Abstract
Background
This study described exposure to abuse (emotional, sexual, and physical) against Latinas in the seasonal farmworker community, and visualized associations of exposure at three time points (past-month, past-12 months, and lifetime) with social network structures.
Methods
Data were collected from 260 Latina seasonal farmworkers in South Florida between 2015 and 2016; the data included 20 friendship networks, each with 13 participants. Chi-square and ANOVA tests describe participants’ characteristics. To evaluate the total number of friendship connections (e.g., ties) an individual (e.g., node), had to the other nodes in a network, R was used to calculate degree centrality. Visone and Cytoscape software were then used to create social network visualizations for each of the sociocentric networks.
Results
Non-U.S. born respondents reported experiencing some form of abuse more often than U.S. born respondents (e.g., 69.7% vs. 13.8% for lifetime emotional abuse). Across all forms of abuse and time points, the prevalence of abuse perpetuated by husbands was the largest, except for lifetime sexual abuse, which was led by close family members (26.8% vs. 21.1%). Network visualizations show that participants who reported lifetime emotional abuse tended to cluster together in their social networks. Cases for the three forms of abuse were present in all networks.
Conclusions
By understanding how women from an undeserved population who have experienced these forms of abuse are linked through their friendship network structures, interventionalists can better identify the role of intimate partner violence in HIV/STD risk reduction interventions, targeted reproductive health approaches, and empower women to report abuse. Network visualizations can be used in process evaluations by informing how to restructure network configurations.
Keywords: Sexual abuse, Emotional abuse, Physical abuse, Latinas
Background
There are approximately 2.9 million agricultural/seasonal farmworkers (seasonal farmworkers) across the United States (US) [1, 2]. The majority of seasonal farmworkers are born outside of the US (70%) of which 63% are born in Mexico according to reports by the National Agricultural Worker’s Survey [3]. Nearly half of farmworkers report being undocumented, with a burgeoning subset of the workforce being composed of women (37%) [4].
Seasonal farmworker communities tend to be isolated, closed networks made up of tight knit social groups, in which behaviors that deviate from cultural, societal, and religious norms are generally not tolerated [5, 6]. These communities are unique due to their adherence to strict gender roles (i.e., machismo and marianismo), the influence of varying levels of acculturation among immigrants, and the interplay of ethnocultural identity, country of origin, and citizenship status [7, 8]. Community members become reliant on one another, especially those from a shared cultural experience; therefore, their social network structures could play an important role in their health outcomes.
In the United States, sexual violence towards Latina women persists. A 2016–2017 Centers for Disease Control and Prevention (CDC) report of weighted lifetime abuse for Latina women living in the US showed that 19.7% had been raped, 16.8% had experienced sexual coercion, 34.8% unwanted sexual contact, and 23.3% sexual harassment in a public place [9]. Latino seasonal farmworker communities have a larger percentage of undocumented workers who may be more susceptible to abuse, discrimination, and prejudice due to their social vulnerability [10]. Studies conducted with Mexican farmworkers in California and Washington demonstrated that experiences of sexual exploitation and harassment are common for women seasonal farmworkers [1, 11, 12]. Kanamori et al. found that Latina seasonal farmworkers’ experiences of mistreatment and abuse from work supervisors included under-payment for hours worked (e.g., stolen hours) [13]. This pattern of exploitation is unsurprising considering that research has linked lower socioeconomic status with a higher prevalence of abuse. Research indicates that low levels of education attainment, poverty, discrimination, unemployment, and limited resources are major factors for intimate partner violence (IPV) among foreign-born and undocumented workers [8, 14–16].
Visualizations are important tools in social network analysis. They help to aggregate the data in a way that makes it easier to understand observations and visualize how nodes (individuals) are tied (related) in a network. Degree centrality refers to the number of ties an individual node has, and this determines a node’s popularity in a network [17]. It can be used to identify actors influencing health outcomes and behaviors within a network [18]. By understanding social network roles and structures, public health interventionists can better pinpoint gaps in community reach or understand what will produce the greatest change [18]. While there are extensive data describing how and why various forms of abuse are accepted among minority populations and how abuse is perpetuated by family and friends, little is known about how abuse clusters in a social network, specifically among immigrant and undocumented communities. The purpose of this study was to describe exposure to abuse (emotional, sexual, and physical) against Latinas in the seasonal farmworker community and to visualize associations of exposure at three time points (past-month, past-12 months, and lifetime) with friendship network structures.
