. Moreover, relaxation techniques help individuals in achieving a greater state of well-being, increasing the ability to cope with stressful situations (resilience), and strengthening the immune system.

Loneliness, social isolation, and pain following the COVID-19 outbreak: data from a nationwide internet survey in Japan

The aim of cross-sectional study was to investigate the association between loneliness, increased social isolation, and pain following the COVID-19 outbreak. A total of 25,482 participants, aged 15–79 years, were assessed using an internet survey; the University of California, Los Angeles Loneliness Scale (Version 3), Short Form 3-item (UCLA-LS3-SF3) was used to assess loneliness, and a modified item of the UCLA-LS3-SF3 was used to measure the perception of increased social isolation during the pandemic. The outcome measures included the prevalence/incidence of pain (i.e., headache, neck or shoulder pain, upper limb pain, low back pain, and leg pain), pain intensity, and the prevalence of past/present chronic pain. Pain intensity was measured by the pain/discomfort item of the 5-level version of the EuroQol 5 Dimension scale. Odds ratios of pain prevalence/incidence and past/present chronic pain prevalence according to the UCLA-LS3-SF3 scoring groups (tertiles) and the frequency of the perceived increase in social isolation (categories 1–5) were calculated using multinomial logistic regression analysis. The mean pain intensity values among different loneliness and social isolation levels were tested using an analysis of covariance. Increased loneliness and the severity of the perceived social isolation were positively associated with the prevalence/incidence of pain, pain intensity, and the prevalence of past/present chronic pain.