title: "Being trans intersects with my cultural identity": Social determinants of mental health among Asian transgender people

authors: Tan, Kyle K. H.

subjects: Social Sciences

abstract: Purpose: While studies on the relationship between social determinants and mental health among transgender people in Asia are increasing, there is a paucity of research on Asian transgender people living in Western countries. This study aimed to examine how social positions (gender, ethnicity, and migrant status) and social determinants of mental health were inter-related for Asian transgender people in Aotearoa/New Zealand.

Methods: We analyzed both quantitative and qualitative data from Asian participants (n=49) who responded to the 2018 Counting Ourselves: Aotearoa New Zealand Trans and Non-Binary Health Survey.

Results: Overall, 35% reported a very high psychological distress level. There were high levels of unmet needs for gender-affirming care, and participants reported a range of negative experiences at health care settings. About two-fifths had been discriminated because of their transgender (42%) or Asian (39%) identities. Fewer than half of participants felt that their family members were supportive of them being transgender (44%), and most reported they had supportive friends (73%). More than two-thirds of participants (68%) had a strong sense of belongingness to the transgender community and 35% reported this for the Asian community. Qualitative findings revealed specific challenges that participants experienced; these included barriers to accessing health care due to their migrant status and language barriers, influences of Asian cultures on mental health experiences, and rejection by family and people in Asian communities.

Conclusion: Our study provides evidence for health care providers, researchers, and policy makers to employ a culturally appropriate lens to improve knowledge about the intersectional experiences of being Asian and transgender.

text: "Being trans intersects with my cultural identity": Social determinants of mental health among Asian transgender people Purpose: While studies on the relationship between social determinants and mental health among transgender people in Asia are increasing, there is a paucity of research on Asian transgender people living in Western countries. This study aimed to examine how social positions (gender, ethnicity, and migrant status) and social determinants of mental health were inter-related for Asian transgender people in Aotearoa/New Zealand.

Methods: We analyzed both quantitative and qualitative data from Asian participants (n=49) who responded to the 2018 Counting Ourselves: Aotearoa New Zealand Trans and Non-Binary Health Survey.

Results: Overall, 35% reported a very high psychological distress level. There were high levels of unmet needs for gender-affirming care, and participants reported a range of negative experiences at health care settings. About two-fifths had been discriminated because of their transgender (42%) or Asian (39%) identities. Fewer than half of participants felt that their family members were supportive of them being transgender (44%), and most reported they had supportive friends (73%). More than two-thirds of participants (68%) had a strong sense of belongingness to the transgender community and 35% reported this for the Asian community. Qualitative findings revealed specific challenges that participants experienced; these included barriers to accessing health care due to their migrant status and language barriers, influences of Asian cultures on mental health experiences, and rejection by family and people in Asian communities.

Conclusion: Our study provides evidence for health care providers, researchers, and policy makers to employ a culturally appropriate lens to improve knowledge about the intersectional experiences of being Asian and transgender.

year: 2021

title: The origins of a New Zealand suicidal cohort: 1970-2007

authors: Curtis, Cate

subjects: New Zealand

abstract: Many western countries have experienced increased rates of youth suicide over recent years. This has been an issue of particular concern in New Zealand, since it had the highest rate of youth suicide among OECD countries in the mid-1990s. However, while attention is drawn to the now declining youth suicide rate by politicians and policy-makers, what is obscured is a cohort effect.

In this paper we will argue that a cohort effect is clearly visible; suicide rates among 15-24 year olds came to the fore in the mid-1980s, peaking 10 years later, and were displaced by that among 25-35 year olds by the late-1990s.
Further, this century has been characterised by the rise of suicide rates among 35-44 year olds. This effect correlates with a dramatic downturn in the New Zealand economy in a five-year period bracketing 1970. We argue for an increased focus on social and economic factors underlying suicide.

text: The origins of a New Zealand suicidal cohort: 1970-2007 Many western countries have experienced increased rates of youth suicide over recent years. This has been an issue of particular concern in New Zealand, since it had the highest rate of youth suicide among OECD countries in the mid-1990s. However, while attention is drawn to the now declining youth suicide rate by politicians and policy-makers, what is obscured is a cohort effect.