Methods
Participation and recruitment
This is a secondary data analysis using data collected from 260 Latina seasonal workers between 2015 and 2016 who met the following criteria: (a) being aged 18 years old or older, (b) lived in a seasonal farmworker community, (c) fluent in Spanish (reading, writing, and speaking), (d) reporting at least one sexual interaction involving condomless sex, (e) reported consumption of alcohol or other drugs three months prior to the interview, and (f) being able to understand and provide written informed consent. Participants were recruited from various cities in South Florida, including Homestead, Florida City, Naranja, and surrounding areas [19, 20]. Participants were compensated for their time. This data was collected as part of the PROGRESO study, which sought to increase human immunodeficiency virus (HIV) prevention knowledge among Latina seasonal farmworkers who use alcohol or other substances [21, 22]. The PROGRESO intervention was delivered in Spanish so Latina seasonal farmworkers who did not read, write, and speak Spanish were excluded.
This study was made possible with a partnership of a community collaborator that specifically works with Latino seasonal farm working communities in South Florida. A respondent sampling approach was used to develop twenty stand-alone friendship networks that each contained 13 participants. The first phase worked to identify twenty seeds, or “Latina Leaders.” Seed selection was based on an individual’s overall influence in their community, including how they were perceived by community members (i.e., well-respected and/or admired) and the size of their friendship group for the second phase of recruitment. During the second phase, each seed was asked to invite three of their friends to join the study, which were then known as first-order friends. The first-order group was then also asked to invite three of their own friends each (second-order friends) until each group ended with 13 participants in total. To ensure that no one individual overlapped between friendship groups, our community collaborator reviewed each of the twenty social networks. Additionally, the study involved cultural beliefs such as personalism and collectivism. Personalism refers to the tendency and preference of Latinos to associate themselves with other individuals with whom they share similar backgrounds, cultural practices and beliefs, and sociodemographic characteristics (i.e., homophily on educational attainment, socioeconomic status, age, and country of birth). By using a respondent-driven sampling approach, participants could develop their own social environment and promote personalism. Second, collectivism refers to the propensity to develop strong interpersonal relationships based on cultivating mutual trust and support [21].
Trained bilingual interviewers obtained written consent and then administered a quantitative assessment using REDCap (Research Electronic Data Capture) hosted at Florida International University, which lasted 1 h in duration [23, 24]. The study was approved by the Institutional Review Board of The University of Miami (IRB # 20170868).
Measures
Data were collected on age, education, socioeconomic status, country of birth, time spent in the United States, and partner or spousal status [19, 20]. Interviews began by asking participants if they consider the other network members to be one of their friend – responses were binary yes/no. After this assessment of friendship, participants were then asked questions regarding abuse. The abuse questions were selected from the Addiction Severity Index to assess exposure to abuse (emotional, physical, and sexual) during the past 30 days, 12 months, and throughout an individual’s lifetime [25]. Answers to these questions were dichotomized into simple “yes” or “no” responses. The participants who reported that they had experienced abuse (emotional, physical, and/or sexual) at any time point were asked to identify who perpetuated the abuse against them at each time point.
Analyses
Chi-square and ANOVA tests were used to describe the characteristics of study participants at all three timepoints (past 30 days, 12 months, lifetime) for both categorical (proportions) and continuous variables (means and standard deviations). For each of the twenty social networks, a friendship adjacency matrix was obtained to identify relationships between nodes or people. To evaluate the total number of friendship ties a node, or individual, had to the other nodes in a network, R was used to calculate degree centrality. Visone and Cytoscape software were then used to create social network visualizations for each of the sociocentric networks [26, 27]. Participants were represented with circular nodes, popularity was reflected in the node’s size, and colors depicted experiences of abuse (Figs. 1, 2 and 3).
Fig. 1.
Perpetrators of Abuse Among Latina Seasonal Farmworkers by Time of Exposure. South Florida, 2015
Fig. 2.
Social network visualizations and experiences of emotional abuse based on time: a last 30 days, b past 12 months, and c lifetime
Fig. 3.
Social network visualizations and experiences of physical abuse based on time: a last 30 days, b past 12 months, and c lifetime
Results
In the original study, 260 Latina seasonal farmworkers participated. The majority of participants were married (38.5%), were non-U.S. born (82.7%), and had less than a high school education (52%), see Table 1.
Table 1.
