Nursing students' academic conditions, psychological distress, and intention to leave school: A cross-sectional study

BACKGROUND

Psychological distress and intention to leave school are highly prevalent among nursing students. Academic conditions, including psychosocial stressors and school-work-life conflicts, could contribute to psychological distress and intention to leave school.

OBJECTIVE

To explore the associations between academic conditions and 1) psychological distress and 2) intention to leave school.

DESIGN

Cross-sectional correlational design.

SETTINGS

Data collection was performed in February and October 2021 in two nursing schools in Canada: Cegep (publicly funded college, technical degree) and university (bachelor's degree).

PARTICIPANTS

230 nursing students (Cegep 131, university 99).

METHODS

A self-administered online questionnaire assessed academic conditions (psychosocial stressors (Demand-Control-Support, Effort-Reward Imbalance and Overcommitment scales) and school-work-life conflicts (single item)), psychological distress (Kessler-6 scale), intention to leave school, and several covariates. Poisson robust multivariate regression models were built to explore the associations between academic conditions and 1) psychological distress and 2) intention to leave school.

RESULTS

A large proportion of participants experienced high efforts, school-work-life conflicts, overcommitment, and psychological distress (49.5-84.7 %). One out of five participants had had intention to leave school "many times" (Cegep 20.61 %; university 22.22 %). In adjusted analysis, overcommitment and school-work-life conflicts were associated with a higher prevalence of psychological distress (Prevalence ratio = 2.10; 95 % Confidence Intervals = 1.15-3.84 and Prevalence ratio = 2.32; 95 % Confidence Intervals = 1.24-4.32, respectively). Adverse associations were observed between effort-reward imbalance (Prevalence ratio = 2.32; 95 % Confidence Intervals = 1.09-4.94) as well as school-work-life conflicts (Prevalence ratio = 2.40; 95 % Confidence Intervals = 1.05-5.45) and intention to leave school.

CONCLUSIONS

Academic conditions might be risk factors for psychological distress and intention to leave school among nursing students. Interventions targeting modifiable academic conditions might improve nursing students' mental health and retention.

Association between psychosocial job characteristics and sickness absence due to low back symptoms using combined DCS and ERI models

OBJECTIVE

To evaluate the combined demand-control-support (DCS) and effort-reward-overcommitment (ERI-OC) stress models in association with sickness absence due to low back symptoms (SA-LBS).

METHODS

A total of 2,737 blue-collar workers recruited from 13 companies in the most populous province (Henan) of China were included in the study. Personal and physical job characteristics, psychosocial scales of the stress models, and SA-LBS data in the preceding year were collected by a self-reported questionnaire and analyzed by a multivariable logistic regression model. Tertile exposure levels (low, medium and high) were constructed to discriminate a risk level. Odds ratios (OR) with 95% confidence intervals (CI) were used as the association with SA-LBS.

RESULTS

A large percentage (84.5%) of the Chinese workers did not take sick leave after reporting low back symptoms during the preceding year. High job demand or medium-high reward was associated with SA-LBS. The association of the combined stress models and SA-LBS was not evident.

CONCLUSIONS

The ERI-OC model appeared to be more predictive of SA-LBS than the DCS model in the study population. The advantage of using combined stress models for predicting SA-LBS is not evident.

Co-effect of Demand-control-support model and effort-reward imbalance model on depression risk estimation in humans: findings from Henan Province of China

OBJECTIVE

To investigate the co-effect of Demand-control-support (DCS) model and Effort-reward Imbalance (ERI) model on the risk estimation of depression in humans in comparison with the effects when they are used respectively.

METHODS

A total of 3 632 males and 1 706 females from 13 factories and companies in Henan province were recruited in this cross-sectional study. Perceived job stress was evaluated with the Job Content Questionnaire and Effort-Reward Imbalance Questionnaire (Chinese version). Depressive symptoms were assessed by using the Center for Epidemiological Studies Depression Scale (CES-D).

RESULTS

DC (demands/job control ratio) and ERI were shown to be independently associated with depressive symptoms. The outcome of low social support and overcommitment were similar. High DC and low social support (SS), high ERI and high overcommitment, and high DC and high ERI posed greater risks of depressive symptoms than each of them did alone. ERI model and SS model seem to be effective in estimating the risk of depressive symptoms if they are used respectively.

CONCLUSION

The DC had better performance when it was used in combination with low SS. The effect on physical demands was better than on psychological demands. The combination of DCS and ERI models could improve the risk estimate of depressive symptoms in humans.