BackgroundHealthcare workers (HCWs) from COVID-19 hotspots worldwide have reported poor mental health outcomes since the pandemic's beginning. The virulence of the initial COVID-19 surge in Spain and the urgency for rapid evidence constrained early studies in their capacity to inform mental health programs accurately. Here, we used a qualitative research design to describe relevant mental health problems among frontline HCWs and explore their association with determinants and consequences and their implications for the design and implementation of mental health programs.Materials and methodsFollowing the Programme Design, Implementation, Monitoring, and Evaluation (DIME) protocol, we used a two-step qualitative research design to interview frontline HCWs, mental health experts, administrators, and service planners in Spain. We used Free List (FL) interviews to identify problems experienced by frontline HCWs and Key informant (KI) interviews to describe them and explore their determinants and consequences, as well as the strategies considered useful to overcome these problems. We used a thematic analysis approach to analyze the interview outputs and framed our results into a five-level social-ecological model (intrapersonal, interpersonal, organizational, community, and public health).ResultsWe recruited 75 FL and 22 KI interviewees, roughly balanced in age and gender. We detected 56 themes during the FL interviews and explored the following themes in the KI interviews: fear of infection, psychological distress, stress, moral distress, and interpersonal conflicts among coworkers. We found that interviewees reported perceived causes and consequences across problems at all levels (intrapersonal to public health). Although several mental health strategies were implemented (especially at an intrapersonal and interpersonal level), most mental health needs remained unmet, especially at the organizational, community, and public policy levels.ConclusionsIn keeping with available quantitative evidence, our findings show that mental health problems are still relevant for frontline HCWs 1 year after the COVID-19 pandemic and that many reported causes of these problems are modifiable. Based on this, we offer specific recommendations to design and implement mental health strategies and recommend using transdiagnostic, low-intensity, scalable psychological interventions contextually adapted and tailored for HCWs.

General information

The UMHT is a specialised program developed to train frontline professionals on high-quality and evidence-based responses to the mental health needs of the population they serve. Police officers, emergency responders, social services workers, educators, pharmacists, priests, and other professionals daily interact with a substantial number of people. Whereas their professional roles imply working with people in crisis who experience strong emotions and require support, a high level of mental health awareness and skills to manage mental health issues are needed. Therefore, UMHT was developed as an educational instrument for Ukrainian frontline professionals to raise their mental health awareness, reduce stigma toward people with mental disorders and develop particular skills for giving support.

The training is called Universal because its 5-step model offers a standard frame for interaction with people with mental health issues. Also, it is Universal because it is suitable for different types of frontline workers – the general interaction structure is not changing, only the set of relevant mental health conditions.

The Mental Health Training for Frontline Professionals (UMHT) was developed in 2021 and piloted in 2021-2023 within the context of the Mental Health for Ukraine Project (MH4U), implemented in Ukraine by GFA Consulting Group GmbH (donor - Swiss Confederation). The University of Luxembourg, with the support of the European Commission through the MSCA4Ukraine fellowship scheme by the Alexander von Humboldt Foundation (AvH) for premier investigator Viktoriia Gorbunova, is leading a full-scale efficacy study of the UMHT in 2023-2025.

Data and file overview

Three efficacy measurements were used in the outcome assessment: readiness to interact with people with mental health issues at work, mental health awareness, and mental health proficiency.

Readiness to interact with people with mental health issues at work

To measure the changes in readiness to interact with people with mental health issues at work (according to the 5-step model), all participants self-assessed their general readiness as well as readiness to do particular actions according to the 5-step model on a five-point scale (from 5 - "absolutely ready" to 1 - "absolutely not ready").

In the instruction, participants were asked: "Reading the next statements, please assess your readiness for a different kind of interaction with people with mental health conditions. The scale is from 1 to 5, where 1 is the absolute absence of readiness, and 5 – is the absolute readiness".

The next set of statements was proposed to participants:

Readiness to interact with people with mental health issues at work (general readiness).

Readiness to recognise mental health conditions (readiness for step 1 of the 5-step model).

Readiness to initiate and lead conversation with a person with mental health issues and his/her caregivers (readiness for step 2).

Readiness to support a person with mental health issues and his/her caregivers (readiness for step 3).

Readiness to refer a person with mental health issues, and his/her caregivers, to professional support (readiness for step 4).

Readiness to ensure that professional help is received by a person with mental health issues and his/her caregivers (readiness for step 5).

Mental health awareness

Mental health awareness assessment was based on the KAP (knowledge, attitudes, and practices) model (Andrade et al., 2020). There is the experience of using such KAP-based surveys in Ukraine (Quirke et al., 2021). Based on the KAP model, a short survey was developed related to the knowledge about mental health issues, attitudes toward people with mental health disorders, and practice of interaction with them.

Knowledge regarding people with mental disorders was assessed with the query: "Choose the statements that apply to people with mental health disorders" (max = 8 scores, where each score was awarded either for a choice of a correct statement or for a non-selection of a wrong statement):

They are dangerous to the people around them.

They are themselves guilty of their condition.

They are incapable of true friendships.