Socio-demographic summary of Latina seasonal farmworker participants who reported experiencing emotional, physical and sexual abuse. South Florida, 2015
| Emotional Abuse (n = 260) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 30 days (%) | 12 months (%) | Lifetime (%) | ||||||||
| All | Yes | No | Yes | No | Yes | No | ||||
| Marital Status |
4.055 (= 5) p-value < 0.42 |
3. 5) p-value < 0.598 |
||||||||
| Married | 38.5 | 5.8 | 32.7 | 8.8 | 29.6 | 18.1 | 20.4 | |||
| Separated | 3.8 | 0.4 | 3.5 | 0.8 | 3.1 | 1.9 | 1.9 | |||
| Divorced | 3.1 | 0.0 | 3.1 | 0.8 | 2.3 | 1.9 | 1.2 | |||
| Widowed | 0.4 | 0.0 | 0.4 | 0.0 | 0.4 | 0.4 | 0.0 | |||
| Never married | 20.0 | 3.1 | 16.9 | 6.2 | 13.8 | 11.2 | 8.8 | |||
| Living with a partner | 34.2 | 3.5 | 30.8 | 5.8 | 28.5 | 15.0 | 19.2 | |||
| Country of Origin | ||||||||||
| U.S. Born | 17.3 | 1.9 | 15.4 | 4.2 | 13.1 | 7.7 | 9.6 | |||
| Non-U.S. Born | 82.7 | 10.8 | 71.9 | 18.1 | 64.6 | 40.8 | 41.9 | |||
| Mean age in years (standard deviation) |
35.04 (10.44) |
35.93 (10.32) |
34.93 (10.48) |
42.196 (= 43) p-value < 0.506 |
35.47 (10.82) |
34.92 (10.35) |
44. = 43) p-value < 0.429 |
35.28 (10.06) |
34.82 (10.82) |
54. = 43) p-value < 0.109 |
| Education | ||||||||||
| No formal education of any kind | 5.8 | 0.8 | 5.0 | 1.5 | 4.2 | 2.7 | 3.1 | |||
| Less than high school | 52.0 | 6.3 | 45.7 | 10.1 | 41.9 | 24.7 | 27.3 | |||
| High school diploma | 15.3 | 1.5 | 13.8 | 2.7 | 12.7 | 7.3 | 8.1 | |||
| High school equivalency diploma (G.E.D) | 14.7 | 3.5 | 11.2 | 5.4 | 9.2 | 8.1 | 6.5 | |||
| Some training/college after high school | 9.2 | 0.8 | 8.5 | 2.7 | 6.5 | 5.0 | 4.2 | |||
| Bachelor’s degree | 3.1 | 0.0 | 3.1 | 0.0 | 3.1 | 0.8 | 2.3 | |||
| Physical Abuse (n = 260) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 30 days (%) | 12 months (%) | Lifetime (%) | ||||||||
| All | Yes | No | Yes | No | Yes | No | ||||
| Marital Status |
8.281 (= 5) p-value < 0.141 |
|||||||||
| Married | 38.2 | 1.9 | 36.5 | 3.1 | 35.1 | 15.8 | 22.4 | |||
| Separated | 3.9 | 0.8 | 3.1 | 0.8 | 3.1 | 1.9 | 1.9 | |||
| Divorced | 3.1 | 0.0 | 3.1 | 0.4 | 2.7 | 1.2 | 1.9 | |||
| Widowed | 0.4 | 0.0 | 0.4 | 0.0 | 0.4 | 0.0 | 0.4 | |||
| Never married | 20.1 | 1.9 | 18.1 | 2.7 | 17.4 | 10.8 | 9.3 | |||
| Living with a partner | 34.4 | 0.8 | 33.5 | 2.3 | 32.0 | 15.4 | 18.9 | |||
| Country of Origin | ||||||||||
| U.S. Born | 17.3 | 1.9 | 15.4 | 2.7 | 14.7 | 7.7 | 9.7 | |||
| Non-U.S. Born | 82.7 | 3.5 | 79.2 | 6.6 | 76.1 | 37.5 | 45.2 | |||
| Mean age in years (standard deviation) |
35.04 (10.44) |
33.21 (9.69) |
35.15 (10.49) |
43.278 43) p-value < 0.459 |
35.04 (11.81) |
35.06 (10.33) |
35.49 (10.07) |
34.60 (10.75) |
||
| Education | 2 | |||||||||
| No formal education of any kind | 5.8 | 0.4 | 5.7 | 0.4 | 5.4 | 2.7 | 3.1 | |||
| Less than high school | 52.0 | 2.7 | 49.2 | 5.8 | 45.9 | 24.3 | 27.8 | |||
| High school diploma | 15.4 | 0.4 | 15.0 | 0.8 | 14.7 | 9.3 | 6.2 | |||
| High school equivalency diploma (G.E.D) | 14.6 | 1.2 | 13.5 | 1.5 | 13.1 | 5.4 | 8.9 | |||
| Some training/college after high school | 9.2 | 0.8 | 8.5 | 0.8 | 8.5 | 2.3 | 6.9 | |||
| Bachelor’s degree | 3.1 | 0.0 | 3.1 | 0.0 | 3.1 | 1.2 | 1.9 | |||
| Sexual Abuse (n = 260) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 30 days (%) | 12 months (%) | Lifetime (%) | ||||||||
| All | Yes | No | Yes | No | Yes | No | ||||
| Marital Status | ||||||||||
| Married | 38.5 | 1.2 | 37.3 | 1.2 | 37.3 | 7.3 | 31.2 | |||
| Separated | 3.8 | 0.0 | 3.8 | 0.4 | 3.5 | 1.9 | 1.9 | |||
| Divorced | 3.1 | 0.0 | 3.1 | 0.4 | 2.7 | 1.5 | 1.5 | |||
| Widowed | 0.4 | 0.0 | 0.4 | 0.0 | 0.4 | 0.0 | 0.4 | |||
| Never married | 20.0 | 0.8 | 19.2 | 1.5 | 18.5 | 6.9 | 13.1 | |||
