It is commonly claimed that sleep duration has declined in recent years – over a period coinciding with a marked increase in personal electronics and communications use. The aim of this study was to assess change in sleep duration among Canadians from 1998 to 2010, and examine any associations with non‐work‐related screen time. The analysis uses population‐representative data from Statistics Canada's General Social Survey cycles of 1998 and 2010; the respective samples numbered 10 749 and 15 390 individuals. Response rates were 80% in 1998 and 55% in 2010. Respondents were aged 15 years and older, residing in private households in the 10 Canadian provinces. The General Social Survey is administered by computer‐assisted telephone interviewing. Data on sleep duration (excluding naps outside essential sleep time) and recreational screen time were obtained using a 24‐h time‐use diary. Survey weights were applied to adjust for non‐response and non‐landline households. Frequencies (respondent characteristics) and averages (time‐use variables) were estimated by age group and sex. Sleep duration was examined by weighted quartile of screen time. Confidence intervals (95%) were calculated around estimates. Average sleep duration increased from 8.1 h in 1998 to 8.3 h in 2010. Average screen time increased from 140 min in 1998 to 154 min in 2010. Sleep duration and screen time were positively related in both years. The percentage of people averaging less than 6 h sleep decreased from 9.6% in 1998 to 8.6% in 2010. Between 1998 and 2010, increases in screen time did not occur at the expense of sleep duration.

Introduction Reflecting a widespread perception that modern society imposes a ‘time crunch’, a common assertion is that substantial proportions of people today do not get enough sleep (Centers for Disease Control, 2015; Park, 2009; Robinson and Michelson, 2010). With few exceptions (Ford et al., 2015; Keyes et al., 2015), however, most of the research reported suggests that sleep duration has stabilized or increased slightly over the past few decades (Bin et al., 2012; Bonke, 2015; Hoyos et al., 2015; Robinson and Michelson, 2010; Statistics Finland, 2012; Youngstedt et al., 2016). While methodological inconsistencies may account for some of the contradictory findings, the evidence to support the assumption of a sleep deficiency ‘epidemic’ is thus rather scarce. Although the true prevalence of insufficient sleep may be under debate, links to a variety of health problems are reasonably well established. Unusual sleep duration (both short and long) can increase the risk of hypertension and metabolic syndrome; diabetes; cardiovascular disease; stroke; and all‐cause mortality (Cappuccio et al., 2010, 2011; Mullington et al., 2009; Sabanayagam and Shankar, 2010; da Silva et al., 2016). As the health consequences of sleep abnormalities are becoming better understood, other research has explored factors that might underlie disturbances in sleep patterns or duration. A quickly growing area of inquiry focuses on possible links between use of electronic communications devices and sleep. Studies of ‘blue‐screen’ exposure – from television, personal computers and other screen‐equipped devices – suggest an association with shorter sleep; however, most evidence to date is based on observations among children and adolescents (Cain and Gradisar, 2010; Falbe et al., 2015; Figueiro and Overington, 2015; Hysing et al., 2015; Li et al., 2007; Owens, 2014; Owens et al., 1999; Shochat, 2012; Van den Bulck, 2004). In adults in the USA, long‐duration sleep has been positively linked to time spent viewing television (Basner et al., 2007). Although this finding contrasts with observations in adolescents, it is consistent with data collected from the 1970s to the late 1990s in seven western countries. In five of the countries, increases were observed in both television‐viewing time and sleep duration (Gimenez‐Nadal and Sevilla‐Sanz, 2011). Exceptions to these trends occurred in Norway, where television‐viewing time increased but sleep duration decreased; and among women in the UK, where television‐viewing time decreased but sleep increased. Research in adults on the possible association between sleep duration and the use of screen‐equipped devices other than television is scarce – partly because of the recency of their development. In a study in which screen time included television and total computer use, no association was observed with self‐reported sleep duration (Vallance et al., 2015). While it is clear that pursuits such as texting, online gaming and various forms of video entertainment occupy a greater portion of people's waking hours, the question of how this increase might relate to sleep duration has not yet been fully examined. This study focuses on the question of whether or not sleep time in Canadians has changed over the period of years coinciding with the growth in computing and electronic personal communications technologies. Sleep duration is compared at two points in time: in 1998, just prior to the introduction of social media and the upsurge in other electronic devices usage; and in 2010, as the use of such technologies (e.g. Facebook, Twitter), along with interactive gaming and online entertainment, was becoming widespread. Patterns of association between sleep duration and recreational screen time are investigated; a sub‐analysis compares the percentage of people reporting sleep duration of less than 6 h in 1998 and 2010.

