Insomnia ranks among the most prevalent complications across cancer trajectories, manifesting as difficulties with sleep onset, maintenance, duration, and early-morning awakening [1]. Breast cancer demonstrates the strongest insomnia association among all types of malignancies, with epidemiological prevalence ranging from 42% to 69% [2]. In affected patients, insomnia is associated with cascading effects that diminish quality of life, worsen psychiatric symptoms, impair cognition, and contribute to adverse prognoses through bidirectional physical and psychological decline [3].

Prolonged screen exposure has emerged as an important public health concern, with particularly notable effects on sleep. Investigations of presleep screen use demonstrate that short-wavelength blue light emission suppresses melatonin secretion while concomitantly reducing delta waves (slow-wave sleep) and enhancing alpha waves (wakefulness associated), thereby disrupting sleep architecture [4,5]. Growing evidence links cumulative daily screen exposure to insomnia and related sleep problems, with interactive media (eg, smartphones) exerting stronger sleep-disruptive effects than passive media (eg, television) [6]. Smartphones have become ubiquitous owing to their portability, versatility, and interactive features, exerting increasing influence on daily life; however, few studies have objectively assessed screen time using device-based measures [7,8].

Perceived stigma may also be relevant to screen-related sleep disturbance in patients with breast cancer. Stigma’s relationship to breast cancer may involve internalized shame, perceived social rejection, altered body image (eg, alopecia and mastectomy), and reluctance to disclose illness-related concerns [9,10]. These experiences may increase psychological distress and promote smartphone use for information seeking, emotional support, or social connection. Empirically, stigma has been associated with poorer sleep quality among patients with breast cancer [11]. Therefore, we examined perceived stigma as a potential vulnerability factor that may modify the association between screen time and insomnia.

This study aimed to explore the association between smartphone screen time and insomnia in patients with breast cancer while examining effect modification by perceived stigma. We hypothesized that greater total and presleep screen time would be associated with higher odds of insomnia and that these associations may be stronger among patients reporting higher stigma as stigma heightens vulnerability and reliance on interactive devices. Understanding the association between screen time and insomnia is essential for developing targeted behavioral interventions that mitigate sleep disruption and improve quality of life during breast cancer treatment.

This study aimed to examine the association between screen time and insomnia among patients with breast cancer and effect measure modification by perceived stigma. The analytic samples comprised 240 participants in the total daily screen time analysis and 644 participants in the presleep screen time analysis (Figure 1). In the total daily screen time sample, mean age was 51.82 (SD 10.62) years, median time since diagnosis was 14.00 (IQR 7.00-29.25) months, and 77.5% (186/240) had an insomnia diagnosis. In the presleep screen time sample, mean age was 53.46 (SD 10.76) years, median time since diagnosis was 15.00 (IQR 7.00-36.00) months, and 65.1% (419/644) had an insomnia diagnosis (Table 1).

The median total daily screen time was 334.00 (IQR 232.50-440.25) minutes, and median presleep screen time was 30.00 (IQR 10.00-120.00) minutes. Participants with high total daily screen time were younger (mean age 48.94, SD 9.94 vs 54.74, SD 10.54 years; P<.001) and more likely to be engaged in mental work (77/121, 63.6% vs 33/119, 27.7%; P<.001). Those with high presleep screen time had higher rates of insomnia diagnosis (247/319, 77.4% vs 172/325, 52.9%; P<.001; Table 1).

In fully adjusted models, each 30-minute increase in total daily screen time was associated with 14% increased odds of insomnia (adjusted OR [aOR] 1.14, 95% CI 1.05-1.23), whereas each 30-minute increase in presleep screen time was associated with 41% increased odds of insomnia (aOR 1.41, 95% CI 1.26-1.57). When analyzed as binary variables, high total daily screen time (more than the median [334 minutes per day]) was associated with 2.46-fold increased odds of insomnia (95% CI 1.16-5.21), and high presleep screen time (more than the median [30 minutes]) was associated with 3.22-fold increased odds of insomnia (95% CI 2.25-4.62) compared with low–screen time groups (Figure 2).

Perceived stigma did not significantly modify the association between screen time and insomnia. Among participants with low perceived stigma, high total daily screen time was not significantly associated with insomnia (aOR 1.69, 95% CI 0.67-4.30), whereas among those with high perceived stigma, high total daily screen time was associated with 4.5 times higher odds of insomnia (aOR 4.53, 95% CI 1.42-14.49). However, tests for effect modification were not statistically significant on either the multiplicative scale (ratio of ORs=2.68, 95% CI 0.65-11.11) or the additive scale (RERI=3.07, 95% CI –1.77 to 7.91; Table 2). For presleep screen time, associations with insomnia were strong in both the low-stigma (aOR 4.01, 95% CI 2.44-6.60) and high-stigma (aOR 2.59, 95% CI 1.54-4.37) groups, with no evidence of effect modification on either scale (RERI=0.14, 95% CI –2.52 to 2.80; ratio of ORs=0.65, 95% CI 0.32-1.32; Table 3). Although the stratum-specific estimates suggested a stronger association between high total daily screen time and insomnia among participants with high perceived stigma, the CIs were wide, and formal tests for interaction were not statistically significant. These findings should therefore be interpreted as exploratory.

