Sleep as an effect modifier for physical activity intervention efficacy: secondary analysis of data from two randomized controlled trials

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Latinas have high rates of inactivity and are disproportionately burdened by health conditions associated with regular PA. Thus, research is needed to elucidate determinants of success in PA interventions in this population. Sleep is a health behavior that has an established bidirectional relationship to PA, yet it remains unclear how sleep may moderate PA intervention efficacy. Purpose : This study examines sleep as a moderator of the intervention effect on PA outcomes in two randomized controlled trials among sedentary Latinas. Methods : Using a series of generalized mixed effects models with subject-specific intercepts, we tested whether nighttime sleep duration moderated intervention effects on PA outcomes. Analyses were run separately on data from two studies to help establish consistency of findings across two similar participant populations. Results : Results indicated that nighttime sleep duration (whether operationalized continuously or dichotomously based on guidelines) was a significant moderator of intervention effects on PA outcomes over time, p’s<.05. Across studies, women who reported more nightly sleep, showed greater benefits from intervention vs. control (in Study 1) and enhanced vs. original intervention (in Study 2). Conclusions : To our knowledge, this is the first study to examine sleep as an effect modifier of PA intervention success. Findings suggest that sufficient sleep allows Latinas to benefit more from PA interventions and also additional points of contact and features. Figures Figure 1 Figure 2 Introduction It is well established that physical activity (PA) is important for women’s health across various domains. For example, PA lowers cardiovascular risk [1], improves mental health [2, 3], strengthens bones [4], reduces risk for certain cancers [5, 6], and supports healthy pregnancy [7, 8]. However, despite the large evidence base on these health benefits, women remain less physically active than men, and the gap has widened over time, reflecting a persistent disparity [9]. Consequently, interventions to increase PA have been designed and tested, demonstrating varying degrees of success across diverse samples of women. PA promotion interventions that target Latina women specifically are especially important as Latinas not only have higher rates of inactivity compared to non-Hispanic White women, but they are also disproportionately burdened by related health conditions (e.g., certain forms of cancer [10, 11], stroke [12], diabetes [13]). Over the past decade, PA interventions targeting insufficiently active Latinas have been designed and tested. Specifically, researchers designed an empirically supported Spanish-language, individually-tailored, website-delivered intervention [14], Pasos Hacia La Salud I (Pasos I). Results from a randomized controlled trial (RCT) found that participants in the intervention group experienced a greater increase in weekly moderate to vigorous physical activity (MVPA) compared to those in the control group [15]. However, despite the noted improvements in MVPA observed among those in the intervention group, few participants met national PA guidelines of at least 150 minutes of MVPA per week [16]. The researchers then created a more intensive enhanced version of the intervention that included text messaging and additional data-driven content and interactive features [17]. While Pasos Hacia La Salud II (Pasos II) superiority RCT found that those receiving the enhanced intervention outperformed those receiving the original intervention at 18 and 24 months, still less than half of participants ended up meeting PA guidelines [18]. Thus, research is needed to further understand potential barriers or determinants of success in the context of PA interventions targeting this population. Sleep is an important health behavior that has an impact on PA behavior [19]. Previous work has established that there are bidirectional associations between sleep and PA [20-24]. That is, sufficient sleep (i.e., at least 7 hours per day [25]) promotes PA and increased PA promotes sleep. Given the former, it is plausible that insufficient sleep may be a barrier to success in PA promotion interventions, but to our knowledge, this has not yet been investigated. As the prior RCTs provide a rich opportunity to address this gap in the literature, notably among a population who also experiences sleep disparities [26, 27], the present study examines nighttime sleep duration as a moderator of intervention efficacy in Pasos I and Pasos II. We hypothesized that the intervention effect would be stronger for participants meeting the national sleep