Materials and methods The analysis uses population‐based data from two cycles of Statistics Canada's General Social Survey (GSS): Cycle 12, administered from February 1998 to January 1999; and Cycle 24, administered from January to December 2010. The GSS is cross‐sectional, and one of Statistics Canada's routinely administered, population‐representative national surveys. The GSS collects data from persons aged 15 years and over living in private households in Canada, excluding residents of the Northwest Territories, Yukon and Nunavut, and full‐time residents of institutions. Potential respondents to the GSS surveys were informed that participation was voluntary, and that their privacy and the confidentiality of information they provided would be protected. Descriptions of the methodology of the GSS have been previously published (Statistics Canada, 2007). The GSS samples were drawn using a random‐digit‐dialing technique; individual respondents were selected at random from a list of household members provided by the person answering the telephone. Respondents were interviewed in English or French over land‐based telephones. Interviews were conducted using computer‐assisted telephone interviewing techniques by trained Statistics Canada interviewers. Households without land‐based telephones were not included in the GSS samples. In 1998, less than 2% of the population lived in a household without a land‐based telephone; by 2010 the percentage had grown to an estimated 13% (Statistics Canada, 2007, 2011). To adjust for persons without landlines and for survey non‐response, survey weights were produced by Statistics Canada for both cycles using socio‐demographic factors. The weighted data were representative of the household population aged 15 years or older residing in the Canadian provinces in each of the survey years. The GSS cycles of 1998 and 2010 collected information on time use: a 24‐h diary was constructed for each respondent by asking for the start‐ and stop‐times of all activities of at least 5 min duration undertaken in the previous day. Time‐use variables examined for this study included sleep duration and non‐work‐related screen time; socio‐demographic characteristics were also included. The response rate for Cycle 12 was 80%; usable time‐use data were provided by 10 749 respondents. For Cycle 24 the response rate was 55.2%; 15 390 respondents provided usable data. A diary was deemed acceptable when activities for at least 20 out of 24 h of activities were reported. Each day of the week was sampled, and calculations from time‐use data were averaged over a 7‐day period (Statistics Canada, 2007, 2011). Sleep duration Data from the 24‐h time‐use diary constructed for each respondent were used to estimate sleep duration. Sleep duration was defined as time spent sleeping at night (or time spent in ‘essential sleep’ for those reporting sleeping at other times of the day). Although respondents were instructed to report activities as specifically as possible, it is possible that time reported as ‘sleeping’ could have included total time in bed – including time awake prior to the onset of sleep, during the night (or essential sleep period) and before rising from bed. Naps taken outside the essential sleep period were not included. Although the time‐use diary method cannot measure sleep duration with the same accuracy that objective measures do, the same means of measurement was used in both cycles. For the purposes of this study, focusing on change in sleep duration over two points in time, the validity of the measure of sleep duration is less of a concern than is the consistency of the measure. Age‐sex‐specific means were calculated for each cycle. Sleep duration of less than 6 h was defined as ‘short sleep time’, consistent with previous research in this area (Bin et al., 2013; Knutson et al., 2010). Screen time Screen time was measured as the total amount of time spent watching television, playing video games, or using the computer or other screen‐equipped device for any recreational purpose during leisure time. Work‐related screen time was not included. While it would have been preferable to examine the separate components of screen time individually, non‐television screen time was relatively brief; in 1998, the population 15 years or older averaged 2 h and 12 min per day watching television, and 8 min on other screen time; in 2010 the respective averages were 2 h and 6 min, and 29 min (Statistics Canada, 2011). Age‐sex‐specific means and quartiles were calculated for each cycle. Analysis All calculations were performed using weighted data adjusted for non‐landline ownership and survey non‐response. Weighted frequencies (respondent characteristics) and averages (time‐use variables) were estimated by age group (15–34, 35–64 and 65 + years) and sex. While it would have been preferable to examine the data by narrower age groups (in particular, to separate adolescents from adults), preliminary analysis indicated that many of the estimates based on smaller age ranges were statistically unreliable due to insufficient power. Sleep duration was examined by weighted quartile of screen time; screen‐time quartiles were determined by dividing the weighted distribution of screen time for each respective survey population (Cycle 12 and Cycle 24 of the GSS). Confidence intervals (95%) were calculated around estimates.