| Living with a partner | 34.2 | 0.0 | 34.2 | 1.5 | 32.7 | 11.2 | 23.1 | |||
| Country of Origin | ||||||||||
| U.S. Born | 17.3 | 0.8 | 16.5 | 1.2 | 16.2 | 4.6 | 12.7 | |||
| Non-U.S. Born | 82.7 | 1.2 | 81.5 | 3.8 | 78.8 | 24.2 | 58.5 | |||
| Mean age in years (standard deviation) |
35.04 (10.44) |
46.69 (14.98) |
34.79 (10.22) |
42.31 (13.49) |
34.66 (10.15) |
35.85 (9.97) |
34.71 (10.63) |
|||
| Education | ||||||||||
| No formal education of any kind | 5.8 | 0.4 | 5.4 | 0.4 | 5.4 | 3.5 | 2.3 | |||
| Less than high school | 52.0 | 1.2 | 50.8 | 3.9 | 48.1 | 15.4 | 36.6 | |||
| High school diploma | 15.4 | 0.0 | 15.4 | 0.0 | 15.4 | 4.2 | 11.2 | |||
| High school equivalency diploma (G.E.D) | 14.6 | 0.0 | 14.6 | 0.4 | 14.2 | 3.1 | 11.5 | |||
| Some training/college after high school | 9.2 | 0.4 | 8.8 | 0.4 | 8.8 | 1.9 | 7.3 | |||
| Bachelor’s degree | 3.1 | 0.0 | 3.1 | 0.0 | 3.1 | 0.8 | 2.3 | |||
Participants who reported being married reported experiencing emotional (EMO) and physical (PHY) abuse but not sexual abuse with the greatest frequency when compared to any other marital status (Table 1). Non-U.S. born citizens reported experiencing some form of abuse more often than U.S. born respondents across all abuse types and time points (Table 1). While the mean age in years for the sample was 35.04, the mean age in years of women who reported sexual abuse in the past 30 days (46.69) and 12 months (42.31) was approximately a decade older. Abuse was highest among participants with less than a high school diploma and lowest among those with a bachelor’s degree across all abuse types and timepoints.
Exposure to abuse
Of the 260 Latinas seasonal farmworkers included in this analysis, 12.7% reported experiencing emotional abuse both in the last 30 days and in the last 12 months, while 48.5% of participants reported experiencing emotional abuse at some point in their lifetime (Fig. 1). In the last 30 days, 5.4% of participants reported experiencing physical abuse, 9.23% reported physical abuse in the last 12 months, and 44.2% reported experiencing physical abuse in their lifetime. Among participants who reported experiencing sexual abuse, 1.5% were in the last 30 days, 5% in the last 12 months, and 5.4% experienced sexual abuse at some point in their lifetime.
Perpetuators of abuse
Among women who reported experiencing emotional abuse in the past 30 days, 33.3% identified their husbands, 9.1% identified both casual sexual partners and their fathers equally, and 21.2% identified their coworkers as being the perpetrators of abuse. This trend continued for the 12-month timepoint, where 52% identified their husbands and 12% identified their casual sexual partners and coworkers equally as being emotionally abusive. Among lifetime reports of emotional abuse, husbands were identified by 44% of participants, casual sexual partners were identified by 14.8%, and other family members were the third most identified subgroup at 13.1%.
Similarly, women who reported experiencing physical abuse primarily identified their husbands as the abusers across all time points (42.9% vs. 45.8% vs. 36.5%). Additionally, casual sexual partners were once again the second leading perpetrators of abuse identified by participants across all time points (21.4% vs. 8.3% vs. 19.1%). Participants identified their siblings and other family members tying for the third highest perpetrator of physical abuse at 14.3% each. In the previous 12 months, brothers, sisters, and daughters ended in a three-way tie at 8.3% each. Finally, over an individual’s lifetime, father and other family members were the third and fourth leading subgroups at 16.5% and 13%, respectively.