guideline of at least 7 hours per day than those with short sleep duration [25]. Method Study Design and Participants We analyzed data from the Pasos Hacia La Salud I (Pasos I) and Pasos Hacia La Salud II (Pasos II) RCTs. In the Pasos I RCT, 205 insufficiently active (defined as participating in less than 60 minutes of MVPA per week) Latinas were randomly assigned to the intervention group or wellness contact control group [15]. The study has been previously described in detail, but briefly, the original website-based intervention included features for self-monitoring and goal setting, as well as a discussion forum, links to online resources, tip sheets, and individually tailored and motivation-matched physical activity (PA) feedback reports [14, 15]. The wellness contact control condition was also website-based, and participants in both groups received emails on a tapered schedule over 6 months to alert them about new website content, and participants completed follow-up assessments at 6-months and 12-months. After enhancing the intervention, including adding text messaging and additional data-driven content and interactive features, we conducted another RCT, Pasos II, with 195 insufficiently active Latinas who were randomly assigned to receive either the enhanced or original intervention [18]. In this superiority RCT, participants completed follow-up assessments at 6-months, 12-months, 18-months, and 24-months. Further details on the differences between the original and enhanced interventions have been previously published [17, 18]. All Pasos I and II participants are included in this secondary analysis. Measures PA was self-reported as total weekly minutes of MVPA using the 7-Day Physical Activity Recall (PAR) [28, 29]. For both RCTs, the 7-Day PAR was administered by a trained interviewer who probed participants about the frequency, duration, and intensity of their PA on each day over the past week. The 7-Day PAR is both reliable and valid as a measure of MVPA that is sensitive to change [28, 29]. Sleep, specifically nighttime sleep duration, was derived from the 7-Day PAR. Namely, participants self-reported the times they got in and out of bed each day over the past week. These times were then used to calculate total weekly minutes of nighttime sleep. Participants were classified as either meeting the sleep guideline (at least 7 hours per night) or not based on their average nighttime sleep duration (calculated by dividing total weekly minutes of nighttime sleep by 7 and converting to hours). Sociodemographic characteristics were also self-reported from participants in both RCTs using questionnaires, which were administered at baseline. Characteristics assessed included age, Latino subgroup, highest level of education, employment status, and marital status. Participants also reported their height and weight, which were used to calculate body mass index (BMI). Additionally, they completed the Short Test of Functional Health Literacy in Adults (STOHFLA) [30, 31]. All questionnaires and PARs were administered in Spanish. Data for Pasos I were collected from 2011 to 2014, while data for Pasos II were collected from 2018–2022. Statistical Analyses Exploratory data analysis included descriptive statistics to summarize baseline sociodemographic, sleep, and PA behavior across study arms and separately by study. Between-group differences have already been reported and were summarized for the purpose of the current analysis [15, 18, 32, 33]. Analyses were run separately by study (Pasos I and II), with the goal of testing the effects in the first RCT (Pasos I) and replicating in the second (Pasos II). Using a series of generalized mixed effects models with subject-specific intercepts, we tested the hypothesis that sleep moderated the intervention effects on PA outcomes. Models simultaneously regressed minutes per week of MVPA at each follow-up on time, group, time*group, sleep, time*sleep, group*sleep, and time*group*sleep. Interest was in understanding if: 1) effects of the intervention differed by sleep and if 2) differential effects based on sleep also differed over time. Sleep was quantified both continuously and dichotomously (whether or not participants met the sleep guideline of at least 7 hours) [25]. Analyses were conducted in R Studio 3.6.0 with significance level set at .05 a priori [34]. Results Descriptive Statistics Full descriptions of the study samples have been published elsewhere. In brief, participants in Pasos Hacia La Salud I (Pasos I) (N = 205) were 39.2 (SD = 10.5) years of age on average. The majority identified themselves as Mexican American (84%), White (52%), and first-generation in the United States (82%). On average, participant BMI (28.8 +/− 5.2) was in the overweight range. Most participants had some college education (61%) and