Results As shown in Table 1, the socio‐demographic characteristics of the weighted survey population in 2010 were similar in most respects to those in 1998. Reflecting changes over this period that occurred in the Canadian population, the age distribution shifted upward somewhat but not significantly, while the level of education rose. By 2010, a significantly higher percentage had completed a university degree (26%) than in 1998 (17%; Statistics Canada, 2015a). Table 1. Percentage distribution of selected characteristics of weighted sample, population aged 15 years or older, GSS cycles 12 (1998) and 24 (2010) Characteristic GSS cycle 12 (1998) GSS cycle 24 (2010) Sex Male 49.2 49.3 Female 50.8 50.6 Age distribution 15–34 years 35.8 32.8 35–64 years 49.5 51.1 65+ years 14.7 16.1 Education completed Less than high school diploma 25.9 16.4a High school diploma or post‐secondary 50.5 55.8 University degree 16.9 25.7a Marital status Married/living as a couple 61.3 62.4 Unmarried 38.5 37.5 Figure 1 shows that time spent sleeping increased significantly, from an average of 8.1 h in 1998 to 8.3 h in 2010. Although people in all age groups reported sleeping longer, the increases in people aged 15–34 years were the most pronounced: for males, from 8.1 h in 1998 to 8.5 h in 2010 (a difference of 27 min); and for females, from 8.3 to 8.6 h (22 min), as shown in Table 2. Only for the age group 15–34 years did the increases in sleep duration attain statistical significance. Figure 1 Open in figure viewer PowerPoint Bar graph representing sleep duration in hours per night (vertical axis), by age group (horizontal axis) and year (red bar: 1998; blue bar: 2010). Table 2. Average duration of sleep, by sex and age group, population aged 15 years or older, Canada, 1998 and 2010 1998 2010 h (95% CI) min (95% CI) h (95% CI) min (95% CI) Both sexes Total, 15+ years 8.1 (8.0–8.1) 484.3 (481.8–486.8) 8.3 (8.2–8.3) 496.0 (493.7–498.2) 15–34 years 8.2 (8.1–8.3) 491.8 (486.7–496.8) 8.6 (8.5–8.7) 515.3 (510.1–520.5) 35–64 years 7.9 (7.8–7.9) 472.9 (469.8–476.0) 8.0 (7.9–8.0) 478.3 (475.3–481.2) 65+ years 8.4 (8.3–8.5) 504.8 (499.7–509.8) 8.5 (8.5–8.6) 512.8 (508.6–517.1) Males Total, 15+ years 8.0 (7.9–8.0) 477.8 (474.0–481.6) 8.2 (8.1–8.2) 490.4 (486.9–494.0) 15–34 years 8.1 (8.0–8.2) 487.1 (479.7–494.5) 8.5 (8.4–8.7) 512.1 (503.7–520.4) 35–64 years 7.8 (7.7–7.8) 465.3 (460.7–470.0) 7.9 (7.8–7.9) 471.3 (467.0–475.6) 65+ years 8.3 (8.2–8.4) 499.6 (492.3–506.8) 8.5 (8.3–8.6) 507.6 (500.4–514.8) Females Total, 15+ years 8.2 (8.1–8.2) 490.7 (487.4–494.0) 8.4 (8.3–8.4) 501.4 (498.6–504.3) 15–34 years 8.3 (8.2–8.4) 496.5 (490.0–503.1) 8.6 (8.5–8.8) 518.6 (512.2–525.0) 35–64 years 8.0 (7.9–8.1) 480.4 (475.7–485.0) 8.1 (8.0–8.2) 485.2 (481.3–489.0) 65+ years 8.5 (8.4–8.6) 508.8 (502.2–515.3) 8.6 (8.5–8.7) 517.2 (512.4–521.9) Between 1998 and 2010, recreational screen time grew from 140 to 154 min (Table 3); the increase was also reflected in a shift upward in the weighted distribution (Table 4). Males aged 15–34 years averaged the greatest increase – from 140 to 165 min per day. Increases in screen time were statistically significant in males in the age groups 15–34 years and 35–64 years, and in females aged 35–64 years. Table 3. Average duration of recreational screen time per day, by sex and age group, population aged 15 years or older, 1998 and 2010 1998 2010 Min (95% CI) Both sexes Total, 15+ years 139.9 (136.9–142.8) 154.3 (151.3–157.3) 15–34 years 123.8 (118.5–129.1) 140.6 (134.8–146.5) 