Abstract
Purpose:
Goals are an important component of quality of life (QoL) as they provide motivation to accomplish tasks we strive to achieve. Stigma has been identified as a factor that may be deleterious to achieving personal goals. People living with HIV(PLWH) continue to face HIV-related stigma. As HIV prevalence continues to grow in the U.S., it is important to focus on factors that can help improve the health and QoL of PLWH. This study aims to examine the association between HIV-related stigma and goal setting behaviors among PLWH in Florida.
Methods:
We used baseline data collected from the Marijuana and Potential Long-term Effects (MAPLE) observational cohort study. We collected life goals data using an abbreviated version of the Personal Projects Analysis inventory. Participants listed up to 3 goals in 5 domains and were asked about each goal’s difficulty and importance. HIV-related stigma was measured using an abbreviated version of the Herek HIV-related stigma scale. Relative risk estimates and 95% confidence intervals were estimated using multivariate linear regression models.
Results:
The overall sample (n=232) was majority male (52.4%), Black (72.4%), and non-Latino (84.9%). HIV-related stigma was positively associated with the total number of listed goals (β= 0.042[0.003, 0.082]; p=0.037) and perceived goal difficulty (β=0.010[0.003, 0.017];p=0.004), but not significantly associated with perceived goal importance (β=0.001[−0.002, 0.004];p=0.562).
Conclusion:
The results suggest that HIV-related stigma may be affecting the pursuit of goals among PLWH. There is a need to develop and evaluate QoL interventions that are tailored to PLWH and focused on achieving goals in the face of HIV-related stigma.
Keywords: life goals, quality of life, HIV/AIDS, stigma
Introduction
Goals are an important component of quality of life (QoL) as goals provide motivation to accomplish life tasks that matter to people [1–4]. Characteristics of goals are multidimensional including dimensions of importance, difficulty, specificity, temporal range, level of consciousness, and complexity [5]. Moreover, goals occur in different aspects of our lives including career/educational achievement, love, health, etc. Understanding factors that may influence life goals and their achievement can identify potential areas of intervention to improve goal attainment.
One factor that has been hypothesized to be deleterious to personal life goals is stigma [6]. As described by Goffman, stigma is an attribute that one has that is socially discrediting being marked as undesirable by others [7]. Since the beginning of the HIV epidemic, PLWH have faced stigma in the form of discrimination, ostracism, and violence. Frameworks of HIV-related stigma identify 4 sub-constructs that comprise HIV-related stigma including: community, anticipated, enacted and internalized stigmas [8]. Community stigma is the perceived stigma in one’s surroundings, while anticipated stigma is the fear of consequences due to HIV-disclosure [8]. Enacted stigma is the direct acts of discrimination of one person to another, while internalized stigma is negative beliefs about one’s self [8]. Previous research has found that HIV-related stigma is associated with poorer mental [9–14] and physical [9, 15, 16] health outcomes, as well as a considerable barrier to HIV care and treatment [14, 17, 18]. As the prevalence of HIV continues to grow in the U.S., it becomes increasingly important to focus on factors that can help improve the health outcomes of PLWH, but also their QoL.
Frameworks such as the “Why Try” model show how stigma may be associated with behaviors to pursue life goals [6]. Corrigan (2009) describes a process in which constructs of stigma influence one another and yield a “Why Try” response [6]. Current editorials on searching for love while living with HIV anecdotally describe this phenomenon, where some PLWH describe experiencing/anticipating rejection, accepting this rejection will occur inevitably, and ultimately giving up on the goal [19–21]. Though the original focus of the “Why Try” model was on mental illness stigma, research cites the theory as it relates to drug use stigma [22, 23], chronic condition stigma (HIV/AIDS, obesity [24], inflammatory bowel disease [25], etc.), and sexuality stigma.
To date, there are no studies that quantitatively examine the relationship between HIV-related stigma and goal characteristics among PLWH in the U.S., which is an important factor in QoL. However, a previous qualitative study among 54 emerging gay/bisexual adults living with HIV found that overcoming interpersonal issues was an obstacle to goal achievement (i.e. HIV status disclosure, working on intimate relationships, etc.) [26]. In addition, a large source of resilience in goal achievement was identified in acting as a role model of PLWH [26]. Though the study by Bruce et al. (2012) was able to elucidate the nuances of goals among young adults living with HIV, the findings may not be generalizable to all PLWH.
