An m-health application has been developed and implemented with community health workers to improve their counseling in a rural area of India. The ultimate aim was to generate demand and improve utilization of key maternal, neonatal, and child health services. The present study aims to assess the impact and cost-effectiveness of this project.A pre–post quasi-experimental design with a control group will be used to undertake difference in differences analysis for assessing the impact of intervention. The Annual Health Survey (2011) will provide pre-intervention data, and a household survey will be carried out to provide post-intervention data.Two community development blocks where the intervention was introduced will be treated as intervention blocks while two controls blocks are selected after matching with intervention blocks on three indicators: average number of antenatal care checkups, percentage of women receiving three or more antenatal checkups, and percentage of institutional deliveries. Two categories of beneficiaries will be interviewed in both areas: women with a child between 29 days and 6 months and women with a child between 12 and 23 months. Propensity score matched samples from intervention and control areas in pre–post periods will be analyzed using the difference in differences method to estimate the impact of intervention in utilization of key services.Bottom-up costing methods will be used to assess the cost of implementing intervention. A decision model will estimate long-term effects of improved health services utilization on mortality, morbidity, and disability. Cost-effectiveness will be assessed in terms of incremental cost per disability-adjusted life year averted and cost per unit increase in composite service coverage in intervention versus control groups.The study will generate significant evidence on impact of the m-health intervention for maternal, neonatal, and child services and on the cost of scaling up m-health technology for accredited social health activists in India. Globally, maternal and child mortality is declining, although the pace of decline is not sufficient to attain Millennium Development Goals (MDGs) 4 and 5 in almost 128 out of 137 developing countries  in India in 2005, a number of interventions have been introduced to bolster the coverage of services such as institutional delivery, immunization, and antenatal and postnatal care .To supplement community health worker training and retention of knowledge, mobile technology has been considered an effective and sustainable method in developing countries . With thUse of technology in the health sector, especially in rural areas that have significant health workforce deficiencies, has been endorsed by the government of India at the highest level . In thisSimilar m-health interventions in other countries have proven beneficial. For example, in Afghanistan m-health resulted in 20% improvement in antenatal attendance and a 22.3% improvement in the number of women receiving skilled deliveries at a health facility . In termA study reviewed all the controlled trials of m-health interventions between 1990 and 2010 to determine the effectiveness of m-health technologies in improving health care service delivery . The resAnother systematic review on the economic evaluation of m-health has shown that there is a lack of concrete evidence to fully assess the economic impact of telemedicine, e-health, and m-health systems . DeficieWe therefore propose to undertake an impact assessment and a cost-effectiveness study to assess the incremental cost per disability-adjusted life year (DALY) averted and incremental cost per unit increase in composite coverage indicator with use of an m-health intervention delivered through ASHA workers for strengthening MNCH services compared with routine MNCH service delivery in one of the districts of UP in northern India.The study will be conducted in the Kaushambi district in UP. Out of the district's eight community development blocks, the m-health intervention has been implemented in two blocks: Mooratganj and Manjhanpur.To register each pregnant womanTo update her ANC record during home visits on the mobile applicationTo track her from pregnancy into the postpartum periodTo track the health of the newbornTo track the status of routine immunization until 2 years of ageTo provide appropriate counseling and support at each of these stepsThe phones contain locally relevant audio and visual prompts to help ASHAs navigate through the application. These recordings and pictures enrich the counseling experience of ASHAs during their home visits. The application uses the data entered about the pregnancy to guide ASHAs in providing timely and appropriate health information; it helps them to prioritize home visits; and it employs algorithms to assist in the early identification, treatment, and rapid referral to appropriate care of any danger signs among pregnant women or neonates (The Catholic Relief Services (CRS) with the help of a local NGO, Vatsalya, introduced the CommCare m-health application to 259 ASHAs in the two intervention blocks in 2012. The ASHAs in the ReMiND project were provided with basic Java-based mobile phones operating on open source CommCare software . Extensineonates . While AData on services due and utilized by pregnant women, recorded by ASHAs through the m-health application, are pooled on a common server. The sector facilitators use the data to monitor all the ASHAs working in their area. These data are also shared with the health education officer at the primary health center level during monthly meetings. Thus, CRS works in coordination with the health system to monitor the performance of ASHAs using data generated by the m-health application .The state of UP is one of the major contributors in total maternal and child deaths in India with low coverage of key MNCH services . KaushamOne of the ways to generate demand is through quality counseling of women during pregnancy. Previous assessments of ASHA performance found them wanting in terms of their skills to counsel women effectively . Use of Increase in coverage of preventive services is likely to result in reduction of morbidities during pregnancy, child-birth, and neonatal period. Reduction in morbidity will in turn contribute to reduced mortality. The intervention is also likely to improve the care seeking during an episode of illness. Improved care seeking is likely to have an impact on mortality as a result of reduced case-fatality rates with treatment as compared with no treatment. Finally, the contact with public health services through the medium of ASHA workers may also change patterns of care seeking, that is, public versus private sector utilization of care. This is likely to affect the cost of health care services through reduction in out-of-pocket (OOP) expenditures and an increase in health system costs for provision of care. This is likely to have a bearing on the overall cost-effectiveness of intervention  22)..22).First, the primary objective of the present study is to assess the impact of the m-health application in the ReMiND project for ASHA workers on utilization of MNCH service coverage. Second, we aim to assess the cost-effectiveness of this m-health intervention in terms of incremental cost per DALY averted for delivering the intervention, as compared with routine services. Cost-effectiveness will also be assessed in terms of incremental cost per unit increase in composite service coverage indicator. Finally, we will assess the cost of scale-up for the m-health application, as it is implemented in the ReMiND project, at district and state level in India.Impact assessment of the m-health intervention is provided in detail below.The study has been approved by the Institute Ethics Committee of the Post Graduate Institute of Medical Education and Research, Chandigarh, India. Written informed consent will be obtained from all study participants. Administrative approval will be obtained for collection of relevant data.We will use a quasi-experimental design comprising pre- and post-intervention observations with a control to assess the impact of the ReMiND project. Data from the Annual Household Survey (AHS) undertaken by the Registrar General of India in district Kaushambi in 2011 will be used for baseline or pre-intervention assessment . The AHSWe will undertake a cost-effectiveness analysis household (CEAHH) survey in 2015 in two intervention blocks and two control blocks from the Kaushambi district to assess the coverage of various MNCH services that represent the post-intervention status. To carry out the CEAHH survey, two structured interview schedules were developed after an extensive review of existing tools used in AHS, the National Family Health Survey, the District Level Household Survey, and the Coverage Evaluation Survey.Together, the AHS and the CEAHH will be used to assess the impact of the ReMiND m-health intervention using a difference in differences (DID) analysis. To reduce selection bias, before DID is performed, propensity score matching (PSM) will be used to match the cases from the intervention blocks with those in the control group based on their socio-demographic characteristics, for the period between 2011 and 2015 . FurtherThe study area for the CEAHH survey will be two intervention and two control blocks out of a total of eight community development blocks in the Kaushambi district. The two control blocks will be selected based on matching for three health service utilization indicators: average number of ANC checkups, percentage of women receiving three or more ANC checkups and percentage of institutional deliveries.The primary sampling unit (PSU) for the CEAHH survey will be a village. For selection of PSUs, a list of all villages from the two intervention and two control blocks will be prepared. From all villages in Kaushambi, 10% of each will be selected from the intervention area and the control area. This means that 69 PSUs each will be selected randomly from the intervention and control areas, using the probability proportional to size method.In each PSU, a household enumeration will be undertaken to identify all mothers with a child in the age group of 29 days to 6 months, or between 12 and 23 months on the date of the survey. This list will serve as the sampling framework to randomly select the required number of mothers in each category for interview. The number of clients to be interviewed per PSU will again be selected by