had an annual household income lower than $ 30,000 (66.4%). In Pasos Hacia La Salud II (Pasos II) (N = 195) the average age of participants was 43.31 years (SD = 10.3), the most reported Latino subgroup was Dominican (41%), and 41% of the sample reported at least some college education. Full descriptives of sociodemographic characteristics for the samples are presented in Tables 1 and 2 . Sleep durations for both study samples are summarized in Table 3 . In Pasos I, average sleep/night was 8.60 hours or 3613 minutes/week. Overall, 92% of participants were meeting the sleep guideline at baseline. In Pasos II, 95% of participants were meeting the sleep guideline at baseline (average sleep minutes/week was 3775 min/week or an average of 8.99 hours/night). Table 3 Unadjusted Baseline Sleep, Pasos Hacia La Salud I (N = 205) and Pasos Hacia La Salud II (N = 195) Pasos Hacia La Salud I Pasos Hacia La Salud II N = 205 N = 195 Total Weekly Sleep Minutes 3613.68 (621.16) 3775.33 (627.59) Average Nightly Sleep Hours 8.60 (1.48) 8.99 (1.49) Meeting Sleep Guideline ( ≥ 7 hours per night) 189 (92%) 185 (95%) Pasos Hacia La Salud I Model results indicated a significant conditional effect of sleep on the intervention effects on moderate to vigorous physical activity (MVPA) outcomes at follow-up. When sleep was considered dichotomously (meeting the guideline vs. not), results indicate that among those meeting the guideline, those randomized to the intervention group reported 56.91 minutes/week more MVPA at 6-months compared to the control group (SE = 14.87, p<.01). There were no significant intervention effects among those not meeting the sleep guideline at baseline (p=.98). Similarly, at 12-months, among those meeting the sleep guideline, participants randomized to the intervention group outperformed control participants (b = 30.22, SE = 16.04, p=.04), whereas there were no significant between-group differences among those not meeting the sleep guideline (p=.72). Findings are presented in Fig. 1 . A similar pattern was seen with continuous minutes/night of sleep (with significant between-group differences favoring intervention among those reporting longer nighttime sleep (sleep x intervention effect = 26.51, SE = 10.93, p=.02 at 6 months; sleep x intervention effect = 19.01, SE = 10.06, p=.04 at 12 months). Pasos Hacia La Salud II Model results indicated that sleep was a significant moderator of the intervention effect at 18- and 24-months. When sleep was dichotomized, among those meeting the guideline, participants who received the enhanced intervention reported 22 minutes/week more MVPA (p=.10) at 18-months and 36 minutes/week more at 24-months (p=.03) than those who received the original intervention, as shown in Fig. 2 . A similar pattern was seen with continuous minutes/night of sleep (with significant between-group differences favoring the enhanced intervention among those reporting longer nighttime sleep). Specifically, interactions between continuous sleep and intervention assigned were significant at 18 and 24 months (sleep x intervention effect = 22.30, SE = 1.76, p=.001 at 18 months; sleep x intervention effect = 13.41, SE = 1.99, p=.001, at 24 months). This pattern of results is similar to those seen in the first RCT. Discussion This secondary analysis aimed to examine whether sleep moderated the intervention effect in two randomized controlled trials (RCTs) testing website-based physical activity (PA) interventions for insufficiently active Latinas. Findings supported our hypothesis, that the intervention effect would be stronger for participants sleeping at least 7 hours per day. In Pasos I, which tested the original intervention against a wellness contact control, those with sufficient sleep benefited from being in the intervention vs. control group at both 6- and 12-months. Those with insufficient sleep, on the other hand, did not benefit from being in the intervention group. In Pasos II, which tested an enhanced version of the intervention against the original intervention, those with sufficient sleep benefited from being in the intervention vs. control group at 18- and 24-months. Those with insufficient sleep, on the other hand, performed similarly at these timepoints regardless of which intervention they received. Insufficient sleep can lead to reduced PA through increasing fatigue, altering mood, and reducing motivation [35, 36]. Insufficient sleep can also impair muscle strength [37] as well as recovery after exercise [38], and is associated with sedentary behavior [35, 39]. Thus, in the context of PA interventions, insufficient sleep may lead to barriers that negatively impact participants’ PA (e.g., feeling too tired to implement intervention strategies). It is also plausible that insufficient sleep may lead participants to engage less with intervention