One out of four people we surveyed said their access to healthcare has been better since the onset of the COVID pandemic. More than one quarter of survey respondents did not use any digital technologies to manage their health in the past year. When it comes to the care experience, emotional support is just as important as medical support. Digital adoption in healthcare: Reaction or revolution? Harnessing technology and human ingenuity. Health and Life Sciences Experience Survey shows the healthcare experience is changing The healthcare system showed resilience over this past year and remained accessible to many.
Rising digital adoption in healthcare? Only in a few areas It perhaps comes as no surprise that more people used digital technologies to manage their health this year. Negative experiences can have lasting consequences Better experiences can improve engagement with the healthcare system. Pharmaceutical companies can boost trust As in years past, people trust their healthcare providers far more than health insurance companies, technology companies, pharmaceutical companies or the government.
Moving from reaction to revolution The healthcare system used technology to accomplish great feats for patients during the COVID pandemic, yet will these gains last?
Members of the healthcare ecosystem must present information about benefits more clearly to people to boost adoption and to help them understand how technology can support a more human healthcare experience. Ecosystem players must come together to make healthcare experiences simpler, more coordinated, more empathetic and, ultimately, more effective for people.
Consumer Experience Elevating the patient experience to fuel growth. Consumer Experience How can we bring a human touch to virtual health? Life Sciences Driving digital in biopharma: Podcast. Related capabilities. Health experience. Patient services. Precision medicine. There are testable success criteria for each guideline. A guide to understanding and implementing Web Content Accessibility Guidelines 2.
Work is being done to make the system fully compliant with this level. Press esc, or click the close the button to close this dialog box. The Program will likewise provide interventions at the level of industry or sector, to wit: Technology forecasting and gap analysis; Provision of support facilities such as Specialized laboratory, Innovation Centers, TBI; Capacity building; and Policy development and support.
Large household size reduces the probability that a farmer will participate in the market. This could be due to the fact that large household size has the tendency to reduce the marketable surplus, as more of the rice output would be consumed within the household since rice is the most important staple food crop in the Nigerian diets. This is in line with the findings of Mekhura et al. In the same vein, distance to the seed source is an indication of travel time and transportation cost and as these increase, farmers may not find it worthwhile to sell all their paddy rice, but rather prefer to keep some as seed for next season planting.
This attitude will therefore probably decrease market participation. This finding confirms the findings of Omiti et al. The second stage OLS outcome model involved examination of the effect of market participation on welfare.
The IMR for all the estimated models for the pooled data, upland and lowland farmers was positive and significant, which implies that the error terms in the selection and the outcome equations are positively correlated, hence unobserved factors that make participation more likely tend to be associated with higher household welfare.
This indicates that sample selection bias is a problem and it therefore justifies the use of the Heckman two-step model. The coefficient of gender GNR of household head is statistically significant in the pooled data, among the sub-population of the upland and lowland rice farming households. This implies that the male headed households have better welfare than the female headed households. The positive and statistically significant coefficients of yield YIELD and vocational training VOCT in the pooled data suggest that welfare of the farming households is positively influenced by the yield and vocational training.
The years of formal education YEDUC and years of residence in the village, were positive and statistically significant in generating welfare improvement in the pooled data and among the lowland rice farming households. Household size negatively affects welfare in the pooled data and among the sub-populations of the upland and lowland rice farmers. In the pooled data, the coefficient of age has a negative and statistically significant effect on welfare.
This implies that as age of the household increases, welfare also increases. The study assessed factors that determined the intensity of IRVs adoption and the determinants of market participation and their effect on welfare of rural households. It can be stated that higher adoption of IRVs would lead to an increase in rice yield and rural farmers could, consequently, have marketable surplus.
The farmers are still in the productive age at 45 years. The majority of the rice farmers also participate and obtain addition income from off-farm activities. The farm size is small and fragmented. Access to credit is major constraint in rice production and farmers need to travel an average of 4. The IRVs have higher yield compared to the traditional rice varieties. Adopters of IRVs are better off in terms of welfare than the non-adopters. In addition, farmers that participate in the market are wealthier than those who did not participate in the market.
The results of the multivariate analyses adopted to examine the effect of market participation on welfare using the Heckman two-step model also show significant variation in the effects of the included variables by rice producing systems.
Welfare of the farming households is influenced by yield, income and education of the household head. It is necessary to increase the intensity of IRVs adoption to generate an increase in yield.
Excess output above the consumption level of the households will generate marketable surplus, which encourages farmers to participate in the output market. Therefore, increase in those variables that lead to increasing IRVs adoption and market participation should be the focus of any welfare enhancing programs or policy. Access to seed and information about the improved rice varieties are also essential in order to increase the intensity of its adoption.
Programmes that would improve contact with extension agents, access to credit, educational background and enlarging the area devoted to the cultivation of improved rice varieties should be promoted in order to increase market participation and generate improvement in the welfare of rural households. See the description and definition of the variables in Table 1. See the description and definition of the variables used in the model in Table 1. Abay, A. An Msc. Abayneh Y, Tefera T Factors influencing market participation decision and extent of participation of haricot bean farmers in Meskan District, Ethiopia.
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Agrofor Syst 32 1 :1— Agrekon 39 4 — Food Policy 33 4 — Food Policy — Agric Econ 43 1 :1— Astewel T Analysis of rice profitability and market chain: the case of forega woreda, South Gondar zone, Amhara national regional State, Ethiopia. Agric Econ 44 — J Dev Agric Econ 6 9 — World Dev 38 7 — Afr J Agric Resour Econ 3 1 — Agric Econ 38 1 :1—7.
World Bank, Washington, DC. Diagne A, Demont M Taking a new look at empiricalmodels of adoption: average treatment effect estimation of adoption rates and their determinants.
Agric Econ 37 2—3 — A shorter version of the paper is being presented as contributed paper at the 27th Conference of the International Association of Agricultural Economists. August 16—22, Beijing, China. Quarterly Journal of International Agriculture 50 3 — Development Policy Review 22 6 — Ellis F Rural livelihoods and diversity in developing countries.
Oxford University Press, Oxford. Tropicultura — Oxford Econ Papers 42 2 — Greene WH Econometric Analysis. Pearson, New York, p CAB International, Wallingford. Heckman JJ The common structure of statistical models of truncation, sample selection and limited dependent variables and a sample estimator for such models. Ann Econ Soc Meas — Heckman JJ Sample selection bias as a specification error. Econometrica — In: female labour supply: theory and estimations, ed.
Princeton University Press, Princeton, pp — Appl Econ — Itana, A. Alemaya University, Alemaya. Jagwe JN Impact of transaction costs on the participation of smallholder farmers and intermediaries in the banana markets of Burundi, Democratic Republic of Congo and Rwanda.
International Livestock Research Institute, Nairobi. J Pain — World Dev 39 10 — Am J Agric Econ 95 2 — Makhura, M. Transaction costs and smallholder participation in the maize market in the Northern Province of South Africa. Afr J Agr Res 7 14 — KwaZulu Natal. Dev Southern Afr 18 3 — Mendola M Agricultural technology adoption and poverty reduction: a propensity-score matching analysis for rural Bangladesh. Food Policy 32 — Available to companies to cover labour expenditures incurred to eligible computer animation and special effects activities.
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Available to companies that are commercializing intellectual property developed at Canadian universities and colleges and operate in the following sectors; advanced health, bioeconomy including clean energy technologies , telecommunications, computer, or digital technologies production. Grant funding available to start-ups and small and medium enterprises SMEs with solutions that can create value and mitigate environmental impacts in the production of natural gas in Canada.
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