the probability proportional to size method and will be determined based on the relative size of the PSU.The clients (mothers with a child in the 29 days to 6-month or 12- to 23-month age range) within each PSU will be selected using systematic random sampling. If more than one child in the respective age category is present in a given household (i.e. more than one child is between 29 days and 6 months or more than one child is between 12 and 23 months), then one will be randomly selected. If the family has one child in the 29 days- to 6-month range and one in the 12- to 23-month range, then both children would be part of the sampling frame and would have the same probability of being selected as would any other child in the sampling frame.Two categories of individuals will be identified in each PSU: 1) women with one or more children aged 29 days to 6 months and 2) women with one or more children aged 12–23 months. The sample size for each category was estimated with respect to differences in coverage of two key MNCH services  and neonatal and child morbidity rate for severe disease. For mothers with children in the younger age group, neonatal and child morbidity rates and institutional delivery coverage were used to determine sample size. For mothers with children in the older age group, the difference in rates of full immunization coverage was used to assess sample size.We determined the sample size required to detect a 5% change in the coverage of MNCH services and neonatal and child morbidity rates, with a power of 80% and an alpha error of 5%. Baseline coverage of 15.1% and 30.8% for institutional delivery and full immunization coverage in control area, respectively, was assumed . SimilarBasic socio-demographic data such as religion, caste, occupation, education, and wealth quantile will be collected from both categories of clients. Additionally, mothers of the younger group will be interviewed for utilization of ANC, institutional delivery, postnatal care, full immunization, neonatal & child morbidity, treatment sought and any hospitalization for the child. Information will be collected on the number of ANC visits, tetanus toxoid immunization, iron–folic acid supplementation, and type of health facilities used for ANC and institutional delivery. Data on OOP expenditures incurred at public or private health facilities for ANC and institutional delivery will be elicited. The mothers will also be questioned about any illness during the neonatal period, its symptoms, treatment sought, type of health facility, and OOP expenditures incurred. Similarly, mothers will be asked about any episode of hospitalization for the child, place of hospitalization, and OOP expenditures incurred.Mothers of children in the older child group will be asked about immunizations received by the child. Data collection based on the immunization card would be preferable; however, mothers’ recall will be used in cases where an immunization card is unavailable in the home at the time of the interview. The use the mother's recall for eliciting information on immunization received by the child is a standard practice in developing and developed countries and is used in several household surveys, for example, Coverage Evaluation Survey, District Level Health Survey, National Family Health Survey, and Demographic Health Survey . Second,Additionally, mothers in both categories will be interviewed in the intervention and control area about the extent and quality of services offered by the ASHAs during the antenatal and postnatal home visits. Specific questions will be posed to mothers in the intervention area to assess the usage of the mobile application and their satisfaction with this mobile-assisted counseling.DID will be the primary analysis and will be based on the AHS and CEAHH data from intervention and control areas. Propensity scores will be used to match the women of intervention area with control area based on their socio-demographic characteristics. This will help to reduce the selection bias by taking into account the variation caused by known confounders. The AHS dataset for analysis comprises a total of 450 women: 225 from the intervention areas and 225 from the control areas. The CEAHH data have 1,053 women with a child aged 1–6 months each in intervention and control area. Similarly, a total of 1,391 women with a child aged 12–23 months in intervention and control area are part of the CEAHH dataset.(a) PSM: The non-random choice of the two intervention blocks could result in selection bias. In order to minimize this bias, the PSM method will be used to control for demand-side characteristics that could influence utilization of various MNCH services. The PSM approach attempts to render the effects of different observed covariates X on participation as a single propensity score or index defined byservices . Then, et=0 before the program and t=1 after program implementation, letting t, the DID method will estimate the average program impact as follows:T1=1 denotes treatment or the presence of the program at t=1, which is evaluated from CEAHH data, whereas T1=0 denotes absence of the program, which is evaluated using AHS data. Outcomes in the form of coverage of key MNCH services such as ANC, immunization and institutional deliveries will be assessed ((b) DID: This method essentially compares intervention and control groups in terms of outcome changes over time relative to the outcomes observed for a pre-intervention baseline. That is, given a two-period setting where assessed . Along wData quality will be assessed during the survey as adherence to the sampling plan, correctness, completeness and accuracy of data. With these aspects of quality in mind, a team of supervisors will monitor the sampling techniques followed by field investigators while collecting the data. During the quality visits, 10% of the data collected by each investigator will be collected again by the supervisor and further analyzed to check for discrepancies. If a wide range of discrepancies within or across investigators or items is found, a standard set of procedures, for example, validation or repeat sampling procedures, will be followed to resolve the same. Missing data will be imputed with the standard regression imputation technique.First, costing will be undertaken from a societal perspective. Data on OOP expenditures for accessing MNCH services such as ANC, institutional delivery and curative care  during the neonatal and infancy period will be collected during the CEAHH survey. A bottom-up costing method will be used to collect data on health system costs of implementing the m-health application as in the ReMiND project. This will comprise data on start-up costs such as planning meetings, development of software, and training of ASHAs. The initial start-up costs (such as trainings and software development) will be considered as capital costs and will be annualized based on the expected life of the product produced. Second, these will be apportioned to the two blocks of UP, assuming a scenario that the application can be scaled up in all of UP without further adaptation. Cost of implementation of the program will be assessed in terms of resources of implementing partners such as CRS and Vatsalya, which implemented the program in the intervention area. These resources include staff salaries, equipment, building and space, drugs and consumables, and other overheads. Health system costs for delivering services through ASHAs will be assessed by collecting data on performance-based incentives paid to the ASHAs. For the purpose of cost scale-up analysis, only those start-up costs will be considered that are likely to be incurred by the health system as part of scale-up – for example, adaptation of the software in the new state, trainings, and any manuals to be developed.Other health system costs that are incurred for delivery of preventive and curative MNCH services will be drawn from published studies –28. TogeAn existing model to evaluate the impact of IMNCI would be adapted and used to undertake the cost-effectiveness analysis . A decisCosts and benefits will be analyzed from both a health system and a societal perspective. Benefits on health status will be measured in terms of illness episodes averted, child deaths prevented, maternal deaths prevented, life years gained and DALYs averted. Evaluation of health benefits will be undertaken by modeling the improvements in service utilization and reduction in illnesses during the neonatal period and infancy, as well as reduction in maternal and infant mortality and disability. Finally, reduction in DALY as a result of implementation of the m-health application will be estimated. The effects on maternal and infant mortality will be modeled for the following intermediate consequences: improvement in ANC and institutional delivery; reduction in neonatal and infant morbidity, predominantly pneumonia and diarrhea; and improvements in care seeking for sick newborns. The existing evidence based on the LiST model and pertaining to investigation of improvements in MNCH-related preventive services will be reviewed to assess these relationships. This will build on the existing evidence that is used for modeling the effect of improvements in these preventive services, as well as care seeking in the LiST (Lives Saved Tool) model . BenefitA composite coverage measure will be computed by taking the arithmetic mean of output indicators, viz., institutional delivery, full ANC, and full immunization coverage. The data on each of the input indicators is on a ratio scale. However, these are non-comparable as they measure different dimensions of health services . Therefore, geometric means will be used for aggregating. Because all the input indicators are in the form of percentage ranging from 0 to 100, there is no need for scaling. Weights will also be assigned, which will be derived through expert opinions and published literature. The nature of current data available does not support determining of weights with multivariate statistical methods such as principal component analysis or regression analysis. Both costs and benefits will be discounted at 3% to account for time preference of cost and utility . We willThe data would be collected from the ASHAs in intervention and control areas to assess their knowledge, beliefs and attitudes about the acceptability of the application based on self-administered ASHA knowledge assessment tool. A self-administered and semi-structured