Participants identified husbands (50%), casual sexual partners (50%), coworkers (25%), and close friends (25%) as the only perpetrators of sexual abuse in the past 30 days. At the 12-month timepoint, husbands (46.2%), casual sexual partners (38.5%), coworkers (15.4%), and close friends (7.7%) were the only perpetrators of sexual abuse reported. Across an individual’s lifetime, husbands (21.1%), casual sexual partners (18.3%), and other family members (26.8%) were the leading perpetrators of sexual abuse reported.
Overall, across all forms of abuse and timepoints, participants reported their husbands as being the primary perpetrator of the abuse they experienced.
Social network visualization of abuse in friendship networks
In the social network visualizations shown in Figs. 2, 3 and 4, degree centrality is depicted by the size of each node in the nine visualizations. The larger the circumference of a node, or individual, the greater their overall popularity in the friendship network in which they participate. Each relationship tie, or friendship connection, may be unidirectional (straight line) or bidirectional (curved line). The bidirectionality of the line implies a friendship connection that is acknowledged by both nodes. Each abuse type is represented by its own color with shades highlighting each of the three timepoints. Participants, or nodes, who reported experiencing emotional abuse are diagramed in shades of red, while physical abuse and sexual abuse are shown in green and blue, respectively.
Fig. 4.
Social network visualizations and experiences of sexual abuse based on time: a last 30 days, b past 12 months, and c lifetime
At the past 30-days and previous 12-months timepoints for emotional, physical, and sexual abuse, there is little to be drawn from the network visualization to describe whether abuse is associated with social network structures. The lifetime data provide a more telling story of the friendships formed and abuse experienced by Latina seasonal farmworkers. For lifetime emotional abuse, each network has a clear majority with the nodes that had greatest degree centrality, regardless of identifying as abused vs. non-abused nodes, in a network being indicative of whether the network had more nodes who reported abuse or not. This trend was less apparent in the social network visualizations for either physical or sexual abuse. In the lifetime data visualization for physical abuse (Fig. 2), few social network groups were predominantly composed of nodes who reported abuse. This inclination was mirrored in the lifetime social network visualization for sexual abuse (Fig. 3). Participants who reported lifetime emotional abuse tended to cluster together in their social networks. Such clusters were also seen in lifetime physical and sexual abuse visualizations to a lesser degree. Every network had at least one node that reported experiencing some form of abuse over an individual’s lifetime.
Overall, the social network visualizations depict a well-socialized network that has, with few exceptions, robust traversing lines with definitive bidirectionality, further describing a well-connected host of friendship networks.
Discussion
Findings from this study highlight the significant proportion of Latina seasonal farmworkers who experience emotional, physical, and sexual abuse during their lifetime. Husbands were the primary perpetrators across most forms of abuse, except for lifetime sexual abuse, where close family members were more frequently identified. Male relatives and social contacts were also more commonly reported as abusers than female counterparts in all abuse categories. These results underscore that Latina seasonal farmworkers experience victimization from many sources. Further, the multiple perpetrators of abuse suggests that there are a complex dynamics within this community which may allow violence to persist.
Social network analysis has been shown to identify community-level gaps in intervention approaches for emotional and physical abuse [28] and sexual health [29, 30] and can be used to understand community characteristics and relationships. These data can then be employed to make suggestions about how different health outcomes or behaviors are influenced by shared experiences, peer influence/popularity, and characteristic-specific trends in a network. A study found that social networks in seasonal farmworker communities are increasingly being disrupted, which influences their closeness with members from the community [13]. Latina seasonal farmworkers reported that changes in network closeness were due to (1) a changing community, (2) acculturation and decreasing respect, and (3) the restrictive schedule of seasonal work [13]. Disruptions in the networks of Latina seasonal farmworkers may be related to the widespread experiences of violence, as protective resources and support networks are disrupted. This emphasizes the need for programs and interventions that promote social cohesion as a protective factor.
The importance of promoting social cohesion is emphasized in immigrant and migrant communities were community acceptance and social conformity are driving factors of behavior [7, 31]. A study mapping how IPV acceptance is clustered among Honduran households found that reporting IPV acceptance was linked to having other social network contacts also reporting acceptance of IPV [32]. Notably, similar patterns are seen in our emotional and physical violence networks (Figs. 2 and 3), in which the majority of networks have multiple connected respondents reporting abuse.
