A Longitudinal Study of Organizational Stressors and Mental Health in the Irish Olympic Team Before and After the “Tokyo 2020” (2021) Olympic Games

<p>本研究目的在了解正負向指標篩檢心理健康型態集群分佈情形，是否符合Keyes主張以主觀幸福感與憂鬱症狀雙指標區分的完整心理健康模式。研究設計以心理健康BMI幸福感問卷、病人健康狀況憂鬱問卷，做為正負向指標篩檢工具，架構完整心理健康模式；以問卷調查法立意取樣739份樣本，經群集分析法作統計分群。結果能區分出有意義的四群集，包括擁有高幸福低憂鬱之完整圓滿心理健康型態的「心盛型」群集（46.28%）、不完整心理健康型態三個群集:「冷靜型」（低幸福低憂鬱之不完整心理亞健康型態，31.94%）、「奮戰型」（高幸福高憂鬱之不完整心理健康型態，11.10%）、「混沌型」（低幸福高憂鬱之不完整心理健康型態，10.69%）。低憂鬱者佔全體 78.22%，其中59.17%擁有高幸福而處於完整圓滿心理健康型態；高憂鬱者佔全體21.78%，其中50.93%擁有高幸福感。驗證了幸福感、憂鬱傾向作為正負向心理健康指標，篩檢完整或不完整心理健康型態。建議:（1）高憂鬱者參照「奮戰型」這群人高幸福感來源，藉由參與社團獲得人際支持、找到工作及收入來增加自我價值感；（2）「冷靜型」不能單看低憂鬱的心理健康篩檢，需提升「友善人際支持 正念情緒平穩 認同自我價值意義」之正向心理健康BMI幸福感，以獲得完整心理健康；（3）未來研究可依據正負向心理健康指標去發展心理健康素養能力，作為心理健檢與自主管理完整心理健康之用。</p> <p> </p><p>This study aimed to understand the cluster distribution of positive and negative indicators for screening mental health patterns and whether they conform to Keyes’ claim that positive and negative indicators should be included in the complete mental health state model. The positive mental health indicators included social, emotional, and psychological well-being, which should be measured using the Mental Health Continuum Short Form (MHC-SF). Negative indicators measure the level of symptoms of mental illness concurrently, serving as a complete assessment of whether the individual is in a healthy state of positive and negative mental health indicators. Keyes employed these to distinguish four clusters of people with four mental health modes, of which the incomplete mental health cluster was in the state. Even if they have a negative mental illness, they could have positive mental health and well-being. Although some people do not have negative mental illness, they cannot have positive mental health and well-being. Therefore, Taiwanese scholar Li corresponded to these three well-being developments and selected three operational mental health skills: ""Befriend-Mindfulness-Identity"" as the Mental Health BMI Well-Being Index questionnaire (mBMI). After using them to evaluate 739 people, it was evident that the scores of the above two questionnaires were significantly correlated, and the mBMI questionnaire total score and Questions B, M, and I could effectively predict the total score, social, emotional, and psychological well-being of the MHC-SF, with a total explanatory power of 30.3%. This test should be used as a simple screening for well-being and as a positive mental health screening tool. Additionally, a Depression Scale Screening Tool for Negative Mental Health Depression was combined to explore the complete mental health state model of Taiwanese people. </p> <p> Therefore, in this study, the mBMI questionnaire was selected as a simple tool to measure positive mental health well-being, and the patients’ health questionnaire for depression was used as a screening tool for negative mental health indicators. These are used as positive and negative indicators to test whether a complete or incomplete mental health state model fits. The questionnaire survey method was used to deliberately sample the data from 739 valid samples, and the cluster analysis method was used for statistical grouping to verify its suitability. According to the results of the aforementioned positive and negative indicators, four meaningful clusters were distinguished, including one complete and three incomplete mental health models. One cluster was ""Flourishing type""(46.28%) of high well-being and low depression, which belonged to the complete mental health state model. The other three clusters were incomplete mental health state models. ""Fighting type"" (31.94%) of high well-being and high depression, ""Calm type"" (11.10%) of low well-being and low depression, and ""Chaos type"" (10.69%) of low well-being and high depression could fight for high well-being. It was verified that well-being and depression could be used as positive and negative mental health indicators to screen for complete or incomplete mental health state models. When we identified people with high depression, we encouraged them to refer to the source of high well-being of the ""fighting type"" group and increase their sense of self-worth by participating in clubs to obtain interpersonal support, find jobs, and earn income. We reminded the ""calm type"" people with low depression to promote their high well-being to have a complete mental health state. Finally, we monitored positive and negative indicators of mental health using screening tools of the Mental Health BMI Well-Being Index and the Patient Health Questionnaire (PHQ-9) to screen for complete or incomplete mental health states as a reference for promoting positive and negative mental health. The befriend-mindfulness-identity skills should be improved to promote well-being and adjust depression to achieve complete mental health.</p> <p> </p>