questionnaire was developed to interview the ASHAs, which was based on the ASHA training modules under National Health Mission and an earlier study undertaken for evaluation of ASHA performance , 33. TheWe will also monitor the implementation of any other intervention or change in the intensity of existing interventions in the study area during the period of evaluation, especially to determine whether the additional or existing interventions are implemented differentially between the intervention and control area.Health care interventions have been traditionally evaluated using randomized controlled trials, which are considered as the best form of evidence. However, allocation of usual health system interventions in routine programmatic settings is not randomly allocated, which poses special challenge to researchers for evaluation . As a reThe present study is being undertaken to assess the impact and cost-effectiveness of an m-health application used by village-level ASHAs for improving MNCH services. To date, per our knowledge there is no cost-effectiveness evaluation of an m-health application delivered through community health workers for maternal and child health care from India or any other Southeast Asian country . More thIn view of these health system and policy debates, the present evaluation holds immense significance to provide evidence from an economic viewpoint on whether such m-health interventions should be scaled up. Hence, it is a comprehensive study that evaluates the intervention thoroughly in terms of its process evaluation, impact, cost, and cost-effectiveness.It has been argued by others that researchers should consider enough period of implementation for their evaluation to begin, such that intervention has sufficient time to demonstrate its impact. Generally, it has been seen that the incremental community-based interventions in the field of maternal and child health bring out a change in about 2–4 years period, especially in areas with the low coverage of health indicators –40. SimiWe note certain limitations of the present study. Design of health program evaluations has been dominated traditionally by experimental approaches used in medicine, in which specific individuals or clusters of people are allocated randomly to receive an intervention whereas others do not. Studies tend to be undertaken in controlled environments in which the influence of external factors is minimized or eliminated. Such randomized controlled trials are considered to provide the highest quality of evidence to evaluate an intervention or program. However, real-world health system interventions are far from controlled experiments . MoreoveIn the context of the present study, the intervention is to be rolled out in two blocks in the district. This offers distinct benefits for evaluating the impact. However, the choice of the two intervention blocks was not random, and this selection bias can limit the causal attribution if inherent differences in the two intervention blocks versus the remaining six control blocks of the district influence the outcome. However, we will attempt to account for this in our analysis, where the demand-side factors at household level will be controlled using PSM, and the supply-side health system factors other than m-health application are controlled using the DID estimator.Second, the intervention involves use of mobile phones to deliver health messages and counseling. Given the nature of the intervention, it is not possible to blind the participants. Also since specific questions pertaining to the use of intervention are included in the structured questionnaire on delivery of intervention, the investigators who assess outcomes also cannot be blinded to the intervention.Third, we aim to assess provision of home-based postnatal care through ASHAs, morbidity and care seeking during the neonatal and infancy periods. We note that these were not the primary objective of ReMiND, as its m-health application was limited to being a job aid for ANC, institutional delivery, and immunization. However, since the m-health application might affect the performance of ASHAs and their contact with the women during pregnancy, it is likely to have spin-off effects during the postnatal period. Whatever differences accrue for neonatal care seeking, postnatal care, and so on, the same differences will be modeled as health gains in the form of DALY averted. Moreover, the baseline survey elicited data on provision and quality of ASHA visits during the postnatal period, neonatal morbidity and care seeking. Hence, it is feasible to assess impact, if any.There are also some limitations in the way DALYs and composite coverage indicators are defined. It is well known that the maternal and child health services have many non-health benefits. For example, healthy children have better school performance, and non-anemic women have better productivity. However, to capture such benefits is outside the scope of the present study. Similarly, the creation of composite indicators is also methodologically debated in terms of the weights allocated to each input indicator. In order to address this uncertainty, we will undertake a sensitivity analysis to account for the variability introduced with and without weighting. However, as mentioned previously, the nature of current data  does not support determination of weights using multivariate statistical methods such as principal component analysis or regression analysis.Overall, the present study will generate estimates on incremental cost per DALY averted with the m-health application intervention in comparison with routine services. The study will also be able to generate evidence on the cost of scale-up for such an intervention, which will address important fiscal feasibility issues. Together, the two will help the government of UP and the government of India to consider replication of such an intervention in the entire state or country. India is a diverse nation with considerable heterogeneity in terms of baseline levels of service utilization, organization of the health care delivery system and its quality. As a result, several factors will need to be considered to generalize the findings of the study in India. These include the characteristics of the study population and of the intervention, the setting of the study, and other contextual issues, all of which will be interpreted in the context of the current evidence available in the literature.Click here for additional data file.


Low income countries like Ethiopia are underrepresented in clinical research. As a major public commitment to clinical research, Ethiopia celebrated the International Clinical Trial Day (ICTD) for the first time on 20 May 2014 under the auspices of Addis Ababa University. The motto for the day was ‘Clinical Trials for Excellence in Patient Care’. The celebration offered an opportunity to inform academic staff, researchers, students and the leadership about clinical trials being conducted and to discuss the future of clinical trials in the country. Although clear challenges to the conduct of trials abound, clinical trials registered from Ethiopia in trial registration databases is increasing. Cross-country collaborations, international funding support, motivation of academic staff to conduct clinical trials and the commitment and engagement of the leadership in research are all improving. The overall impact of clinical trials is also encouraging. For example, some of the trials conducted in Ethiopia have informed treatment guidelines. However, administrative capacity, research infrastructure as well as financial support remain weak. There is a need for enhanced university-industry linkage and translation of research findings into locally relevant evidence. Ethiopia, as well as the whole of Africa, has an unparalleled opportunity to lead the way in clinical trials, given its prospect of development and the need to have locally relevant evidence for its growing population. In this commentary we reflect on the celebration of ICTD, the status and opportunities for conducting clinical trials and the way forward for facilitating clinical trials in Ethiopia and Africa. Ethiopia, with a population of over 90 million , is the The broad national indicators of progress happening in Ethiopia make it one of the most promising countries in Africa to conduct clinical trials. Within this context, Ethiopia celebrated its first International Clinical Trial Day (ICTD) on 20 May 2014, with the motto of ‘Clinical Trials for Excellence in Patient Care’ . For example, the share of studies registered from Africa  is only 0.02%, although the region represents about 15% of the population of the world. Within Africa, most of the clinical trials are conducted in South Africa 47.3%), which makes one of the largest financial investments on health and has a relatively well-developed health system in Africa . Only a .3%, whicEthiopia has relatively advanced ethics procedures and review processes to protect participants in research. Various ethics committees are established at the level of institutions and there is one national committee. The national-level ethics committee, the National Research Ethics Review Committee (NRERC) , handlesA Strength, Weakness, Opportunity and Threat (SWOT) analysis matrix is presented in Figure Regulatory frameworks are either underdeveloped or imported directly without consideration of the local context. Regulatory functions are frequently slow and bureaucratic. However, plenty of opportunities exist for the conduct of clinical trials both in Ethiopia and other African countries. Research is receiving increasing recognition, particularly in some academic institutions; there is better networking and international collaboration, a massive expansion of medical schools and healthcare services, use of technology is improving and the generally improving economy in Ethiopia and many African countries are more conducive for conducting clinical research.It is in Africa’s best interest to commit to clinical trials both to serve its people, its region and the world at large. Specific recommendations are listed below. Within Ethiopia, a recommendation was made to establish a clinical trial committee, which would conduct needs assessments, explore opportunities for collaboration, assess priority areas for clinical trials in line with the country’s priorities and make recommendations for effective establishment of leading clinical trial centers in the country. The main