The association between life satisfaction, emotional support, and perceived health among women who experienced intimate Partner violence (IPV) - 2007 behavioral risk factor surveillance system

The association between psychological distress, abusive experiences, and help-seeking among people with intimate partner violence

BACKGROUND

Intimate partner violence (IPV) is a serious public health problem associated with countless adverse physical and mental health outcomes. It places an enormous economic and public health burden on communities. The aim of this study was to examine the associations between psychological states (such as depression or hopeless) and help-seeking experiences of IPV survivors after experiencing IPV, based on the Allegheny County Health Survey (ACHS).

METHODS

Data from 2015 to 2016 Allegheny County Health Survey with N = 8,012 adults were analyzed. The 6-item version of the Kessler Psychological Stress Scale, located in Module 11 of the ACHS questionnaire, was used to measure psychological stress in participants. Module 12 of the ACHS questionnaire collected information on participants' experiences of intimate partner violence and help-seeking in the past 12 months. Descriptive statistical analysis, Pearson's chi-square or two sample independent t-tests statistical analysis, and multivariate binary logistic regression models were used to analyze the relationship between IPV experience and psychological distress.

RESULTS

A total of 212 of the 8,012 participants had IPV experience, with age, marital status, education, income, and race significantly different from those without IPV experience. The psychological stress of participants feeling hopeless (OR = 2.02, 95% CI = 1.37-2.99), restless or fidgety (OR = 1.83, 95% CI = 1.27-2.65), perceiving everything was an effort (OR = 1.55, 95% CI = 1.08-2.22) and worthless (OR = 1.49, 95% CI = 1.01-2.20) was associated with the IPV experience. Help-seeking behaviors of IPV survivors were associated with psychological distress, such as hopelessness (OR = 6.71, 95% CI = 1.38-32.60).

CONCLUSIONS

This study explored the association between IPV experience, help-seeking and psychological distress, and the need to expand community support. It is necessary to implement targeted interventions, enhance training of professionals, and promote the identification of early IPV cases as well as collaboration between healthcare and social support departments to reduce the occurrence of IPV or psychological distress following IPV.

Examining the Supports and Advice That Women With Intimate Partner Violence Experience Received in Online Health Communities: Text Mining Approach

BACKGROUND

Intimate partner violence (IPV) is an underreported public health crisis primarily affecting women associated with severe health conditions and can lead to a high rate of homicide. Owing to the COVID-19 pandemic, more women with IPV experiences visited online health communities (OHCs) to seek help because of anonymity. However, little is known regarding whether their help requests were answered and whether the information provided was delivered in an appropriate manner. To understand the help-seeking information sought and given in OHCs, extraction of postings and linguistic features could be helpful to develop automated models to improve future help-seeking experiences.

OBJECTIVE

The objective of this study was to examine the types and patterns (ie, communication styles) of the advice offered by OHC members and whether the information received from women matched their expressed needs in their initial postings.

METHODS

We examined data from Reddit using data from subreddit community r/domesticviolence posts from November 14, 2020, through November 14, 2021, during the COVID-19 pandemic. We included posts from women aged ≥18 years who self-identified or described experiencing IPV and requested advice or help in this subreddit community. Posts from nonabused women and women aged <18 years, non-English posts, good news announcements, gratitude posts without any advice seeking, and posts related to advertisements were excluded. We developed a codebook and annotated the postings in an iterative manner. Initial posts were also quantified using Linguistic Inquiry and Word Count to categorize linguistic and posting features. Postings were then classified into 2 categories (ie, matched needs and unmatched needs) according to the types of help sought and received in OHCs to capture the help-seeking result. Nonparametric statistical analysis (ie, 2-tailed t test or Mann-Whitney U test) was used to compare the linguistic and posting features between matched and unmatched needs.

RESULTS

Overall, 250 postings were included, and 200 (80%) posting response comments matched with the type of help requested in initial postings, with legal advice and IPV knowledge achieving the highest matching rate. Overall, 17 linguistic or posting features were found to be significantly different between the 2 groups (ie, matched help and unmatched help). Positive title sentiment and linguistic features in postings containing health and wellness wordings were associated with unmatched needs postings, whereas the other 14 features were associated with postings with matched needs.

CONCLUSIONS

OHCs can extract the linguistic and posting features to understand the help-seeking result among women with IPV experiences. Features identified in this corpus reflected the differences found between the 2 groups. This is the first study that leveraged Linguistic Inquiry and Word Count to shed light on generating predictive features from unstructured text in OHCs, which could guide future algorithm development to detect help-seeking results within OHCs effectively.