In this paper we will argue that a cohort effect is clearly visible; suicide rates among 15-24 year olds came to the fore in the mid-1980s, peaking 10 years later, and were displaced by that among 25-35 year olds by the late-1990s.
Further, this century has been characterised by the rise of suicide rates among 35-44 year olds. This effect correlates with a dramatic downturn in the New Zealand economy in a five-year period bracketing 1970. We argue for an increased focus on social and economic factors underlying suicide.

year: 2011

title: Mana Motuhake Ringa: The non-invasive neural interface based artificial hand

authors: Owen, Mahonri W.

subjects: Prosthetics

abstract: Ten million people on the earth at any given time suffer from the loss or lack of a limb. Three million of these are upper extremity amputees. No matter the cause or reason for amputation the amputees’ life is never the same again. Independence can be lost and never regained. The loss of a limb can be an overpowering event that effects the mental, social, and physical well-being of a person. Although there has been many attempts to restore hand function through neural prosthetics there is little to no credible solutions to regain it. This thesis presents methods to restore hand function based on the human grasping system and addresses key challenges in the practical application of those methods. The contribution of this work lies in improving artificial hand function by mimicking the human grasping system. The human grasping system consists of the brain, the nervous system and the hand. The methods used investigate: biomechanical design principles for artificial hands, the limitations of machine learning in non-invasive neural interfaces (NI’s) and the development of an autonomous hand control framework for artificial hand control. 

The application of the Support Vector Machine (SVM) to a non-invasive neural interface is principally limited to binary applications in the real world. In order to overcome this limitation an autonomous approach is developed to achieve better response and accuracy from NI control frameworks. In binary applications the SVM performed well with a classification accuracy of around 80% accompanied by a response time of just under 5 seconds. When applied to multiple classifications the SVM decreased in accuracy and response dramatically. The accuracy of the autonomous hand control framework had a classification accuracy of 95% with a response time comparable to that of the SVM. This outcome has the potential to move non-invasive NI research into the real world and to restore hand function in an intuitive and meaningful way. A key learning of this research is that machine learning methods for non-invasive neural interfaces are not the best way to restore hand function for amputees. Hand function is best restored through the combining of machine learning and machine vision into a single NI based control framework. Additionally, this work is based in Mātauranga Māori with a western science approach. By so doing, amputees will be empowered, have increased independence and enjoy a better quality of life.

The scope of this work is limited to the consideration of hand function restoration for upper extremity amputees. In particular trans-radial amputees. Focus is given to non-invasive methods of control, therefore, investigations are limited to the electroencephalography (EEG) signal. Mimicking the human grasping system is a complex and difficult process, therefore, the attempts in this work to restore hand function only consider mechanisms and processes related directly to the motor control of the human hand.

text: Mana Motuhake Ringa: The non-invasive neural interface based artificial hand Ten million people on the earth at any given time suffer from the loss or lack of a limb. Three million of these are upper extremity amputees. No matter the cause or reason for amputation the amputees’ life is never the same again. Independence can be lost and never regained. The loss of a limb can be an overpowering event that effects the mental, social, and physical well-being of a person. Although there has been many attempts to restore hand function through neural prosthetics there is little to no credible solutions to regain it. This thesis presents methods to restore hand function based on the human grasping system and addresses key challenges in the practical application of those methods. The contribution of this work lies in improving artificial hand function by mimicking the human grasping system. The human grasping system consists of the brain, the nervous system and the hand. The methods used investigate: biomechanical design principles for artificial hands, the limitations of machine learning in non-invasive neural interfaces (NI’s) and the development of an autonomous hand control framework for artificial hand control. 

The application of the Support Vector Machine (SVM) to a non-invasive neural interface is principally limited to binary applications in the real world. In order to overcome this limitation an autonomous approach is developed to achieve better response and accuracy from NI control frameworks. In binary applications the SVM performed well with a classification accuracy of around 80% accompanied by a response time of just under 5 seconds. When applied to multiple classifications the SVM decreased in accuracy and response dramatically. The accuracy of the autonomous hand control framework had a classification accuracy of 95% with a response time comparable to that of the SVM. This outcome has the potential to move non-invasive NI research into the real world and to restore hand function in an intuitive and meaningful way. A key learning of this research is that machine learning methods for non-invasive neural interfaces are not the best way to restore hand function for amputees. Hand function is best restored through the combining of machine learning and machine vision into a single NI based control framework. Additionally, this work is based in Mātauranga Māori with a western science approach. By so doing, amputees will be empowered, have increased independence and enjoy a better quality of life.

The scope of this work is limited to the consideration of hand function restoration for upper extremity amputees. In particular trans-radial amputees. Focus is given to non-invasive methods of control, therefore, investigations are limited to the electroencephalography (EEG) signal. Mimicking the human grasping system is a complex and difficult process, therefore, the attempts in this work to restore hand function only consider mechanisms and processes related directly to the motor control of the human hand.

year: 2019