threats to conducting clinical trials are the poor administrative capacity in many institutions, the lack of expertise and brain drain to international institutions and non-governmental organizations (NGOs) within the country. Within country, brain drain occurs not only because of the financial incentives but because of the extremely limiting administrative capacity that hinders the conduct of clinical trials. Institutions and governments should address these needs urgently. Clinical trials should be grounded in solid ethical principles and should be conducted for the benefit of patients.Trials should be for patients’ benefit at all times. Competent regulatory frameworks should be able to scrutinize trials whether the principle of beneficence and non-maleficence are upheld. People in low income countries are particularly vulnerable owing to poverty, low education and restrained political empowerment. Therefore, stringent regulatory frameworks are required.Even when regulatory frameworks have to be stringent, they also have to be efficient, especially in the context of international collaborations.Both research and administrative capacity limitations are significant threats to the conduct of clinical trials. International collaborations should therefore support both administrative and research capacity development.We would like to go even further. If international institutions or industries are interested in working with low income institutions in conducting clinical trials, they should consider it their ethical responsibility to support both human and material capacity development in low income countries before embarking on serious clinical trials.Although the priority of clinical trials in low income countries will be on infectious diseases, it is important to understand that interventions (or the delivery mechanisms) for non-communicable disease require even more local contextualization. Considering this need for contextualization and the increasing burden they cause, it is not too early to focus attention on these diseases.All institutions interested in participating in clinical trials should be encouraged to do so. Establishing institutional clinical trial committees may help to support capacity development, collaborations and setting priorities.These institutions should also be prepared to be subject to regulatory standards set by local and international regulatory bodies. Full transparency and accountability in relation to registering trial protocols, monitoring and reporting are minimum standards.Regulatory frameworks need to be contextualized for the country and treatment being considered.Clinical trials have the potential to benefit patients, institutions and nations if they are conducted with the right tools. Therefore all interested medical institutions should be encouraged to participate in the conduct of clinical trials. The following recommendations are meant to support institutional engagement in clinical trials:Several measures to strengthen frameworks for the protection of patients, particularly the most vulnerable, in the area of clinical trials has been a main agenda of the government. Most institutions are committed to uphold these principles. The implementation of these principles in practice needs to be facilitated. We support full transparency in the conduct of clinical trials, including registration on web-based clinical trial registration databases. However, these regulatory frameworks have to be contextualized and relevant for the country and for the specific study . RegulatFinally, to the best of our knowledge, this is the first celebration of its kind in Africa. It might help for countries to celebrate the ICTD annually, both as an opportunity to celebrate clinical trials, and as an occasion to unite and push for the goal of improving the life of patients through clinical trials.Local evidence is essential and is more likely to influence policy and practice , 23. The


In ageing populations, informal care holds great potential to limit rising health care expenditure. The majority of informal care is delivered by spouses. The loss of informal care due to the death of the spouse could therefore increase expenditure levels for formal care.To investigate the impact of the death of the spouse on health care expenditure by older people through time. Additionally, to examine whether the impact differs between socio-demographic groups, and what health services are affected most.Longitudinal data on health care expenditure (from July 2007 through 2010) from a regional Dutch health care insurer was matched with data on marital status (2004–2011) from the Central Bureau of Statistics. Linear mixed models with log transformed health care expenditure, generalized linear models and two-part models were used to retrieve standardized levels of monthly health care expenditure of 6,487 older widowed subjects in the 42 months before and after the loss of the spouse.Mean monthly health care expenditure in married subjects was €502 in the 42 months before the death of the spouse, and expenditure levels rose by €239 (48%) in the 42 months after the death of the spouse. The increase in expenditure after the death of the spouse was highest for men  and the oldest old . Expenditure levels showed the highest increase for hospital and home care services (together €166).The loss of the spouse is associated with an increase in health care expenditure. The relatively high rise in long-term care expenses suggests that the loss of informal care is an important determinant of this rise. In many developed countries, population ageing can be directly related to a rise in health care expenditure. In the Netherlands, for example, the share of people aged 65 and above is expected to increase from 15% in 2008 to 26% in 2040 It is plausible that informal care from spouse to spouse accounts for the biggest share expenditure prevention. It has been found that women offer the highest share of informal care, either as wives or daughters Therefore, in a large and complete dataset of Dutch health care expenditure, we have investigated the impact of the death of the spouse on health care expenditure through time. We collected figures of individual health care expenditure within a large population over a long period of time from the database of a health care insurer, and linked this information with data on marital status. First, we analysed the effect of having a spouse and other socio-demographic determinants on health care expenditure in our total study population. Second, we focused only on clients who became widowed, and observed if individual levels of health care expenditure change before and after the death of the spouse. We also discerned whether there is a difference in this effect between men and women, younger and older people, and people with a lower and higher socio-economic status. Third, we investigated how expenditure levels for different health services change before and after the death of the spouse. Insight into the economic value of formal care prevention by spouses is important for policy-makers who are concerned with improving the lives of older people and who are, at the same time, obliged to curtail ever rising levels of health care expenditure.After consulting the internal review board (IRB) of the regional health insurer, data on health care expenditure was retrieved from a health insurer. A formal waiver of IRB approval was received from the Central Bureau of Statistics (CBS) for data collection. After consulting the IRB of the CBS a single transfer of data from the health insurer to the Central Bureau of Statistics (CBS) was undertaken over a secure line. A formal waiver was received by the IRB of the CBS. After the data transfer, the CBS first removed any personal data. The leading author could then only access the de-identified data in a secured room of the CBS. The authors had no access to identifying information. Any output destined for publication was first scrutinized by the IRB of the CBS, so no output could be traced back to individuals. No data is publicly available. Data collection and analysis was in full accordance with privacy legislation and protocol.Health care in the Netherlands can be separated into two main sectors: medical care and long-term care. Medical care refers to consultations, medication and treatment from general practitioners, medical specialists, dentists, pharmacists, and therapists (such as physiotherapists and psychotherapists). Some forms of instrumental aid and transportation are also provided through the medical care sector. In the studied time period, health care providers bill health care insurers in the form of diagnosis related groups. Medical care is legally arranged through the Health Insurance Act (HIA).care offices. After an indication is set, the care office appoints a health care provider for a client, or distributes a personal budget. The health care insurer who has the highest share of clients in a region acts as the care office for that region.Long-term care in the Netherlands is legally arranged through the Exceptional Medical Expenses Act (EMEA). Entitled to care through the EMEA are people who cannot satisfy their basic care needs independently due to a physical, psychogeriatric or psychiatric ailment, or a mental, physical or sensorial handicap. Before someone may receive long-term care through the EMEA, the Center for Indication Setting has to evaluate the client’s health status and issue an official indication. When an indication is set for a client, the actual provision of long-term care is arranged by so-called st 2007, intramural care is indicated in terms of Care Weight Packages (CWPs). CWPs are pre-defined bundles of residential care, consisting of housing with different types of long-term care on different levels.There were basically five separate long-term care services funded through the EMEA in the studied time period: (1) personal care , (2) nursing care (e.g. wound dressing), (3) counseling , (4) treatment (forms of rehabilitation or therapy) and (5) residence. Indications for extramural care are defined in type and level (hours per week). Since July 1Leiden Health care Costs in Old Age (LHCOA) study was started in 2011. For this study, data on health care expenditure for 61,495 people aged 65 and older in a period of 42 months were retrieved from a regional Dutch health insurer (Zorg & Zekerheid) and matched with data on socio-economic characteristics from the Central Bureau of Statistics (CBS).With the aim to perform multiple studies on the association between the life situation of older people and their health care costs, the Data were collected in the following steps:After consulting the internal review board (IRB) of the regional health insurer, data on medical care expenditure were retrieved from the health insurer’s management information system. Data were collected for the period July 2007 through 2010 for all persons who lived in the regions where the health care insurer acted as the long-term care office, and who reached the age of 65 before 2011. Addresses were linked with data on socio-economic status by postal code, provided by the Netherlands Institute for Social Research.Collecting data on expenditure for separate medical care services proved to be highly time consuming. These data were only retrieved for a subpopulation, randomized for socio-economic status. Eight separate services were identified: general practice, hospital, pharmacy, allied health care, psychology, instrumental aids, dental care, and other medical care.In accordance with the IRB of the health insurer, data on long-term care utilization were collected from the EMEA Care Registration system (ECR), an information system which offers an oversight of all the coded messages that are sent between organizations active within the confounds of the EMEA. ECR messages designating the start and end of long-term care provision were linked with national average fees per volume unit, provided by the Health Insurance Board. The received volumes of extramural treatment were unknown, and no expenses could be calculated for this service.After consulting the IRB of the CBS a single transfer of data from the health insurer to the CBS was done over a secure line. CBS staff merged the data using citizen service numbers and dismissed any personal data afterwards. The authors could then only access the de-identified data in a secured room of the CBS. The authors had no access to identifying information. Any output destined for publication was first scrutinized by the IRB of the CBS, so no output could be traced back to individuals. No data is publicly available. Data collection and analysis was in full accordance with privacy legislation and protocol. Socio-demographic variables collected at the CBS were: age, gender, marital status, and time of death.After these steps, the total study population comprises 61,495 subjects. Expenditure for separate medical care services are known for 18,995 subjects.A more detailed description of the data collection procedure can be found in H stands for HCE for individual i in month j, G for gender, AG for age group, M for marital status, SG for socio-demographic status group, and Y for calendar year. To estimate the effect of each determinant in the equation, we calculated the exponential function of each β in the equation.In the overall analysis, we used the total study population  to investigate what influence gender, age, marital status, socio-economic status (SES), and calendar year have on monthly health care expenditure (HCE). All determinants are defined as categorical variables. We have defined two groups for age  and SES (score <6.45 and score ≥6.45) based on the medians . As there are multiple, monthly observations for each subject in our dataset, and HCE is skewed to the right, leptokurtic and heteroskedastic, we used a linear mixed model with a log transformation of HCE (LLMM). Visual inspection of the distribution of the residuals in the model now showed a normal distribution. The model can be expressed with the following equation:H stands for HCE for individual i in month j (j =  42 to +42), G stands for gender, A for age, S for socio-demographic status score, Y for calendar year, and MW for each month before or after widowhood.Hereafter, the focus was shifted to the subjects who became widowed in the period 2004–2011 . Data on marital status was available for a longer time period (2004–2011) than data on HCE (July 2007–2010). This way, we could measure the impact of the death of the spouse on HCE with a maximum time span of 42 months before and 42 months after the month in which the subjects became widowed. A LLMM was used to estimate HCE for every month. Standardization was applied for socio-demographic variables and calendar year by holding them constant on the mean. Monthly point estimates of HCE before and after the loss of the spouse were also calculated for different socio-demographic groups: both genders, two age groups, and two socio-economic status groups. The LLMM used in the second analysis can be expressed with the following equation:Monthly points estimates will provide eye evidence on a possible effect of widowhood on HCE. To test whether the level of HCE during widowhood differs significantly from the period before widowhood, we compared the mean monthly levels of both periods in a two-sample t-test. The means of HCE for each period were calculated from the estimates from the LLMM .g is the link function, and T stands for average monthly expenditure for a specific health service for individual i in period p, G stands for gender, A for average age, S for socio-demographic status, and Y stands for average calendar year. The 2PM is expressed as:In analysing the effect of the loss of the spouse on expenditure levels in specific health services, we selected subjects for whom expenditure were known for each separate medical care service and who became widowed from 2004 to 2011 . For some health services, only a relative low number of subjects received care. As the outcome variables were thus not only characterized by problems with skewness, kurtosis and heteroskedasticity, but also with a high share of zero values, a LLMM could not be applied. Therefore, we first pooled monthly expenses of each health service for every subject, and then used either a generalized linear model (GLM) or two-part model (2PM) with a logit model for the first part, and a GLM with gamma distribution and a log link for the second part x′ expresses the set of determinants, and η the GLM (see x′ and η). For each health service, comparison of the average monthly expenditure levels before the loss of the spouse with the average level after the death of the spouse was performed with a two-sample t-test.The descriptive statistics of the total study population, the widowed population and the widowed subpopulation can be found in In the second analysis, we only focus on the subjects who became widowed in the period 2004–2011. As can be seen from The mean levels of HCE in the 42 months before and after the loss of the spouse in the widowed population, and different socio-demographic groups, are shown in In The death of the spouse impacts the level of health care expenditure of an older person. On average, monthly expenditure increases with almost 50% after the death of the spouse. Overall, the rise sets in at the month someone becomes widowed, and is highest for men and the oldest old. The relative increase in long-term care expenditure after the loss of the spouse is five times higher in the long-term care sector than in the medical care sector.Since spouses can provide each other with intensive levels of informal care, one could argue that marriage has preventive effects on formal care use. Although the loss of a spouse is treated as an exogenous shock, different endogenous factors could be at play in the association between widowhood and health care expenditure. One could argue from a marriage selection perspective Bereavement is also related to health risks, and could therefore induce higher health care expenditure Other studies take the effects of marriage selection, a shared environment, and bereavement into account by directly measuring the “substitution” effect of informal care reception on health care utilization Our findings are particularly useful for economists studying the impact of human behaviour or the costs and benefits of prevention programs. Because informal care is not financially compensated, it is usually not taken into account in economic analyses. In literature, it remains unclear what the best method is to express informal care in economic terms This study can also benefit policy-makers and physicians. For example, results show that health care expenditure of older people is not only higher after the death of the spouse, but also in the months before widowhood. Emotional stress and a higher burden of informal care could be an underlying dynamic. It is also possible that some subjects postponed the use of health care services for themselves until intensive care for their dying spouse was no longer required. Intervention programmes including information, support, therapy, and respite care for older people providing intensive care for their spouses could have financial merit besides any potential beneficial effects on well-being An important strength of our paper is that individual characteristics and expenditure levels were collected within a large study population over a relatively long time period (July 2007 through 2010). However, we could only collect data on marital status and some widows and widowers will have started a new relationship outside the bonds of marriage. Also, information on the causes of death of the spouse, or the actual reception of informal care before widowhood was missing. Additionally, the effect of the death of the spouse on health care expenditure is likely mediated by the presence of children, as well as other family members or friends. On the other hand, not all widowed subjects from our study received informal care prior to widowhood, showing that informal care provided in spousal relations is economically more valuable than the extra 239 euros per month that widowed people cost. Hence, we want to emphasize that we have measured the effect of having a spouse on health care expenditure and not the effect of informal care per se.To our knowledge, we are the first to perform an in depth investigation into the effect of the loss of a spouse on health care expenditure through time. Our results are in line with previous papers on the utilization of health care by widowed people. Our research not only points out the value of informal care to society in economic terms, but also provides further basis to develop interventions for the support of widows and widowers. This way, future financial strains on the health care system can be avoided, and, more importantly, the quality of life of widows and widowers can be improved.


