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Think Your Dog Disturbs Your Sleep? It May Be The Other Way Around : ScienceAlert (opens in a new tab)

sciencealert.com · 2026-10-17

Short answerEvidenceSource

Short answer

Mixed

Mixed.

One claim goes further than the study. 2 other points were not covered by the paper.

  • 3 supported
  • 1 overstated
  • 2 not covered

Checked against the study summary. The full text wasn't available, so some details couldn't be settled either way.

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Follow the evidence trail
1
2

NewsLink checks it

Mixed

One claim overstates the study. Three of six check out. Two claims the study doesn't address.

  • 3 supported
  • 1 overstated
  • 2 not covered
Open claim evidence
3
Then inspect each claim

Evidence layer

Claim by claim

Each claim gets a verdict. Expand it to see the evidence directly below.

6 claims in this story

Showing all 6 claimsChoose a verdict to focus the list.

Claim 1 of 6OverstatedA new study from anthropologists at the University of Toronto suggests that humans may be disturbing their dogs' sleep as much as the other way around.View evidenceHide evidence

Why this verdict

The abstract-level profile supports human–dog nighttime activity coupling and shows human activity preceded dog activity more often than the reverse among correlated dyads. However, the story's lead framing that humans may be 'disturbing their dogs' sleep' turns accelerometer activity correlations and lead–lag patterns into a sleep-disturbance/causal interpretation. The hedge helps, but the lead still outruns the abstract-supported evidence.

1

Study evidence

A majority of dyads (61%) showed significant correlation between human and dog nighttime activity states.61%

“Human and dog nighttime activities were found to be significantly correlated.”
Claim 2 of 6Not coveredThe researchers found that human and dog nighttime activities were linked, even when the dog was not in bed, with one individual's movement often followed by the other's within a few minutes.View evidenceHide evidence

Why this verdict

The abstract-level profile supports that human and dog nighttime activities were significantly correlated and that lagged correlations were assessed within five minutes. But the specific statement that this held 'even when the dog was not in bed' is not available in the supplied abstract-level profile.

1

Study evidence

A majority of dyads (61%) showed significant correlation between human and dog nighttime activity states.61%

“Human and dog nighttime activities were found to be significantly correlated.”
Claim 3 of 6Not coveredThe authors speculate that heightened stress during COVID-19 lockdown may have increased human nighttime activity, which then disturbed dogs and contributed to later dog activity.View evidenceHide evidence

Why this verdict

The supplied abstract-level profile supports human-before-dog lead–lag activity patterns but does not include the COVID-19 lockdown stress explanation or the quoted author speculation. That interpretation may be in the full paper, but it is not verifiable from the provided abstract-depth profile.

1

Study evidence

A majority of dyads (61%) showed significant correlation between human and dog nighttime activity states.61%

“Human and dog nighttime activities were found to be significantly correlated.”
Claim 4 of 6SupportedUsing survey data and motion trackers, the researchers analyzed nighttime activity in 25 participants in Canada, including 38 human-dog pairs.View evidenceHide evidence

As stated25 participants; 38 human-dog pairs

Why this verdict

The profile explicitly reports an observational at-home study of 25 Canadian participants totaling 38 human–dog pairs, using accelerometers and survey data.

1

Study evidence

None of the tested demographic/household variables (including co-sleeping/bedsharing, dog sleeping location, multiple dogs, and other demographics) significantly affected objectively measured human sleep or dog nighttime activity in linear mixed-effects models.

“we examined the nighttime activity of 25 Canadian participants, totaling 38 human-dog pairs using accelerometers and survey data.”
Claim 5 of 6SupportedAmong the 22 human-dog pairs whose activity patterns were linked, human activity preceded dog activity in 45 percent of cases, while dog activity came first in 18 percent.View evidenceHide evidence

As stated45 percent; 18 percent

Why this verdict

The profile supports the key lead–lag percentages: among correlated dyads, human activity preceded dog activity more often than dog activity preceded human activity, 45% versus 18%. The exact count of 22 pairs is not reported in the abstract-level profile, which instead states 61% of dyads showed correlation, but the central quantitative comparison is supported.

1

Study evidence

A majority of dyads (61%) showed significant correlation between human and dog nighttime activity states.61%

“Human and dog nighttime activities were found to be significantly correlated.”
Claim 6 of 6SupportedThe study found no association between bed-sharing and sleep duration or efficiency.View evidenceHide evidence

Why this verdict

The profile states that co-sleeping/bedsharing had no observed effect on human sleep duration or efficiency. The story frames this as no association, which is appropriately non-causal for the observational design.

1

Study evidence

None of the tested demographic/household variables (including co-sleeping/bedsharing, dog sleeping location, multiple dogs, and other demographics) significantly affected objectively measured human sleep or dog nighttime activity in linear mixed-effects models.

“we examined the nighttime activity of 25 Canadian participants, totaling 38 human-dog pairs using accelerometers and survey data.”
Then look for missing context

Context layer

What the story left out

Important study details the story did not include.

  • The abstract reports that 61% of dyads showed significant correlation in activity states and that 36% showed synchronized activity within the same 1-minute period.

    The story covers the general coupling and lead–lag directionality but does not report the 61% correlated-dyad figure or the 36% same-minute synchronization result.

    From time-series lag correlation

  • The observational design limits causal inference about whether one partner's movement caused or disturbed the other's sleep or activity.

    Although several story claims are hedged, the caveats do not explicitly acknowledge the causal-inference limitation. This matters because the lead uses disturbance language that can imply causation.

