Wellbeing Framework Study: Protective Factors and Mental Health
Recommended citation: Dominguez, G., & Khan, M. (2025). Wellbeing Framework Study: Protective Factors and Mental Health. MindArchHealth.com. Retrieved [Date Retrieved], from https://www.mindarchhealth.com/
ABSTRACT: This study explores the role of preventative care in mental health by examining key factors that sustain wellbeing through the lens of the 5-Elements of Systemic Wellbeing Framework: secure, regulated, valued, decided, and related. Using 2 consecutive surveys comprising 60 Likert-scale statements, participants' self-reported experiences with these elements, examining internal and external protective factors on mental health and resilience. Recruitment efforts targeted a diverse convenience sample through online platforms (Reddit, SurveyCircle, SurveySwap), physical outreach (flyers on the Stony Brook University campus), and peer networks (GroupMe and co-intern collaborations), resulting in 424 completed responses across both surveys. Analysis of the dataset revealed average scores across the five elements, highlighting critical patterns and trends in the psychological health and protective factors influencing mental well-being. Key findings can provide actionable insights into the most significant contributors to resilience and mental health in unique populations, informing strategies for proactive population mental health interventions using aggregated results and personalized support through individual results. This preventative, data-driven approach aims to add proactive population health models to existing treatment models, enhancing positive health outcomes.
BACKGROUND: While population mental health surveys have traditionally focused on mental disorders, there is a growing recognition of the importance of positive mental health (PMH). PMH is increasingly understood not only as the absence of illness, but as a distinct and valuable construct encompassing well-being, flourishing, and resilience (Keyes et al., 2010). This broader perspective acknowledges that mental health exists on a continuum. Studies suggest that PMH can play a significant role in influencing the impact of mental disorders on overall health outcomes (Vaingankar et al., 2020). For example, high levels of PMH may buffer the negative effects of mental health challenges. Furthermore, research indicates that PMH is a key factor in predicting both recovery from mental health conditions (Schotanus-Dijkstra et al., 2019) and the future risk of developing mental illness (Keyes et al., 2010). Therefore, incorporating measures of positive mental health into these surveys could provide a more comprehensive and nuanced understanding of population mental health, moving beyond a solely deficit-based approach to encompass the full spectrum of mental well-being.
INTRODUCTION: In recent years, there has been a growing recognition of the importance of mental health in overall well-being, with increasing attention on identifying and addressing key factors that influence mental health before they develop into more severe issues. While much of the mental health discourse has historically focused on diagnosing and treating mental illness, our initiative emphasizes preventative care by examining the underlying factors that contribute to mental health in everyday life. This approach aims to shift the conversation toward understanding the elements that sustain mental wellness and resilience, providing insights into the needs that support individuals across various circumstances. The purpose of this study is to understand an average score on the 5-Elements of Systemic Wellbeing survey tools by surveying a general sample population. The 5-Elements of Systemic Wellbeing Framework has 2 consecutive surveys assessing both the respondents’ psychological health and their protective factor needs. Both surveys are 30 questions for a total of 60 questions, each rated on a Likert scale (i.e. Most Often, Often, Sometimes, Rarely, Very Rarely) to capture the significance of these needs and factors in respondents’ lives. Examining these elements systematically provided a comprehensive picture of how everyday mental health needs present across different demographics. These surveying tools hold particular significance as they provide valuable data on the factors that contribute to mental health and well-being. The findings from our study will be useful not only for understanding general mental health needs but also for informing preventative strategies and interventions that can support mental wellness in a proactive, personalized way. This shift toward identifying and addressing mental health factors earlier offers potential for both improved well-being and broader public health outcomes.
5-Elements of Systemic Wellbeing Framework: Mental health is influenced by various factors, including psychological, social, and environmental conditions. The framework identifies five key resiliency factors that help buffer against stress related conditions: Secure, Regulated, Valued, Decided, and Related. Each element represents a core aspect of mental wellbeing:
Secure: Promotes safety, calmness, and belonging.
Regulated: Encourages emotional control and healthy routines.
Valued: Fosters self-assurance and meaningful connections.
Decided: Enhances self-efficacy and goal achievement.
Related: Supports interpersonal connection and problem-solving.