The current limited evidence may be suggestive that mandibular advancement appliance (MAAs) result in improvements in AHI scores, but it is not possible to conclude that MAAs are effective to treat paediatric OSA. There are significant weaknesses in the existing evidence due primarily to absence of control groups, small sample sizes, lack of randomization and short-term results. Aim: the objective of the present study was to evaluate MAAs in children with OSA.Children presenting an apnea-hypopnea index (AHI) greater than or equal to one event per hour were considered to be apneic. This group of children with AHI greater than or equal to one was randomly divided through a draw into two subgroups: half of them in an experimental subgroup and half of them in a control subgroup. In the experimental subgroup, molds of each of these children’s maxillary and mandibular arches were taken using standard molds and molding material. The control group did not use any intraoral device and did not undergo any type of treatment for OSAS. The MAAs used in this study had the aim of achieving mandibular advancement, thereby correcting the mandibular position and dental occlusion, and perhaps increasing the airway and treating OSAS. After 12 consecutive months of use of the mandibular advancement devices, polysomnography examinations using the same parameters as in the initial examinations were requested for both the experimental and the control subgroup.There was a decrease in AHI in the experimental group and an increase in the control group, with statistical significance. These data were used to calculate the sample size, which was 28 children in total in the groups.There was a decrease in AHI one year after implementing use of mandibular advancement devices, in comparison with the group that did not use these devices.Key words:Mandibular advancement appliance, obstructive sleep apnea. The great development that has taken place in studies on sleep disorders over recent years, among which description of obstructive sleep apnea syndrome (OSAS) is perhaps the most significant, has demonstrated the complexity of the problem and shown the need for multidisciplinary interrelations in various healthcare fields. OSAS is a chronic evolutive disease with high morbidity and mortality rates that comprises a polymorphous set of symptoms going from snoring to excessive daytime somnolence, with severe general hemodynamic, neurological and behavioral repercussions ,2.Many studies have now been conducted with the aims of defining anatomical abnormalities that predispose towards OSAS and describing different tests and treatments for OSAS in adult populations ,2. HowevOSAS during childhood leads to significant physical and neuropsychomotor impairment. Thus, it needs to be recognized and treated early on, in an attempt to avoid or attenuate its consequences, which are very deleterious to proper child development ,4. AdenoThis was a randomized controlled prospective clinical trial. The sample was obtained from children from the school Campinas who were at the physiological stage of mixed dentition. They had a clinical diagnosis of mandibular retrusion, with symptoms of obstructive sleep apnea (OSAS): Mouth breathing, agitation, coughing, choking, hyper extended neck during sleep, snoring, daytime hyper somnolence, hyperactivity and behavioral alterations . These cChildren presenting an apnea-hypopnea index (AHI) greater than or equal to one event per hour were considered to be apneic . This grIn the experimental subgroup, molds of each of these children’s maxillary and mandibular arches were taken using standard molds and molding material . These were filled with plaster, thus producing working models on which intraoral mandibular advancement devices were constructed. The control group did not use any intraoral device and did not undergo any type of treatment for OSAS.The construction of the mandibular advancement devices used in this study was based on the principles of neuro-occlusal rehabilitation and on the device proposed by Pedro Planas , but modPatients presenting craniofacial malformation, prognathism, obesity or previous orthodontic or orthopedic treatment were excluded from the sample. Likewise, patients who had undergone phonotherapeutic treatment or otorhinolaryngological surgery prior to this study were also excluded from the sample.In installing the device, the adaptation of the acrylic plate to the mucosa and back teeth was checked. The child was asked to insert and remove the device several times, so as to observe whether there was any difficulty in removing it. The following instructions were issued:1- Use: the device was to be used at all times, including while sleeping, and was only to be removed for meals and for cleaning.2- Cleaning: the device was to be cleaned periodically.3- Maintenance: return visits were to be made every month, for a check-up regarding the adaptation of the device and any presence of lesions or ulcerations, and to make adjustments due to wear, polish the device when necessary and verify the mandibular advancement.After 12 consecutive months of use of the mandibular advancement devices, polysomnography examinations using the same parameters as in the initial examinations were requested for both the experimental and the control subgroup. The researcher who read the polysomnograms was kept unaware of the group to which each child belonged and from which child each examination came, so as to avoid bias.This study was previously approved by the research ethics committee of the institution where it was conducted: Discipline of Otorhinolaryngology- Medicine School - Unicamp (Campinas State University) - São Paulo - Brazil. Parents and caretakers signed consent form.Between March 2013 and February 2014, 97 children who fulfilled the inclusion criteria underwent polysomnography examinations at the outpatient clinic of the university hospital of Unicamp (Campinas State University) - São Paulo - Brazil. Out of the 97 polysomnography examinations, the results from seven of them could not be used because of failures in recording the examination, and these examinations were excluded from the sample. Among the remaining 90 examinations, 16 presented AHI greater than or equal to one event per hour and were included in this study. This sample was randomly divided by means of a draw, such that eight children used mandibular advancement devices for 12 months and the remaining eight children did not use mandibular advancement devices or any other treatment for OSAS.After a one-year period, new polysomnography examinations were undertaken in both groups, using the same parameters as in the initial examinations. The examination was performed on eight children in the experimental group and on six children in the control group, with a sample loss of two children in the control group.The mean age of the children at the time of the initial examination was 8.13 years in the experimental group and 8.39 years in the control group, without any significant difference. Regarding the sex distribution, there were nine girls and five boys .There was a decrease in AHI in the experimental group and an increase in the control group, with statistical significance Fig. . These dThe results from this study demonstrate that there was a decrease in AHI after the mandibular advancement devices had been used and an increase in this index in the control group. The mean AHI of the sample was initially 1.8. This level can be considered to be low. We believe that this factor can be explained because we excluded children who had undergone otorhinolaryngological surgery or who were obese, from our sample  to its adequate treatment. Nonetheless, we believe and our results indicate that when mandibular advancement devices are properly indicated, they may be more than coadjuvants in treating childhood OSAS.There was a decrease in AHI one year after implementing use of mandibular advancement devices, in comparison with the group that did not use these devices.


