feat(data): Extract Carstens2018

This commit is contained in:
Marty Oehme 2023-12-09 16:16:53 +01:00
parent a51e11b7f6
commit efdb42f36f
Signed by: Marty
GPG key ID: EDBF2ED917B2EF6A
4 changed files with 63 additions and 4 deletions

View file

@ -2239,7 +2239,7 @@ does NOT look at inequalities affected}
usage-count-last-180-days = {0},
usage-count-since-2013 = {7},
web-of-science-categories = {Health Care Sciences \& Services; Health Policy \& Services; Public, Environmental \& Occupational Health},
keywords = {inequality::disability,relevant,TODO::full-text,type::structural},
keywords = {done::extracted,inequality::disability,relevant,type::institutional,type::structural},
note = {looks at inequality; LM markers; policy intervention (in Medicaid programme independent variable)},
file = {/home/marty/Zotero/storage/QVXP8EZY/Carstens_Massatti_2018_Predictors of labor force status in a random sample of consumers with serious.pdf}
}
@ -2743,7 +2743,7 @@ does NOT look at inequalities affected}
usage-count-last-180-days = {0},
usage-count-since-2013 = {2},
web-of-science-categories = {Economics},
keywords = {country::Australia,inequality::income,inequality::migration,region::AP,relevant,TODO::full-text,type::institutional},
keywords = {cite::channels,country::Australia,inequality::income,inequality::migration,region::AP,type::institutional},
file = {/home/marty/Zotero/storage/E8DH8NRR/Clibborn_Wright_2022_The efficiencies and inequities of australia's temporary labour migration regime.pdf}
}

View file

@ -0,0 +1,46 @@
author: Carstens, C., & Massatti, R.
year: 2018
title: Predictors of labor force status in a random sample of consumers with serious mental illness
publisher: Journal of Behavioral Health Services & Research
uri: https://doi.org/10.1007/s11414-018-9597-8
pubtype: article
discipline: health services
country: United States
period: 2014-2015
maxlength: 1
targeting: explicit
group: mentally ill
data: survey data
design: observational
method: multinomial logistic regression model
sample: 917
unit: individual
representativeness: national
causal: 0 # 0 correlation / 1 causal
theory: human capital theory; strength-based therapy
limitations: small sample due to low response rate; over-representation of women, older persons, racial minorities
observation:
- intervention: subsidy (health care)
institutional: 1
structural: 1
agency: 0
inequality: disability
type: 1 # 0 vertical / 1 horizontal
indicator: 1 # 0 absolute / 1 relative
measures: employment probability
findings: LFP significantly increased for employment incentives; significantly reduced for employment barriers and Medicaid ABD programme participation; marginally reduced for
channels: Medicaid ABD generates benefits trap of disability determination
direction: -1 # -1 neg / 0 none / 1 pos
significance: 2 # 0 nsg / 1 msg / 2 sg
notes: employment motivators captured as increased responsibility and problem-solving, stress management, reduced depression and anxiety; employment barriers
annotation: |
An analysis of the potential factors influencing mentally ill individuals in the United States to participate in the labour force, using correlation between different programmes of Medicaid and labour force status.
In trying to find labour force participation predictors it finds employment motivating factors in reduced depression and anxiety, increased responsibility and problem-solving and stress management being positive predictors.
In turn barriers of increased stress, discrimination based on their mental, loss of free time, loss of government benefits and tests for illegal drugs were listed as barriers negatively associated with labour force participation.
For the government benefits, it finds significant variations for the different varieties of Medicaid programmes, with the strongest netagive labour force participation correlated to Medicaid ABD, a programme for which it has to be demonstrated that an individual cannot work due to their disability.
The authors suggest this shows the primary channel of the programme becoming a benefit trap, with disability being determined by not working and benefits disappearing when participants enter the labour force, creating dependency to the programme as a primary barrier.
Two limitations of the study are its small sample size due to a low response rate, and an over-representation of racial minorities, women and older persons in the sample mentioned as introducing possible downward bias for measured labour force participation rates.

View file

@ -2288,7 +2288,7 @@ does NOT look at inequalities affected}
usage-count-last-180-days = {0},
usage-count-since-2013 = {7},
web-of-science-categories = {Health Care Sciences \& Services; Health Policy \& Services; Public, Environmental \& Occupational Health},
keywords = {inequality::disability,relevant,TODO::full-text,type::structural},
keywords = {done::extracted,inequality::disability,relevant,type::institutional,type::structural},
note = {looks at inequality; LM markers; policy intervention (in Medicaid programme independent variable)},
file = {/home/marty/Zotero/storage/QVXP8EZY/Carstens_Massatti_2018_Predictors of labor force status in a random sample of consumers with serious.pdf}
}
@ -2809,7 +2809,7 @@ does NOT look at inequalities affected}
usage-count-last-180-days = {0},
usage-count-since-2013 = {2},
web-of-science-categories = {Economics},
keywords = {country::Australia,inequality::income,inequality::migration,region::AP,relevant,TODO::full-text,type::institutional},
keywords = {cite::channels,country::Australia,inequality::income,inequality::migration,region::AP,type::institutional},
file = {/home/marty/Zotero/storage/E8DH8NRR/Clibborn_Wright_2022_The efficiencies and inequities of australia's temporary labour migration regime.pdf}
}

View file

@ -755,6 +755,19 @@ and that much of the increases in welfare are based on movement of rural workers
The study creates causal inferences but is limited in its modelling approach representing a limited subset of empirical possibility spaces,
as well as having to make the assumption of no population growth for measures to hold.
## Disability
@Carstens2018 conduct an analysis of the potential factors influencing mentally ill individuals in the United States to participate in the labour force, using correlation between different programmes of Medicaid and labour force status.
In trying to find labour force participation predictors it finds employment motivating factors in reduced depression and anxiety, increased responsibility and problem-solving and stress management being positive predictors.
In turn barriers of increased stress, discrimination based on their mental, loss of free time, loss of government benefits and tests for illegal drugs were listed as barriers negatively associated with labour force participation.
For the government benefits, it finds significant variations for the different varieties of Medicaid programmes, with the strongest netagive labour force participation correlated to Medicaid ABD, a programme for which it has to be demonstrated that an individual cannot work due to their disability.
The authors suggest this shows the primary channel of the programme becoming a benefit trap, with disability being determined by not working and benefits disappearing when participants enter the labour force, creating dependency to the programme as a primary barrier.
Two limitations of the study are its small sample size due to a low response rate, and an over-representation of racial minorities, women and older persons in the sample mentioned as introducing possible downward bias for measured labour force participation rates.
They thereby not only reinforce their recommendation for strength-based approaches, emphasizing the benefits of work, but also highlight the targeting importance of subsidy programmes in general on the one hand,
in the worst case reducing equity through bad targeting mechanisms,
and their negative reinforcement effects widening existing inequalities of gender, age and racial discrimination through such targeting on the other.
# Conclusion
The section with conclude with reflections on the implications of findings for policy.