Our study addresses this gap by quantitatively examining the association between HIV-related stigma and goal characteristics including: 1) the total number of goals, 2) the average importance of goals, 3) and the perceived difficulty of each goal. We hypothesize that those with higher levels of HIV-related stigma will have a lower number of goals and have lower perceptions of goal importance and ease.
Methods
We used baseline data collected from the Marijuana and Potential Long-term Effects (MAPLE) study. The MAPLE study is an observational cohort study overseen by the Southern HIV & Alcohol Research Consortium (SHARC), whose mission is to improve health outcomes and reduce HIV transmission among people affected by alcohol and HIV in Florida (for more information see https://sharc-research.org/). The MAPLE study recruited from 3 HIV clinical and service provider sites in Alachua (Gainesville), Hillsborough (Tampa), and Miami-Dade Counties (Miami). Participants were eligible to participate in the study if they were living with HIV, ≥ 18 years of age, could communicate in English, and had either confirmed marijuana use or no/very limited marijuana use. Participants completed an interviewer-administered survey at the recruitment site using Research Electronic Data Capture (REDCap). Surveys collected demographic, behavioral, cognitive, and social factors. The survey took approximately 3 hours to complete, and participants received $75 after completion. The Florida International University, University of Florida, and Florida Department of Health Institutional Review Boards have approved the protocol of this study.
Outcomes of Interest
Our outcomes of interest were based on goal characteristics. We utilized an adapted version of the Personal Projects Analysis inventory [27]. Participants were prompted with the following passage, “For this next task, we are going to discuss your goals. I will ask if you have any goals in these categories: personal health, activities or hobbies, family or friends, career or education, and community, church or organizations. Then I will ask some follow up questions for each goal. Choose up to 3 goals for each category. If you do not have any goals in one of these categories, we will move on to the next one.” After all goals were listed in each category, participants were asked for each goal “How important is this goal to you?” and “How easy do you think this goal is to accomplish?”
Total Number of listed Goals
Total number of listed goals was determined by adding the number of goals that were listed by the participant. The total possible number of goals ranged from 0-15, where each of the 5 goal categories had a total possible number of 0-3.
Average Goal Importance
Participants could give each of their listed goals a level of importance of high (score=3), moderate (score=2), low (score=1). The importance scores of the goals were summed and divided by the total number of goals to achieve the average goal importance.
Average Goal Difficulty
Participants could give each of their listed goals a level of difficulty of easy (score=1), moderate (score=2), hard (score=3). The difficulty scores of the goals were summed and divided by the total number of goals to achieve the average goal difficulty.
Predictor of Interest
HIV-related stigma was measured using a version of the Herek HIV-related stigma measure used in the Medical Monitoring Project (α=0.84) [28]. The scale includes items on all 4 sub-constructs of HIV-related stigma including enacted (3-items), community (2-items), anticipated (2-items), and internalized stigma (3-items). The scale included 10, 5-point Likert style questions that assessed agreement with statements of HIV-related stigma, ranging from “strongly disagree” (score=1) to “strongly agree” (score=5). Sample items included, “Having HIV makes me feel unclean,” “Most people think that a person with HIV is disgusting,” etc. Total possible scores ranged from 10-50, high scores meaning higher stigma.
Demographics and Substance Use
Model covariates were self-reported and included age group (18-34, 35-44, 45-54, 55+), biological sex (male, female), race (White, Black, Other/Multi-racial), ethnicity (Hispanic, Non-Hispanic), sexual minority (Yes/No), relationship status (Single/Divorced/Separated, Married/Long-term partner), marijuana use in the past 12 months (Yes/No), and other non-injection drug use in the past 12 months (Yes/No). Those who identified as homosexual, bisexual, or other were coded as ‘Yes’ for sexual minority status while those who identified as heterosexual were identified as ‘No’.
Analysis
All data were analyzed using SAS (v9.4; SAS Institute Inc., Cary, NC). Descriptive characteristics were used to report sample characteristics and characteristics of reported goals. Unadjusted linear regression models were created between HIV-related stigma and other potential covariates with each of the specific goal characteristic outcomes. Covariates with p>0.20 in the unadjusted models were excluded from the final adjusted linear regression models, with the exception of HIV-related stigma which was included in all adjusted models as it was the main predictor of interest. Finally, adjusted linear regression models were conducted using the 1) total number of goals, 2) average goal importance, and 3) average goal difficulty as the outcomes of interest and a cumulative score of HIV-related stigma as the predictor of interest while adjusting for other predictor variables. To be considered significant, α was set to 0.05.