The effect of sanctions on cooperation depends on social and cultural norms. While free riding is kept at bay by altruistic punishment in certain cultures, antisocial punishment carried out by free riders pushes back cooperation in others. In this paper we analyze sanctions in both a standard public goods game with a linear production function and an otherwise identical social dilemma in which the minimum contribution determines the group outcome. Experiments were run in a culture with traditionally high antisocial punishment (Southern Europe). We replicate the detrimental effect of antisocial sanctions on cooperation in the linear case. However, we find that punishment is still widely effective when actions are complementary: the provision of the public good significantly and substantially increases with sanctions, participants punish significantly less and sanctions radically transform conditional cooperation patterns to generate significant welfare gains. Social dilemmas have been extensively analyzed in the lab when the team's output is a linear function of the joint contribution to the team . The provision of the public good typically declines over time in the vast majority of studies. However, certain mechanisms, such us communication, the inclusion of a threshold and sanctions, make the provision of the public good to be stable or even increasing over time  depicts the extreme case in which the minimum effort level determines the team's output, and has been widely used to explore coordination problems in organizations  individual allocation to the public account in the VCM (WLM). Our main objective is to analyze the effectiveness of punishment in this non-linear environment. How does this change in the production function may affect sanctioning patterns? Our rationale follows two simple but powerful intuitions. The first one relates to the lack of a clear-cut theoretical prediction for the behavioral logic of social antisocial sanctions in the WLM. The second, with the existence of culture effects described above. We describe these two intuitions one by one.Even when individuals make very similar  allocation decisions in the two environments, the logic of sanctions is fundamentally altered. While social punishment (sanctioning low contributors) may pursue similar objectives in both games , the behavioral rationale for low contributions is quite different. While in the VCM low contributors free ride on the contributions of others , in the WLM low contributors do not benefit from the contribution of others, as only the minimum contribution, their low contribution, determines the group outcome . As every single contribution profile is an equilibrium of the stage game in the WLM, low contributors' actions may be the consequence of pessimistic beliefs in a sophisticated equilibrium selection problem, rather than the outcome of selfish intentions . If the actions of low contributors are judged on the basis of their consequences on the group outcome, social punishment could be as prevalent (and cooperation enhancing) as in the VCM. As long as their decisions are considered to be, at least partially, the consequence of mistakes, wrong beliefs, or aversion to the strategic uncertainty of the game, we could expect social punishment to be less intense than in the VCM, at the cost of less public good provision.Note that the analysis of antisocial punishment leaves a similarly open question. Antisocial punishment may follow very different logics depending on the information individuals receive about punishers in the previous round. From blind retaliation of the rest of the group, to targeted retaliation of those who punished, or the perverse punishment of those who contributed or punished less than the average, or punished contributors, the behavioral analysis of antisocial punishment has identified very different rationales for antisocial behavior  linked to the existence of survey based social norms outside the laboratory (related to civic cooperation and the rule of law), in the WLM the effect and interpretation of social norms becomes more problematic. As Herrmann et al.  make it Antisocial punishment, defined as sanctions targeting co-operatorsIf the intensity of social punishment they receive is perceived as particularly unfair because low contributors do not benefit from the contribution of others, blind retaliation could ignite an escalation of highly detrimental sanctions. As high co-operators pay a relatively higher price in the WLM , this escalation of antisocial punishment could feedback “social” punishment motivated by retaliation. The net effect of both behavioral forces on antisocial punishment is impossible to predict without a controlled behavioral test like the one we run in this paper.To address these issues we run a series of laboratory experiments in one particular culture (Southern Europe), where antisocial punishment has traditionally prevented sanctions to induce full cooperation in linear public goods. The rationale for this decision is not difficult to explain. If the virtuous circle based on the acceptance of  punishment of low contributors and the absence of retaliation based escalation holds, sanctions could yield a positive result even in Southern Europe. If the vicious circle of antisocial punishment driven by the lack of guilt in low cooperators (because they never profited from the actions of others) triggers a generalization of social and antisocial punishment, sanctions in the WLM could generate even less provision of the public good, particularly in a location with weak norms of civic cooperation.Our results are clear. We start by replicating the finding that sanctions are of very limited use in some cultures in linear environments like the VCM. We then document that the production technology has significant and vast consequences in the effectiveness of sanctions. While antisocial punishment is still largely present in the VCM, social punishment dominates in the WLM. Individuals punish significantly less in the WLM than in the VCM, and punishment generates large and significant welfare gains. Antisocial punishment is rare in the WLM, and low contributors do not retaliate. Interestingly, cooperation adjustments are massively asymmetric in the WLM, as cooperators do not adjust down their contributions when contributing more than others, at a huge personal cost, while upward adjustments are large and significantly stronger than in the VCM.The rest of the paper goes as follows. Next section reviews the literature. After this, the subsequent section presents the experimental design and procedures. The next section introduces the quantitative analysis of contributions, punishment and efficiency for the two games simultaneously. Finally, the last section concludes.The effects of both social and antisocial sanctions in cooperation have largely been studied  the collective account profits are determined by the linear aggregation of contributions (the average contribution to the team account), while in the second (the WLM) is a multiple of the minimum contribution.The main strategic differences between our games are two. First, while a unique inefficient equilibrium exists in the VCM, every symmetric contribution profile is equilibrium of the stage game in the WLM. The intuition is that from every symmetric profile, unilateral deviations never pay. By contributing more individuals do not expand the public good, and still pay for the larger contribution. By contributing less, players reduce the whole team's outcome at a net personal cost. Second, contributing to the public good more than others is costlier in the WLM, as no additional public good is created. But, low contributors receive no benefit from high contributions, as the team's output is only determined by the minimum contribution. In other words, low contributors cannot free ride on high contributions. Croson et al.  and FataIntroducing a non-trivial equilibrium selection problem, the WLM is a much richer strategic environment. Interestingly, individuals still get the same earnings in both environments if they all contribute the same proportion of their endowment. Each symmetric contribution profile yields the same earnings in both games. The difference is that symmetric contribution profiles are equilibria of the stage game only in the WLM. Being the strategy space of both games quasi-continuous, the equilibrium selection problem is far from trivial in the WLM. Full contribution Pareto dominates all other actions, while no contribution satisfies the maximin criterion and risk dominates the other equilibria of the game, minimizing losses associated to strategic uncertaintyFrom the group's fitness perspective, contributing to the public good is now riskier because contributions above the minimum do not increase the collective account benefits. Strong contributors may totally waste their contributions if another player in their group does not contribute to the public good. Punishment coming from strong cooperators may still be considered as social punishment as long as it promotes more cooperation and contributes to the collective or social welfare (but not because it sanctions free riding). Punishment implemented by low contributors when punished may still be defined as antisocial, as it might be highly detrimental for group cooperation.The interaction between different types of punishment and the effect of sanctions on group fitness through incentives is far from trivial when no information about the identity of the punisher is provided, as in this study. Incentives are the same if an intermediate cooperator is punished by a complete free rider or by a full cooperator. However, in this paper we explicitly follow an agnostic view and consider that even if participants never know who is punishing them, different types of punishment may (or may not) have first order effect on group fitness through different levels of effectiveness. Following Herrmann et al. , our papIn this paper we explore the preeminence of social and antisocial punishment in both public goods games in a particular location: Spain. Gächter and Herrmann  and GächWe run our experimental sessions in Valencia, Spain. We are particularly interested in replicating, first, the prevalence of antisocial punishment in linear public goods games (the VCM) and willing to learn whether punishment follows a similarly destructive dynamic when the production technology is non-linear.voluntary contribution mechanism (VCM) and the weakest link mechanism (WLM)Our experiment