METHODS:
The primary objective was to recruit a minimum of 150 participants across both surveys (for a total of 300 individual responses) to capture nuanced responses across various dimensions of the 5-Elements Framework. A multi-method outreach strategy was implemented targeting both online and offline communities through convenience sampling. This comprehensive approach helped us maximize accessibility and attract a varied group of participants, ultimately supporting our goal of collecting diverse data to analyze responses within the 5-Elements Framework.
Reddit Posts: Informative posts were developed and published on Reddit to raise awareness about our surveying initiative. Each post clearly outlined our purpose, and engagement was encouraged by including digital posters alongside most posts. Each post featured a QR code linking directly to the survey. This approach allowed us to make participation as accessible as possible while reaching a broad and diverse online audience. Leveraging Reddit's community-based platform supported open dialogue on the post, engaging people who might benefit from assessing their score.
Survey Exchange Platforms: SurveyCircle.com and SurveySwap.io were utilized to expand our reach and ensure a steady flow of responses from a varied audience. Both platforms are popular in the research community and function as survey-exchange networks, where users earn points or other incentives by completing each other’s posted surveys. Listing our dual-survey on these sites engaged individuals already inclined to participate in studies, many of whom had a genuine interest in research and contributing to data collection efforts. This approach increased the likelihood of gathering responses from a diverse and engaged sample while being reflective of various demographics and backgrounds.
Physical Flyers on Campus: An offline strategy was implemented to compliment online efforts by distributing physical flyers across the campus of State University of New York at Stony Brook. These flyers prominently featured key information and displayed a QR code for easy access. These flyers were placed in high-traffic areas such as student centers, libraries, dining halls, and academic buildings to maximize visibility. Ensuring the QR code was accessible to students who might not engage with online platforms encouraged a broader range of participants, including those who prefer offline interaction and may not be active on Reddit or survey exchange sites.
GroupMe and Peer Sharing via Co-Interns: Peer networks were used by sharing the link and digital flyer through GroupMe, a popular group messaging app frequently used by students and campus organizations. Additionally, other interns shared the digital flyer on their own GroupMe channels, social media, and other communication platforms. By using peer-to-peer sharing, individuals were reached in a more personal, informal way, increasing both response rates and the diversity of our respondent base.
Our secondary objective focuses on analyzing our results to gain meaningful insights into the mental health factors reported by participants. To accomplish this, the survey data was examined, identifying key trends and patterns that provide a deeper understanding of the reported mental health factors. Specifically:
Scored Data: The dataset was obtained from the MindArch Health software in a spreadsheet format. It contained approximately 424 rows, each representing a survey that was completed. There were 238 Psychological Health Survey responses, with 186 participants following through and completing the Protective Factors Survey. Using the raw data obtained, individual scores were calculated on all 5 elements for both the Psychological Health Survey and Protective Factors Survey.
Score Construction: Each of the 60 question stems were scored from 0-4 on the presented scale (Most Often, Often, Sometimes, Rarely, Very Rarely). Using the individual scores, the average scores were calculated for each element, feedback scores, and demographic data, and represented as a percentage of the total score possible for each survey. Given 30 questions and a maximum score of 4 on each question stem response, the total possible score for each survey is 120. Six question stems are associated with each Element, with a maximum possible Element score of 24 for each of the 5-Elements. Feedback scores were calculated from two questions at the end of each survey asking about comfortability in responding to the questions and an understanding of the questions. Feedback questions used the same scale as the survey question stems (Most Often, Often, Sometimes, Rarely, Very Rarely) and were similarly scored with a maximum score of 4 and a minimum score of 0 for each question and represented as a percentage.
Highlighted Emerging Patterns: After scoring the data, tables were created to aid in identifying emerging patterns and trends. The tables were generated to illustrate average scores across the 5-Elements Framework, highlighting overall scores for each survey as well. This approach allowed us to compare the relative importance of each element in contributing to mental health and resilience.
Explored Demographic Variances: The dataset included demographic information such as gender, race, childhood income and educational background. Response differences to demographic questions were examined across the surveys, providing insights into how different groups experience and prioritize mental health needs.