Results
Sample Characteristics
Our study was comprised of n=241 PLWH among 3 different study sites in Florida. Nine participants with incomplete HIV-related stigma scores were removed from the sample leaving a total sample of n=232. The average age of our total sample was 49.3 ± 11.5 years with a range of 22–72 years. The sample was majority male (52.4%), Black (72.4%), non-Latino (84.9%), and heterosexual (67.7%). The overall mean of HIV-related stigma scores was 26.6 ± 9.8 with a range of 10–50 scores. The characteristics of our sample can be found in Table 1.
Table 1.
Sample characteristics of n=232 people living with HIV in Florida
| N (%) | |
|---|---|
| Age group | |
| 18-34 | 38 (16.4) |
| 35-44 | 28 (12.1) |
| 45-54 | 79 (34.1) |
| 55+ | 87 (37.5) |
| Biological Sex | |
| Male | 121 (52.4) |
| Female | 110 (47.6) |
| Relationship status | |
| Single/Divorced/Separated | 185 (79.7) |
| Married/ Long-term partner | 47 (20.3) |
| Race | |
| White | 43 (18.5) |
| Black | 168 (72.4) |
| Other/Multi-Racial | 21 (9.1) |
| Ethnicity | |
| Non-Hispanic | 196 (84.9) |
| Hispanic | 35 (15.2) |
| Sexual Minority | |
| No | 157 (67.7) |
| Yes | 75 (32.3) |
| Education Level | |
| < High School Graduate | 72 (31.0) |
| High School Graduate | 74 (31.9) |
| > High School Graduate | 86 (37.1) |
| Recent Marijuana Use | |
| No | 70 (30.2) |
| Yes | 162 (69.8) |
| Recent Other Non-Injection Drug Use | |
| No | 149 (64.2) |
| Yes | 83 (35.8) |
| HIV-Related Stigma Scale | |
| Total Score | 26.6±9.8a |
Mean±Standard Deviation
Goal Characteristics
Among our participants, there were a total of 1,348 listed goals. Health goals had the highest frequency of being listed (31.5%), while organizational goals had the lowest frequency of being listed (15.1%). Educational/career goals had the highest average difficulty (mean±std:2.12±0.72) had the highest average importance (mean±std:2.90±0.29), while organizational/church goals had the lowest average difficulty (mean±std:1.76±0.75) and activities/hobby goals had least average importance (mean±std:2.77±0.43) (Table 2).
Table 2.
Descriptive Characteristics of Goals stratified by category among PLWH in Florida
| Health | Activities/Hobbies | Family/Friends | Education/Career | Organizational/ Church | |
|---|---|---|---|---|---|
| n (%) or mean±std | n (%) or mean±std | n (%) or mean±std | n (%) or mean±std | n (%) or mean±std | |
| Total number listed | 425 (31.5) | 279 (20.7) | 217 (16.1) | 224 (16.6) | 203 (15.1) |
| Average Difficultya | 2.02±0.68 | 1.85±0.68 | 2.09±0.69 | 2.12±0.72 | 1.76±0.75 |
| Average Importanceb | 2.87±0.30 | 2.77±0.43 | 2.85±0.38 | 2.90±0.29 | 2.83±0.41 |
| Examples | • “Be undetectable” • “Lose 2 pounds per week for 1 year” • “Eat more vegetables and fruits” |
• “Go to Busch Gardens in August” • “Bowl 1 time per week” • “Practice violin 2 times per day” |
• “Get married” • “Get back on good terms with sister” • “Spending more time with father” |
• “Find a job in the next 3 months” • “Get high school diploma” • “Become a motivational speaker” |
• “Volunteer at a hospital” • “Go to church more” • “Go to church with family once a week” |
Higher scores indicate higher difficulty
Higher scores indicate increased perceived importance
Total number of listed goals
The average number of goals listed by the sample was 5.6±3.1 with a range from 0-15. HIV-related stigma, age, race, sexual minority identification and education were associated with total number of listed goals at a significance level of p<0.20 (Table 3). In the adjusted model, total number of listed goals was positively associated with each unit increase of HIV-related stigma (β= 0.042[0.003, 0.082]; p=0.037) and with education ((>H.S. vs H.S.) β=1.357[0.425, 2.290]; p=0.004) (Table 4).