Sensitivity analyses yielded generally consistent results with some attenuation. Using inverse probability of treatment weighting, associations remained significant for both high total daily screen time (aOR 2.61, 95% CI 1.19-5.72) and high presleep screen time (aOR 2.86, 95% CI 1.99-4.09; Figure S2 in Multimedia Appendix 1). With g-computation, the association for high total daily screen time was no longer statistically significant (aOR 2.17, 95% CI 0.99-4.79), whereas high presleep screen time maintained a strong association (aOR 3.00, 95% CI 2.16-4.17; Figure S3 in Multimedia Appendix 1). When missing presleep screen time data were handled using median or mode imputation, the association between high presleep screen time and insomnia remained robust (aOR 2.55, 95% CI 1.83-3.57; Figure S4 in Multimedia Appendix 1). Using ordinal logistic regression with ISI and PSQI scores as outcomes, high presleep screen time remained significantly associated with worse outcomes (ISI: aOR 1.87, 95% CI 1.35-2.59; PSQI: aOR 2.52, 95% CI 1.87-3.40), whereas high total daily screen time showed nonsignificant associations (ISI: aOR 1.28, 95% CI 0.70-2.34; PSQI: aOR 1.54, 95% CI 0.88-2.70; Figures S5 and S6 in Multimedia Appendix 1). Effect modification findings remained exploratory across sensitivity analyses (Tables S3-S11 in Multimedia Appendix 1). E-value analysis showed that an unmeasured confounder would need to be associated with both high presleep screen time and insomnia by a risk ratio of at least 2.99 (2.37 for the lower confidence limit) to fully account for the observed association. The corresponding e-values for high total daily screen time were more modest (2.51 for the point estimate; 1.37 for the lower confidence limit), in accordance with the less consistent findings for this exposure across sensitivity analyses.

This cross-sectional analysis found that both total daily and presleep screen time were associated with higher odds of insomnia among patients with breast cancer, with a stronger association for presleep screen time. However, evidence on total daily screen time was less consistent in sensitivity analyses and should be interpreted with considerable caution because of extensive missing objective screen time data and possible selection bias. Perceived stigma did not significantly modify either association.

Our findings align with literature associating digital media exposure with adverse sleep outcomes, including inadequate sleep duration, poor quality, daytime somnolence, and various types of insomnia problems, primarily documented in school-aged cohorts [7,17]. Although most previous studies have focused on adolescents and young adults, our results suggest that screen exposure may also be relevant to sleep health in patients with breast cancer, a population with a high burden of insomnia. Given the clinical burden of insomnia in oncology, screen-related sleep problems warrant further investigation in breast cancer supportive care.

Several mechanisms may explain the association between presleep screen exposure and insomnia. Evening exposure to light-emitting screens may delay circadian timing, suppress melatonin secretion, and increase cognitive or emotional arousal before bedtime [4,5,18]. In contrast, the role of perceived stigma is more speculative. Perceived stigma is clinically relevant to sleep health in patients with breast cancer and may reflect a vulnerability context for screen-related sleep disturbance [9-11,19]. However, the effect modification analyses did not provide statistically significant evidence that perceived stigma modified the associations between screen exposure and insomnia on either the multiplicative or additive scale. Therefore, the observed stratum-specific patterns should be interpreted as exploratory and hypothesis generating rather than confirmatory and require confirmation in larger longitudinal studies.

This study has several limitations. First, the cross-sectional design precluded determination of temporality, and reverse causation remains possible because patients with insomnia may use smartphones when they have difficulty falling asleep or during nocturnal awakenings. To mitigate this concern, we excluded participants with insomnia that began before breast cancer diagnosis and remained ongoing at enrollment; however, reverse causation remains possible. Second, exposure assessment differed between the 2 screen time indicators. Measurement error in smartphone-recorded total daily screen time may have been nondifferential by insomnia status, but the direction and magnitude of bias cannot be predicted with certainty in multivariable analyses involving categorized exposures and common outcomes. Self-reported presleep screen time may be differentially misclassified. Future studies should use objective time-stamped measures of presleep exposure and consider probabilistic bias analysis. Third, incomplete screen time data, particularly for total daily screen time, may have introduced selection bias. Comparisons of participants with and without complete screen time data can be found in Tables S1 and S2 in Multimedia Appendix 1 to evaluate missingness patterns. Participants with complete total daily screen time data had a higher prevalence of insomnia than those with missing data, suggesting possible selection bias; therefore, findings for total daily screen time should be interpreted with considerable caution. Fourth, because insomnia was common, especially in the total daily screen time sample, ORs may overestimate relative risks and should be interpreted accordingly. Finally, we did not assess the content, purpose, or emotional engagement of smartphone use. Several psychological factors that may influence both screen use and sleep, such as anxiety, depression, and psychiatric history, were not measured and could contribute to residual confounding. Although e-value analysis quantified the strength of unmeasured confounding that would be needed to explain away the observed associations, it does not eliminate the possibility of residual confounding by these unmeasured psychological factors.

In conclusion, greater presleep smartphone screen time was consistently associated with higher odds of insomnia among patients with breast cancer, whereas findings for total daily screen time were less consistent and should be interpreted cautiously because of extensive missing objective screen time data. Perceived stigma did not significantly modify these associations. These findings support larger longitudinal studies using objective screen exposure measures and more detailed assessment of screen use context.