Developed Actionable Insights: Based on the trends and patterns observed, factors that play the most significant role in supporting mental health were identified for this random sample. This was also reflected as a predictive goal generated by the MindArch Health MAP software. These findings were also contextualized within the broader mental health discourse to highlight their relevance to preventative care.
RESULTS/FINDINGS: A total of 238 participants enrolled in the study, with 186 completing both the initial and follow-up surveys. This represents a substantial completion rate of 78.2%, though it also indicates a loss of 52 participants (21.8%) between the two surveys.
Survey tables with psychological health scores, protective factor scores, and user experience questions and responses.
Demographic tables with gender, race, education and income responses.
DISCUSSION AND ANALYSIS: The results of this study highlight the importance of understanding mental health needs through a proactive lens. By utilizing the 5-Elements Framework, significant trends were identified regarding psychological health and protective factors that contribute to mental wellbeing. Notably, participants’ average scores across the two surveys revealed that the “Decided” and “Related” elements consistently ranked as the strongest elements. "Regulated" had the lowest average score in the Psychological Health Survey, while "Secure" had the lowest average score in the Protective Factors Survey. This indicates that, while participants felt generally confident in their sense of self-efficacy and relationships, emotional control and feelings of safety may be an area of vulnerability.
The key predictive goal generated by the MindArch Health software, “Increase Security By Improving Equity,” provides further insights into these trends. The “Secure” element underscores the role of environmental conditions in fostering internal safety and emotional stability. A dependable environment is critical to developing a sense of security, which enables individuals to form connections and face challenges with reduced sense of failure. This allows for further evaluation to examine causality between subjective sense of security and equity which may protect systematically disadvantaged groups. This goal aligns with the dual continuum model of mental health, which suggests that PMH is not merely the absence of mental illness but rather a distinct construct (Winzer et al., 2014). This underscores the importance of proactively fostering protective factors such as security and equity to support long-term mental wellbeing. In the survey, the question stem related to the key factor of “Equity” asks respondents to rate their agreement to the statement, “People, including me, are treated fairly.” The most common response was “Sometimes”. This indicates that while some people feel they are treated fairly some of the time, there is a significant portion of people who don't feel they are always treated fairly. This could be due to many factors, such as bias, discrimination, or lack of understanding, which have been shown to impact mental health outcomes (Torales et al., 2023).
Demographic patterns observed in the study offer further insights into these dynamics and highlight this predictive goal. Results of the Psychological Health Survey show that white individuals consistently scored highest across all five elements, highlighting potential privileges in access to conditions that promote mental health. Women scored highest in all elements aside from “Valued”, where men reported slightly higher averages, and “Related”, where scores were similar. These findings mirror broader research trends indicating that gender and racial disparities play a crucial role in determining mental health outcomes (Greggory Swann et al., 2020; “Racial and Gender Discrimination,” 2021). Childhood income patterns revealed varying findings: individuals from below-average incomes reported the highest “Secure” scores, while those from average incomes excelled in “Regulated”, “Valued”, and “Related” Elements, and were comparable to those with above-average incomes within the “Decided” Element. These variations emphasize the importance of understanding situational contexts of equity and impact on mental health.
The Protective Factors Survey observed similar trends, reinforcing the importance of fostering equity to strengthen a sense of security. As the “Secure” element urges the needs for feelings of belonging and safety, interventions aimed at improving equity have the potential to enhance security across different demographics. Strategies such as fostering inclusive spaces and accounting for systemic barriers can address these observed gaps in emotional security by ultimately benefiting psychological resilience. Moreover, by focusing on preventative care and applying early intervention as a means to address security and equity can help foster mental wellbeing before challenges arise, leading to long-term improvements.
The attrition between the Psychological Health Survey and the Protective Factors Survey raises potential concerns about the applicability of the results, as it is possible that those who dropped out differed systematically from those who remained. As a result, the data may overrepresent individuals who are more psychologically protected, while those who dropped out may have reported lower levels of protective factors. Several factors could explain this drop-off rate, including survey fatigue, disinterest, lack of time, or technical issues. These issues can be addressed in future research by simplifying survey design, shortening questions, and providing clearer instructions, reducing survey length, or offering incentives. These strategies can help reduce attrition and increase the reliability of the findings.
