Demographic on Help-Seeking between People based on Use of (Mental) Healthcare

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Introduction
Help-seeking behavior has been broadly defined and has multiple confounding variables. Multiple health, psychiatric, educational, and other problems often require an individual to seek help from professionals such as doctors, psychologists, social workers, educators, etc. It has been understood that having certain problems may limit a person's desire to seek help whether it be due to social anxiety, lack of motivation, or lack of understanding about the issue they're having. Cornally and McCarthy conducted a study that identified help-seeking behavior utilizing the definition of both help and seeking to present a simple model of the concept as the act of looking for a source of relief to meet a need; however, this definition may fluctuate relative to the need that the individual is seeking help for (e.g., response to health fluctuations vs. communicating in effort to understand and gain support for a problem). This study also focused on the presence of prerequisites to help seeking behavior which feed into the defining attributes of help-seeking, and the action of help-seeking leads to the consequences of doing so; however, help seeking behavior is also implicated by the resources available to the individual seeking help (Figure 1; 2011).  (Cornally & McCarthy, 2011).
Another important distinction is the difference between help-seeking behavior and help-seeking intention. This is important for us to understand because any individual in distress may intend to seek help for whatever problem they may be facing; however, there may be barriers in the way to actively doing so. These barriers may come in as an antecedent (e.g., where individuals fail to recognize a problem), in the defining attributes of help-seeking (e.g., where there is no action to resolve the problem), or with the empirical factors (e.g., where there is no source available to seek help or a person misunderstands where to get help from). Predictors of help-seeking intentions involve an individual's awareness of their needs, social supports, and affective presentation (e.g., depression inhibits help-seeking). While help-seeking intention is a major predictor of help-seeking behavior, it cannot be assumed that having intention will lead to the behavior because there are factors that may intervene before a plan is put into action. The implementation of help-seeking behavior has been shown to be moderated by gender, an individual's understanding of their subjective needs, and their symptom presentation; there is also a significant interaction between subjective needs and social support, though social support is more indicative in help-seeking intention (Nagai, 2015). Given that we understand that these things impact an individuals' decision to seek help for their needs, it is important for us to explore how help-seeking behavior is moderated by external factors to the process itself.