BackgroundThe mental health of university staff members is often neglected and might have been exacerbated during the coronavirus disease 2019 (COVID-19) pandemic.AimThe aim of this study was to determine the mental health and well-being of staff members in an Eastern Cape university just after levels 4 and 5 lockdowns (01 June 2020) in South Africa.SettingThe university was closed during lockdown and staff members had to work from home, trying to save the 2020 academic year.MethodsA cross-sectional exploratory survey of a sample of 280 staff members (response rate = 27.75%), with a mean age of 48.84 ± 10.17 years, completed the Kessler Psychological Distress Scale (K10) and Mental Health Continuum – Short Form (MHC-SF).ResultsA number (27.6%) of staff members reported psychological distress, whilst the majority (60%) was flourishing during lockdown. Socio-economic collapse, contracting the virus and the completion of the academic year were their biggest worries. Whilst a strong negative correlation between psychological distress and mental well-being (MWB) was observed (r = −0.595), age had an inverse correlation with psychological distress (r = −0.130) and a positive correlation with MWB (r = 0.153). Female staff members, staff members with comorbidities and workers in the administration and service sections were significantly more likely to report psychological distress. The mental health of female staff members and members with comorbidities were almost two times more at risk for psychological distress.ConclusionThe mental health and well-being of some university staff members were at an increased risk during lockdown.

Background: In recent decades, the relationship between mental health and well-being has been explored from many perspectives, with emphasis on the two-continua model of health in different contexts, with an emphasis on young higher education students. Both mental health and well-being are considered predictors of academic success. This study aims to analyze the relationship between mental health and well-being among first- and fourth-year nursing students. The sample consisted of 473 nursing students from a university in the central region of mainland Portugal. Methods: Data were collected using the short versions of the Depression, Anxiety and Stress Scale (DASS-21) and the Mental Health Continuum—Short Form (MHC-SF). Results: Canonical correlation analysis revealed a significant negative association between psychological distress and mental well-being. The first statistically significant canonical function (p < 0.05; Cr = 0.601) was primarily defined by depression (canonical loading = −0.992) in the distress group and emotional well-being (canonical loading = 0.948) in the well-being group. Redundancy analysis confirmed a significant interdependence: variables related to psychological distress explained 27.8% of the variance in well-being, while well-being variables explained 23.8% of the variance in distress. Conclusions: These results reinforce the two-continua model, highlighting the need to address both mental health and well-being throughout higher education.

Background: In recent decades, the relationship between mental health and well-being has been explored from many perspectives, with emphasis on the two continua model of health, and in different contexts, with an emphasis on young higher education students. Both mental health and well-being are considered predictors of academic success. This study aims to analyze the relationship between mental health and well-being among first- and fourth-year nursing students. The sample consisted of 473 nursing students from a university in the central region of mainland Portugal. Methods: Data were collected using the short versions of the Depression, Anxiety and Stress Scale (DASS-21) and the Mental Health Continuum-Short Form (MHC-SF). Results: Canonical correlation analysis revealed a significant negative association between psychological distress and mental well-being. The first statistically significant canonical function (p &amp;amp;lt; 0.05; Cr=0.601) was primarily defined by depression (canonical loading = -0.992) in the distress group and emotional well-being (canonical loading = 0.948) in the well-being group. Redundancy analysis confirmed a significant interdependence: variables related to psychological distress explained 27.8% of the variance in well-being, while well-being variables explained 23.8% of the variance in distress. Conclusions: These results reinforce the two continua model, highlighting the need to address both mental health and well-being throughout higher education.

Psychosocial Work Conditions and Mental Health: Examining Differences Across Mental Illness and Well-Being Outcomes.

Nurses suffering in silence: Addressing the stigma of mental health in nursing and healthcare.