Table 3.
Unadjusted relative risk estimates and 95% confidence intervals for goal seeking behavior outcomes association with HIV-related stigma and other relevant covariates among PLWH in Florida (n=242)
| Number of Goals | Average Importance | Average Difficulty | |
|---|---|---|---|
| RR (95% C.I.) p | RR (95% C.I.) p | RR (95% C.I.) p | |
| Age group | |||
| 18-34 | --- | --- | --- |
| 35-44 | 0.481 (−1.020, 1.983) P=0.530 | 0.049 (−0.060, 0.158) P=0.379 | −0.104 (−0.358, 0.150) P=0.421 |
| 45-54 | −0.365 (−1.555, 0.825) P=0.548 | 0.043 (−0.044, 0.131) P=0.329 | −0.190 (−0.392, 0.013) P=0.066 |
| 55+ | −0.832 (−2.005, 0.340) P=0.164 | 0.064 (−0.022, 0.149) P=0.146 | −0.290 (−0.488, −0.091) P=0.004 |
| Biological Sex | |||
| Male | --- | --- | --- |
| Female | −0.062 (−0.853, 0.729) P=0.878 | 0.012 (−0.047, 0.071) P= 0.699 | 0.041 (−0.097, 0.179) P=0.564 |
| Relationship status | |||
| Single/Divorced/Separated | --- | --- | --- |
| Married/ Long-term partner | 0.461 (−0.532, 1.453) P=0.363 | 0.036 (−0.036, 0.108) P=0.329 | −0.007 (−0.177, 0.163) P=0.938 |
| Race | |||
| White | --- | --- | --- |
| Black | 0.502 (−0.533, 1.538) P=0.342 | 0.037 (−0.039, 0.113) P=0.343 | −0.065 (−0.244, 0.114) P=0.477 |
| Other/Multi-Racial | 1.240 (−0.373, 2.853) P=0.132 | −0.012 (−0.129, 0.105) P=0.841 | 0.082 (−0.195, 0.358) P=0.561 |
| Ethnicity | |||
| Non-Hispanic | -- | --- | --- |
| Hispanic | 0.728 (−0.385, 1.840) P=0.200 | 0.018 (−0.065, 0.101) P=0.668 | 0.089 (−0.107, 0.284) P=0.374 |
| Sexual Minority | |||
| No | --- | --- | --- |
| Yes | 0.637 (−0.214, 1.488) P=0.142 | −0.039 (−0.101, 0.023) P=0.212 | 0.115 (−0.031, 0.261) p=0.122 |
| Education Level | |||
| < High School Graduate | −0.893 (−1.855, 0.069) P=0.069 | −0.034 (−0.108, 0.040) P=0.367 | 0.221 (0.039, 0.384) P=0.017 |
| High School Graduate | --- | --- | --- |
| > High School Graduate | 1.335 (0.413, 2.256) P=0.005 | −0.067 (−0.136, 0.003) P=0.060 | 0.156 (−0.007, 0.319) P=0.061 |
| Recent Marijuana Use | |||
| No | --- | --- | --- |
| Yes | −0.126 (−0.997, 0.745) P=0.776 | 0.032 (−0.032, 0.095) P=0.329 | 0.032 (−0.032, 0.095) p=0.329 |
| Recent Other Non-Injection Drug Use | |||
| No | --- | --- | --- |
| Yes | 0.052 (−0.782, 0.886) P=0.903 | 0.011 (−0.050, 0.072) P=0.729 | −0.074 (−0.218, 0.070) p=0.311 |
| HIV-Related Stigma Scale | |||
| Total Score | 0.051 (0.011, 0.092) P=0.013 | 0.000 (−0.003, 0.004) P=0.792 | 0.012 (0.005, 0.019) p=0.001 |
Table 4.