Demographic Features
Research has demonstrated that demographic factors are significant in help-seeking behaviors. Younger individuals are more likely to seek help; whereas, older adults tend to have negative attitudes to doing so. Women are often more open to seeking help than men are. Ethnic groups tend to vary significantly in their help-seeking patterns, utilization, and attitudes toward resources which is often influenced by religion, illness attribution, and stigma. Education has a significant interaction with help-seeking behavior where lower education is often deterrent due to lack of understanding about their conditions and the resources available to them. Finally, marital status is often negatively associated with help-seeking behavior, where individuals who have never been married are more likely to seek help (Picco et. al., 2016).
Men have demonstrated significantly less visitation to professionals than women do, and while there has been consideration that this is related to women's additional needs (i.e., prepartum care), men have demonstrated less participation in preventive care measures. This difference is being understood as a fundamental difference in how men seek help. Men are significantly less likely to report emotional distress, and their baseline for visiting a professional is physical symptomatology. These differences have been more significantly correlated to life choices when comparing men and women directly than a fundamental difference between the genders (Galdas et. al., 2005). When assessing these lifestyle differences, age is a major factor in whether men will seek help, and contrary to the general population, men are more likely to seek help with older age than when they are young. Demographic region also impacts this differential as men living outside of a major city are less likely to seek help. Lifestyle factors that are more common in men which have a detrimental impact on help seeking behavior include smoking and frugality, where women tend to prioritize their health instead of saving extra money; however, the opposite is true of men who are diagnosed with ongoing or chronic conditions (Schlichthorst et. al., 2016).
Women's help-seeking behaviors are also influenced by other socio-demographic factors; however, in general, women are more likely to seek help than men regardless of age or culture. As such, women's help-seeking behaviors are mitigated by factors like intimate partner violence and symptoms postpartum depression. Postpartum depression acts similarly to other symptoms of depression in decreasing the likelihood of help-seeking behavior. The impact of intimate partner violence may involve a variety of somatic symptoms as well as vulnerability to multiple psychiatric symptoms; however, help-seeking behavior among abused women is significantly lower than non-abused women, despite utilizing more healthcare services (Hooker et. al., 2019). This experience is mitigated further by age, education, abuse severity, and relationship to the abuser; however, ethnicity was most significant because women of different cultures may have more inherent distrust of medical or legal services. Women that make up minority populations are less likely to seek these services, but they are also likely to use these services differently. For example, where Caucasian women would present to a hospital, African American women are more likely to call the police (Flicker et. al., 2011).
When looking specifically at individuals' ethnicity and its impact on help-seeking behavior, it's noticeable that racial discrimination plays a pivotal role in individuals' distrust of the resources that are set up as a part of the system that discriminated against them. Racial discrimination inherently involves vast emotional and psychological complications, including a general stress response that is maintained throughout minority communities. The stressors are unique to different minority groups: Native American individuals received less education in general, Asian Americans reported the most education, African Americans are more likely to be pulled over while driving, and Latinos are more likely to be called out for violating social norms. Many of these behaviors are immediately reflective of the participants' trust in help-seeking agencies, most of which being a significant negative impact (Carter & Forsyth, 2010). These minority groups often also have reduced access or have experiences in their life that confirm the bias that helpful agencies will not be helpful to them. To feed into the mistrust, minority patients are unlikely to receive care from professionals of their same race. While the culture of mistrust for the majority group prevents minority individuals from seeking care, the occasional utilization of (mental) healthcare from individuals of the majority group often prevents individuals from seeking care unless it becomes imperative to their health (Townes, et. al., 2009).
Age is a significant predictor of (mental) healthcare utilization. While we see the general trend that younger people are more receptive to help-seeking than their older counterparts, there is a disparity in the adolescent population borne out of a lack of understanding about what symptoms they should be seeking help for. Almost half of adolescents are diagnoseable with mood disorders, 30% of whom are reporting experiences of hopelessness daily when reflecting a two-week period. Adolescents who correctly identify their difficulties do not feel comfortable consulting trusted adults which has been affiliated with cultural differences (i.e., Latino males' help-seeking is threatening to their expected presentation of machismo), increased stigma, or decreased normalization related to seeking help outside of the family or religious leaders (De Luca et. al., 2019). Institutional sources of intervention (i.e., school suicide prevention programs) that are utilized in effort to normalize help-seeking in adolescents often further stigmatizes their symptoms by further pathologizing the symptoms that they need help for which propagates the fear that their peers will tease them and tends to counteract the desired effect (Strunk et. al., 2014).
Sexual orientation has also been demonstrated to impact help-seeking behavior. This occurs in part because there is less perceived access to care for these groups which in part is true due to less benefits associated with partner insurance and other policies. This is detrimental to their health because, like any other minority, they are more predisposed for psychiatric diagnoses. Additionally, this population is more at risk for sexually transmitted infections. While the distribution of this population demonstrates high factors of mistrusting the healthcare system and providers, so they are less likely to disclose information, they also demonstrate higher risky behaviors (e.g., smoking, drug use, social isolation) and lower self-efficacy behaviors (McKirnan et. al., 2013).