Limitations of this study include our use of convenience sampling, which may not be entirely representative of the general population. All demographic groups listed in the software were represented at least once across both surveys, however, the rates of representation differed drastically across race and gender. The primary demographic of survey respondents self-identified as White and female, which limits the relevance of our analysis to various demographics. Future studies can benefit from a larger and more diverse sample to increase generalizability of findings.
This study represents a preliminary exploration of the 5-Elements Framework and its relationship to various demographic factors. Future research with a larger sample size and the inclusion of inferential statistical analysis will allow for more robust conclusions about the significance of these relationships. While this study was limited in its statistical analysis, the descriptive findings provide valuable insights into the relative importance of the different elements of wellbeing and highlight potential areas for intervention and support, particularly regarding the 'Secure' element and its connection to equity.
CONCLUSION: This study explored the importance of preventative care in mental health by examining the 5-Elements of Systemic Wellbeing Framework. Despite the limitations of our convenience sample and the absence of inferential statistical analysis, our findings offer valuable insights into the factors that contribute to psychological wellbeing within this specific group. Mental health surveys often prioritize measuring mental disorders over positive mental health (Smith & Bryant, 2023). Our survey seeks to shift this focus towards proactive intervention, aiming to promote mental wellbeing before issues arise. It is important to acknowledge that each sample population will yield unique results, reflecting the diverse needs and experiences of its members. The 5-Elements Framework, however, provides a versatile tool for interpreting such unique population health data and identifying specific needs. By assessing the relative strengths and vulnerabilities across the five elements, researchers and practitioners can gain a deeper understanding of the key factors that promote mental wellbeing within a given population. Overall this study serves as an example of how the 5-Elements Framework can be applied to uncover patterns and trends in psychological health and protective factors. Future research utilizing this framework with diverse samples and more robust statistical analysis will further enhance our understanding of mental wellbeing across various populations. Ultimately, this approach can inform the development of targeted interventions and support systems that address the unique needs of different communities and promote preventative mental health care.
References
Keyes, C., Dhingra, S., & Simões, E. (2010). Change in level of positive mental health as a predictor of future risk of mental illness. American journal of public health, 100(12), 2366–71. https://doi.org/10.2105/AJPH.2010.192245
Schotanus-Dijkstra, M., Keyes, C., De Graaf, R., & Have, T. (2019). Recovery from mood and anxiety disorders: The influence of positive mental health. Journal of affective disorders, 252, 107–113. https://doi.org/10.1016/j.jad.2019.04.051
Smith, R., & Bryant, R. (2023). Reconsidering the Use of Population Health Surveys for Monitoring of Mental Health. JMIR Public Health and Surveillance, 9. https://doi.org/10.2196/48138
Swann, G., Stephens, J., Newcomb, M., & Whitton, S. (2020). Effects of sexual/gender minority- and race-based enacted stigma on mental health and substance use in female assigned at birth sexual minority youth. Cultural diversity & ethnic minority psychology. https://doi.org/10.1037/cdp0000292.
Torales, J., Aveiro-Róbalo, T. R., Ríos-González, C., Barrios, I., Almirón-Santacruz, J., González-Urbieta, I., Ventriglio, A. (2023). Discrimination, stigma and mental health: what’s next? International Review of Psychiatry, 35(3–4), 242–250. https://doi.org/10.1080/09540261.2023.2186218
Vaingankar, J., Chong, S., Abdin, E., Kumar, F., Chua, B., Sambasivam, R., Shafie, S., Jeyagurunathan, A., Seow, E., & Subramaniam, M. (2020). Understanding the relationships between mental disorders, self-reported health outcomes and positive mental health: findings from a national survey. Health and Quality of Life Outcomes, 18. https://doi.org/10.1186/s12955-020-01308-0
Winzer, R., Lindblad, F., Sorjonen, K., & Lindberg, L. (2014). Positive versus negative mental health in emerging adulthood: a national cross-sectional survey. BMC Public Health, 14. https://doi.org/10.1186/1471-2458-14-1238
(2021). Racial and Gender Discrimination Predict Mental Health Outcomes among Healthcare Workers Beyond Pandemic-Related Stressors: Findings from a Cross-Sectional Survey. International Journal of Environmental Research and Public Health, 18. https://doi.org/10.3390/ijerph18179235.