An assessment of self-rated life satisfaction and its correlates with physical, mental and social health status among older adults in India

Life satisfaction refers to the assessment of one's own life in terms of self-perceived favourable qualities. It is an integral part of healthy and successful course of ageing. It is widely associated with the health status and social well-being. The present study attempted to determine the constructing factors of self-rated life satisfaction, such as socio-demographic, physical, social, and mental well-being of older adults. We analysed information from the Longitudinal Ageing Study in India (LASI-1), the initial phase conducted during 2017-18 for the population of older adults in India. We applied descriptive statistics for prevalence assessment and association was checked using chi-square test. Further, to determine the adjusted outcome of predictor covariates on the likelihood of an individual being satisfied from life estimated by applying hierarchical multiple logistic regression models. Several noteworthy affirmations on the relationship between the socio-demographic variables and health risk behaviours with life satisfaction were observed. The results were consistent with studies showing change in life satisfaction subject to the state of physical and mental health, presence of chronic diseases, friends and family relations, dependency, and events of trauma or abuse. While comparing respondents, we found varying degrees of life satisfaction by gender, education, marital status, expenditure and other socio-economic features. We also found that besides physical and mental health, social support and well-being play a pivotal role in achieving higher life satisfaction among older adults. Overall, this work contributes to the study of the subjective well-being of older adults in India based on self-reported levels of life satisfaction and further narrows the gap in knowledge about associated behaviour. Hence, with on-going ageing scenario, there is need for multi-sectorial policy-oriented approaches at individual, family, and community level, which helps to take care of older-adults' physical, social, and mental health for the betterment of healthy ageing.

Harnessing Machine Learning in Tackling Domestic Violence-An Integrative Review

Domestic violence (DV) is a public health crisis that threatens both the mental and physical health of people. With the unprecedented surge in data available on the internet and electronic health record systems, leveraging machine learning (ML) to detect obscure changes and predict the likelihood of DV from digital text data is a promising area health science research. However, there is a paucity of research discussing and reviewing ML applications in DV research.

METHODS

We extracted 3588 articles from four databases. Twenty-two articles met the inclusion criteria.

RESULTS

Twelve articles used the supervised ML method, seven articles used the unsupervised ML method, and three articles applied both. Most studies were published in Australia (n = 6) and the United States (n = 4). Data sources included social media, professional notes, national databases, surveys, and newspapers. Random forest (n = 9), support vector machine (n = 8), and naïve Bayes (n = 7) were the top three algorithms, while the most used automatic algorithm for unsupervised ML in DV research was latent Dirichlet allocation (LDA) for topic modeling (n = 2). Eight types of outcomes were identified, while three purposes of ML and challenges were delineated and are discussed.

CONCLUSIONS

Leveraging the ML method to tackle DV holds unprecedented potential, especially in classification, prediction, and exploration tasks, and particularly when using social media data. However, adoption challenges, data source issues, and lengthy data preparation times are the main bottlenecks in this context. To overcome those challenges, early ML algorithms have been developed and evaluated on DV clinical data.

Satisfaction with the life of Polish women experiencing domestic violence

Introduction

Domestic violence against a woman, inflicted by her husband/partner, disrupts the socially recognized model of partnership and family life and endangers the health and life of the victim. The aim of the study was to assess the level of satisfaction with the life of Polish women experiencing domestic violence and compare it to results of women not experiencing domestic violence.

Methods

A cross-sectional study was conducted on a convenience sample of 610 Polish women divided in two groups: victims of domestic violence (Group 1, n = 305) and women not experiencing domestic violence (Group 2, n = 305).

Results and Conclusions

Most Polish women experiencing domestic violence are characterized by low life satisfaction. The mean value of life satisfaction in Group 1 was 13.78, SD = 4.88, significantly lower when compared to Group 2 (M = 21.04, SD = 5.61). Their satisfaction with life is related, among other things, to the form of violence inflicted upon them by their husband/partner. Abused women with low life satisfaction are most often victims of psychological violence. The most common cause is the perpetrator's addiction to alcohol and/or drugs. Assessment of their life satisfaction is unrelated to help-seeking and to the occurrence of violence in their family home in the past.

Coping and Protective Factors of Mental Health: An Examination of African American and US Caribbean Black Women Exposed to IPV from a Nationally Representative Sample

Existing research continues to highlight the harm that intimate partner violence (IPV) can pose to health and well-being. However, little is done to understand the effectiveness of coping and protective mechanisms in helping women manage under adverse circumstances. The current study addresses the mental health of US Black women and the role of coping and protective moderators. An analysis of data from the National Survey of American Life (2001-2003), the most comprehensive survey on the health of US Blacks, was conducted. The association between severe physical intimate partner violence and mental health outcomes were confirmed. Resilience moderated the relationship between severe intimate partner violence and mood disorder among US Black women, but this differed between African American and Caribbean Blacks. Resilience, emotional family support, and spirituality reduced the likelihood of having a mental health condition for some African American and Caribbean Black women, while the opposite was found for religiosity. Demographic factors were also associated with mental health conditions and behaviors. The study draws our attention to potential coping and protective mechanisms that could be incorporated into counseling and intervention practices while recognizing factors that may be harmful to the mental health of individuals.