They can work.

By appearance, it is clear that the person is not all right.

Anyone can have a mental disorder.

Mental disorders are incurable.

Most people with mental disorders can recover.

Attitude towards people with mental issues was assessed with the question: "What is the best way of behaviour for people with mental health issues?" (max = 8 scores):

Do not tell anyone about their condition.

Discuss everything with a doctor, but do not inform relatives.

Hide this information at work/school.

Tell loved ones and ask for help from specialists.

Hide it from the family.

Live among those like themselves.

Should not marry and have children.

The question for assessment practices of interactions with people with mental disorders: "What is the proper way of interactions with people with mental health disorders?" (max = 9 scores):

You would better avoid any contact with them.

You shouldn't allow them to make any decisions.

You would better avoid working with them in one team or performing tasks together.

You should be careful about conversations with them.

You should be ashamed and try to hide the fact you have a relative with a mental health disorder.

They should have the same rights as anyone else.

It is normal to have a friend with a mental health disorder.

It is normal to marry a person with a mental health disorder.

You should treat them with care and sympathy.

Practices of care about people with mental health issues were analysed with the question: "What is the best way to care about people with mental health issues?" (max = 6 scores):

In a psychiatric hospital where they are under supervision and control (psychiatrist).

Outside the hospital in specialised centres or privately (psychologist, psychotherapist).

Alternative methods of treatment (traditional medicine, homoeopathy, vitamins, massage).

Normal family relationships is the best treatment.

Do not waste energy, it is not possible to cure mental disorders.

At the primary level of health care (family doctor, paediatrician, general practitioner).

Mental health awareness scores were collected as the sum of scores for each scale.

Mental health proficiency

Mental health proficiency, as the ability to recognise mental health disorders' symptoms, was assessed by the tests that include correct and non-correct symptoms. Three true and two false symptoms (based on DSM-5) were offered for selection in each case. Mental health proficiency was estimated as the sum of the correct choices of symptoms for every disorder learned by participants. For instance, the participants who worked during the training with depressive disorders should choose all appropriate parameters among depressed mood, markedly diminished interest or pleasure in almost all activities, excessive or inappropriate feelings of worthlessness or guilt, inattention as, difficulties following instructions and failure to finish tasks, restlessness as fidgeting with or tapping hands or feet or squirming in the seat.

Additional one-month follow-up questions

Additional questions for the one-month follow-up test were: "Did you work after the training with people with mental health issues that you studied?", "What kind of the issues?", "Did you use training knowledge and skills?", "Which knowledge and skills did you use in particular?"

Sharing and accessing information

Information (raw anonymized data) is openly available through Zenodo. It is possible to use the information with research aims to evaluate UMHT or compare data with other similar programs. Our research team kindly asks to notify the contact person (Viktoriia Gorbunova) about any usage of the dataset.

Methodological information

The study was quasi-experimental (no complete randomization was possible at this piloting stage). Two groups were involved: the experimental group (received UMHT) and the control group (no training, waiting list).

The pilot trial of UMHTs' efficacy was conducted with 307 frontline professionals divided into 24 training groups (social workers (12 groups, 128 persons), educators (4, 63), police officers (4, 60), priests and clerics (1, 15), military volunteers (1, 12), workers of occupation centres (1, 13), emergency workers (1, 16)). All participants were recruited for training by their team leaders, who were informed about training possibilities by letters sent from the training developers. The only requirement for participation was working in the field with people.

The control group included 211 persons with the same occupation background who participated in training later (waiting list). The control group consisted of social workers (97 persons), educators (32), police officers (40), priests and clerics (12), military volunteers (13), workers of occupation centres (7), and emergency workers (10).

Data-specific information

Excel file (UMHT_dataset_pilot_trial.xlsx) containing four pages.

1. Page "Training groups_before UMHT". Contains the answers to questionaries completed by UMHT training participants before the training.

2. Page "Training groups_after UMHT". Contains the answers to questionaries completed by UMHT training participants immediately after the training.

3. Page "Training groups_after one month". Contains the answers to questionaries completed by UMHT training participants the month before the training.

4. Page "Control group_before-after". Contains the answers to questionaries completed by UMHT control group participants (waiting list) before and after the training.

In 2023, first-line supervisors of housekeeping and janitorial workers were the highest paid workers among the employees in cleaning occupations in the United States, who earned approximately 50,000 U.S. dollars for the year. On the other hand, maids and housekeeping cleaners earned an annual wage of almost 35,000 U.S. dollars as of May 2023, coming bottom of the list of earners.

