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1.
Behav Cogn Psychother ; 49(1): 50-61, 2021 Jan.
Article in English | MEDLINE | ID: mdl-32993831

ABSTRACT

BACKGROUND: Cognitive behaviour therapy (CBT), self-help and guided self-help interventions have been found to be efficacious and cost effective for victims of trauma, but there are limited data from low- and middle-income countries on culturally adapted interventions for trauma. AIMS: To investigate the feasibility and acceptability of culturally adapted trauma-focused CBT-based guided self-help (CatCBT GSH) for female victims of domestic violence in Pakistan. METHOD: This randomized controlled trial (RCT) recruited 50 participants from shelter homes in Karachi and randomized them to two equal groups. The intervention group received GSH in nine sessions over 12 weeks. The control group was a waitlist control. The primary outcomes were feasibility and acceptability. Secondary outcomes included Impact of Event Scale-Revised (IES-R), Hospital Anxiety and Depression Scale (HADS) and the WHO Disability Assessment Schedule 2 (WHO DAS 2). Assessments were carried out at baseline and at 12 weeks. RESULTS: Out of 60 clients who met DSM-5 criteria for post-traumatic stress disorder (PTSD), 56 (93.3%) agreed to participate in the study. Retention to the intervention group was excellent, with 92% (23/25) attending more than six sessions. Statistically significant differences were noted post-intervention in secondary outcomes in favour of the intervention. CONCLUSIONS: A trial of CatCBT GSH was feasible and the intervention was acceptable to Pakistani women who had experienced domestic violence. Furthermore, it may be helpful in improving symptoms of PTSD, depression, anxiety and overall functioning in this population. The results provide a rationale for a larger, confirmatory RCT of CatCBT GSH.


Subject(s)
Cognitive Behavioral Therapy , Domestic Violence , Anxiety , Feasibility Studies , Female , Humans , Pakistan
2.
Environ Sci Pollut Res Int ; 26(3): 2806-2819, 2019 Jan.
Article in English | MEDLINE | ID: mdl-30488245

ABSTRACT

The relationship between renewable energy consumption (REC), foreign direct investment (FDI) inflows, economic growth, and their resulting impact on CO2 emissions is widely discussed area in energy and environmental literature; however, there is an unseen literature on moderation and mediation effect of per capita income and FDI inflows with the renewable energy consumption on CO2 emissions in developing countries like Pakistan, which is being evaluated in this study by using a consistent time series data for a period of 1975-2016. The results show that economic growth and FDI inflows both increase CO2 emissions, while REC substantially decreases CO2 emissions during the study time period. The results do not support the inverted U-shaped Environmental Kuznets Curve (EKC) hypothesis for per capita income (and FDI inflows) and per capita CO2 emissions in a country. The results supported 'pollution haven hypothesis' where FDI inflows damage the natural flora of the country. By inclusion of moderation and mediation effect of per capita income and FDI inflows with the REC on CO2 emissions averted the positive impact of REC, and converted into negative externality, where environmental sustainability agenda is compromised by lower environmental regulations and unsustainable production techniques that increase country's economic growth. The study concludes that by adding REC in existing energy portfolio may help to reduce CO2 emissions while strict environmental compliance may disregard the negative externality of unsustainable production and it will support to achieve green development programmes in a country.


Subject(s)
Carbon Dioxide/analysis , Economic Development/trends , Environmental Pollution/analysis , Investments/economics , Renewable Energy/economics , Developing Countries , Economic Development/statistics & numerical data , Environmental Pollution/statistics & numerical data , Income , Internationality , Investments/statistics & numerical data , Least-Squares Analysis , Pakistan , Renewable Energy/statistics & numerical data
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