itself (e.g., lower use of the intervention website), particularly among Latinas who report that lack of time as a substantial barrier to PA [40, 41]. However, as prior research in this area has predominantly been observational, more studies are needed. Our findings, that sleep was a significant moderator of the intervention effect in Pasos II, where all participants received a PA intervention (either the original intervention or an enhanced version), further suggest that the influence of sleep on intervention efficacy could depend on characteristics of the PA intervention. A key difference between the original and enhanced intervention is that for the original intervention, while participants continue to have access to the intervention website, no additional contacts are made after 12 months, whereas for the enhanced intervention participants receive weekly text messages and bi-weekly emails. Our findings suggest that sufficient sleep allowed participants to benefit from the more intensive enhanced intervention particularly during the second year, whereas those with insufficient sleep did not benefit from the additional points of contact and features. Interestingly, while a majority of the research on sleep and PA has focused on how PA impacts sleep (with findings largely supporting that PA leads to better sleep), studies that have simultaneously examined how sleep impacts PA have found that sleep is a stronger predictor of PA than PA is of sleep [42–44]. Thus, both baseline and subsequent sleep likely have important implications for PA intervention success. Given our findings, that sleep was an effect modifier for intervention efficacy in two different RCTs with different samples, future PA interventions should consider tailoring intervention content or materials based on characteristics of participant sleep. Indeed, prior research has demonstrated the benefits of tailoring PA interventions based on various participant characteristics including medical conditions [45, 46] and psychological factors [47, 48]. While solely targeting sleep to increase PA is likely insufficient [49, 50], targeting sleep in conjunction with PA may maximize PA benefits. The implications of our findings are particularly relevant for PA interventions targeting Latinas. As stated, Latina women are at high risk for both low levels of PA and related health conditions [10–13]. They are also at greater risk than their non-Hispanic White counterparts to get insufficient amounts of sleep [26, 27]. While most participants in our analysis were classified as meeting the sleep guideline, this was likely a result of the way sleep was measured. Namely, using time in bed and time out of bed overestimates sleep. This is a limitation of the current analysis (i.e., examining sleep was not a primary aim of the parent study and we were limited to self-reported time in and out of bed as a measure of sleep duration). Given that sleep was self-reported, we used self-reported MVPA for consistency. An additional limitation, given that both RCTs targeted insufficiently active Latinas, is that our results may not be generalizable to other populations. Nonetheless, to our knowledge, this is the first study to examine sleep as an effect modifier in a PA intervention. Additional strengths include the use of repeated assessments of PA in a high-risk population of Latina women and our ability to analyze data from two separate RCTs. Along with our findings, this study thus makes a novel contribution to understanding the role of sleep in shaping responses to PA interventions. Declarations Author Contribution Tayla von Ash: conceptualization, funding acquisition, methodology, writing – original draft, writing – review & editing; Shira Dunsiger: formal analysis, methodology, visualization, writing – original draft, writing – review & editing, Belinda O’hagan: writing – original draft, writing – review & editing; Michael Chidinma Onu: writing – original draft, writing – review & editing; Sugandha K. Gupta-Louis: writing – review & editing; Lauren Connell Bohlen: writing – review & editing; Tanya J. Benitez: writing – review & editing; Bess H. Marcus: funding acquisition, resources, supervision, writing – review & editing Data Availability • The studies from which the data came were pre-registered at clinicaltrials.gov (NCT01834287 and NCT03491592).• The analysis plan was not formally pre-registered.• De-identified data from this study are not available in a public archive. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8809571","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597655093,"identity":"4cecfad7-86ac-4288-8029-3ab9c119aa8e","order_by":0,"name":"Tayla von Ash","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYHACxgMg0oC9ByaQgF89DxBDtPCcIVmLRA6RWuzZzxgc+MFgZ28u+fbYh49tdxj42XMM8NvCk2NwsIchOXHn7LzkmTPbnjFI9rwhoIUhx+AADwNzgsHtHGNm3m2HGQxuELKF/43BwT8M9fYGN89AtNgT1CKRY3CYh+Ew44YbPFBbJAhpufGs4LAMw/HEDWfykhln/jvMI3HmWQFeLez9yRsfvmGotjc4fvYww4czh+X425M34NXCwMBhwMD4D8laAsrB9jwgQtEoGAWjYBSMaAAAt9JHM7bo984AAAAASUVORK5CYII=","orcid":"","institution":"Brown University School of Public Health","correspondingAuthor":true,"prefix":"","firstName":"Tayla","middleName":"","lastName":"von Ash","suffix":""},{"id":597655097,"identity":"340381ea-c123-43a7-be03-549b2df35b74","order_by":1,"name":"Shira Dunsiger","email":"","orcid":"","institution":"Brown University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Shira","middleName":"","lastName":"Dunsiger","suffix":""},{"id":597655101,"identity":"2bc291f4-44f7-4fba-b795-a9c2a6f55147","order_by":2,"name":"Belinda O'Hagan","email":"","orcid":"","institution":"Brown University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Belinda","middleName":"","lastName":"O'Hagan","suffix":""},{"id":597655102,"identity":"d750479c-ac6b-4bbc-81db-c31b05fdc265","order_by":3,"name":"Michael Chidinma Onu","email":"","orcid":"","institution":"Brown University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"Chidinma","lastName":"Onu","suffix":""},{"id":597655103,"identity":"5484f906-96dc-4b8e-aa01-c4b0d131ae3d","order_by":4,"name":"Sugandha K Gupta-Louis","email":"","orcid":"","institution":"Yeshiva University","correspondingAuthor":false,"prefix":"","firstName":"Sugandha","middleName":"K","lastName":"Gupta-Louis","suffix":""},{"id":597655104,"identity":"3712f5db-2e55-4e5f-9827-2eabd9caa007","order_by":5,"name":"Lauren Connell Bohlen","email":"","orcid":"","institution":"Brown University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Lauren","middleName":"Connell","lastName":"Bohlen","suffix":""},{"id":597655105,"identity":"7a709642-613f-46b0-b42e-872c1bf3e32a","order_by":6,"name":"Tanya J Benitez","email":"","orcid":"","institution":"Brown University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Tanya","middleName":"J","lastName":"Benitez","suffix":""},{"id":597655106,"identity":"d827fb6c-0eb6-4645-8d69-78e10f00694f","order_by":7,"name":"Bess H Marcus","email":"","orcid":"","institution":"Brown University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Bess","middleName":"H","lastName":"Marcus","suffix":""}],"badges":[],"createdAt":"2026-02-06 17:09:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8809571/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8809571/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103733821,"identity":"2964957b-e5ed-455b-8f30-63edc889332b","added_by":"auto","created_at":"2026-03-02 09:29:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":147472,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSleep as a Moderator of Intervention Effect in Pasos Hacia La Salud I\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8809571/v1/e46a471d73bc9a63b22daf0a.png"},{"id":103733822,"identity":"18cd9c2b-05a9-4b8f-b434-02c36dc58955","added_by":"auto","created_at":"2026-03-02 09:29:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":149087,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSleep as a Moderator of Intervention Effect in Pasos Hacia La Salud II\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8809571/v1/8045b82fb2629d62604f250f.png"},{"id":103733861,"identity":"ffc2251b-dea7-401d-a05d-cadd2ffdd3c0","added_by":"auto","created_at":"2026-03-02 09:29:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":859238,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8809571/v1/0aba397a-2b9b-4f39-977e-40a3e56d7ed0.pdf"},{"id":103733820,"identity":"250f23bb-dd68-4ce9-9eda-1024b499f87c","added_by":"auto","created_at":"2026-03-02 09:29:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17943,"visible":true,"origin":"","legend":"","description":"","filename":"Table12.docx","url":"https://assets-eu.researchsquare.com/files/rs-8809571/v1/f1836f5569a56a380b98832b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sleep as an effect modifier for physical activity intervention efficacy: secondary analysis of data from two randomized controlled trials","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIt is well established that physical activity (PA) is important for women\u0026rsquo;s health across various domains. For example, PA lowers cardiovascular risk [1], improves mental health [2, 3], strengthens bones [4], reduces risk for certain cancers [5, 6], and supports healthy pregnancy [7, 8]. However, despite the large evidence base on these health benefits, women remain less physically active than men, and the gap has widened over time, reflecting a persistent disparity [9]. Consequently, interventions to increase PA have been designed and tested, demonstrating varying degrees of success across diverse samples of women. PA promotion interventions that target Latina women specifically are especially important as Latinas not only have higher rates of inactivity compared to non-Hispanic White women, but they are also disproportionately burdened by related health conditions (e.g., certain forms of cancer\u0026nbsp;[10, 11], stroke\u0026nbsp;[12], diabetes\u0026nbsp;[13]).