Adjusted relative risk estimates and 95% confidence intervals for goal seeking behavior outcomes association with HIV-related stigma and other relevant covariates among PLWH in Florida (n=252)
| Number of Goals | Average Importance | Average Difficulty | |
|---|---|---|---|
| RR (95% C.I.) p | RR (95% C.I.) p | RR (95% C.I.) p | |
| Age group | |||
| 18-34 | --- | --- | --- |
| 35-44 | 0.512 (−0.926, 1.951) P=0.485 | 0.065 (−0.045, 0.174) P=0.249 | −0.105 (−0.352, 0.142) P=0.405 |
| 45-54 | 0.183 (−1.000, 1.366) P=0.762 | 0.046 (−0.043, 0.134) P=0.311 | −0.166 (−0.369, 0.038) P=0.111 |
| 55+ | −0.354 (−1.558, 0.850) P=0.565 | 0.073 (−0.015, 0.161) P=0.105 | −0.248 (−0.455, −0.042) P=0.019 |
| Biological Sex | |||
| Male | ---a | ---a | ---a |
| Female | a | a | a |
| Relationship status | |||
| Single/Divorced/Separated | ---a | ---a | ---a |
| Married/ Long-term partner | a | a | a |
| Race | |||
| White | --- | ---a | ---a |
| Black | 0.678 (−0.318, 1.675) P=0.182 | a | a |
| Other/Multi-Racial | 0.875 (−0.661, 2.411) P=0.264 | a | a |
| Ethnicity | |||
| Non-Hispanic | ---a | ---a | ---a |
| Hispanic | a | a | a |
| Sexual Minority | |||
| No | --- | ---a | --- |
| Yes | −0.098 (−0.995, 0.798) P=0.830 | a | 0.051 (−0.101, 0.202) P=0.515 |
| Education Level | |||
| < High School Graduate | −0.744 (−1.707, 0.220) P=0.131 | −0.042 (−0.116, 0.033) P=0.272 | 0.276 (0.107, 0.444) P=0.001 |
| High School Graduate | --- | --- | --- |
| > High School Graduate | 1.357 (0.425, 2.290) P=0.004 | −0.070 (−0.140, − 0.000) P=0.005 | 0.153 (−0.006, 0.313) P=0.060 |
| Recent Marijuana Use | |||
| No | ---a | ---a | ---a |
| Yes | a | ---a | ---a |
| Recent Other Non-Injection Drug Use | |||
| No | ---a | ---a | ---a |
| Yes | a | a | a |
| HIV-Related Stigma Scale | |||
| Total Score | 0.042 (0.003, 0.082) P=0.037 | 0.001 (−0.002, 0.004) P=0.562 | 0.010 (0.003, 0.017) P=0.004 |
Values p>0.20 were not included in adjusted analyses.
Average goal importance
The average goal importance was 2.8±0.2 with a range from 2-3. Increased age and high school education were associated with increased average goal importance at a significance level of p<0.20 (Table 3). HIV-related stigma was not associated with average goal importance at a significance level of p<0.20. In the adjusted model, average goal importance was negatively associated with education ((>H.S. vs H.S.) β=−0.070[−0.140, −0.000]; p=0.005) (Table 4).
Average goal perceived difficulty
The average goal perceived difficulty was 2.0±0.5 with a range from 1-3. HIV-related stigma, age, sexual minority identification, and education were associated with average goal perceived difficulty at a significance level of p<0.20 at the bivariate level (Table 3). In the adjusted model, average goal perceived difficulty was positively associated with each unit increase of HIV-related stigma (β=0.010[0.003, 0.017];p=0.004) and lower education ((<H.S. vs H.S.) β=0.276[0.107, 0.444];p<0.001), and negatively associated with age ((55+ vs 18-34) β=−0.248[−0.455, −0.042];p=0.019) (Table 4).
Discussion
The primary finding of this study was that HIV-related stigma was significantly associated with greater perceived difficulty of goal achievement. Based on the classic work by Locke (1968), harder goals should yield a higher level of performance than easily attainable goals [4]. However, in the “Why Try” model, presented by Corrigan et al. (2009), self-stigma is hypothesized to disempower people, making it harder for them to reach their goals [6]. Our finding could mean that difficulty that is not self-imposed (i.e. HIV-related stigma) could have deleterious effects on the pursuit of life goals, while self-imposed goal difficulty could lead to improved pursuit in life goals. The findings by Kennedy & Willcutt et al. (1964) reported that blame had consistently exhibited a negative effect on goal performance, while praise had a positive effect [29]. We hypothesize that HIV-related stigma may be acting in similar mechanism to reproof and future studies should examine this relationship with additional goal characteristics.