Household name McDonald’s accounted for around 150 thousand employees in 2023. This figure remained consistent with the previous year. Overall, the number of McDonald's employees has more than halved in the past decade. The number of employees in the restaurant industry in the U.S., as of 2022, was 12.5 million. Unit growth, staff declineThe number of McDonald’s restaurants across the globe is on the rise. The company operated and franchised a total of 41,822 restaurants worldwide in 2023. This figure has seen a year-on-year increase for the last 18 years. McDonald's has implemented a growth strategy named “Velocity Growth Plan” for its emphasis on speed of expansion. Yet the number of employees has decreased dramatically over the past five years. So, why is this? More tech = fewer workers? McDonald’s is in the process of updating its stores using three accelerators to do so - “Digital”, “Delivery” and “Experience of the Future” – two of these three initiatives are technology-based. The “Digital” initiative allows customers to order eat-in, takeout and drive thru food through a mobile ordering and payment system. Meanwhile, the “Experience of the Future” accelerator includes self-serve digital kiosks and table service. While people are still needed for many aspects of the work (serving, delivery, management to name a few), many of the ordering components have now been taken over by technology. Tech and the digitalization of the restaurant industry worldwide may not be the only factors for McDonald’s downsizing its staff, but they could very well have had an impact.

Through its multidisciplinary team, provides tailored training and support services for young persons with high-functioning autism (HFA) to meet their individualised needs in coping with the challenges during their transition into adulthood. SPA also offers support services for their parents/carers; and provides professional consultation service and training for frontline workers serving persons with autism.

Abstract

What do we know about incentives and norms in health bureaucracies and service delivery points at various levels of a state in India? For example, the logic of economic theory suggests that governments should be direct providers of services when there is a role for attracting intrinsically motivated agents (Francois, 2000), but we have no empirical evidence on integrity and public service motivation among state personnel across different cadres of service delivery. The available research has focused on documenting evidence of weak incentives and low accountability for service delivery in the public sector, and thence on evaluating interventions targeted at strengthening incentives, such as making some part of pay conditional on performance indicators (for example, Singh and Masters, 2017). But what is available is barely scratching the surface of knowledge needed to help reform leaders think about how to structure government bureaucracies and assign tasks to leverage intrinsic motivation and to reduce reliance on high-powered incentives. Even when increasing the power of incentives has been shown to “work”, the authors of those findings concede that implementing optimal incentive contracts at scale can place significant demands on state capacity (Muralidharan and Sundararaman, 2011). There is even less evidence available about the incentives and motivation of mid-level bureaucrats within the health system, compared to a growing body of research on frontline providers such as doctors and community health workers. Finally, the logic of economic theory, and growing international evidence in support of it, further suggests that politics casts a long shadow on culture in the bureaucracy, but we have no rigorous evidence for this claim for India.

To address these knowledge gaps we designed and implemented a complex survey of multiple types of respondents across districts, blocks (administrative sub-units within districts) and village governments (Gram Panchayats or GPs) in Bihar, one of the poorest states of India and with some of the worst statistics of child malnourishment.

Geographic coverage

16 study districts, from among the 38 of Bihar, selected to represent the 9 administrative divisions of Bihar: Patna, Tirhut, Darbhanga, Kosi, Purnia, Saran, Bhagalpur, Munger, Magadh

Analysis unit

Households Health Staff Politicians Bureaucrats

Universe

Citizens, Within the category of citizens, the survey additionally targeted office-bearing members of women’s Self Help Groups (SHG) under a rural livelihoods program in Bihar known as Jeevika. Politicians Bureaucrats Public Providers of Health Services

Kind of data

Sample survey data [ssd]

Sampling procedure

Budget and implementation constraints required us to select a sample of districts rather than covering all 38 districts of Bihar. At the same time, we needed a large sample to be representative of the diversity within the state, and allow us to capture some variation across district-level institutional characteristics. These constraints led us to determine 16 as the number of districts in which to undertake the survey. The purposive selection of which 16 study districts, from among the 38 of Bihar, was made using the following criteria:

• represent the 9 administrative divisions of Bihar: Patna, Tirhut, Darbhanga, Kosi, Purnia, Saran, Bhagalpur, Munger, Magadh • represent both border and interior districts • select "old" and "new" districts (those which were created after 1991) because district age might matter in interesting ways for their capacity to deliver (to be discussed further) • select districts which might vary in historical institutions that shape norms.

We first explored an established literature in India which finds that there are persistent effects on current service delivery of the long-gone historical institution of the Zamindari system of land revenue (Pandey, 2010; Banerjee and Iyer, 2005). However, since all of the districts of Bihar are classified as belonging to the Zamindari system, we could not use this established measure of historical institutions in selecting the study districts. We then turned to a newer literature which examines the early construction of railway lines in the late 1800s in the United States and India as a potential source of institutional variation (Donaldson, 2018; Donaldson and Hornbeck, 2016; Atack, Haines and Margo, various). The 16 districts in our study include those through which passed the first railway lines in Bihar, and those that received railway lines a decade or so later.

Within each of the 16 districts, 4 blocks were selected using a random number generator,after stratifying by proximity to the main railway line. Within each block, 4 Gram Panchayats (GPs) were selected using a random number generator. However, in one block each in the districts of Lakhisarai and Buxar, 3 GPs instead of 4 were selected because the sampling protocol required a sufficient number of replacement respondents to be available, and these districts only had 3 GPs fulfilling the replacement requirement (more details in section on Respondents below). This yields a sample of respondents drawn from 16 districts, 64 blocks from within those districts, and 254 Gram Panchayats (GPs) from within those blocks.