\u003c/p\u003e\n\u003cp\u003eOver the past decade, PA interventions targeting insufficiently active Latinas have been designed and tested. Specifically, researchers designed an empirically supported Spanish-language, individually-tailored, website-delivered intervention [14], Pasos Hacia La Salud I (Pasos I). Results from a randomized controlled trial (RCT) found that participants in the intervention group experienced a greater increase in weekly moderate to vigorous physical activity (MVPA) compared to those in the control group [15]. However, despite the noted improvements in MVPA observed among those in the intervention group, few participants met national PA guidelines of at least 150 minutes of MVPA per week [16]. The researchers then created a more intensive enhanced version of the intervention that\u0026nbsp;included text messaging and additional data-driven content and interactive features [17]. While Pasos Hacia La Salud II\u0026nbsp;(Pasos II) superiority RCT found that those receiving the enhanced intervention outperformed those receiving the original intervention at 18 and 24 months, still less than half of participants ended up meeting PA guidelines [18]. Thus, research is needed to further understand potential barriers or determinants of success in the context of PA interventions targeting this population.\u003c/p\u003e\n\u003cp\u003eSleep is an important health behavior that has an impact on PA behavior [19]. Previous work has established that there are bidirectional associations between sleep and PA [20-24]. That is, sufficient sleep (i.e., at least 7 hours per day [25]) promotes PA and increased PA promotes sleep. Given the former, it is plausible that insufficient sleep may be a barrier to success in PA promotion interventions, but to our knowledge, this has not yet been investigated. As the prior RCTs provide a rich opportunity to address this gap in the literature, notably among a population who also experiences sleep disparities [26, 27], the present study examines nighttime sleep duration as a moderator of intervention efficacy in Pasos I and Pasos II. We hypothesized that the intervention effect would be stronger for participants meeting the national sleep guideline of at least 7 hours per day than those with short sleep duration [25].\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Participants\u003c/h2\u003e \u003cp\u003eWe analyzed data from the Pasos Hacia La Salud I (Pasos I) and Pasos Hacia La Salud II (Pasos II) RCTs. In the Pasos I RCT, 205 insufficiently active (defined as participating in less than 60 minutes of MVPA per week) Latinas were randomly assigned to the intervention group or wellness contact control group [15]. The study has been previously described in detail, but briefly, the original website-based intervention included features for self-monitoring and goal setting, as well as a discussion forum, links to online resources, tip sheets, and individually tailored and motivation-matched physical activity (PA) feedback reports [14, 15]. The wellness contact control condition was also website-based, and participants in both groups received emails on a tapered schedule over 6 months to alert them about new website content, and participants completed follow-up assessments at 6-months and 12-months.\u003c/p\u003e \u003cp\u003eAfter enhancing the intervention, including adding text messaging and additional data-driven content and interactive features, we conducted another RCT, Pasos II, with 195 insufficiently active Latinas who were randomly assigned to receive either the enhanced or original intervention [18]. In this superiority RCT, participants completed follow-up assessments at 6-months, 12-months, 18-months, and 24-months. Further details on the differences between the original and enhanced interventions have been previously published [17, 18]. All Pasos I and II participants are included in this secondary analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003ePA was self-reported as total weekly minutes of MVPA using the 7-Day Physical Activity Recall (PAR) [28, 29]. For both RCTs, the 7-Day PAR was administered by a trained interviewer who probed participants about the frequency, duration, and intensity of their PA on each day over the past week. The 7-Day PAR is both reliable and valid as a measure of MVPA that is sensitive to change [28, 29].