Based on the references below, can you summarise the synthesis gaps and limitations as well as derive a topic for this article.
Public policy refers to a strategic action led by a public authority in order to limit or increase the presence of certain phenomena within the population (NCCHPP,2012). There are factors determining mental health called the “determinants of mental health”. There are levels that determine the influence of public policies like the individual, social, structural and environmental. Well-being is a complex and multifactorial construct whose measures are sometimes divided into objective measures which mostly refer to the standard of living and subjective measures. When these measures concern psychological aspects, they are often referred to as measures of psychological well-being (PWB)(Trudel et al 2019). Existing literature indicates that several PWB dimensions are associated with a reduced risk of premature all-cause mortality among the general population, with small to medium effects. Among the dimensions reviewed purpose in life, optimism and ikigai had the strongest evidence followed by life satisfaction, positive affect, mastery and sense of coherence (Trudel et al 2019). The profound impacts of the COVID-19 pandemic on population’s mental health like rising rates of depression, anxiety, post-traumatic stress symptoms and increases in suicidal thoughts and behaviours. Mental challenges are a leading concern for youth globally requiring a comprehensive approach incorporating promotion, prevention and treatment within a healthy public framework (Jenkins et al,2020). Mental health promotion is concerned with strengthening protective factors for good mental health and enabling access to skills, resources and supportive environments that enhance equity and keep individuals and populations mentally healthy. There are eight priority areas and three calls for action for mental health promotion.
Sample sizes for quantitative analyses will be small. PWB-mortality associations have been rarely investigated across the sociodemographic group and many interventions have been restricted to clinical or convenience samples, mostly in high-income countries which may not be generalizable to other populations. Besides country-level income, the role of other indicators of socioeconomic status in the PWB mortality relationship specifically is less known. It remains unclear whether findings obtained from studies assessing the PWB-mortality association in high-income countries and adjusting for certain SES indicators may generalize in those of lower-middle-income countries and other socioeconomic groups.
Focus on well-being could influence the future direction of public policy in general. PWB has promising potential to improve mental and physical health. PWB-mortality associations can be more investigated across sociodemographic groups and generalizable to other populations. Rigorous methodologies should be favoured. Systematically incorporating well-being scales in large national cohort studies will help solidify the evidence of PWB’s causal role in health outcomes. Additional research exploring whether and how well-being strategies and policies can be implemented in communities will be needed to achieve a population-level impact.
There is significant evidence suggesting that the social determinants of health impact all facets of health, including mental health and psychological wellness. Many of these risk and protective factors for positive mental health occur outside of individual control, influenced by systems, structures, and institutions (Jenkins et al., 2020; Mantoura, 2014; Trudel-Fitzgerald et al., 2019). Healthy public policy has an important role in addressing these risk and protective factors, as policy can strategically target key factors affecting large populations (Mantoura, 2014). By recognizing “upstream” influences on health outcomes and by addressing root causes of inequities within these structures through policy, mental health risk and protective factors can be targeted across multiple socio-ecological domains (Jenkins et al., 2020; Mantoura, 2014; IUHPE; Trudel-Fitzgerald et al., 2019). Healthy public policies improve mental health across populations by improving the conditions that people live within (Mantoura, 2014). This includes dimensions of psychological well-being, such as life purpose, satisfaction, optimism, and quality of life measures (Trudel-Fitzgerald et al., 2019). In addition, positive psychological well-being has been associated with decreased disease and mortality risks (Trudel-Fitzgerald et al., 2019), which emphasizes the interconnectedness of different health measures; this is important to note as it suggests that health implications from policy changes can be far-reaching beyond an intended intervention. Thus, small policy changes can create ripple effects in different areas of health (Trudel-Fitzgerald et al., 2019). Importantly, implementing targeted health policies allows broader population-level interventions in diverse groups, instead of only addressing the most vulnerable within a community (Mantoura, 2014). Some examples of priorities for mental health policy are those influencing positive childhood development, healthy workplaces, community empowerment, positive health services, and reduced stigmatization (IUHPE, 2021).
Because there is little evidence on cause-and-effect relationships between mental health policy and psychological well-being, future research should be focused on creating frameworks that align policies with determinants of mental health to create clear foundations to support improved mental health outcomes. Multi-dimensional measures and indicators of mental health need to be studied in detail to support this research (Mantoura, 2014). Extending this to larger-scale studies would help provide causal evidence to mental health measures and provide opportunities to explore other scales of well-being (Trudel-Fitzgerald et al., 2019). Additionally, there is also evidence to support the need for engagement and collaboration with target populations to ensure those policies are effective interventions (Jenkin et al., 2020). This is an important future research direction as it would directly influence the gaps in the literature on differential impacts on varying sub-groups previously identified. Voices of marginalized populations are of specific priority, as these are the individuals who are least likely to be heard.