Citizen Survey: The citizen survey was aimed at respondents from 16 households residing in each GP area. The survey firm was provided with a list of respondents (with replacements) drawn randomly from the electoral rolls available of all voting-age adults in Bihar's population. The target sample size is thus 4064 citizens (16 each from 254 GPs). Within the category of citizens, the survey additionally targeted office-bearing members of women's Self Help Groups (SHG) under a rural livelihoods program in Bihar known as Jeevika. However, we had no lists available with names of SHG leaders of the village-level organziations across GPs. In the absence of these lists, we relied on the survey firm to ensure that enumerator teams would identify SHG leaders during their field-work. The data from SHG leaders that has been provided to us is thus subject to a greater than usual caveat: the risk of whether the enumerator teams accuratelyidentified and obtained interviews with the targeted SHG respondents. The instructions provided to the survey teams was to ask the GP Mukhiya and other GPlevel respondents (such as the ANM, ASHA and AWW) about the GP-level federated organzation of all the SHGs across the GP's communities to identify its President,Secretary and Treasurer. That is, 3 SHG leaders were targeted for each GP, for a total sample of 762 (3 each from 254 GPs) SHG leaders.

Politician Survey: Lists were provided to the survey teams of all incumbent Mukhiyas to be interveiwed, and a random selection (with replacement) of 3 Ward members and 3 candidates from among those who contested the previous GP elections of 2016. The targeted sample size of GP politicians is thus 1778 (7 each from 254 GPs)

Bureaucrats: The survey firm was responsible for identifying and interviewing the respondents holding these positions. The final data submitted by the survey firm contains 293 respondents in supervisory or management positions, including: 13 Civil Surgeons,11 Chief Medical Officers (including 4 who were in Acting capacity), 23 Superintendents (including 13 in Deputy or Acting capacity), 9 District Programme Officers- NHM, 4 District RCH and Immunization In-charge, 7 District Community Mobilizers, 58 MOICs, 58 Acting Facility Incharge, 43 Block Program Managers-NHM, 29 Block RCH Programme officers, and 35 Block Community Mobilizers.

Public Providers of Health Services: The survey team was provided a list (with replacements) of 3 AWW workers to interveiw per GP, for a targeted sample of 762 AWW respondents. The survey team was provided with a list of randomly selected candidates for the categories of respondents for all the PHCs and higher-level health facilities (such as District Hospitals) across the 64 blocks of the study area.

Sampling deviation

Block Level: The survey firm was responsible for identifying the block-level politicians targeted to be interviewed. The targeted sample size of Block-Panchayat (Panchayat Samiti) elected members’ is 128 respondents (2 each from 64 blocks). The 57 MLAs across the 64 blocks of the study area were also identified by the survey firm. However, because of problems of reaching politicians at a time that was close to the 2019 elections in India, the survey firm was able to complete interviews with only 39 MLAs (of the targeted 57) , and with 119 Panchayat Samiti members (of the targeted 128).

District Level: The survey firm was responsible for identifying the MPs from constituencies within the 16 study districts, and the 32 respondents of the District-Panchayat (Zilla Parishad). Again, because of problems reaching political leaders at election time, the survey firm was able to interviewonly 9 MPs, and 28 Zilla Parishad members.

Public Providers of Health Care Services: The survey team was provided with a list of randomly selected candidates for the categories of respondents for all the PHCs and higher-level health facilities (such as District Hospitals) across the 64 blocks of the study area. However, the survey team reports substantial difficulty in adhering to this list because the personnel were not found at the health facilities. The survey team was not able to reach a random sample of providers appointed at these positions.

Abstract

The health care system in the Republic of Tajikistan has required a substantial reform in order to adequately meet the health needs of the population and to ultimately lower morbidity and mortality rates.

In order to support future reform efforts, a Public Expenditure Tracking Survey (PETS) was carried out in 2006 by the World Bank and the Tajikistan government with the financial support from the UK's Department for International Development. The study was designed to provide information on where and on what health care funds were spent and which institutions within the government - both central and local - had the greatest influence on the allocation of resources. The PETS aimed to collect budget data at each level that public resources passed through before reaching frontline providers such as hospitals and clinics.

The structure of the health care system in Tajikistan in 2000s has remained similar to the Soviet model, with the State as the main provider of care services. The administration of the services has been divided into four levels: central, oblast, rayon, and jamoat.

At the time of the study, public resources devoted to health care were very low. An estimated 1.1 percent of GDP was allocated by all levels of government to health. The state of health facilities was so poor that underfunding was easily apparent. The 2005 Poverty Assessment identified that the bulk of health expenditures in Tajikistan were paid out-of-pocket by individuals either as formal or informal payments. The largest category of private medical spending was on pharmaceuticals. Moreover, even the more affluent members of the population indicated that they did not seek health care in some instances because of the high cost. Thus, the main objective of this research was to assist the Tajik government in improving the public financial system to ensure efficient and appropriate use of scarce resource.

The survey collected data on 317 health facilities and 1,282 health facilities employees from 30 rayons (districts) nationwide.