Insurance Coverage & Socioeconomic Status
Insurance coverage can be a significant barrier to receiving healthcare; however, research has demonstrated that when making access available to individuals who experiences a barrier associated with their socioeconomic status, having health insurance coverage did not reduce the relative mortality risk of these individuals, implying that help-seeking behavior is pivotal for individuals to improve their (mental) health outcomes (Sudano & Baker, 2006). This has been connected to healthcare policy and education of individuals.
Public policy impacts this association because healthcare policy has become more active, diverse, long-term, and risk-based regarding the patients' roles. Years ago, the sick role was a temporary status that would occur in response to acute symptoms; therefore, the patient was passively participating in whatever intervention the professional would utilize to treat their symptoms. The sick role has evolved in the presence of chronic ailments to be prolonged and involve the active participation of the client, whether that be in taking medicine, checking blood glucose measures, or frequent appointment follow ups. There are inherent biases within this system, as discussed in the demographics section, that may impede help-seeking behaviors, but there is also a greater need for patients to reach out and engage that many people are not equipped to do financially, in consideration with their work schedule, or otherwise (Boyer & Lutfey, 2010). A study by Courtmanche that estimated the effects of the Affordable Care Act (ACA) determined that the ACA improved access to care across all measurable dimensions and subsequently has improved patient treatment in the spectrum of chronic disease and mental health (2018). Policy like this can change the entire (mental) healthcare landscape and inherently improve help-seeking behavior by removing barriers to access.
Regarding education, a key factor in socioeconomic statis, it has been demonstrated that individuals who do not receive a high school diploma are associated with increased susceptibility to both medical and psychiatric problems (e.g., diabetes, depression chronic health condition), and the socioeconomic position of individuals is more significant than the stressors that the individuals presented with in their life. An exploratory mechanism for this explains that education implicates health behaviors, psychosocial stressors, and access to insurance coverage ( While education is significant in the production of future help-seeking behavior, students who are currently in the higher education system demonstrate higher levels of stress and expectation that propagate (mental) health problems (Chang et. al., 2019). When assessing medical students, the burnout rate is up to half of them with a clinically significant presentation of depression or anxiety. Of these students, less than 20% engaged in formal or informal help-seeking behaviors, and while more research is required to understand why this is the case, there were reports that help-seeking was nonnormalized, and students feared complications with licensure associated with reporting mental health symptoms (Fischbein & Bonfine, 2019).
To expand on the broader concept of socioeconomic status, research has established that both parental and patient socioeconomic status has a direct impact on help-seeking behavior. Across different forms of help-seeking (e.g., formal help-seeking vs. informal help-seeking), there is an agreement that poor socioeconomic status is associated with the general tendency to seek few sources of formal help and less sources of informal help than the general population. This is vitally important because socioeconomic status is affiliated with other factors that predict poor help-seeking behavior (e.g., ethnicity, intimate partner violence). This, of course, applies as well to the fundamental underpinnings of socioeconomic status, education and income (Cattaneo & DeLoveh, 2008). Additionally, research has shown that women with poor socioeconomic status are more likely to seek help from spiritual houses rather than more formal professionals (Oladipo & Balogun, 2009 Individuals who meet diagnostic criteria for psychiatric disorders have been shown to avoid psychological treatment due to factors including social stigma, treatment concerns, fear of emotions, anticipated utility versus the risk, and concerns about self-disclosure (Vogel et. al., 2007). While depressed individuals of different cultures are still susceptible to cultural impacts, depressed individuals are also more likely to experience reduced self-efficacy and hopelessness, as such, it's important to identify any additional barriers to care in order to treat as much of the affected population as possible. It has been established that individuals with major depression, longer-term depression, and comorbid diagnoses are more likely to access care (Magaard et. al., 2017). A study by Roness and colleagues identified that only 11% individuals with diagnoseable depression and/or anxiety ever sought help for their symptoms, regardless of the source that they were seeking help from (2005). When they surveyed their participants regarding why they did or did not seek help, stigma was a salient factor as well as the thought that psychological disorders weren't something that could be improved (Roness et. al., 2005).

Specific Aims
The first aim of the study is to determine if demographic factors impact help-seeking behavior regarding mental health care. There are mixed results about whether demographic factors impact help-seeking behavior in the research that has been performed so far. Varying results are often contingent on one issue being more salient than another (i.e., depression is a stronger predictor that can cross otherwise agreed upon demographic information). Establishing the significance of demographic variables would give (mental) healthcare providers a better idea of how to approach patients of different demographic makeups. The major hypothesis of this specific aim is that there will be significant differences between different demographic factors of patients in the healthcare system.
The second aim of the study is to compare patients within treatment foci to determine if people who seek help are significantly different from people who often refrain from seeking help. This will also inform us about differences of people who seek certain types of treatment, have different symptomatology, and who delay care. This information surpasses the demographic information to enable professionals to tailor their patient care more appropriately still. The hypothesis here is that people who seek therapy services, psychotropic medications, and mixed modalities of healthcare will be significantly different from one another.
There are multiple general studies about help-seeking behavior in individuals, and this study will add to the research base by utilizing the most recent data from the Center for Disease Control (CDC) Household Pulse Survey at the time of data analysis to attempt to identify demographic information in the population today. The purpose of this study is to determine the effects of demographic variables on help-seeking behavior; it is then hypothesized that individuals who seek help are significantly different from individuals who do not seek help. Likewise, when comparing groupings based on insurance coverage, diagnoses, or differing treatment within themselves, it is hypothesized that individuals will differ significantly from one another depending on help-seeking behavior, symptom presentation, and type of treatment sought.