BackgroundUnderstanding and measuring mental health and wellbeing amongst teenagers has recently become a priority. The Warwick-Edinburgh Mental Well-being Scale (WEMWBS) is validated for measuring mental wellbeing in populations aged 16 years and over in the UK. We report here a study designed to establish the validity and reliability of WEMWBS in teenagers in the UK.MethodsWEMWBS and comparator scales, together with socio-demographic information and self-reported health, were incorporated into a self-administered questionnaire given to pupils aged 13 to 16 years in six schools in Scotland and England. Psychometric properties including internal consistency, correlations with comparator scales, test-retest stability and unidimensionality were investigated for WEMWBS. Twelve focus groups were undertaken to assess acceptability and comprehensibility of WEMWBS and were taped, transcribed and analysed thematically.ResultsA total of 1,650 teenagers completed the questionnaire (response rate 80.8%). Mean WEMWBS score was 48.8 (SD 6.8; median 49). Response scores covered the full range (from 14 to 70). WEMWBS demonstrated strong internal consistency and a high Cronbach's alpha of 0.87 (95% CI (0.85-0.88), n = 1517). Measures of construct validity gave values as predicted. The correlation coefficient for WEMWBS total score and psychological wellbeing domain of the Kidscreen-27 was 0.59 (95% CI [0.55; 0.62]); for the Mental Health Continuum Short Form (MHC-SF) was 0.65, 95% CI [0.62; 0.69]; and for the WHO (WHO-5) Well-being Index 0.57 (95% CI [0.53; 0.61]). The correlation coefficient for the Strengths and Difficulties Questionnaire (SDQ) was -0.44 (95% CI [-0.49; -0.40]) and for the 12-item General Health Questionnaire (GHQ12) -0.45 (95% CI [-0.49; -0.40]). Test-retest reliability was acceptable (Intraclass correlation coefficient (ICC) 0.66 (95% CI [0.59; 0.72] n = 212)). Confirmatory factor analysis demonstrated one underlying factor.WEMWBS was significantly associated with the Family Affluence Score (WEMWBS increased with increasing household socio-economic status) and had a positive association with the physical health dimension of the Kidscreen-27, but was unrelated to age, gender or location/school. Eighty students took part in focus groups. In general, although some students considered some items open to misunderstanding or misinterpretation, WEMWBS was received positively and was considered comprehensible, and acceptable.ConclusionsWEMWBS is a psychometrically strong population measure of mental wellbeing, and can be used for this purpose in teenagers aged 13 and over.

Background: Adolescence is a crucial stage of development marked by significant biological, social, and emotional changes that influence mental health and well-being. This study aims to (a) assess the relationship between resilience, life satisfaction, and mental well-being in adolescents aged between 10 and 18 years who are attending 5th to 12th grade in the central region of mainland Portugal, and (b) assess the quality of fit of a structural mediation model in which life satisfaction mediates the relationship between resilience and mental well-being. Methods: A total of 589 adolescents participated in the study and responded to the Escala de Avaliação do Eu Resiliente, the Multidimensional Life Satisfaction Scale for Adolescents, and the Mental Health Continuum–Short Form. Descriptive analyses, ANOVA, canonical correlation analysis, and structural equation modeling with mediation were carried out. Results: A high canonical correlation (r = 0.873, p < 0.001) was found between resilience and well-being/life satisfaction. Mediation analysis revealed that life satisfaction partially mediates the relationship between resilience and positive mental health (r2 = 0.34), indicating direct and indirect effects. Conclusions: These results suggest that more resilient adolescents tend to report higher levels of life satisfaction and well-being, which reinforces the importance of promoting resilience and life satisfaction as protective factors for mental health during adolescence.