Ultimately, one of the most significant challenges in mental health policy advocacy research is that it is difficult to determine the impact of a policy within a population. There is little evidence that sufficiently examines the connection between policy and outcomes, and as such, determining cause-and-effect relationships is difficult (Mantoura, 2014). These challenges are also faced when studying psychological well-being as a measure to support healthy public policy. Longitudinal associations are not significant enough to indicate causation, and in practice, there are multiple factors impacting psychological well-being that can not always be identified. This also creates uncertainty about whether health status is influencing psychological well-being, or if the reverse is true (Trudel-Fitzgerald et al., 2019). Additionally, because policy affects such broad and diverse populations, there is a need to grow evidence examining differential impacts on sub-groups, including varying age groups, cultures, socioeconomic status, education levels, etc. (Jenkins et al., 2020; Mantoura, 2014; Trudel-Fitzgerald et al., 2019). Jenkins et al. (2020) noted that when studying healthy public policy among youth that there was a lack of mental health promotion evidence for this specific population group, and that there was a potential for bias within the study as affluence can be related to increased engagement; thus, marginalized youth were more difficult to engage. This can represent a significant barrier in this area of research, as those who are marginalized may experience an increased need for these interventions due to competing socio-ecological risk factors, but who may be the least likely to be represented in research?
Mental health policies aim to enhance protective factors and limit risk factors in the population, with the goal of promoting mental well-being and improving quality of life. These policies fall outside the purview of the formal mental health sector, aiming to address social and structural conditions in order to create living conditions conducive to positive mental health and eradicate inequities for disadvantaged groups (Mantoura, 2014; Jenkins et al., 2021). The key determinants of mental health can be conceptualized in terms of their level of influence; these include the individual, social, structural, and environmental levels (Mantoura, 2014). Population-based approaches extend beyond individual-level services and encompass a broader spectrum of interventions at the social, structural, and environmental levels. One element of population-based approaches includes mental health promotion, which strives to enable access to services that promote mental well-being (Jenkins et al., 2021). Interventions that can promote mental health include integrating positive mental health in child development services, promoting school-based initiatives, integrating mental health promotion in workplace policies, implementing community-empowerment programs, incorporating mental health promotion in primary care services, enhancing public awareness, and promoting policies aimed at enhancing equity and justice (Jenkins et al., 2021). Furthermore, individual-level interventions promoting facets of psychological well-being— such as life satisfaction, positive affect, optimism, and autonomy— can be adapted and implemented alongside upstream efforts targeting social determinants. PWB interventions decrease mortality, improve physical health, and increase quality of life; if implemented at the institutional level, they can have far-reaching impacts on the population’s well-being (Trudel-Fitzgerald et al., 2019). Lastly, there has been growing interested in youth engagement in public policy, particularly as it pertains to mental health promotion. This interest led Jenkins et al. (2020) to develop The Agenda Gap— a mental health promotion intervention developed in collaboration with youth. The intervention strives to help youth identify factors that impact mental health, develop strategies to effect policy change, and engage with stakeholders. Ultimately, this intervention can empower future generations to lead changes to improve the social and structural conditions that influence mental health.
Research on the impact of public policies on mental health is sparse, and most of the evidence informing policy decisions infers benefits based on established links between living conditions and mental health outcomes (Mantoura, 2014). Thus, causal links between interventions and outcomes cannot be made at this point. Furthermore, there is a dearth of evidence to inform policy engagement by youth, and a lack of rigorous studies examining the efficacy of PWB interventions at the institutional level (Trudel-Fitzgerald et al., 2019; Jenkins et al., 2020). While the above articles highlight the potential of these initiatives and provide actionable strategies for policy development, more systematic research is needed to better understand the impact of these interventions on mental and physical health outcomes. The key principle underlying mental health promotion is the acknowledgement that mental health is strongly influenced by social and structural conditions. Marginalized groups are disproportionately impacted by these determinants of mental health and would benefit the most from interventions. However, given the systemic barriers they face, they may also be the hardest groups to engage and may be underrepresented as a result, which can limit generalizability when evaluating the impacts of these interventions. The relevance, feasibility, and sustainability of these interventions should be considered in light of the specific sociocultural contexts in which they are implemented. Communities differ in terms of their values, needs, and resources, so interventions that work for one community may not work for another. This highlights the necessity of conducting trials with diverse samples to determine generalizability. Furthermore, differences in outcomes between communities could be an artifact of these sociocultural differences rather than the interventions themselves, which can create confounds if this variability is not accounted for. Finally, implementing population-wide initiatives requires rigorous planning, monitoring, evaluation, and ongoing collaboration and consultation with stakeholders. This process is time-consuming and resource intensive and requires inter- and intra-agency engagement. This can be difficult to achieve, especially for communities with fewer resources and lower incomes.
There are a number of considerations for future research. First, to facilitate the planning, monitoring, and evaluation of these interventions, researchers should operationally define the constructs they are measuring. People’s definitions of mental health and well-being can vary depending on sociopolitical and cultural contexts, and many of these constructs are multi-dimensional in nature. When using scales, care should be taken to ensure these measures are psychometrically sound; whether they have cross-cultural validity and content validity is of particular importance. Surveying local communities to assess their concerns and priorities can help to ensure that proposed interventions adequately address their needs. Consulting with community members can also promote rapport, establish trust, and allow marginalized community members to gain a sense of autonomy and have a voice in effecting policy changes that directly impact them. All of these benefits can, in turn, enhance engagement with these initiatives, increasing the representativeness of samples as well as statistical power. Ongoing monitoring, consultation, and dissemination of intervention progress and outcomes can promote transparency and facilitate dialogue between researchers, agencies, and community members. This can help to ensure that interventions are being implemented as planned and that they are having the intended impact. Quasi-experimental, longitudinal, mixed-methods designs can help researchers establish temporal precedence and provide a more holistic view of how these initiatives work, whilst minimizing threats to ecological validity. However, this type of study would necessitate the use of matched groups, and the measurement and statistical control of extraneous variables to reduce the potential for confounds.
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