    From Observational at-home accelerometry study (paired human–dog); time-series lag correlation

  • At abstract depth, detailed model outputs, effect estimates, confidence intervals, covariate specifications, and details of the lag-correlation methods are unavailable.

    The story notes that some findings were statistically weak, but it does not reflect the broader abstract-level limitation that key statistical details and precision estimates are not available.

    From Observational at-home accelerometry study (paired human–dog); cross-sectional; time-series lag correlation

  • Accelerometer-derived activity and sleep measures may not capture all sleep disturbances or contextual behaviors, and the abstract does not detail validation against polysomnography.

    The story says motion trackers were used but does not mention limitations of accelerometry for inferring sleep quality, awakenings, or behavioral context.

    From Observational at-home accelerometry study (paired human–dog); time-series lag correlation

5 things the story did carry across
  • The study was an observational at-home accelerometry plus survey study of 25 Canadian participants and 38 human–dog pairs.
  • Co-sleeping/bedsharing had no observed effect on objective human sleep duration or sleep efficiency, nor on dog nighttime activity.
  • Human and dog nighttime activity states were significantly correlated within dyads, and lagged analysis found human activity preceded dog activity more often than the reverse among correlated dyads.
  • Having multiple dogs was associated with poorer self-reported sleep quality (p = 0.042), but this was not mirrored in objective sleep measures.
  • The study's modest sample size limits precision, power, and generalizability.
Then read the study layer

Study layer

Study at a glance

Scan the study first. Expand only the parts you want to inspect.

Pieces of work

3

Evidence read

study summary

Lead result

human in vivo

1Lead resulthuman in vivoQuantify how demographic/household factors (e.g., co-sleeping/bedsharing, dog sleeping location, multiple dogs) relate to objectively measured human sleep and dog nighttime activity.Observational at-home accelerometry study (paired human–dog)Expand

In plain English

Observational at-home study of 25 participants (38 human–dog pairs) using paired human and dog accelerometry plus survey data to test whether household/demographic factors (co-sleeping/bedsharing, dog sleeping location, multiple dogs, other demographics) predict objectively measured human sleep and dog nighttime activity via linear mixed-effects models.

Key findings

  • None of the tested demographic/household variables (including co-sleeping/bedsharing, dog sleeping location, multiple dogs, and other demographics) significantly affected objectively measured human sleep or dog nighttime activity in linear mixed-effects models.
  • Co-sleeping (bedsharing) had no observed effect on human sleep duration or efficiency, nor on dog nighttime activity.
“we examined the nighttime activity of 25 Canadian participants, totaling 38 human-dog pairs using accelerometers and survey data.”
What this piece can’t prove
  • Observational, at-home design limits causal inference about directionality of effects between household factors and sleep/activity.
  • Objective measurement relied on accelerometry; abstract does not detail device placement, scoring algorithms, or validation against polysomnography for sleep outcomes.

2 further details could not be confirmed from the summary.

2human in vivoAssess whether demographic variables predict self-reported (subjective) human sleep quality and whether this diverges from objective measures.cross-sectionalExpand

In plain English

Cross-sectional analysis using self-reported sleep quality from questionnaires and a generalized linear model to test demographic and household dog predictors. In this sample (25 human participants comprising 38 human-dog pairs) having multiple dogs was associated with poorer subjective sleep (p = 0.042) while dog sleeping location did not affect perceived sleep quality; this subjective effect was not mirrored in objective accelerometry-derived sleep measures.

Key findings

  • Having multiple dogs was associated with poorer self-reported (subjective) sleep quality.p = 0.042
  • Dog sleeping location (e.g., bedsharing) did not affect perceived human sleep quality.
“a generalized linear model to assess the effects of demographic variables on self-reported sleep quality.”
What this piece can’t prove
  • Cross-sectional observational design as reported in abstract.
  • Modest sample size (25 participants; 38 human-dog pairs) limits precision and generalizability.
  • Abstract does not report full GLM specification, covariates, or effect size estimates beyond p-values.
3human in vivoCharacterize the coupling/directionality of human–dog nighttime activity via contemporaneous and lagged (time-series) correlations within dyads.time-series lag correlationExpand

In plain English

Using simultaneous accelerometer records from 38 human–dog dyads, the study computed contemporaneous correlations and performed a time-series (lagged) correlation analysis within five-minute windows to classify dyads by lead–lag relationships and short-window synchronization. The authors report that 61% of dyads showed significant correlation in nighttime activity states; among correlated dyads human activity preceded dog activity more often (45%) than the reverse (18%), and 36% of dyads exhibited activity synchronized within the same 1-minute period.

Key findings

  • A majority of dyads (61%) showed significant correlation between human and dog nighttime activity states.61%
  • Among dyads classified as correlated, human activity preceded dog activity more often (45%) than dog activity preceded human activity (18%).45% vs 18%
“Human and dog nighttime activities were found to be significantly correlated.”
What this piece can’t prove
  • Relatively small sample size (38 dyads) limits precision and generalizability.
  • Reliance on accelerometer-derived activity states may not distinguish types of movements or contextual behaviors that drive lead–lag relations.
  • Unclear denominators and confidence intervals for reported percentages at abstract depth.

1 further detail could not be confirmed from the summary.

Finally, the search trail

Method layer

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Papers considered

The selected paper, plus nearby candidates.

Europe PMC, Crossref, PubMed · 15 candidate papers

Candidate

An Exploratory Study of Human–Dog Co-sleeping Using Actigraphy: Do Dogs Disrupt Their Owner’s Sleep?

Anthrozoös · 2018 · Crossref

Source (opens in a new tab)

And 9 more candidates considered.