Data Sample
A sample of data from the CDC Household Pulse Survey during the dates of March 17 th and March 29 th in 2021 was utilized for this study. This survey is a 20-minute investigation of individuals' use of (mental) healthcare, insurance status, and symptom presentation related to both depression and anxiety. Adaptations of the Patient Health Questionnaire-2 (PHQ-2), a two question assessment of depression, and the General Anxiety Disorder-2 (GAD-2), a two question assessment of anxiety, were utilized to survey symptom presentation (National Center for Health Statistics, 2021b). Participants were asked when in the past month they needed mental health services (National Center for Health Statistics, 2021c). Participants were asked if they are currently covered by health insurance and to specify how they were insured (e.g., through an employer, Medicare, or other specific health maintenance organizations; National Center for Health Statistics, 2021a). Finally, participants were asked if they delayed or didn't access care at any time in the past month in order to determine restrictions of access to care during the pandemic (National Center for Health Statistics, 2021d). The data was reported in the format of the frequency in the population who was surveyed, adults who completed the United States Census with access to an email and internet connection (National Center for Health Statistics, 2021b). The Pulse Survey reports frequencies in order to protect the confidentiality of their participants; however, access to the frequency information is available for public use (United States Census Bureau, 2021).

Defining Constructs
The results of the Pulse Survey have been adapted to represent the constructs that this study is interested in reviewing. Most of this is applying the general results to normal circumstances when they were surveyed during and related to the COVID-19 pandemic, understanding that some of the results may be inflated in this context.

Health Insurance Coverage
Health insurance coverage can present as an impediment to accessing care and is often correlated with socioeconomic status. As such, this study attempts to analyze health insurance coverage in the context of demographic characteristics to understand who is most likely to maintain insurance coverage. Correlational statistics will also be utilized to understand how groups with different health insurance coverage vary from one another. As reported from the survey, health insurance coverage is broken down into levels consisting of: uninsured, public insurance, and private insurance.

Anxiety and Depression
As we understand help-seeking behavior, individuals with anxiety and depression may be less likely to present to (mental) health services. As reported from the survey, Anxiety and Depression are broken down into levels consisting of: anxiety symptoms, depression symptoms, and both. Symptom presentations of depression and anxiety as screened by the survey are utilized to understand the proportion of the population is currently presenting with diagnoseable depression and/or anxiety. Subsequently, we attempt to understand if there is a demographic effect associated with individuals who report depressive and anxiety symptomatology and to compare depressed or anxious individuals to each other.

Help-Seeking for Mental Health Care
The report of help-seeking care for mental health problems was explicit in asking if participants were using psychiatric medication, psychotherapy, both, and not receiving care that they understand they need (National Center for Health Statistics, 2021d). The intention is to utilize this information as a metric of help-seeking behavior for mental health concerns. This data is used to identify demographic differences in individuals who seek help for mental health concerns; additionally, comparing the differences between people who use different mental healthcare services provides an idea if there are differences associated with the use of different services.

Help-Seeking for Medical Care
The report of help-seeking for medical care asked if individuals delayed access to healthcare or refrained from accessing healthcare, regardless of whether it is mental healthcare or medical care. As reported from the survey, Medical Care is broken down into levels consisting of: delaying care and not seeking care. This data is used to identify demographic differences in individuals who seek help or delay it. Comparing the differences between people who delay or do not access services provides an idea of whether there are differences associated with the delay of healthcare rather than refusing to seek help at all.

