Accessibility to Digital Mental Health Services among the General Public throughout COVID-19: Trajectories, Influencing Factors and Association with Long-Term Mental Health Symptoms

Psychosocial risk profiles to address future health emergencies: a country study during the COVID-19 lockdown period in Colombia

Introduction

The different strategies used worldwide to curb the COVID-19 pandemic between 2020 and 2021 had a negative psychosocial impact, which was disproportionately higher for socially and economically vulnerable groups. This article seeks to identify the psychosocial impact of the confinement period during the COVID-19 pandemic for the Colombian population by identifying profiles that predict the levels of different mental health indicators (feelings of fear, positive emotions or feelings during free time, and work impact) and based on them, characterize the risk factors and protection that allows us to propose guidelines for prevention or recovery from future health emergencies.

Methods

This is an observational, cross-sectional, retrospective ex post facto study. Multistage cluster probabilistic sampling and binary logistic regression analysis were used to predict extreme levels of various mental health indicators based on psychosocial indicators of the COVID-19 confinement period and to identify risk and protection factors.

Results

A relationship was established between the combination of some of the different psychosocial factors evaluated (this combination being the predictive profile identified) with each of the three main variables: feeling of fear (n = 8,247; R = 0.32; p = 0.00; Poverall = 62.4%; 𝜔overall = 0.25; 1-𝛽overall = 1.00), positive emotions or feelings during free time (n = 6,853; R = 0.25; p = 0.00; Poverall = 59.1%; 𝜔overall = 0.18; 1-𝛽overall = 1.00) and labour impact (n = 4,573; R = 0.47; p = 0.63; Poverall = 70.4%; 𝜔overall = 0.41; 1-𝛽overall = 1.00), with social vulnerability determined by sociodemographic factors that were common in all profiles (sex, age, ethnicity and socioeconomic level) and conditions associated with job insecurity (unemployed, loss of health insurance and significant changes to job's requirements) and place of residence (city).

Conclusion

For future health emergencies, it is necessary to (i) mitigate the socio-employment impact from emergency containment measures in a scaled and differentiated manner at the local level, (ii) propose prevention and recovery actions through psychosocial and mental health care accessible to the entire population, especially vulnerable groups, (iii) Design and implement work, educational and recreational adaptation programs that can be integrated into confinement processes.

How Does Sustainable Leadership Affect Environmental Innovation Strategy Adoption? The Mediating Role of Environmental Identity

This paper uses social identity theory to develop an environmental identity theory and interpret why sustainable leadership can influence environmental identity, which in turn, results in environmental innovation strategy (EIS) adoption. Data were collected from 90 samples of technology manufacturing firms in Taiwan, and a latent growth curve model was employed to analyze the longitudinal data. The research results confirm all hypotheses. Mediating analysis also supports the environmental identity as a mediating role between sustainable leadership and EIS. Indeed, past studies have not explored the mechanism studied in this paper, a novel mechanism which can not only advance the literature on sustainable development but also help companies to realize sustainable development through environmental innovation strategy adoption.

Long-term psychological profile of general population following COVID-19 outbreak: symptom trajectories and evolution of psychopathological network

AIMS

COVID-19 has long-term impacts on public mental health, while few research studies incorporate multidimensional methods to thoroughly characterise the psychological profile of general population and little detailed guidance exists for mental health management during the pandemic. This research aims to capture long-term psychological profile of general population following COVID-19 by integrating trajectory modelling approaches, latent trajectory pattern identification and network analyses.

METHODS

Longitudinal data were collected from a nationwide sample of 18 804 adults in 12 months after COVID-19 outbreak in China. Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and Insomnia Severity Index were used to measure depression, anxiety and insomnia, respectively. The unconditional and conditional latent growth curve models were fitted to investigate trajectories and long-term predictors for psychological symptoms. We employed latent growth mixture model to identify the major psychological symptom trajectory patterns, and ran sparse Gaussian graphical models with graphical lasso to explore the evolution of psychopathological network.

RESULTS

At 12 months after COVID-19 outbreak, psychological symptoms generally alleviated, and five psychological symptom trajectories with different demographics were identified: normal stable (63.4%), mild stable (15.3%), mild-increase to decrease (11.7%), mild-decrease to increase (4.0%) and moderate/severe stable (5.5%). The finding indicated that there were still about 5% individuals showing consistently severe distress and approximately 16% following fluctuating psychological trajectories, who should be continuously monitored. For individuals with persistently severe trajectories and those with fluctuating trajectories, central or bridge symptoms in the network were mainly 'motor abnormality' and 'sad mood', respectively. Compared with initial peak and late COVID-19 phase, aftermath of initial peak might be a psychologically vulnerable period with highest network connectivity. The central and bridge symptoms for aftermath of initial peak ('appetite change' and 'trouble of relaxing') were totally different from those at other pandemic phases ('sad mood').

CONCLUSIONS

This research identified the overall growing trend, long-term predictors, trajectory classes and evolutionary pattern of psychopathological network of psychological symptoms in 12 months after COVID-19 outbreak. It provides a multidimensional long-term psychological profile of the general population after COVID-19 outbreak, and accentuates the essentiality of continuous psychological monitoring, as well as population- and time-specific psychological management after COVID-19. We believe our findings can offer reference for long-term psychological management after pandemics.