35–64 years 126.8 (122.7–130.9) 140.3 (136.7–143.9) 65+ years 222.8 (214.3–231.4) 226.2 (219.1–233.2) Males Total, 15+ years 154.0 (149.2–158.7) 173.9 (169.1–178.8) 15–34 years 139.5 (130.9–148.1) 164.6 (155.3–173.8) 35–64 years 141.3 (135.4–147.3) 157.3 (151.6–162.9) 65+ years 243.7 (229.4–258.0) 253.2 (240.9–265.4) Females Total, 15+ years 126.2 (122.6–129.9) 135.1 (131.4–138.8) 15–34 years 107.8 (101.8–113.7) 116.0 (109.1–122.9) 35–64 years 112.3 (107.0–117.7) 123.5 (119.1–127.9) 65+ years 206.9 (196.8–216.9) 203.9 (194.9–212.8) Table 4. Range of time (min) in each quartile of daily recreational screen time, population aged 15 years or older, 1998 and 2010 1998 2010 Screen‐time quartile min min 1st <29.4 <29.9 2nd 29.4 to <107.9 29.9 to <119.3 3rd 107.9 to <208.5 119.3 to <224.3 4th 208.5+ 224.3+ Figures 2 and 3 indicate that in both 1998 and 2010, screen time and sleep duration were positively related, i.e. with each increasing quartile of screen time, average overall sleep duration also increased. Patterns varied according to age group and sex. Table 5 shows that in males and females aged 15–34 years, a strong positive association between screen time and sleep duration was observed in both cycles; in those aged 35–64 years the pattern was modest but still positive, while in those aged 65 years or older, no association was discernible. Figure 2 Open in figure viewer PowerPoint Line graph showing average hours of sleep duration (vertical axis) by quartile of screen time (horizontal axis) for total population (blue line), males (red line) and females (green line), aged 15+ in 1998. Figure 3 Open in figure viewer PowerPoint Line graph showing average hours of sleep duration (vertical axis) by quartile of screen time (horizontal axis) for total population (blue line), males (red line) and females (green line), aged 15+ in 2010. Table 5. Average duration of sleep, by quartile of recreational screen time, sex and age group, population aged 15 years or older, 1998 and 2010 1998 2010 1998 2010 Average number of h (95% CI) Screen‐time quartile Males 15+ years Females 15+ years 1st 7.5 (7.3–7.6) 7.7 (7.5–7.9) 7.8 (7.7–7.9) 8.1 (8.0–8.2) 2nd 7.9 (7.8–8.0) 8.0 (7.9–8.1) 8.1 (8.0–8.2) 8.2 (8.1–8.3) 3rd 8.0 (7.9–8.2) 8.4 (8.3–8.5) 8.3 (8.2–8.4) 8.5 (8.4–8.6) 4th 8.3 (8.2–8.4) 8.4 (8.3–8.6) 8.5 (8.4–8.7) 8.6 (8.5–8.7) Screen‐time quartile Males 15–34 years Females 15–34 years 1st 7.3 (7.0–7.6) 7.9 (7.6–8.2) 7.8 (7.6–8.0) 8.4 (8.1–8.6) 2nd 8.0 (7.8–8.3) 8.4 (8.2–8.6) 8.2 (8.0–8.4) 8.4 (8.3–8.6) 3rd 8.3 (8.0–8.5) 8.8 (8.6–9.0) 8.5 (8.3–8.7) 8.8 (8.5–9.0) 4th 8.8 (8.6–9.0) 8.9 (8.6–9.2) 8.9 (8.6–9.1) 9.4 (9.1–9.7) Screen‐time quartile Males 35–64 years Females 35–64 years 1st 7.5 (7.3–7.7) 7.5 (7.3–7.7) 7.7 (7.6–7.8) 7.8 (7.6–8.0) 2nd 7.7 (7.6–7.9) 7.7 (7.5–7.8) 8.0 (7.9–8.2) 8.0 (7.9–8.1) 3rd 7.8 (7.6–8.0) 8.0 (7.9–8.2) 8.1 (8.0–8.3) 8.3 (8.2–8.4) 4th 7.9 (7.8–8.1) 8.2 (8.0–8.3) 8.3 (8.1–8.5) 8.2 (8.1–8.4) Screen‐time quartile Males 65 + years Females 65 + years 1st 8.5 (8.0–9.1) 8.4 (8.1–8.8) 8.5 (8.2–8.9) 8.7 (8.4–8.9) 2nd 8.6 (8.2–8.9) 8.7 (8.4–9.0) 8.5 (8.2–8.8) 8.5 (8.3–8.6) 3rd 8.3 (8.1–8.6) 8.5 (8.2–8.7) 8.4 (8.2–8.6) 8.8 (8.6–8.9) 4th 8.2 (8.1–8.4) 8.4 (8.2–8.6) 8.5 (8.3–8.7) 8.6 (8.4–8.7) Table 6 shows that the percentage of people reporting average sleep duration of less than 6 h per night declined modestly between 1998 and 2010, from 9.6 to 8.6%. In males aged 15–34 years, the decrease was more pronounced – from 12.4% in 1998 to 9.4% in 2010. Table 6. Percentage