Negative Conditions
Negative conditions were created in order to represent individuals who reported not needing these resources.
Since the data was presented in the format of percentages out of one hundred, the positive conditions (i.e., for mental healthcare: using psychiatric medication, using psychotherapy, both, or needing services but not seeking them) presented as results of the study were summed and subtracted from one hundred in order to obtain the percentage of participants who reported the negative condition (i.e., for mental healthcare: the absence of use for psychiatric medication or psychotherapy). These negative conditions are: not reporting mental health symptoms (for anxiety and depression), not needing psychiatric care (for mental healthcare), and not needing medical care (for medical care).

Statistical Analysis
The data was transformed from frequency data to nominal data that reflected either the presence or absence of a condition. To recreate the frequency information in the cleaned dataset, data lines were organized by demographic identifiers and repeated, so the sum of each demographic condition for each variable (i.e., location, gender, health insurance status, etc.) was 30 lines, as required to make a simple random sample, making each entry equal to approximately 3.33%. This complication is accepted in order to appropriately apply the demographic information to the various levels of each variable that was considered in this study. Statistics were run in SPSS.

Chi Squared
The Chi Squared test is utilized to understand how individuals between the demographic groups differ for each factor that was considered. Every level of demographic factors, insurance coverage, mental health diagnoses, and help-seeking behaviors is compared against the demographic identifiers to identify differences between the sample in each level of these constructs. The observed values for the demographics are compared to what would be expected in the event that the sample demonstrated a standardized distribution of symptoms, insurance coverage, or help-seeking behaviors.

Correlations
Correlations are utilized within demographic factors, insurance coverage, mental health diagnoses, and help-seeking behaviors to determine if individuals at each level of the individual constructs are different from one another. This does not inform us of how the constructs are different, but we can identify weak and strong relationships within the different levels of each construct. These relationships can be positive, indicating that they are related to one another, or negative, indicating that they are different from one another.

Demographic Factors
The results of the chi squared test demonstrate significant relationships in several levels of the demographic factors, insurance coverage, mental health diagnoses, and help-seeking behaviors; however, not all of them are different from what would be expected of a sample distribution. When sorting by the identifier, uninsured status, diagnosis of comorbid depression and anxiety, not needing (mental) healthcare, and reporting no mental health symptoms are all characterized of different demographics than what would be expected from a standardized sample.

Health Insurance Coverage
The distribution of individuals who are younger, males, Hispanic or Latino, less educated, and located in the Southern Atlantic region are most likely to be uninsured. The distribution of individuals who are older, women, multiracial, more educated, and located in the New England region are most likely to be insured.

Anxiety and Depression
The distribution of individuals who are younger, female, multiracial, and less educated are more likely to be diagnoseable with comorbid depression and anxiety. There is no specific region that consistently presents more with comorbid diagnoses; however, there are some specific states that are more likely to present with comorbid depression and anxiety (specific states include: California, Hawaii, Mississippi, Nevada, West Virginia). The distribution of individuals who are older, male, Asian, more educated, and located in the Midwestern region (in addition to Virginia and Delaware) are less likely to be diagnoseable with comorbid depression and anxiety. It's important to note that this is in reference to comorbid anxiety and depression; results related to anxiety or depression themselves were not related.

Help-Seeking for Mental Health
The distribution of individuals who are young, female, more educated, a part of any ethnic minority (particularly multiracial individuals), and are located in the southern region of the United States as well as parts of the Pacific Region and the Northeast Region are more likely to report needing mental health treatment. The distribution of individuals who are older, male, less educated, Hispanic or Latino, and are located in the Western and Midwestern Region as well as Florida are less likely to report needing mental health services. When considering help-seeking for mental healthcare, there was no difference associated with utilization of psychiatric medication or psychotherapy based on demographic factors; however, there is information identifying demographic characteristics of individuals who do or do not seek mental health treatment.