Geographic coverage

National

Analysis unit

• Rayon Administrations;
• Central Rayon Hospitals;
• Jamoat Administrations;
• Health Facilities;
• Health Facilities Staff.

Kind of data

Sample survey data [ssd]

Sampling procedure

1) The Universe of Health Facilities. At the time of PETS 2006 in Tajikistan, there was no sample frame of health providers in the country. The starting point was to build the sample frame from which to draw a representative sample for the PETS. A local Tajik firm, Zerkalo, was hired to compile the full list of health facility in the country during August 2006. The firm came back with a full list of facilities with a breakdown along a number of variable such as location (Oblast, rayon and jamoat if applicable), rural/urban, type of the facility, number of beds when in-patients services are provided and whether the facility is public or private. Since only public facilities will be interviewed during this PETS all the private facilities have been excluded from the sample frame for the sampling. Overall, there are 60 rayons (districts) in Tajikistan plus Dushanbe. The jamoat is the administrative entity just below the rayon. Jamoats matter in the PETS because they handle public resources. There are 356 jamoats in Tajikistan. However, for the purpose of the sampling strategy, cities and urban settlements which can be considered as "urban" jamoats are included which brings the total to 445 jamoats. The list of facilities identified 2617 public facilities in the country including the CRHs which are sampled with certainty whenever the rayon is selected. Therefore, Central Rayon Hospitals (CRH) have been excluded form the sample frame which left 2559 health facilities to choose from.

2) Selection of Rayons. Tajikistan counts 5 oblasts or regions and 61 rayons. Dushanbe, the capital city, enjoys a special status and is considered both as an oblast and rayon by itself for the survey's purpose. For the survey, the overall 'optimal' number of rayons is fixed at 30. Dushanbe is included in the sample with probability one because of its importance. Two other rayons, Varzob among the Rayons of Republic Subordination (RRS), and Dangara in the Khatlon oblast are also purposively chosen because the survey result will be used as a baseline for future evaluation of per capita financing scheme that is being piloted in the two rayons. The remaining twenty-seven rayons are allocated across the four strata using proportionate allocation which allows each oblast to contribute to the sample in proportion to its importance in the universe. The rayons have been sampled with probability proportional to size (PPS).

3) Sampling of Jamoats. The initial sampling strategy was to randomly sample ten facilities in each of the rayons. However, given that jamoats play a central role in the financing of facilities and the important number of jamoats, randomly selecting the facilities within each rayon would have brought about a very high number of jamoats to survey resulting in a sharp increase in the survey cost. Therefore, in each rayon four jamoats have been sampled with equal probability of selection. When there are four jamoats or less in the rayon, all jamoats are chosen with probability one. In the end, 107 jamoats were included in the survey.

4) Sampling of Health Facilities The final step consists of selecting the facilities. Within the facilities under the authority of the four jamoats that were selected in the preceding phase ten facilities were randomly chosen.

5) Selecting Staff and Staff Sampling Weights. In each facility, seven staff members have been randomly selected for the staff survey. Facilities with seven or fewer employees are "take-all" cases i.e. all staff have been administered the questionnaire. The computation of the staff probability of selection is simply the minimum between one and seven divided by the number of employees in the facility. The weight of the staff is the inverse of that probability. However, because of absent staff, sometimes in facilities with, say, 5 employees only 3 questionnaires have been filled out. An adjustment procedure needs then to be used to account for the absent staff. This procedure is relevant only in facilities where the staff size is lower than 7 and in which employees were missing in action at the time of the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

Tracking public expenditure in the health sector requires designing appropriate instruments in order to collect budget data at each level public resources went through before reaching frontline providers. In Tajikistan, this includes at local level Rayons, Central Rayon Hospitals, Jamoats and health facilities. This section describes the survey questionnaires that were designed in close collaboration with the key government counterparts in Ministries of Health, Finance, and Executive Office of the President (EOP). A consultation workshop with key counterparts was held with representatives of these agencies to discuss comments. Their inputs were incorporated in the final draft questionnaires. The field survey was administered by Zerkalo, a local survey company.

Six questionnaires were designed for this study.

1) Rayon (District) Questionnaire was applied to the rayon administration and responded by rayon financial department. The rayon questionnaire tracked budgetary revenues (tax and non tax and transfers from republican budget and subsidies) as well as additional resource both in cash and in kinds contributed to the health sector budget by government at various levels, donors, local communities, etc. On the expenditures side, the rayon questionnaire tracked allocation of budgetary resource to key sectors (general administration, education, health, and housing and communal services), allocation of resource within the health sector (by economic classification, function, and by budget institution unit). The questionnaire also examined the role and responsibilities of the rayon chairman in budget preparation, execution as well as issues in financial reporting, internal and external audit. Information from the rayon questionnaire can be cross validated with information from central rayon hospital and jamoat questionnaires. However, cross validation of information with the facility questionnaire is not possible as rayon allocates budgetary fund to health through central rayon hospitals and jamoats.

