Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.     

Causes of Urban Migration in Bangladesh: Evidence from the Urban Health Survey

Mass migration is increasing urban populations globally. One country where urban migration is significantly increasing is Bangladesh, where systematic research will explore the reasons for urban migration in order to devise policies in this area, including maintaining the balance of urban–rural developments. This study used the Urban Health Survey (UHS) 2013 to ascertain the reasons for urban migration in large divisional cities in Bangladesh. The 2013 survey examined the differences between male and female migration, alongside any significant sociodemographic factors that might contribute to their motivation for moving to the city. The survey revealed that a majority of women (64.8%) migrated for family purposes, for example, joining husbands or in-laws, or parents/children. However, in recent years, female migrants have been involved in income-generating activities mostly due to a recent garment-making boom in Dhaka and its suburbs. A higher proportion of men (85.3%) moved to urban areas for work-related reasons: searching for new jobs, better income, or transfer in services. Among the sample in this study, 77% of the respondents (79.3% female and 73.5% male) migrated from villages. This migration mostly centered on Dhaka, the capital city of Bangladesh, where 68.1% of the total study sample migrated followed by 15.7% who went to Chittagong. The results indicate that the contemporary urban-centered economic policy in Bangladesh might require revision to accommodate the increased migrants from rural areas.

     

Correction to: Assessing recall bias and measurement error in high-frequency social data collection for human-environment research

Population and Environment - The original version of this article unfortunately contained a mistake. The name of “Md. Ehsanul Haque Tamal” is now corrected in the author group of this...     

The nexus between extreme weather events,sexual violence,and early marriage: a study of vulnerable populations in Bangladesh

Population and Environment - This study aims to explore whether a relationship exists between extreme weather events, sexual violence, and early marriage. We selected two districts in Bangladesh...     

Assessing recall bias and measurement error in high-frequency social data collection for human-environment research

Population and Environment - A major impediment to understanding human-environment interactions is that data on social systems are not collected in a way that is easily comparable to natural...     

Construction of circular partially balanced-Repeated measurement designs using cyclic shifts

Repeated measurement designs are widely used in medicine, pharmacology, animal sciences and psychology. These designs balance out the residual effects. The situations where balanced repeated measurements designs require a large number of the subjects, partially-balanced repeated measurements designs should be used. In this paper some infinite series are developed which provide circular partially-balanced repeated measurement designs for p (periods) even. Catalogues of circular partially-balanced repeated measurement designs are also presented for v (treatments) ≤ 100 with p = 5, 7 & 9.     

Analysing local perceptions of post‐conflict and post‐floods livelihood interventions in Swat,Pakistan

The Swat valley in Pakistan’s Khyber Pakhtunkhwa (KP) province was affected by a protracted conflict and super flood between 2007 and 2010. This article explores local perceptions of the Swat response, which presented complex challenges for rehabilitation and livelihood recovery of affected communities. This study examines local perceptions of how non‐governmental organizations (NGOs) and government response addressed livelihood revival needs, considers questions relating to the nature and dynamics of the conflict and floods and reflects on the issues and lessons of post‐disaster relief and development. The qualitative case study was conducted between September 2010 and February 2011. Primary data were collected in 11 villages and localities from beneficiaries and non‐beneficiaries, government representatives, community leaders and programme officials involved in livelihood interventions. This article identifies the shortcomings associated with the targeted response, as well as the types of response offered in the form of beneficiary selection and elite co‐opting of aid. The response was affected by a lack of relief, recovery and development programme co‐ordination, weak institutional support and non‐prioritization of local needs. The article recommends that for effective development policy and practice, local ownership of response and recovery programmes needs to be promoted.     

Enrolling girls without learning: Evidence from public schools in Afghanistan

While more girls are now attending school in Afghanistan than prior to 2010, there is a lack of evidence on how school attendance is helping their cognitive development. We use data from a large sample of all‐girls state‐funded school students to estimate for the first time the “learning profile” for Afghanistan. Students enrolled in grades 4 to 9 were assessed using the Early Grade Reading Assessment (EGRA) and the Early Grade Mathematics Assessment (EGMA) test items. We find that higher grade progression (particularly in grades 6–9) leads to almost no gain in numeracy (addition and subtraction) skills that should have been achieved in early grades. Similar results follow from the analysis of student performance in the EGRA test, particularly in oral reading fluency (correct words read per minute) and oral reading comprehension (number of correct answers out of 12). These findings warn that simply enrolling girls in school without improving the relationship between grade completion and learning is unlikely to transform the lives of women in Afghanistan.     

Why bother to ‘downshift’? The characteristics and satisfaction of downshifters in the Brisbane-South East Queensland region,Australia

Using the data collected as part of a Quality of Life (QoL) survey in the Brisbane-South East Queensland region (SEQ) of Australia, this paper examines differences in satisfaction levels between downshifters and non-downshifters, and identifies socio-economic predictors of the downshifting phenomenon. Almost 30% of survey respondents are classified as downshifters. Multivariate Analysis of Covariance reveals significant differences between downshifters and non-downshifters in a number of life-satisfaction domains, although the degree to which they were satisfied with their life before downshifting is unknown. Analysis of Covariance shows that downshifters reported a significantly lower level of satisfaction than non-downshifters, especially with respect to satisfaction with the amount of money available to them, independence or freedom, and employment. Multivariate logistic regression analysis reveals that post-secondary education and employment were positively associated with downshifting, while age was significantly associated with downshifting. It is argued that if downshifting is associated with lower levels of satisfaction, intervention may be required to initiate programs to engage downshifters more fully in the workforce by facilitating more flexible work arrangements and an improved working environment.