Help-Seeking for Medical Care
The distribution of individuals who are older, educated with a high school diploma or GED, Non-Hispanic Caucasian, located in the Mountain region, located in parts of the South Atlantic region, located in the Northeast region, or located in the Midwest Region are less likely to need medical care. The distribution of individuals who are younger, educated with less than a high school diploma, Hispanic or Latino, Asian, multiracial, located in the Southern Region, or located in the Pacific region are more likely to need medical care. With this results for help-seeking for medical care there was no difference associated with delaying or not seeking medical care but comparing the individuals who reported not needing medical care to the entire sample of individuals who reported needing medical care provided differences relative to the demographic features of both groups.

Differences within Healthcare Utilization Categories
The results of bivariate correlation demonstrate differences within the levels of the demographic factors, insurance coverage, mental health diagnoses, and help-seeking behaviors. This demonstrates relational differences within the groups and the strength or weakness of the relationship. This information is useful because it informs us that there are differences in the demographics of people who have health insurance coverage, anxiety and depression, and help-seeking behaviors when looking at the different levels within each construct.

Health Insurance Coverage
There is a strong negative correlation between individuals who use private insurance and those who use public insurance (r = -0.783, p < 0.01). There is a moderate negative correlation between individuals with private insurance and individuals who are uninsured (r = -0.486, p < 0.01); however, there is only a mild negative correlation between individuals who are uninsured and those who have public insurance (r = -0.160, p < 0.001). Note. **. Correlation is significant at the 0.01 level.

3.2.1Anxiety and Depression
There is a moderate to strong negative relationship between no reported symptoms and depression (r = -0.624, p < 0.01), anxiety (r = -0.669, p < 0.01), and a mixed presentation (r = -0.434, p < 0.01). When comparing the symptom presentations to one another, depression has a mild positive relationship with anxiety (r = 0.208, p < 0.01) and a moderate to strong positive relationship with a mixed presentation (r = 0.622, p < 0.01); whereas, anxiety has a moderate relationship with a mixed presentation of symptoms (r = 0.576, p < 0.01). Note. **. Correlation is significant at the 0.01 level.

Help-Seeking for Mental Health
Individuals who received mental health treatments via different modalities had more differences than similarities. Individuals who were treated with psychiatric medication had a mild negative relationship with those who were treated with psychotherapy (r = -0.177, p < 0.01) and a moderate negative relationship with individuals who are treated with both psychiatric medication and psychotherapy (r = -0.229, p < 0.01). When comparing individuals who were treated with psychotherapy to individuals who were treated with both modalities of treatment, there is a mild negative relationship (r = -0.197, p < 0.01). There is a mild negative relationship between individuals who did not receive treatment that they reported needing and use of psychiatric medication (r = -0.187, p < 0.01), use of psychotherapy (r = -0.123, p < 0.01), and a multimodal approach to treatment (r = -0.209, p < 0.01). Note. **. Correlation is significant at the 0.01 level.

Help-Seeking for Medical Care
There are moderate to strong negative relationship between individuals who did not seek care for their concerns and both individuals who delayed medical care (r = -0.526, p < 0.01) and individuals who reported not needing care (r = -0.598, p < 0.01). Individuals who reported not needing care have a moderate negative relationship with individuals who delayed medical care (r = -0.367, p < 0.01). Note. **. Correlation is significant at the 0.01 level.