2) Central Rayon Hospitals (CRH) Questionnaire was applied to central rayon hospital administration responded by Head Doctor of Central Rayon Hospitals or by delegated staffs. Central rayon hospital plays an important role in allocating budgetary resources to health facilities included in the CRH network. These health facilities are not legal entities and therefore they do not have approved budgets based on organization. The questionnaire examines the role and responsibilities of the Head doctor of the central rayon hospitals. It tracks budgetary and non-budgetary revenues (in cash and in-kinds) as well as expenditure by economic, functional and budget institution of a central rayon hospital. Tracking of economic classification focuses on wage bill and other inputs including goods and services (foods, drugs, and travel expenses), repair and maintenance and communal services. However, cross validation of expenditures with health facilities is limited to payments of wage. Cross validation of expenditure on other inputs can not be done as there is no record on how much inputs health facilities received from the central rayon hospital. Central rayon hospital and jamoat have no financial relations as they both play role as paymaster to

Snapshot img

Coverall Market Size 2024-2028

The coverall market size is forecast to increase by USD 2.31 billion at a CAGR of 8.09% between 2023 and 2028.

The market is witnessing significant growth due to various trends and challenges. One of the key growth factors is the increasing number of accidents in hazardous work environments, leading to a higher demand for protective coveralls. Additionally, the adoption of e-commerce platforms by coverall companies is expanding their reach and making it more convenient for customers to purchase coveralls. Eco-friendly and sustainable materials, such as polypropylene and blends, are increasingly gaining traction In the market due to their comfort, breathability, and reduced environmental impact. However, a lack of awareness and adherence to regulations poses a challenge to market growth. Companies must prioritize educating their customers about the importance of using appropriate coveralls in hazardous work environments and ensure compliance with relevant regulations to maintain market competitiveness. The market is expected to continue its growth trajectory, driven by these factors and others.

What will be the Size of the Coverall Market During the Forecast Period?

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The market encompasses a range of garments designed to shield the body from hazardous conditions and substances. These garments include coveralls for the head, body, and toes, crafted from various fabrics such as lightweight cotton, breathable polyester, vinyl, Tyvek, and blends. The market caters to diverse industries, with applications in healthcare, industrial activity, and hazardous chemical handling. Coveralls serve as a crucial component of worker protection, providing a barrier against hazardous chemicals and substances. Frontline workers in various sectors rely on these garments to ensure their safety and well-being.

How is this Coverall Industry segmented and which is the largest segment?

The coverall industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Type

  Durable
  Disposable


Distribution Channel

  Offline
  Online


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC



  South America



  Middle East and Africa

By Type Insights

The durable segment is estimated to witness significant growth during the forecast period.

In various industries, including oil and gas refining, durable coveralls serve a crucial role in minimizing workplace accidents and fatalities. Workers encounter hazardous conditions, such as thermal and fire hazards, which can result in severe burns or fatalities. To mitigate these risks, coveralls made from denim, cotton, and linen are commonly used due to their durability and longevity. However, disposable coveralls, often made from PVC or mixed fabrics, offer chemical protection and flame retardant properties. These coveralls are essential for workers in industries with hazardous materials, such as agriculture, construction, mining, manufacturing services, and healthcare.

Ensuring head-to-toe protection, coveralls safeguard against hazardous substances, germs, bacteria, and extreme temperatures. Lightweight and breathable materials, such as cotton and polyester, are increasingly popular for their comfort and wearability. As industries continue to industrialize, the demand for ergonomic, reusable, and lightweight coveralls will persist. Smart technologies, including sensors and wearable devices, are also integrated into coveralls for real-time monitoring and increased safety.

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The durable segment was valued at USD 2.25 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 33% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The North American coveralls market is experiencing growth due to the increasing employment rates and economic development In the region. A significant factor contributing to this growth is the growth in infrastructure projects, such as the Hudson Yards project in Manhattan and the 78 project, which are currently underway In the US. These projects require extensive labor and the use of protective coveralls to ensure worker safety in hazardous conditions and against hazardous materials, including chemicals, germs, and bacteria. In 2022, there were 5,486 fatal work injuries In the US, highlighting the importance of proper protecti