Counter to our initial hypotheses, we found that a greater total number of listed goals was significantly associated with increased HIV-related stigma. As described by Ordonez et al. (2009), pursuing too many goals may lead people to abandon quality goals that require more effort but yield greater rewards for goals that are easier to achieve and measure but may not be as beneficial [30]. Additionally, Shah et al. (2002) demonstrated that people with multiple goals are prone to only focus on one goal while the other goals are ignored [31]. One explanation for the relationship between HIV-related stigma and total number of listed goals could be that stigma may have a deleterious effect on focus, as HIV-related stigma has been associated with other mental health issues [10]. Conversely, our finding may suggest that HIV-related stigma may be promoting drive subsequently resulting in higher numbers of goals. As described by Shih et al. (2004), people with stigmatizing attributes may use self-protective strategies to overcome stigma [32]. One psychological process that could be used to explain potential increase in drive is compensation. Compensation can be described as the development of new skills, the adoption of trying harder, or being more persistent in order to overcome stigma [32]. Future research should focus on coping and empowerment’s role in goal characteristics in the face of stigma.
Given the associations between HIV-related stigma and goal-setting behaviors, future interventions should be developed that address the QoL for PLWH with a focus of how stigma may affect QoL. One current intervention known as Quality of Life Therapy is an evidence-based intervention aimed at populations who wish to be happier and more successful in non-clinical settings [33]. The therapy contains 16 life foci used to enhance overall QoL (life goals and values, relationships, work, play, etc.) [33]. As HIV-related stigma may have a deleterious effect on various life foci, addressing stigma among PLWH in Quality of Life Therapy may be important to consider. Interventions such as Quality of Life Therapy should be assessed to determine acceptability and feasibility among PLWH and tailored to address specific barriers among PLWH in achieving optimal quality of life (i.e. HIV-related stigma).
To the authors’ knowledge this is the first paper to quantitatively examine HIV-related stigma and life goal characteristics among PLWH in the U.S. Though there were other factors like age that were statistically significant, clinical significance of the results should be taken cautiously. The sample listed around 1,350 unique goals related to the 5 measured domains. Though a majority of the research about PLWH is focused on improving health outcomes, the diversity of listed goals demonstrated that PLWH are multi-faceted and that future research among this population should highlight these dimensions with aims to improve QoL.
Limitations
Firstly, our study used a convenience sampling of PLWH which may limit the generalizability of our results as those who consented to be a part of the study may have experienced lower levels of HIV-related stigma. Second, our study utilized baseline data of an ongoing cohort study so we were unable to infer causality. Third, participants were prompted to list goals based on 5 different categories, but this prompting may have pressured participants to list a goal in each of the domains and number of times prompted may have been inconsistent between study sites. Future research should avoid prompting participants to see if unprompted goals are different from prompted goals. Fourthly, importance and perceived difficulty were measured using a 3-point Likert options instead of the typical 10-point options, this may have limited the robustness of results for these two goal characteristics. Lastly, our study only included only 3 goal characteristics from the PPA. Additional research should be conducted on other goal characteristics such as goal quality, interconnectedness, visibility, control, time adequacy, and likelihood of success and its association with HIV-related stigma.
Conclusion
Our study found that HIV-related stigma was significantly associated with increased total number of life goals and increased perceived goal difficulty. As goals are an important indicator of QoL, there is a need to develop and evaluate interventions tailored to PLWH to improve goal characteristics in the face of HIV-related stigma with aims of improving overall QoL.
Acknowledgements:
This research was supported by funding from the National Institute on Drug Abuse (NIDA) project number: R01DA042069 (PI:Cook)
Footnotes
Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.
Conflicts of Interest: The authors declare that they have no conflict of interest.
Ethics approval: Approval was obtained from the Institutional Review Boards of Florida International University, the University of Florida, and the Florida Department of Health. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.
Availability of data and material:
Data can be requested through the process outlined on https://sharc-research.org/get-involved/submit-a-concept/
Consent for publication:
Participants signed informed consent regarding publishing their data.
Consent to participate:
Informed consent was obtained from all individual participants included in the study.
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