In News:

The Government of India has undertaken a significant revamp of the Periodic Labour Force Survey (PLFS) from January 2025 to strengthen the quality, frequency, and coverage of employment and unemployment data across the country. Conducted by the National Statistical Office (NSO) under the Ministry of Statistics and Programme Implementation (MoSPI), PLFS plays a pivotal role in informing labour market policies and addressing data gaps in India’s employment landscape.

Key Changes and Objectives

Originally launched in 2017, the PLFS was designed to generate quarterly estimates of labour market indicators for urban areas under the Current Weekly Status (CWS) and annual estimates for both rural and urban areas under both Usual Status (ps+ss) and CWS. The 2025 overhaul expands the PLFS to produce monthly all-India estimates of key indicators—Labour Force Participation Rate (LFPR), Worker Population Ratio (WPR), and Unemployment Rate (UR)—for both rural and urban areas using the CWS framework.

The quarterly results, earlier limited to urban regions, will now also cover rural areas, offering disaggregated and timely data at national and major state levels. Annual results will shift from a July–June cycle to a calendar year reporting format (January–December) to align better with international standards and improve comparability.

Enhanced Sampling Design

A critical aspect of the revamp lies in the revised sampling methodology. The new design uses a multistage stratified approach, ensuring representation from most districts and capturing diverse labour dynamics across geographies. A total of 22,692 First Stage Units (FSUs)—12,504 in rural and 10,188 in urban areas—will be surveyed annually, covering 2,72,304 households, a substantial 2.65-fold increase over the earlier sample size of 1,02,400 households. Each selected household will now be visited four times over four months in a rotational panel format to improve the robustness of estimates.

Inclusion of New Parameters

The revamped PLFS introduces several new data points to enrich its analytical value:

• Household income sources including rent, pension, interest, and remittances
• Land possession and leasing status
• Additional education indicators like years of schooling completed and attendance in the past year
• Information on vocational training, including details of the certifying body

These additions make the PLFS more holistic, offering deeper insights into the economic and social characteristics influencing labour participation.

Significance and Policy Implications

India has long faced a dearth of high-frequency, reliable labour market data. The revamped PLFS addresses this gap by delivering timely, comprehensive, and representative statistics. This is critical for monitoring employment trends, understanding the rural-urban labour divide, and assessing the impact of government schemes, economic reforms, and global shocks.

Further, the alignment with international reporting norms will strengthen India's statistical credibility in global forums and aid in better representation in databases maintained by institutions like the ILO and World Bank.

In conclusion, the PLFS revamp marks a milestone in labour statistics modernization. By offering high-frequency, granular data on a range of labour and socio-economic indicators, it empowers evidence-based policy formulation, a key requirement for inclusive and sustainable economic development—an essential focus for aspirants preparing for the UPSC Civil Services Examination.

Context:

Mental health insurance coverage in India remains critically inadequate despite rising awareness of mental health issues. According to the RiseUP for a Better Tomorrow: Mental Health Report 2025, mental health accounts for less than 1% of total health insurance claims, reflecting a glaring disparity in healthcare priorities. This neglect persists despite a robust legal and regulatory framework aimed at promoting mental health coverage.

The Mental Healthcare Act, 2017 legally mandates that mental health be treated on par with physical health in insurance policies. In line with this, the Insurance Regulatory and Development Authority of India (IRDAI) issued guidelines in 2019 requiring insurers to include mental health illnesses in coverage plans. However, implementation remains patchy, especially in group insurance policies. Many plans continue to exclude essential mental health services, undermining legislative intent.

Current insurance offerings are heavily skewed towards hospitalization for severe mental illnesses, with minimal coverage for outpatient care—counselling, therapy, and medication—which forms the backbone of mental healthcare. Only 17% of insured individuals have access to outpatient mental health services. Additionally, schemes like Ayushman Bharat offer limited support for mental health, and common exclusions such as substance abuse and self-inflicted injuries reduce the scope of coverage.

On the demand side, awareness is a significant barrier. Around 42% of people are unaware of their mental health coverage, while 83% of organizations report low utilization of mental health insurance. Out-of-pocket expenses still account for 60–70% of mental healthcare costs (NMHS 2015–16), adding to the economic burden. A staggering 70–90% of individuals with mental disorders remain untreated, largely due to poor insurance access.

From the supply perspective, policy design is often modeled on physical health, failing to account for the chronic and outpatient nature of many mental health conditions. Nearly 50% of respondents in the RiseUP report cited high treatment costs as a deterrent to seeking care, a concern aggravated by restrictive policies and long claim settlement periods. Furthermore, the limited empanelment of mental health professionals constrains access for insured individuals.

Social stigma continues to be a pervasive barrier. Nearly half of the surveyed individuals fear discrimination if their mental health needs are revealed. This stigma leads to underreporting and delays in seeking care, further deepening the treatment gap.

Government initiatives like the National Mental Health Programme (NMHP) and Tele-MANAS are promising steps but require integration with insurance mechanisms to be effective. Seamless coordination between public services and insurance schemes is crucial.

Way Forward:

There is a pressing need to redesign insurance policies to comprehensively include outpatient mental health care, increase awareness through targeted campaigns, reduce stigma through public health messaging, streamline claims processing, and expand provider networks. Regulatory bodies like IRDAI must ensure compliance through audits and penalties, while employers should be incentivized to offer robust mental health coverage.

Conclusion:
Expanding mental health insurance is vital for a healthier, more inclusive, and productive society. Achieving this calls for a multi-stakeholder approach involving legal enforcement, policy reform, public education, and systemic coordination between government and private actors.