The Coronavirus Disease 2019 (COVID-19) has had devastating effects globally. These effects are likely to result in mental health problems at different levels. Although studies have reported the mental health burden of the pandemic on the general population and frontline health workers, the impact of the disease on the mental health of patients in COVID-19 treatment and isolation centres have been understudied in Africa. We estimated the prevalence of depression and anxiety and associated risk factors in hospitalized persons with COVID-19. A cross-sectional survey was conducted among 489 patients with COVID-19 at the three government-designated treatment and isolation centres in Edo State, Nigeria. The 9-item Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder-7 (GAD-7) tool were used to assess depression and anxiety respectively. Binary logistic regression was applied to determine risk factors of depression and anxiety. Results Of the 489 participants, 49.1% and 38.0% had depressive and anxiety symptoms respectively. The prevalence of depression, anxiety, and combination of both were 16.2%, 12.9% and 9.0% respectively. Moderate-severe symptoms of COVID-19, ≥14 days in isolation, worrying about the outcome of infection and stigma increased the risk of having depression and anxiety. Additionally, being separated/divorced increased the risk of having depression and having comorbidity increased the risk of having anxiety. A substantial proportion of our participants experienced depression, anxiety and a combination of both especially in those who had the risk factors we identified. The findings underscore the need to address modifiable risk factors for psychiatric manifestations early in the course of the disease and integrate mental health interventions and psychosocial support into COVID-19 management guidelines. -- Methods Setting and study design A descriptive cross-sectional study was conducted from 15th April to 11th November 2020. The participants were COVID-19 Real Time-Reverse Transcriptase -Polymerase Chain Reaction (rRT-PCR) positive persons who were hospitalized at the three government- designated treatment and isolation centres in Edo State, Nigeria. Participants and data collection procedure All eligible and consenting persons who were COVID-19 rRT-PCR positive and hospitalized at any of the study institutions within the period of the survey were recruited. The inclusion criteria comprised of persons with confirmed COVID-19, hospitalized at any of the study institutions who consented to participate in the study and were eleven years and above. Exclusion criteria comprised of hospitalized persons who tested positive for COVID-19 but declined or were unable to give consent to participate in the study and persons below 11 years due to the inappropriateness of the assessment tools for anxiety and depression in this age group. Medical records/registers at the treatment and isolation centres were reviewed daily in order to identify new admissions and discharges in the centres and ineligible patients due to age (less than 11 years). A total of 796 persons with confirmed COVID-19 were hospitalized at the three government designated treatment and isolation centres in Edo State over the study period. All patients were informed and acknowledged a detailed description of the study, eligibility requirements and voluntariness to participate in the study. Nineteen of them were below 11 years and were excluded, and 265 patients either refused to give consent or were too ill (critically ill) to consent and participate in the study. A total of 512 were therefore recruited for the study. Semi-structured and structured questionnaires incorporating socio-demographics, basic clinical history/information and an assessment of anxiety and depression were administered to recruited participants on the fifth day of admission into the treatment and isolation centres. The questionnaires were self - administered except for those who opted for interviewer-administered questionnaires (mainly those with severe COVID-19 infection). Questionnaires were administered in the English language as all participants had some levels of formal education and were literate enough to understand the language. Those who were critically ill with COVID-19 infection were unable to consent and participate in the study. Online survey and hard copies of the questionnaires were made available for completion. All the participants preferred hard copies of the questionnaires and a copy of the signed consent form was retained by each participant and one by the researchers. Clinical information on severity of COVID-19 infection and presence and type of comorbidity were obtained from their medical records (case files). Length of stay in treatment and isolation centres was obtained from their case files after discharge from the centres as the questionnaires were coded for ease of identification. Measurements The socio-demographic/clinical history questionnaire This was designed to provide information about the participant’s age, gender, religion, marital status, employment status and the highest level of formal education. Clinical variables such as COVID-19 rRT-PCR status, previous/family history of mental illness, the severity of COVID-19 infection, the number of days in isolation, comorbidity were ascertained as well. To ascertain the worry factor, the question “what is your greatest worry about being COVID-19 positive” was asked. The 9-item Patient Health Questionnaire (PHQ‑9) This consists of nine items, each of which is scored 0 to 3, providing a 0 to 27 severity score.[15] PHQ‑9 severity is calculated by assigning scores of 0, 1, 2, and 3, to the response categories of: Not at all, several days, more than half the days, and nearly every day, respectively. It consists of the nine criteria for depression from the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM‑IV). The PHQ‑9 is comparable or superior in operating characteristics, and valid as both a diagnostic and severity measure.[16] Scores of 5, 10, 15, and 20 represent cut-off points for mild, moderate, moderately severe, and severe depression respectively. A PHQ-9 score of 10 or greater is recommended if a single screening cut-off is to be used, this cut-off point has a sensitivity for major depression of 88% and a specificity of 88%. The modified version for adolescents PHQ-A was used for participants within the ages of 11 and 17 years. A cut-off score of ≥ 10 was used to represent cases of depression. The PHQ-9 can be self-administered or clinician administered. The Generalized Anxiety Disorder-7 (GAD-7) This is a 7-item self-report questionnaire that allows for the rapid detection of GAD, the validity is not compromised if the clinician reads the questions to the client.[17] Participants are asked if they were bothered by anxiety-related problems over the past two weeks by answering seven items on a 4-point scale. The total scores range from 0 to 21. At a cut-off score of 10, the GAD-7 had a sensitivity of 89 % and a specificity of 82 % for detecting GAD compared with a structured psychiatric interview.[17] Notably, among clinical and general population samples, the GAD-7 has demonstrated good reliability and cross-cultural validity as a measure of GAD (16). Its use has been validated in adolescents.[18] A cut-off score of ≥ 10 was used to represent cases of anxiety. Ethics Ethical clearance was obtained from our Research Ethics Committee of the Irrua Specialist Teaching Hospital, Irrua. Informed written consent was obtained from each participant and from the parents or guardians of participants who were less than 18 years. Participants who were less than 18 years also assented to the study. Confidentiality and anonymity were ensured by not indicating the names of the participants on the questionnaires. Statistical analysis The collected data were analysed using the Statistical Package for Social Sciences (SPSS) version 21. Dependent variables were depression and anxiety. Independent variables were sociodemographic and clinical characteristics. Descriptive statistics were used to summarise socio-demographic and clinical related data and mean with standard deviation for continuous variables. Chi-square (χ2) tests were used to test the association of independent variables with dependent variables. Fisher's exact test was used for cells with expected frequencies < 5. The student's t- test was used to compare means. Binary logistic regression was applied to identify predictors of depression and anxiety that were significant at bivariate analysis. All tests were 2-tailed, and the level of significance was set at a P-value of <0.05.

