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Record W2008209544 · doi:10.4103/0972-6748.110938

Women and mental health: Psychosocial perspective

2012· article· en· W2008209544 on OpenAlexaboutno aff
Kalpana Srivastava

Bibliographic record

VenueIndustrial Psychiatry Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPerspective (graphical)Mental healthPsychologyPsychotherapistComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The World Health Organization's Ottawa Charter for Health Promotion sees health as multidimensional and espouses a social model of health. It defines health as 'a positive concept emphasizing social and personal resources, as well as physical capacities.' 'Mental health is the capacity of the individual, the group and the environment to interact with one another in ways that promote subjective well-being, the optimal development and use of mental abilities (cognitive, affective, and relational), the achievement of individual and collective goals consistent with justice and the attainment and preservation of conditions of fundamental equality.[1] Discussions on health issues pertaining to women have largely addressed the biological and reproductive factors. However, women's well-being is apparently beyond biological factors and reproduction. The issues like workload, stress, migration, and nutrition are equally important.[2] The gender perspective into the health sector requires a broad-based definition of health for women as well as men that address well-being across the life cycle and in domains of both physical and mental health. Gender considerations in health promotion and healthcare have to highlight the mental health risks and the socioeconomic and cultural determinants of mental health. Apparently, economic independence, physical, sexual, and emotional safety and security are primarily needed for good mental health. Unfortunately, same are supposedly denied to some women by virtue of their status as women. Such gender-based discrimination is not only a gross violation of human rights but directly contributes to the growing burden of disability caused by poor mental health. Hence, need of the hour is to discuss the association of these factors with mental health of women. In the context of Burden of Disease, it is estimated that depression will become the second most important cause of disease burden in the world by the year 2020. Women in developed and developing countries alike are almost twice as likely as men to experience depression. Other two leading causes of disease burden estimated for the year 2020, namely violence and self-inflicted injuries, have special relevance for women's mental health.[3] Let us try to examine some of the contributory factors and their association with mental health of women. SOCIAL SUPPORT AND ITS RELATIONSHIP WITH MENTAL HEALTH Social support has long been considered to be having an impact on mental health of women. A study carried out by Coker et al.,[4] to find out mental health status of women found good social support was associated with significantly reduced risk of a range of adverse mental health outcomes and further that higher levels of emotional support can modify the effect of intimate partner violence on health. The study suggested that interventions to increase emotional and social support to women victims of violence might reduce the negative consequences of mental and physical health. Violence against women is like an endemic in society. It is estimated that 14–20% of women will experience rape at some point in their lives,[5] and 8–24% will be stalked by someone known or unknown to them. When added to the 25–35% likelihood that the average adult woman has been sexually abused as a child.[67] SOCIAL LEARNING THEORY OF VIOLENCE This theory asserts that human aggression and violence are learned conduct, especially through direct experience and by observing the behavior of others. According to this theory, the individual learns violence through imitation. Individuals pick up the behavior patterns of those they are taught to respect and learn from. Aggressive behavior patterns learned through modeling and imitation remain part of our repertoire of social responses over time. Rewards and punishments also play a crucial role in the learning and expression of behavior patterns. SYMBOLIC INTERACTION THEORY This theory specifies the process by which self-image and identity of a person as 'violent' are formed, and the process by which violent acts acquire individual and socially shared meaning. It explains the origin and maintenance of the structure of meaning that is necessary for all human social behavior, including violence. This perspective focuses its attention on the nature of interaction, the dynamic patterns of social action, and social relationships. It attempts to understand action as the participant himself understands it. Violence in any form may entail harmful consequences. There is evidence of the long-term and deleterious effects of experiencing childhood violence in early years. The association that has emerged has indicated that witnessing childhood violence leads to poor mental health during woman's adult years. Childhood violence also has long-term psychological effects on women. Those women who had witnessed violence were found to be having depression and poor self esteem.[8] Further, women who experienced physical or sexual abuse in childhood also experienced ill-health with regard to physical functioning and psychological well-being as compared to other women.[9] Mental health sequels to spousal violence are significant and have long-term health implications. Battered women were found to have more depressive symptoms than other women.[10] Studies have found the relationship between severity of abuse and physical and mental health. The attempts to quote figures though in India have revealed data on the prevalence, nature, and consequences of domestic violence. Davar's have attributed the rigidly defined roles of Indian women and expectations to be hurdle for growth.[11] POVERTY AND POOR MENTAL HEALTH There seems to be a vicious cycle of adversities in the case of women. Women who were poor and those who were less educated were also found to be at increased risk of poor mental health. Women living in poverty are disproportionately affected by social exploitation. These women are faced with various types of social, physical, and economic hardships, which in association with the experience of domestic violence are likely to increase their vulnerability to mental morbidities.[12] Heise[13] postulated that poverty probably acts as a marker for a variety of social conditions that combine to increase the risk of violence faced by women. Women in better jobs than their husbands were also found to be at risk of poor mental health, a feature that is not unique to India. Counts et al.[14] found that where women have a higher economic status they are seen as having sufficient power to change traditional gender roles, and it is at this point that violence is at its highest. An interesting finding was that higher levels of education of both the woman and her husband acted as a protective buffer against poor mental health, suggesting the important part education could play in reducing violence against women and, thereby, mental disorder. Studies have indeed shown that low academic achievement was one of the risk factors predicting physical abuse of partners by men in New Zealand.[15] Domestic violence is a complex problem and there is no single strategy that will combat all the situations. Since ages, domestic violence against women and children in particular, continue to be one of crucial social mechanism, a result of varied power distribution between men and women. The UN declaration of Elimination of Violence against Women rounds it up as any act of gender-based violence that results in or is likely to result in physical, sexual, or psychological harm or suffering to women.[16] A cross-sectional household survey was conducted in rural, urban, and urban-slum areas across seven sites in India, among women aged 15–49 years, living with a child less than 18 years of age. Trained field workers administered a structured questionnaire to elicit information on spousal physical violence. Out of 9,938 women surveyed, 26% reported experiencing spousal physical violence during the lifetime of their marriage. Higher socioeconomic status and good social support acted as protective buffers against spousal physical violence. The findings provide compelling evidence of the potential risk factors for spousal physical violence, which in turn could help in planning interventions.[17] SOCIAL POSITION, POVERTY, AND HEALTH A strong inverse relationship exists between social position and physical and mental health outcomes. Adverse health outcomes are two to two and a half times higher amongst people in the most disadvantaged social position compared with those in the highest.[18–20] Such health differentials have been found in a number of countries including Finland, Norway, and Sweden.[21] The link between mental health and low income amongst urban women has also been documented in Bombay, Olinda, and Santiago.[22] Socioeconomic circumstances, social support and health-related behaviors all have independent effects on health, but cluster together and are mutually reinforcing. Women have many strengths, and their major problems are not internal, personal deficiencies. Instead, the problems are primarily societal ones, such as sexism and racism. Equality of gender has been the prime concern across all ages of movements pertaining to justice for women. Women empowerment needs multimodal strategies. Protesting against exploitation is only one of the strategies. What is needed is social awareness and indoctrination of value system through community participation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.373
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2012
Admission routes1
Has abstractyes

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