of people averaging less than 6 h sleep per night, by sex and age group, population aged 15 years or older, 1998 and 2010 1998 2010 Percentage (95% CI) Total, both sexes, 15 + years 9.6 (8.9–10.4) 8.6 (8.0–9.1) Males Total, 15+ years 10.9 (9.9–12.0) 9.2 (8.3–10.1) 15–34 years 12.4 (10.6–14.5) 9.4 (7.8–11.3) 35–64 years 11.3 (9.9–12.7) 10.3 (9.1–11.6) 65+ years 5.0a (3.5–7.1) 4.9 (3.7–6.4) Females Total, 15+ years 8.4 (7.6–9.3) 8.0 (7.3–8.8) 15–34 years 9.5 (8.0–11.3) 8.0 (6.7–9.5) 35–64 years 8.6 (7.4–10.0) 9.1 (8.1–10.2) 65+ years 5.5 (4.1–7.4) 4.8 (3.8–6.0)

Discussion This study indicates that between 1998 and 2010 – a period of rapid advances in computer technology, video gaming and electronic social media – average sleep duration increased by 12 min in Canadians aged 15 years and older; the increase was statistically significant. In males and females aged 15–34 years, sleep duration rose significantly in each sex – by 23.5 and 25 min, respectively. Increases were also observed in screen time, which rose significantly in males under 65 years old and in females aged 35–64 years. In younger people of both sexes, increases in sleep duration corresponded with rises in screen time – providing no evidence that growth of screen time occurred at the expense of sleep duration. The overall percentage of people experiencing short‐duration sleep changed little, but the data are suggestive of a decrease among younger males – the group reporting the greatest amount of screen time. Much, but not all, research on sleep duration trends in adults corroborates the GSS findings. In a review of data from 15 countries, sleep duration was reported to have increased in seven, decreased in six, and in two the results were mixed (Bin et al., 2012). Other data suggest that sleep duration has stabilized or increased slightly over the past few decades, partially corroborating the GSS results (Bonke, 2015; Robinson and Michelson, 2010; Statistics Finland, 2012; Youngstedt et al., 2016). Recent research focusing on sleep patterns in three preindustrial societies is also consistent with the GSS findings. In the absence of electricity or any electronic devices in the populations studied, sleep periods – defined as the time between sleep onset and offset, including any time awake – averaged from 6.9 to 8.5 h, comparable to the 2010 GSS estimate of 8.3 h (Yetish et al., 2015). As has been previously suggested, differences in data collection methodologies may account for differences in the direction of sleep duration trends (Hoyos et al., 2015). In a review of sleep duration trend research in the USA from the mid‐1980s to the late 2000s, both increases and decreases were reported; studies showing increasing sleep duration were based on time‐use surveys similar to the GSS, while decreases were based on data from the National Health Information Survey (NHIS; Ford et al., 2015; Hoyos et al., 2015). The time‐use diary elicits information on all activities over a 24‐h period, and does not focus the respondent's attention on sleep in particular. In contrast, the NHIS asks explicitly, ‘On average, how many hours of sleep do you get in a 24‐h period?’ (Ford et al., 2015). With its specific focus on sleep, this approach may be more susceptible to reporting bias. Modal responses to this question have been reported as 7 h for weeknights and 8 h for weekends, suggesting that people give an answer reflecting how long they assume is normal or healthful, rather than a true measure of their own sleep duration (Lauderdale et al., 2008). For any study that focuses on change over time, an important consideration is the possible influence of secular change over the period of study. For example, a rise in the social desirability of appearing too busy or overworked to take time for sleep could prompt respondents to give a lower estimate of sleep time at time two than at time one, resulting in an artefactual decline in sleep duration. Again, the single, focused‐question approach to eliciting sleep duration is likely more susceptible to such systematic bias than is the time‐use diary (Bin et al., 2013; Hoyos et al., 2015). National Health Information Survey data also showed significant increases in the percentage of people who reported less than 6 h sleep per night, again contrasting with the GSS findings (Ford et al., 2015). The GSS results on short‐sleepers correspond well with data for the USA based on 24‐h diaries, which showed that the percentage of people sleeping less than 6 h per night declined from 11.7% in 1985 to 9.2% in 2007 (Bin et al., 2013). Note that the magnitude of the 2007 estimate of short‐sleepers (9.2%) based on time‐use data is much closer to that from the GSS in 2010 (9.4%) than that from the NHIS in 2012 (29.2%; Bin et al., 2013; Ford et al., 2015). The GSS data do not explain the apparent correspondence between increased sleep duration and screen time in older adolescents and young adults, a finding that contrasts notably with research suggesting that exposure of children and adolescents to electronic media interferes with, or displaces sleep (Falbe et al., 2015; Hysing et al., 2015; Li et al., 2007; Owens, 2014; Owens et al., 1999; Shochat, 2012; Van den Bulck, 2004). Sample size restrictions of the current study precluded limiting the analysis to adolescents. Although the positive association between screen time and sleep duration observed for the age group 15–34 years is compelling, the pattern may mask different results for adolescents, as persons aged 15–19 years comprised only about one‐quarter of the age group. Focused monitoring of this subgroup is an area worthy of further investigation. A few limitations of the study should be considered. First, the data are cross‐sectional, and thus causality (e.g. between screen time and sleep duration) cannot be inferred. Notwithstanding the advantage of time‐use data over information based on a single, focused question, any self‐report is an imprecise means of measuring actual duration of activity. The GSS data on sleep have not been validated by objective measures (such as actigraphy or polysomnography), and reported sleep duration may reflect time in bed but not actually asleep. Time in bed may exceed sleep duration by more than 1 h, on average (Leng et al., 2014). It is also possible that time in bed could include screen time – when devices are used in bed. In these cases, ‘sleep’ duration would be over‐reported, and screen time would be under‐reported. On the other hand, the GSS underestimates total sleep time by not including naps – this might disproportionately affect the age group 65 years and older. The extent to which the observed changes over time in sleep duration and screen time might have been affected by such reporting error is unknown. Furthermore, sleep duration is but one indicator of sleep, and does not reflect depth or quality of sleep. Statistical power considerations necessitated the establishment of subpopulations numerous enough to support reliable estimates. As a result, age