Beyond the immediate effects of abuse faced by Latina seasonal farmworkers, the long-lasting repercussions on mental and physical health are extensive. Victimization may be from a single perpetrator, but often they are not isolated events, with higher frequencies of victimization leading to increasingly worse mental and physical health outcomes in later life [8, 15, 33–35]. The results from the nationwide Sexual Assault Among Latinas (SALAS) study showed that 53.6% of women reported at least one experience of victimization (i.e., physical abuse, sexual abuse, witnessing violence, and stalking) during their lifetime, while 66.2% reported two or more experiences of victimization [33]. Among participants who experienced victimization, 20.7%, 30.7%, and 22.1% had clinically significant levels of depression, anxiety, and anger, respectively [15]. In terms of STD/HIV risk, married women experiencing physical and sexual abuse from partners and spouses are at an elevated risk of acquiring HIV compared to women who do not report IPV [36–38]. A systematic review analyzing the last 40 years of IPV and sexual health research found that IPV was linked to several sexual and reproductive health concerns, including inconsistent or condomless intercourse, having an abortion due to an unplanned pregnancy, developing an STD, and sexual dysfunction [39]. These negative ramifications are particularly salient issues for Latina seasonal farmworkers who experience a multitude of barriers to accessing healthcare some of which include cost, language, and insurance coverage.
This study is presented in the context of some limitations. The stigma and silencing gender norms surrounding admitting spousal abuse and sexual abuse may have resulted in underreporting abuse. Additionally, participants were also asked to identify the perpetrators of abuse in their lives, which could have further prevented them from speaking up for fear of any possible repercussions. Generalizability may be limited by the geographical context in which this study was conducted, Miami-Dade is a majority minority county, with a large Latino community. The study includes sociocentric networks of groups of 13 individuals. Finally, eligibility required respondents to be fluent in Spanish, these individuals may differ from English speaking Latinas. Therefore, additional research exploring the experience of English-speaking Latina seasonal farmworkers is required.
By understanding how different factors such as abuse are experienced in an underserved population through their social contacts, interventionalists can better identify and incorporate multilevel risk factors, including the role of IPV in HIV/STD risk reduction interventions, targeted reproductive health approaches, and empowering women to report abuse. Future network-based interventions should be able to incorporate social network approaches, such as (1) identification of opinion leaders who act as peer change agents, (2) participants’ recruitment by community members from each seed using respondent-driven sampling, (3) incorporation of social context in intervention delivery, (4) increase of social cohesion to improve information seeking and social support among group members, (5) information diffusion through social networks, and (6) promotion of women’s empowerment. As a secondary data analysis, the purpose of this work was to elucidate the existence of violence in this underserved community. Further research is needed to understand multilevel factors that facilitate the perpetration of violence in this community. Importantly, future work must consider the socioecological environment and its hinderance of accessing support and leaving abusive situations.
Conclusion
Our study advances knowledge on the associations of sexual, emotional, and physical abuse at different timepoints in a community of women who face more complex barriers to healthcare and resource availability considering their socioeconomic status and immigration status. The structure of social networks should be accounted for in the design of programs and strategies that address the abuse experienced by Latina seasonal farmworkers. The high prevalence of violence against these Latinas underscores the importance of developing and implementing culturally informed, engaging, and accessible programs that can prevent and mitigate the negative health ramifications. Future interventions must empower Latina women and provide them with viable support and resources to escape abusive situations.
Acknowledgements
We acknowledge all participants from the study for their contribution.
Abbreviations
- ANOVA
Analysis of Variance
- EMO
Emotional Abuse
- HIV
Human immunodeficiency virus
- IPV
Intimate partner violence
- PHY
Physical Abuse
- STI
Sexual Transmitted Infections
Authors’ contributions
LS: conceptualization, methodology, formal analysis, and writing – original draft. MK: conceptualization, methodology, supervision, funding acquisition, and writing – review & editing. JAF: formal analysis, visualization, and writing – reviewing & editing. AJ: writing – original draft and writing – reviewing & editing. ER: writing – original draft. TP: writing – original draft and writing – reviewing & editing. LD: writing – original draft and writing – reviewing & editing. All authors reviewed the study design and methods and edited the manuscript. All authors have reviewed and approved the final manuscript.
Funding
Research reported in this publication was supported by the National Institute on Drug Abuse (Awards # K99DA041494 PI: Kanamori; R00DA041494 PI: Kanamori), the National Institute of Mental Health (Awards # R01MH125727 PI: Kanamori; P30MH116867 PI: Safren; Subaward PI: Kanamori), and the National Institute of Minority Health Disparities (Awards # R01MD018343 PI: Kanamori; U54MD002266 PI: Behar-Zusman; P20MD002288 PI: De La Rosa). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse, the National Institute of Mental Health, the National Institute of Minority Health Disparities, or the National Institutes of Health.
Data availability
The data that support the findings of this study were collected for the study Progreso en Salud: Findings from Two Adapted Social Network HIV Risk Reduction Interventions for Latina Seasonal Workers; it is available from Dr. Mario De La Rosa upon reasonable request and with permission from Florida International University.