consists of two games and two treatments. As described above, the two games are the partner protocol). All participants were aware that each block would last exactly 20 periods. However, they were not aware that a second treatment was to followIn our study, the composition of each group remained unchanged throughout the experiment  from the project (0.5 in our design). For convenience, the payoff function was presented to subjects as a function of the relevant statistic (the average).Our first treatment is the standard c et al. . VCM gamci = 0, πi = 50) is a dominant strategy in the stage gamei = 50, πi = 100c). Note that with groups of four players, these parameters generate round numbers and make it relatively easier for participants to understand the consequences of their actions.As usual in these games, allocation decisions have monetary consequences. Participants' monetary compensation depends on the benefits individuals get from their private account (the ECUs they keep for themselves), as indicated by the first term of the equation [1], and from an equal share of the team account's profit (second term of the equation). Equation [1] also implies that full free riding , and the equilibrium in which none contributes to the public good satisfies the safe maximin criterion (ic = 0 and πi = 50).Note that the laboratory protocol used in our WLM is essentially identical to the one described above for the VCM. Individuals are randomly assigned to groups of size four, and each individual received the endowment to allocate between the two accounts, also neutrally framed as an allocation problem. Participants earn the sum of their allocations to the private account and twice the minimum allocation to the public account. Given that participants are able to choose any contribution up to one decimal, the stage game has 501 Nash equilibria in pure strategies. Each symmetric contribution profile is equilibrium of the game. In the Pareto efficient equilibrium everybody allocates her endowment to the public account , and they only participated in one experiment (between-subjects).In the second block of 20 rounds, we introduced a second stage of punishment in both the VCM and the WLM. As in Fehr and Gächter , we use sending punishment points. Relative to Herrmann et al. . The introduction of punishment generates significant cooperation gains in both games, as provision with punishment is substantially larger than in the first block: up to 59.77% and 83.35% of the maximum in the VCM and the WLM (significant at the 1% level running a Wilcoxon sign-rank test).p-value < 0.000). Provision in the last round of the block is significantly higher than in the first round in the WLM  but not in the VCM .Figure easier social dilemma than the VCM. If this interpretation were true, a little help from informal punishment would suffice in one game (the WLM) to increase efficiency, but not in the other. We discard this interpretation because if true, we would expect our participants to do significantly better in the WLM than in the VCM when punishment is not available. In line with Croson et al.  suggests, provision stays stable in the second 10 rounds of the WLM without punishment, and no significant differences are found between both games without sanctions. Moreover, only when punishment is available efficiency significantly increases in the WLM, while it does not in the VCM. As the vast and more general experimental literature on coordination games seems to suggest, we also believe there is not much previous support for the idea that coordination games with multiple equilibria are simpler than linear social dilemmas. If any, and starting from Van Huyck et al. , coordinWe specifically try to address this context dependent issue by showing how in one very particular context , sanctions are significantly more effective in the WLM than in the VCM, even when the number of equilibria is much higher than in the standard minimum game. More than that, we articulate a rationale based on the negligible impact of antisocial punishment in one game (the WLM) and not in the other (the VCM)We analyze now the effectiveness of sanctions paying distinctive attention to the behavioral patterns of social and antisocial punishment in the two games. Following Herrmann et al. , we defiWe measure both the frequency and the intensity of social and antisocial punishment in the VCM and the WLM. We define frequency as the proportion of positive punishment events , and we define intensity as the average number of punishment point sent  and is significantly less intense  . No significant differences are obtained when running the same comparison for social punishment.Interestingly, the WLM looks quite different in our study. While no significant differences in the frequency and intensity of social punishment are observed when comparing the VCM and the WLM (47.6% vs. 34.2% and 1.47 vs. 1.12), antisocial punishment clearly diverges in the two games (32.9% vs. 7.6% and 0.74 vs. 0.27). In order to give these comparisons a statistical support, we compute the average frequency and intensity of social and antisocial punishment per group . We find that antisocial punishment is less frequent in the WLM than in the VCM  as dependent variable , Period, and two variables indicating the lagged difference between subject i's contribution and the average contribution of the other subjects in the same group, Lag above, and Lag below, when the difference is positive (negative), zero otherwise.We now know that punishment decisions significantly differ across games. We need to understand what is the differential effect of social and antisocial punishment in the WLM. In order to understand the behavioral implications of sanctions on public good provision, we run a Tobit regression with the adjustment of individual contributions over time  to capture differences across gamesThese two variables allow us to understand how sanctions shape contribution adjustments when participants are contributing more (less) than the rest of the group; that is, in the position of becoming social  punishers. Additionally, we introduce interaction terms , the adjustment is more intense in the WLM.Differences between both games are well-defined. Participants modify their contributions similarly when contributing less than the rest of the group: they adjust up their contributions, and their reaction is more intense the larger the distance between their contribution in (t-1) and the contribution of the rest of the group. Interestingly, as the significant coefficient of the interaction term suggests  strongly suggest, the different use of antisocial punishment is consistent with an interesting shift of conditional cooperation patters. Figure Differences across games are more intense when participants contribute more than the others. Consistently with standard conditional cooperation patterns, participants exhibit the usual negative adjustment when contributing more than the rest of the team in the VCM. From above, participants in the VCM significantly adjust down their contribution, and the intensity of the adjustment increases with the distance between their lagged contribution and the lagged contribution of the rest of the group. In the WLM, this adjustment pattern simply disappears: participants contributing more than the others do not adjust down their contributions. As the flat figure and the positive interaction term , but differences are extremely large and significant with punishment . Interestingly, earnings significantly increase with punishment in the WLM, p-value < 0.0186 .Not surprisingly, Figure Costly punishment has substantial effects in human cooperation. In this paper we present the results of a sequence of experiments run in Southern Europe using two different public goods games. When the production technology is linear, as in the VCM, punishment has only a small positive effect on contributions, hindered by a substantial amount of antisocial punishment. When the production technology is non-linear, as in the WLM, public good provision is significantly increased by punishment, and contributions go up to 95% of the endowment at the end of the experiment. In this sense, punishment in our experiment has a stronger positive effect in the WLM, as both the trend and the absolute levels of public good provision are significantly above the ones observed in the VCM.Our data provides a rationale for this difference, as participants in our study use punishment in very different ways, and when used, it generates very different behavioral reactions. While social punishment is indistinguishable in the two games, antisocial punishment is rare, and remarkably less intense in the WLM. The moderate use of antisocial punishment generates a positive effect on contribution adjustments, and the conditional cooperation of top contributors is reinforced by the lack of antisocial punishment: contributors do not adjust down their contribution to the contribution of others, boosting provision, and earnings.Our experiments were run in a location where the effectiveness of punishment tends to be moderate. We replicate this findings when the production technology of the public good is linear, but completely fail to replicate this result when the technology follows a weak-ling dynamic and contributions to the public good are complementary. Given that our study was run only in one location, we cannot infer much about the effectiveness of sanctions in other locations when using the same weak link technology. However, under the realistic assumption that the production technology of public goods does not have to be unique, our study significantly contributes to the debate on the co-evolution of cooperation norms and punishment.The very moderate use of antisocial punishment in the WLM shows that the connection between cooperation norms and sanctions may critically depend on the team production technology. Our results suggest that the portability of the vicious circle linking antisocial punishment with weak cooperation norms and poor group performance could be limited to particular types of public goods, and non-necessarily replicable in other forms of group interactions.Enrique Fatas contributed to the original study design, run the experimental sessions, interpreted the data, wrote the final versions of the manuscript. Guillermo Mateu assisted running the sessions, assisted in the interpretation of the data, and wrote the first draft under the supervision of Enrique Fatas.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.