BackgroundIt has been argued that though correlated with mental health, mental well-being is a distinct entity. Despite the wealth of literature on mental health, less is known about mental well-being. Mental health is something experienced by individuals, whereas mental well-being can be assessed at the population level. Accordingly it is important to differentiate the individual and population level factors (environmental and social) that could be associated with mental health and well-being, and as people living in deprived areas have a higher prevalence of poor mental health, these relationships should be compared across different levels of neighbourhood deprivation.MethodsA cross-sectional representative random sample of 1,209 adults from 62 Super Output Areas (SOAs) in Belfast, Northern Ireland (Feb 2010 – Jan 2011) were recruited in the PARC Study. Interview-administered questionnaires recorded data on socio-demographic characteristics, health-related behaviours, individual social capital, self-rated health, mental health (SF-8) and mental well-being (WEMWBS). Multi-variable linear regression analyses, with inclusion of clustering by SOAs, were used to explore the associations between individual and perceived community characteristics and mental health and mental well-being, and to investigate how these associations differed by the level of neighbourhood deprivation.ResultsThirty-eight and 30 % of variability in the measures of mental well-being and mental health, respectively, could be explained by individual factors and the perceived community characteristics. In the total sample and stratified by neighbourhood deprivation, age, marital status and self-rated health were associated with both mental health and well-being, with the ‘social connections’ and local area satisfaction elements of social capital also emerging as explanatory variables. An increase of +1 in EQ-5D-3 L was associated with +1SD of the population mean in both mental health and well-being. Similarly, a change from ‘very dissatisfied’ to ‘very satisfied’ for local area satisfaction would result in +8.75 for mental well-being, but only in the more affluent of areas.ConclusionsSelf-rated health was associated with both mental health and mental well-being. Of the individual social capital explanatory variables, ‘social connections’ was more important for mental well-being. Although similarities in the explanatory variables of mental health and mental well-being exist, socio-ecological interventions designed to improve them may not have equivalent impacts in rich and poor neighbourhoods.

Caitlyn Donaldson, Policy Officer at the Royal Society for Public Health, looks at positive mental wellbeing and how it is being promoted through the work of the RSPH.Mental health and wellbeing is increasingly becoming key topic for the RSPH, and we support the recent NHS Mandate for England1 which states that there needs to be parity between mental and physical health, acknowledging that there can be 'No health without mental health'2The WHO defines mental health as a state of wellbeing in which the individual realises his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make contribution to his or her community. As in the WHO's definition of health (a state of complete physical, mental and social wellbeing and not merely the absence of disease or infirmity) mental health is not just the absence of illness, but requires an additional positive 'something' to be present in the individual. Thus, the concept of an individual's mental health state is increasingly being uncoupled from mental illness, and being seen to consist of psychological, emotional and social components.The highest state of subjective wellbeing is seen by many experts as the place where emotional, psychological and social wellbeing are combined, enabling individuals to flourish.3 Thus, rather than simply focusing on preventing and treating mental illness, there is potential to actively promote positive mental health.Mental health and wellbeing impacts upon an individual's physical health, relationships, education, work and ability to reach their potential. At population level, it has consequences for the country's economy, levels of crime, drug and alcohol dependence and homelessness,4 and as Friedli states: health is also key pathway through which social inequality impacts on health.5Many of the key determinants of mental health are located within social and economic domains,6 which provides opportunity for intervention.In 2011 nef published report to address the question of how flourishing mental health could be promoted and increased.7 The result was their five ways to wellbeing: 'connect'; 'be active'; 'take notice'; 'keep learning'; and 'give'. These five ways are easily applied at individual, community, organizational and strategic levels; and evidence suggests that they are being used in many different settings to encourage improved mental wellbeing.The RSPH believes that policymakers at national and local level have responsibility to ensure that policies help address, not increase, inequalities in mental health and wellbeing. The Department of Health's mental health implementation framework8 provides an important perspective on translating policy into practical actions for improving mental health and we support the use of mental wellbeing impact assessment (MWIA), to ensure that policy, programme, service or project has maximum equitable impact on people's mental wellbeing - at individual, community or national level. We also endorse the Guidance for Commissioning Public Mental Health Services,9 which provides the rationale for spending on mental health and also explains what good quality public mental health interventions look like. …