Demographics
The results of this study support the hypothesis that individuals with different help-seeking behaviors are different from one another based on demographic variables. The ability to identify demographic factors that are associated with help-seeking behaviors, presentation of anxiety and depression, and use of (mental) healthcare provides a trajectory for patient care. There are, of course, going to be exceptions to the standard of care; however, understanding that individuals coming from certain backgrounds are more likely to have certain presentations is a valuable tool.
Treatment standards may be improved significantly if we can apply a general understanding of which individuals are predisposed to certain behavioral patterns. This is an issue associated with culturally informed practices in the field of psychology. Psychologists have a toolbox of treatment procedures that have been studied and empirically validated on population samples; however, there is variability in people. Some variates are simply a product human behavior, perspectives, and free will; however, it has been established that demographic differences often play a role in how people vary. Cognitive-behavioral therapy is the most studied branch of psychotherapy. As such, it is the most widely accepted psychotherapeutic method; however, the research progression has begun to identify applications of cognitive-behavioral therapy that do not apply to certain demographics in their original form. Treatment modalities occasionally need to be modified to best serve patients and to serve different patients. Updates to assessments and treatments are necessary in (mental) healthcare, and demographic differences in the patient population enable these updates to have more utility, efficacy, and specificity than their former versions.
Another use of differentiating individuals of different demographics is targeting new public policy to help individuals who either do not have access to care or refuse to seek it because of their intimidation of the system. Statistically speaking, minority populations fail to trust the system even when they need care. There are multiple reasons that this may be the case ranging from a lack of representation among professionals to a culture of mistrust in the broader context of society. There are small steps that can be taken to change this reality such as ijps.ccsenet.org International Journal of Psychological Studies Vol. 15, No. 2;2023 providing additional scholarships for minority individuals to seek professional education, reducing care and insurance costs, and giving minority practitioners incentive to work in areas where representation is lacking. Additionally, to tackle the problem associated with difficulty to access care, healthcare reform could involve universal healthcare at the government level or a system to increase access at the office level. Providers could do more to set follow-up appointments, keep contact with patients, or reach out in the community to engage new patients. Ultimately changing the outlook of the healthcare system, so clients are not responsible for engaging initially and repeatedly, especially related to preventive care, would better the outlook for the entire patient population. Many of these same suggestions could also be applicable to individuals with low socioeconomic status. Employing changes related to policy or professional approaches to clientele can only improve (mental) healthcare, regardless of predisposition, but an understanding of how peoples' behaviors differ demographically can only help.

Within-Group Differences
The results of this study also support the hypothesis that individuals within the different behavioral groups are different from one another. While we were unable to determine exact details about where the groups diverge from one another, there is an implication that the differences between these groups will impact treatment because of the negative relationships that they have between one another. Additionally, the information that people seeking different kinds of treatment are different may inform treatment trajectories, particularly when patients are expressing a preference to one treatment or another.

Health Insurance Coverage
The strong negative relationship between individuals with public and private insurance informs that there are differences within this population. Given that there is only a mild negative relationship between individuals who are uninsured and individuals who have public insurance, it could be hypothesized that these people generally have similar demographic backgrounds (e.g., slightly better socioeconomic status). It is interesting that there is only a moderate negative relationship between people with private insurance and people who are uninsured. This could mean that individuals who are qualifying for private insurance were a part of the uninsured population, but some reform in the healthcare system has enabled them to receive a plan with a private insurance company.
Since it is impossible, in this study, to know how these groups are differentiated, these hypotheses are purely hypothetical, based on associations that are made about the population and conclusions drawn about demographic differences.

Depression and Anxiety
The finding that there is a moderate to strong negative relationship between individuals who report no psychiatric symptoms and individuals who reported symptoms of depression, anxiety, or both is understandable.
Psychologists expect that there are differences in individuals are diagnosable with psychological disorders and those who do not present pathologically. The important findings are that depression has a mild positive relationship with anxiety and a moderate to strong positive relationship with a mixed presentation while anxiety has a moderate relationship with a mixed presentation of symptoms. This suggests that the demographic characteristics of people who have depression are only somewhat like people who have anxiety, and both symptom presentations have stronger relationships with a mixed presentation. This information, if future research is done to determine how the individuals differ, could be useful in determining who in the population is predisposed to different symptom presentations.

Help-Seeking for Mental Healthcare
The information that individuals who seek different modalities of mental health treatment differ demographically may be influential to treatment trajectory. The mild negative relationship between treatment with psychiatric medication and psychotherapy is expected because different courses of treatment are likely to be effective for different people. Similarly, the mild negative relationship between individuals who did not seek treatment and individuals who sought any form of treatment is understood because the treatment modalities would only be useful to people who need it, and a divergence was identified in individuals who report symptoms. To some degree, people with different diagnoses will differ demographically; there is an understanding that psychiatric disorders are more likely to present in certain types of people (e.g., bipolar disorder in women). The moderate negative relationship between individuals who are treated with psychiatric medication and individuals who are treated with both psychiatric medication and psychotherapy is interesting because there should, theoretically, be more similarity between people who seek treatment with psychiatric medication and both sources of treatment than people who seek psychiatric treatment and psychotherapy alone. There is also a mild negative relationship between individuals who seek psychotherapy and individuals who received mixed modality treatment. Collecting more data about these populations to determine how they are similar and different would be useful for providers to effectively treat the patient population.