Declarations
Ethics approval and consent to participate
All relevant ethical safeguards have been met in relation to participant protection. The study was approved by the Institutional Review Board of The University of Miami (IRB # 20170868). As such, this research adhered to the principles set forth in the Belmont Report. Women interested in participating were given a consent form, in which they were explained the methodology, risks and benefits of the research, and monetary compensation for their time. If signed, participants were given the right to not answer any question(s) and to withdraw from the interview at any time if they felt uncomfortable. All participants included in this project signed the informed consent form prior to the completion of any study activities.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.National Center for Farmworker Health. Facts About Agricultural Workers. 2022. https://www.ncfh.org/facts-about-agricultural-workers-fact-sheet.html.
- 2.National Center for Farmworker Health. 2017 Agricultural Worker Population Estimates [Private Data Source]. 2020. http://www.ncfh.org/population-estimates.html.
- 3.Gold A, Fung W, Gabbard S, Carroll D. Findings from the National Agricultural Workers Survey (NAWS) 2019–2020: a demographic and employment profile of United States farmworkers. In. vol. Research Report #16; 2022.
- 4.Rosenbloom R. A profile of undocumented agricultural workers in the United States. Edited by Center for Migration Studies of New York (CMS) Report. New York, New York: CMS.; 2022.
- 5.Burke Winkelman S, Chaney EH, Bethel JW. Stress, depression and coping among Latino migrant and seasonal farmworkers. Int J Environ Res Public Health. 2013;10(5):1815–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.McCullagh MC, Sanon M-A, Foley JG. Cultural health practices of migrant seasonal farmworkers. J Cult Divers. 2015;22(2):64–7. [PMC free article] [PubMed] [Google Scholar]
- 7.Ravelo GJ, Sanchez M, Cyrus E, De La Rosa M, Peragallo N, Rojas P. Associations between gender norms and HIV self-efficacy among Latina immigrants in a farmworker community. Ethn Health. 2022;27(1):27–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Sabina C, Cuevas CA, Schally JL. The effect of immigration and acculturation on victimization among a National sample of Latino women. Cult Divers Ethn Minor Psychol. 2013;19(1):13–26. [DOI] [PubMed] [Google Scholar]
- 9.Basile KC, Smith SG, Kresnow M, Khatiwada S, Leemis RW. The national intimate partner and sexual violence survey: 2016/2017 report on sexual violence. Edited by National Center for Injury Prevention and Control CfDCaP. Atlanta, GA.; 2022.
- 10.Snipes SA, Cooper SP, Shipp EM. The only thing I wish I could change is that they treat Us like people and not like animals: injury and discrimination among Latino farmworkers. J Agromedicine. 2017;22(1):36–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kim NJ-E, Vásquez VB, Torres E, Nicola RMB, Karr C. Breaking the silence: sexual harassment of Mexican women farmworkers. J Agromed. 2016;21(2):154–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Waugh IM. Examining the sexual harassment experiences of Mexican immigrant farmworking women. J Agric Saf Health. 2010;16(3):237–61. [DOI] [PubMed] [Google Scholar]
- 13.Kanamori M, Shrader CH, St George S, Adkins T, Bartholomew TS, Sanchez M, de la Rosa M. Influences of immigration stress and occupational exploitation on Latina seasonal workers’ substance use networks: a qualitative study. J Ethn Subst Abuse. 2022;21(2):457–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Davila AL, Johnson L, Postmus JL. Examining the relationship between economic abuse and mental health among Latina intimate partner violence survivors in the united States. J Interpers Violence. 2021;36(1–2):NP287–310. [DOI] [PubMed] [Google Scholar]
- 15.Cuevas CA, Sabina C, Picard EH. Interpersonal victimization patterns and psychopathology among Latino women: results from the SALAS study. Psychol Trauma. 2010;2(4):296–306. [Google Scholar]
- 16.Quandt SA, Kinzer HT, Trejo G, Mora DC, Sandberg JC. The health of women farmworkers and women in farmworker families in the Eastern United States. Latinx Farmworkers in the Eastern United States: Health, Safety, and Justice. edn. Edited by Arcury TA, Quandt SA. Cham: Springer International Publishing; 2020. pp. 133–161.
- 17.Golbeck J. Analyzing networks. Introduction to social media investigation. edn. Edited by Golbeck J. Boston: Syngress; 2015. pp. 221–235.