Introduction &amp; BackgroundSocial media use has been proposed as a cause of worsening mental health and wellbeing over the last decade, but its role in mitigating some of the effects of social distancing during the pandemic showed that it also has the potential to improve these outcomes. Whilst existing research disagrees on the degree to which social media use harms or helps, there is growing consensus around the need to move from global measures of social media use to specific measures of types of social media use. These new measures can enable an exploration of proposed mechanisms and causal pathways linking social media use and mental health and wellbeing. A commonly proposed mechanism is nighttime social media use reducing sleep quality, and consequently harming mental health and wellbeing.&#x0D; Objectives &amp; ApproachWe aimed to investigate the relationships between the time Twitter users post content and their mental health, wellbeing and sleep quality using direct measurements of Twitter use linked to standardised mental health measures in a well-characterized cohort.&#x0D; This study uses approximately 1.5 million Tweets harvested between January 2008 and March 2023 from 622 participants in the Avon Longitudinal Study of Parents and Children (ALSPAC). These Tweets have been linked to questionnaire data collected on six occasions spanning April 2019 to May 2021. These questionnaires included standard measures of depressive symptoms, anxiety symptoms, mental wellbeing and difficulty sleeping.We have taken two approaches to explore these relationships, using circular statistical methods novel to social media data analysis to account for day/night cycles. The first approach used mixed effect models to investigate the association between the time a Tweet was posted and the mental health, mental wellbeing and sleep quality of the poster. The second approach explored the relationships between the mean hour participants post Tweets in a given time period, and their mental health, mental wellbeing and sleep quality.&#x0D; Relevance to Digital FootprintsThis research is highly relevant to Digital Footprints, due to its use of data directly extracted from a social media site. The methodologies employed in analysing this alongside more traditional epidemiological survey data provides an example of how digital footprint data can complemented by high quality ground truths.&#x0D; ResultsThere was evidence that the timing of Twitter activity was predictive of the mental wellbeing and sleep quality of participants, even after adjustment for demographic, educational and socio-economic covariates. However, the hour a Tweet was posted at explained very little of the variation in the mental wellbeing or sleep quality of the participant who posted it (0.1% and less than 0.1% respectively). There was weak to no evidence that the timing of Twitter activity was predictive of the depressive and anxiety symptoms of participants.&#x0D; Conclusions &amp; ImplicationsWhilst this study found evidence that the hour participants post on Twitter is predictive of their mental wellbeing and sleep quality, the amount of variation explained by these models suggests that this is not a clinically relevant risk factor. This study supports arguments in the literature that the use of social media has a very small and insignificant effect on mental health, wellbeing and sleep quality.

BackgroundGlobally, promoting mental health and well-being among adolescents has become a public health priority, especially for adolescents living with a physical chronic condition (CC), as research suggests they may be more at risk of developing mental health co-morbidities. Valid and reliable instruments are needed to measure and better understand mental health and mental well-being among adolescents living with a CC. To this end, we reviewed studies reporting on mental health and well-being instruments used in adolescent populations living with a chronic physical condition/disease globally.MethodsWe used a systematic review method guided by PRISMA to identify assess mental health and mental well-being instruments used in adolescents living with a CC. In this instance, mental health instruments were defined as those representing negative domains of mental health (i.e. depression and anxiety) while mental well-being instruments included positive aspects of mental health (i.e. self-concept and resilience).ResultsWe identified 22 articles, which included 31 instruments that were used to measure either mental health (n = 8) or mental well-being (n = 15) or both (n = 8) in adolescents living with a CC. Of these, thirteen studies used a Health-Related Quality of Life (HRQoL) scale to measure mental health and/or mental well-being. The KIDSCREEN questionnaires and the Strengths and Difficulties Questionnaire were identified as being frequently used across the 22 studies. Additionally, 7 out of the 31 instruments were disease specific, with 3 focusing on adolescents with diabetes. All the instruments were developed in high income countries and adapted for use in lower- and middle-income countries (LMICs). Adolescents with Type 1 Diabetes (n = 7) and HIV (n = 4) were researched in 11 out of 22 studies. Only eight studies were conducted in LMIC, of which four were in Africa.ConclusionsHRQoL instruments are useful in measuring mental health and well-being in adolescents living with a CC. However, relatively few valid measures of mental health and mental well-being for adolescents living with a CC exist, which accentuates the paucity of research on mental health and mental well-being of adolescents who are living with a CC. Specific measures need to be developed in and for LMICs where cultural contexts affect mental well-being in unique ways.Systematic review registration: PROSPERO CRD42020186707.