Out of the two billion COVID-19 vaccines administered, over 1.6 billion vaccines were Covishield vaccine developed by Oxford university and AstraZeneca as of September 1, 2022 in India. Vaccinations in India were administered since January 16, 2021, with the administration of vaccines to all health care workers in the first phase. In February, the vaccination program was expanded to cover front line workers. The second phase of the program began in March which included citizens above the age of 60 and subsequently, people above the age of 45 with comorbidities. India’s vaccination program currently includes three vaccines, namely, Oxford University – AstraZeneca’s Covishield vaccine, manufactured by the Serum Institute of India, Bharat Biotech Covaxin and Russia's Sputnik V.

Abstract

In many countries, including Sierra Leone, increases in the allocation of central government funds towards social sector expenditures have not always corresponded with improvements in social sector outcomes. Public Expenditure Tracking Surveys (PETS) have been used to explore and understand this phenomenon. PETS survey tool examines the flow of funds and materials from the central government to frontline services delivery units.

In Sierra Leone, the Ministry of Finance established the PETS Task Team in 2001 to oversee the development and use of the survey. UK's Department for International Development (DFID) and the United Nations Development Programme (UNDP) offered financial support, while the World Bank prepared the technical review and recommendations for future PETS.

Unlike in other countries, PETS in Sierra Leone was entirely home-grown and was first undertaken while the country was still in conflict.

Two surveys (PETS 1 and PETS 2) documenting semi-annual expenditures for 2001 were conducted in January-June and July-December 2001. Overall, the project covered following sectors: - Education, - Health, - Agriculture, - Fisheries and Marine Sector, - Security Sector (Police and Military), - Social Welfare, Gender and Children Affairs, - Rural Development and Local Government, - Provincial Water Supply and Sanitation Services.

The survey sample was selected from 72 chiefdoms and ten wards in areas that were considered safe in 2001.

The coverage of sectors by PETS in Sierra Leone was much wider than in other countries primarily due to the need to fill the accountability gap. However, the coverage by geography and category of expenditure had been narrow. Moreover, as of May 2003, much of the collected information had not been analyzed.

Documented here is the Public Expenditure Tracking Survey conducted in Sierra Leone health sector. 185 health facilities were surveyed in PETS 1 and 176 health facilities were visited during PETS 2.

Kind of data

Sample survey data [ssd]

Sampling procedure

1) Public Expenditure Tracking Survey, January - June 2001 (PETS 1) Sampling was applied to facilities and communities. Due to the absence of any list of agricultural facilities and incomplete or inaccurate lists for education, health and water facilities, 230 Enumeration Areas (EAs) (out of 1380 Census EAs) were selected by probability proportional to size from those Chiefdom/wards considered safe (unsafe areas would not have been receiving goods and services from the government anyway). All communities and facilities in each chosen EA were sampled.

2) Public Expenditure Tracking Survey, July - December 2001 (PETS 2) Sampling was again applied to facilities and communities. Due to concern that the sampling design adopted in the previous PETS did not cover an adequate number of facilities in some sectors and because facilities were found to serve communities in more than one EA, the primary sampling unit for the second PETS was redefined. The primary sampling unit became the whole of a Chiefdom/ward. The same Chiefdoms/wards were used as in the first PETS. Enumerators were instructed to interview up to five facilities of each type and up to five communities within the newly defined EAs which should include the same facilities and communities covered in the first PETS. There was no sampling plan for the additional facilities/communities which have to be regarded as non-random selections.

Mode of data collection

Face-to-face [f2f]

Research instrument

PETS 1 and PETS 2 surveys utilized an elaborate series of some 40 questionnaires, each tailored specifically to one of the eight covered sectors. For each sector, a series of three questionnaires gathered data at headquarters, regional, and district office levels. A further two questionnaires were used to collect information at the facility and community levels.

The public expenditure tracking data collected consisted primarily of non-wage recurrent budget allocations, expenditures and transfers. This was collected for each budget head and sub-head, for each sector, at ministry headquarters, regional and district levels. Information on development expenditure was sought at the Ministry headquarters level.

At the facility level, the survey focused primarily on general sector data such as characteristics of the facility and outputs. Public expenditure-related information collected included: regularity of staff salary payments; timing, adequacy and quality of material supply; access to ancillary government services/subsidies; fees charged; access to non-government support; and inspection and auditing activities.