Help-Seeking for Medical Care
The moderate to strong negative relationship between individuals reported not needing care to individuals who delay medical care and individuals who do not seek care is expected, as a fundamental of this study. The important takeaway is that individuals who delayed care differ demographically, with a moderate to strong negative relationship, from individuals who did not seek care. This is important because, with further research, identifying the difference between people who put off care and never seek it in the first place may lead to the development of an intervention that would make it easier to contact these patients. Doing so would change the scope of treatment, and patients who are reluctant to seek care may be reached by the (mental) healthcare system in effort to provide them with preventive medicine or otherwise engage their use of the (mental) healthcare system.

Limitations and Future Directions
The dataset itself has some limitations because the Household Pulse Survey was designed to reach the United States population during the COVID-19 pandemic. As such, information that would normally be collected by an extensive interview was modified to be reported by an online survey. Other CDC surveys, of the same constructs, have been designed to accommodate face-to-face or telephone interviews as time progresses; however, the Household Pulse Survey was designed from shortened assessments and simple questions. This limits the validity of the information that is provided because if participants fail to understand the questions asked, they are unable to clarify what is wanted from them. This is countered by the benefit of anonymity that is created by answering an online survey rather than reporting to a person. Measurement error (i.e., providing incorrect information, misunderstanding questions), coverage error (e.g., recruitment based on accessibility to internet), nonresponse error (e.g., unwillingness to provide information), and processing error (e.g., lost information or mis-entered information) are all maximized due to the adaptation of this survey and subsequently the dataset (National Center for Health Statistics, 2021b). The dataset may have also overreported reductions in access to care because the questions about access to care were asked in the context of the COVID-19 pandemic (National Center for Health Statistics, 2021d).
This study was limited to some extent by the dataset that was used because the data reported was frequency information, and in order to analyze demographic characteristics, the data was cleaned to be sorted by these demographic characteristics rather than by qualification of symptomatology, insurance, or use of health care. In order to do this, the data was transformed from frequency values into a nominal identification of their status within the defined variables. This limited the statistical tests that could be run on the data. While differences of the between demographic groups were identified utilizing the Chi Square metric, related to the demographic factors, insurance coverage, mental health diagnoses, and help-seeking behaviors assessed in this study, the divergence that occurs in the correlations within construct groups cannot be pinpointed specifically. It is also impossible to compare the different variables to one another, so we cannot determine if these factors are predictive of one another or even if they correlate directly to one another.
In future examinations of demographic factors, insurance coverage, mental health diagnoses, and help-seeking behaviors, it would be most useful to gather data about the individual participants themselves, and rather than reporting their frequencies, utilizing the individual data across all constructs to establish a premise of when and how the constructs present with one another. While we were able to conclude general demographic trends as they are related to help-seeking behavior from this study, the interaction of the constructs would likely identify more demographic differences related to how the presentations are combined. Utilizing the participants' information enables this integral comparison of the constructs and would enable the field to have a better understanding of help-seeking behavior, how it develops, and individual characteristics of participants that may impact the presentation of help-seeking behaviors.

Conclusion
While this study provided some important demographic information about individuals' help-seeking behaviors, further research is needed for us to fully understand when, why, and how different people in different circumstances seek help for medical, mental health, education, and other needs. The hypotheses were confirmed that people are different from one another both between and within groups; however, more specific participant information is required to demonstrate the different layers associated with help-seeking behavior, so that is the future direction that is most recommended. This is important because if we can establish who (culturally, based on age, based on gender, etc.) is more likely to display different help-seeking attitudes, the patient experience can be tailored specifically to reach the broadest expanse of patients.