Background Firstly, we aim to describe any differences in the mean levels of correlates and indicators of mental health and wellbeing between young (25-39 years) and middle-aged adults (40-55 years). Secondly, we aim to compare the network models depicting interrelations between correlates and indicators of mental health and wellbeing among these age groups. Methods This paper draws on longitudinal data from 6 waves (2013-2018) of the Swiss Household Panel (SHP) study, with a total sample of 5,315 individuals, including 2,044 young (25-39 years) and 3,271 middle-aged (40-55 years) participants. We used network analysis to examine and present complex relationships between the correlates and the indicators of mental health and wellbeing. Results Middle-aged individuals had worse mental health and wellbeing on all indicators but energy and optimism, which did not differ across groups. The effect sizes (according to Cohen’s d) were small, reaching the maximum of 0.20 for sadness. Despite higher household income and financial satisfaction, perceived job insecurity and work strain were higher in midlife, with socioeconomic prestige being lower. Moreover, middle-aged individuals had lower social support, relationships satisfaction, and health satisfaction. The network was denser in midlife, with two direct interrelations being stronger in this age group: health satisfaction and energy/optimism as well as accommodation satisfaction and life satisfaction. There were also several other differences in indirect interrelations between correlates and indicators of mental health and wellbeing, including a potentially more important role of self-mastery in midlife in bridging socioeconomic indicators, wellbeing and mental health. Conclusions We suggest further exploring the workplace as an avenue to improving population mental health and wellbeing, with a particular focus on the role of self-mastery. Key messages • Middle-aged individuals appear to have worse mental health and lower wellbeing than young adults. • Health satisfaction is not only lower in midlife, but it seems of greater importance for mental health and wellbeing.

BackgroundOccupational stressors in police work increase the risk for officer mental health morbidities. Officers’ poor mental wellbeing is harmful to the individual, can affect professionalism, organisational effectiveness, and public safety. While the impact of operational stressors on officers’ mental wellbeing is well documented, no review has systematically investigated organisational stressor impacts. This study aimed to conduct a systematic review to assess the relationship between organisational stressors and police officer mental wellbeing.MethodsSystematic review conducted following PRISMA and Cochrane Collaboration guidelines. Literature search was undertaken from 1990 to May 2017 on four databases (EBSCOHOST Medline/SocINDEX/PsycINFO/OVID Embase) and grey literature. Included articles were critically appraised and assessed for risk of bias. Narrative and evidence syntheses were performed by specific mental health outcomes.ResultsIn total, 3571 results were returned, and 15 studies met the inclusion criteria. All included studies were published in English between 1995 and 2016, had cross-sectional study designs, spanned across four continents and covered 15,150 officers. Strong evidence of significant associations was identified for organisational stressors and the outcomes of: occupational stress, psychiatric symptoms/psychological distress, emotional exhaustion and personal accomplishment. The organisational stressors most often demonstrating consistently significant associations with mental health outcomes included lack of support, demand, job pressure, administrative/organisational pressure and long working-hours.ConclusionsThis review is the first to systematically examine organisational stressors and mental health in police officers. Organisational stressors that can be targeted by interventions and policy changes to secure officer wellbeing, a healthy work environment, and benefits to the organisation and the public are identified.

Mental well-being is more than merely the absence of mental illness; it is a multidimensional concept that includes both emotional and functional well-being, which are valuable resources during adolescence. In order to develop relevant interventions and policies to strengthen adolescent mental health, a continuous monitoring of the population well-being becomes important. The aim of the study was to examine the level, distribution, and changes in mental well-being over time in a Swedish adolescent population. Current study is based on four waves (2014-2017-2020-2023) of a cross-sectional student survey (N = 16288, Mage = 16.23). The outcome was measured with the Mental Health Continuum Short Form. Ten explanatory factors were chosen to examine differences in mental well-being in the study population: Grade, Sex, Sexual orientation, Socioeconomic status, Country of birth, Visual, Hearing or Mobility impairment, Specific learning disorder and Neurodevelopmental disorder. Differences in mental well-being between groups as well as temporal trends were examined and evaluated through statistical testing and hierarchical multiple linear regressions modeling. Girls, non-heterosexual adolescents, and adolescents with low socioeconomic status or impairments have lower levels of mental well-being than boys, heterosexual adolescents, and adolescents with higher socioeconomic status or without impairments, respectively. A deterioration in mental well-being is seen over time for several groups; however, results of the multivariable analysis indicates that the deterioration is mainly an effect of sex and the significant decline in mental well-being seen among girls. The most significant factor for explaining the variation in mental well-being in this study is socioeconomic status. This study elucidates temporal changes and differences in levels of mental well-being between social groups in the adolescent population. The overall differences are small, but their potential implications for public health warrant careful consideration since they concern a significant part of the population. The results underscore the imperative of promoting mental well-being in adolescents, particularly among vulnerable groups.