- 18.Stacciarini J-MR, Vacca R, Mao L. Who and where: A socio-spatial integrated approach for community-based health research. Int J Environ Res Public Health. 2018;15(7):1375. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Kanamori M, De La Rosa M, Weissman J, Rojas P, Villar ME, Trepka MJ, Dillon F, Jaramillo M. Associations between drug/alcohol use and emotional abuse: who perpetrates emotional abuse against Latina women? J Epidemiol Res. 2016;2(1):95–101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kanamori M, Weissman J, De La Rosa M, Trepka MJ, Rojas P, Cano MA, Melton J, Unterberger A. Latino Mother/Daughter dyadic attachment as a mediator for substance use disorder and emotional abuse. J Immigr Minor Health. 2016;18(4):896–903. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Kanamori M, De La Rosa M, Diez S, Weissman J, Trepka MJ, Sneij A, Schmidt P, Rojas P. A brief report: lessons learned and preliminary findings of progreso En Salud, an HIV risk reduction intervention for Latina seasonal farmworkers. Int J Environ Res Public Health. 2017;14(1):32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Kanamori M, De La Rosa M, Shrader C-H, Munayco C, Doblecki-Lewis S, Prado G, Safren S, Trepka MJ, Fujimoto K. Progreso En salud: findings from two adapted social network HIV risk reduction interventions for Latina seasonal workers. Int J Environ Res Public Health. 2019;16(22):4530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, McLeod L, Delacqua G, Delacqua F, Kirby J, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95:103208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—A Metadata-Driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.McLellan AT, Kushner H, Metzger D, Peters R, Smith I, Grissom G, Pettinati H, Argeriou M. The fifth edition of the addiction severity index. J Subst Abuse Treat. 1992;9(3):199–213. [DOI] [PubMed] [Google Scholar]
- 26.Brandes U, Wagner D. Analysis and visualization of social networks. Graph drawing software. edn. Edited by Jünger M, Mutzel P. Berlin, Heidelberg: Springer Berlin Heidelberg; 2004. pp. 321–340.
- 27.Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Klevens J, Shelley G, Clavel-Arcas C, Barney DD, Tobar C, Duran ES, Barajas-Mazaheri R, Esparza J. Latinos’ perspectives and experiences with intimate partner violence. Violence against Women. 2007;13(2):141–58. [DOI] [PubMed] [Google Scholar]
- 29.Behler RL, Cornwell BT, Schneider JA. Patterns of social affiliations and healthcare engagement among Young, Black, men who have sex with men. AIDS Behav. 2018;22(3):806–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Bogart LM, Wagner GJ, Green HD, Mutchler MG, Klein DJ, McDavitt B. Social network characteristics moderate the association between stigmatizing attributions about HIV and Non-adherence among black Americans living with HIV: a longitudinal assessment. Ann Behav Med. 2015;49(6):865–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Kim-Godwin YS, Fox JA. Gender differences in intimate partner violence and alcohol use among Latino-Migrant and seasonal farmworkers in rural southeastern North Carolina. J Commun Health Nurs. 2009;26(3):131–42. [DOI] [PubMed] [Google Scholar]
- 32.Shakya HB, Hughes DA, Stafford D, Christakis NA, Fowler JH, Silverman JG. Intimate partner violence norms cluster within households: an observational social network study in rural Honduras. BMC Public Health. 2016;16(234):233–233. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Cuevas CA, Sabina C, Milloshi R. Interpersonal victimization among a National sample of Latino women. Violence against Women. 2012;18(4):377–403. [DOI] [PubMed] [Google Scholar]
- 34.Fortuna LR, Noroña CR, Porche MV, Tillman C, Patil PA, Wang Y, Markle SL, Alegría M. Trauma, immigration, and sexual health among Latina women: implications for maternal–child well-being and reproductive justice. Infant Mental Health J. 2019;40(5):640–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Hazen AL, Connelly CD, Soriano FI, Landsverk JA. Intimate partner violence and psychological functioning in Latina women. Health Care Women Int. 2008;29(3):282–99. [DOI] [PubMed] [Google Scholar]
- 36.Rahman M, Nakamura K, Seino K, Kizuki M. Intimate partner violence and symptoms of sexually transmitted infections: are the women from low Socio-economic strata in Bangladesh at increased risk. Int J Behav Med. 2014;21(2):348–57. [DOI] [PubMed] [Google Scholar]
- 37.Decker MR, Miller E, Kapur NA, Gupta J, Raj A, Silverman JG. Intimate partner violence and sexually transmitted disease symptoms in a National sample of married Bangladeshi women. Int J Gynaecol Obstet. 2008;100(1):18–23. [DOI] [PubMed] [Google Scholar]
- 38.Silverman JG, Decker MR, Saggurti N, Balaiah D, Raj A. Intimate partner violence and HIV infection among married Indian women. JAMA. 2008;300(6):703–10. [DOI] [PubMed] [Google Scholar]
- 39.Coker AL. Does physical intimate partner violence affect sexual health? A systematic review. Trauma Violence Abuse. 2007;8(2):149–77. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study were collected for the study Progreso en Salud: Findings from Two Adapted Social Network HIV Risk Reduction Interventions for Latina Seasonal Workers; it is available from Dr. Mario De La Rosa upon reasonable request and with permission from Florida International University.