groups were broadly defined, which likely had the greatest consequences for the age group 15–34 years. This group comprises both adolescents and adults, and is thus inevitably heterogeneous in terms of the behaviours of interest (sleep duration, screen use) and perhaps also the pattern of association between them. Therefore, the estimates observed for the whole age group may to some extent misrepresent the situation for adolescents alone. Statistical power limitations likely also account for the finding that increases in sleep duration were statistically significant only in the age group 15–34 years. Although the response rate of the GSS in 2010 (55%) compares favourably with that of the Behavioral Risk Factor State Survey in the USA, which fell from about 45% in 2002 to just under 40% by 2010 (National Research Council, 2013), it was nonetheless somewhat lower than that for national surveys conducted by Statistics Canada in previous years. Falling response rates have been widely observed in telephone‐based population surveys, reflecting the availability of caller display features, the increase in cell phone‐only households and increasing resistance to survey participation (Bladon, 2010; National Research Council, 2013; Pew Research Center, 2012; Statistics Canada, 2015b). A disadvantage to telephone interviewing is that households not covered in the sampling frame are concentrated in certain population groups. Young, single, urban Canadians are most likely to live in households without a landline, while households without any telephone are often concentrated in groups with lower income and education levels. Although not all differences between respondents and non‐respondents can be taken into account when producing the survey weights, post‐stratification weighting of the data can compensate to a great extent for deficits in coverage and response rate and thus mitigate non‐response bias (Statistics Canada, 2015b). Strengths of the study include its external validity; observations are derived from measures in large, population‐representative survey samples. The comparability of the estimates from the two survey cycles is maximized by the nearly identical methodology employed. As mentioned above, the time‐use‐diary approach used by the GSS collects information on all activities around the clock and not on sleep alone. The advantage of this approach is that it likely results in a higher degree of data validity than does the single, focused question, which may tend to exaggerate societal‐ or age‐group‐driven biases regarding sleep. Finally, the GSS survey methodology entails data collection over all 7 days of the week and 12 months of the year, and thus mitigates the possibility of bias due to day of week or season – factors shown to be associated with sleep duration (Statistics Finland, 2012). In conclusion, this study provides no evidence of a decline in sleep duration in Canadians aged 15 years and older over the 12‐year period, 1998–2010. Rather, the data show an increase in average sleep time, along with a decline in the percentage of people sleeping less than 6 h per night. The reasons underlying the positive association between screen time and sleep duration remain to be further explored.

Acknowledgement The author thanks Kathryn Wilkins for help with preparation of the manuscript.

Author Contributions Judith Leech designed the study, acquired and analysed the data, and wrote the paper.

Conflict of interest The author declares no conflict of interest.