Categories of harm · Chapter 9 / 15

Platform-driven screen addiction and cognitive effects

Canadian and international data indicate adolescents spend nearly five hours per day on social media. A JAMA Pediatrics systematic review of 58 studies1 found screen media use inversely associated with academic performance. Canadian longitudinal evidence2 confirms that higher screen exposure in early childhood predicts lower developmental scores at ages 3 and 5.

Human capital and educational disruption

Meta-analytic evidence consistently documents an inverse relationship between screen media use and academic performance: pooled effect sizes of approximately −0.19 for television viewing and −0.15 for video game playing on academic performance among adolescents1. Hanushek, Schwerdt, Wiederhold, and Woessmann (2015)3 link cognitive skill levels to lifetime earnings using PIAAC data across 23 OECD countries, finding an average return of approximately 18 percent higher hourly wages per standard deviation in numeracy skills. Returns vary across countries — from roughly 12 percent in high-wage-compression Nordic economies to over 25 percent in higher-dispersion markets — reflecting differences in wage-setting institutions rather than the underlying human capital relationship.

This OECD-wide average is consistent with Canada-specific evidence. Green and Riddell (2007)4 used Statistics Canada's IALSS 2003 dataset of over 22,000 native-born Canadians, finding that a 25-point increase in average literacy score — approximately half a standard deviation — was associated with earnings gains equivalent to one additional year of schooling, implying an approximate earnings premium of 13 to 15 percent per full standard deviation. Canada's return to cognitive skills thus sits in the mid-range of the international distribution. The calculations below use the Green and Riddell Canada-specific range as the primary calibration, producing a conservative estimate relative to the Hanushek et al. (2015) OECD average.

Applying the 0.1–0.2 SD effect size to the approximately 330,000 Canadians entering the labour market annually,5 at median secondary completer earnings of about $50,000, a Canadian wage-return coefficient of 13-15 percent per SD, and discounting the earnings stream at the Treasury Board of Canada Secretariat's standard 3.5 percent social discount rate — equivalent to a present value factor of 8.32 over a 10-year working-life horizon — yields lifetime productivity losses with a present value of approximately $1.8 billion to $4.1 billion per cohort.

Annualized as the equivalent recurring economic cost (the flow that, when discounted, generates this present value), this represents approximately $210 million to $490 million annually in productivity losses imposed on each new cohort of young Canadians entering the labour market. Across all affected cohorts currently in or entering the labour market, the total annual productivity drag is substantially larger.

Given the number of inferential steps involved in this calculation — from screen-time effect on academic outcomes to terminal labour-market effect — this estimate carries higher methodological uncertainty than other components of the analysis and should be read as an illustrative order of magnitude. The lower-bound estimate of $210 million annually is therefore an important guidepost.

Attention-related health costs

Applying a blended attribution factor of 16–24 percent associated with screen time exposure to CIHI's $2.5 billion combined health cost base6 for ADHD, sleep disorders, and obesity-related conditions in youth yields $400 million to $600 million annually.

References & Notes 6
  1. Adelantado-Renau, M., Moliner-Urdiales, D., Cavero-Redondo, I., Beltran-Valls, M.R., Martínez-Vizcaíno, V., and Álvarez-Bueno, C. (2019). “Association Between Screen Media Use and Academic Performance Among Children and Adolescents: A Systematic Review and Meta-analysis.” JAMA Pediatrics. Vol. 173, No. 11, pp. 1058–1067. doi:10.1001/jamapediatrics.2019.3176
    ↩ Back to reference 1↩ Back to reference 1 (2)
  2. Madigan, S. et al. (2019). "Association between screen time and children's performance on a developmental screening test". JAMA Pediatrics. Vol. 173, no. 3. P. 244–250.
    ↩ Back to reference 2
  3. Hanushek, E.A., Schwerdt, G., Wiederhold, S., and Woessmann, L. (2015). “Returns to skills around the world: Evidence from PIAAC.” European Economic Review. Vol. 73, pp. 103–130. doi:10.1016/j.euroecorev.2014.10.006
    ↩ Back to reference 3
  4. Green, D.A. and Riddell, W.C. (2007). "Literacy and the Labour Market: The Generation of Literacy and Its Impact on Earnings for Native-born Canadians". International Adult Literacy Survey, Statistics Canada Catalogue no. 89-552-M No. 18.
    ↩ Back to reference 4
  5. Derived from Statistics Canada Table 17-10-0005-01 and Table 14-10-0287-01 (Labour Force Survey). Domestic-born cohorts currently entering the labour market averaged approximately 340,000–380,000 annual births; applying a participation rate of approximately 63% for the 20–24 age group yields approximately 215,000–240,000 domestic-born entrants per year. Adding immigration-driven net additions yields a total of approximately 310,000–345,000. A central estimate of 330,000 is used. Median earnings from Table 98-10-0411-01, adjusted to 2026 dollars.
    ↩ Back to reference 5
  6. CIHI, NACRS/DAD 2023–24. $2.5 billion combined health cost base for ADHD, sleep disorders, and obesity-related conditions in youth aged 5–24. Based on Madigan et al. (2019) and other studies a higher attribution factor would be suggested, but we have chosen a lower bound in order to more conservatively estimate the costs.
    ↩ Back to reference 6