\u003c/p\u003e \u003cp\u003eSleep, specifically nighttime sleep duration, was derived from the 7-Day PAR. Namely, participants self-reported the times they got in and out of bed each day over the past week. These times were then used to calculate total weekly minutes of nighttime sleep. Participants were classified as either meeting the sleep guideline (at least 7 hours per night) or not based on their average nighttime sleep duration (calculated by dividing total weekly minutes of nighttime sleep by 7 and converting to hours).\u003c/p\u003e \u003cp\u003eSociodemographic characteristics were also self-reported from participants in both RCTs using questionnaires, which were administered at baseline. Characteristics assessed included age, Latino subgroup, highest level of education, employment status, and marital status. Participants also reported their height and weight, which were used to calculate body mass index (BMI). Additionally, they completed the Short Test of Functional Health Literacy in Adults (STOHFLA) [30, 31]. All questionnaires and PARs were administered in Spanish. Data for Pasos I were collected from 2011 to 2014, while data for Pasos II were collected from 2018\u0026ndash;2022.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eExploratory data analysis included descriptive statistics to summarize baseline sociodemographic, sleep, and PA behavior across study arms and separately by study. Between-group differences have already been reported and were summarized for the purpose of the current analysis [15, 18, 32, 33].\u003c/p\u003e \u003cp\u003eAnalyses were run separately by study (Pasos I and II), with the goal of testing the effects in the first RCT (Pasos I) and replicating in the second (Pasos II). Using a series of generalized mixed effects models with subject-specific intercepts, we tested the hypothesis that sleep moderated the intervention effects on PA outcomes. Models simultaneously regressed minutes per week of MVPA at each follow-up on time, group, time*group, sleep, time*sleep, group*sleep, and time*group*sleep. Interest was in understanding if: 1) effects of the intervention differed by sleep and if 2) differential effects based on sleep also differed over time. Sleep was quantified both continuously and dichotomously (whether or not participants met the sleep guideline of at least 7 hours) [25]. Analyses were conducted in R Studio 3.6.0 with significance level set at .05 a priori [34].\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eDescriptive Statistics\u003c/h2\u003e\n \u003cp\u003eFull descriptions of the study samples have been published elsewhere. In brief, participants in Pasos Hacia La Salud I (Pasos I) (N\u0026thinsp;=\u0026thinsp;205) were 39.2 (SD\u0026thinsp;=\u0026thinsp;10.5) years of age on average. The majority identified themselves as Mexican American (84%), White (52%), and first-generation in the United States (82%). On average, participant BMI (28.8 +/\u0026minus; 5.2) was in the overweight range. Most participants had some college education (61%) and had an annual household income lower than \u003cspan\u003e$\u003c/span\u003e30,000 (66.4%). In Pasos Hacia La Salud II (Pasos II) (N\u0026thinsp;=\u0026thinsp;195) the average age of participants was 43.31 years (SD\u0026thinsp;=\u0026thinsp;10.3), the most reported Latino subgroup was Dominican (41%), and 41% of the sample reported at least some college education. Full descriptives of sociodemographic characteristics for the samples are presented in Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv\u003eSleep durations for both study samples are summarized in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. In Pasos I, average sleep/night was 8.60 hours or 3613 minutes/week. Overall, 92% of participants were meeting the sleep guideline at baseline. In Pasos II, 95% of participants were meeting the sleep guideline at baseline (average sleep minutes/week was 3775 min/week or an average of 8.99 hours/night).\u003c/div\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnadjusted Baseline Sleep, Pasos Hacia La Salud I (N\u0026thinsp;=\u0026thinsp;205) and Pasos Hacia La Salud II (N\u0026thinsp;=\u0026thinsp;195)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePasos Hacia La Salud I\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePasos Hacia La Salud II\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eN\u0026thinsp;=\u003c/em\u003e\u0026thinsp;205\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eN\u0026thinsp;=\u0026thinsp;195\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Weekly Sleep\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMinutes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3613.68 (621.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3775.33 (627.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage Nightly Sleep\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHours\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.60 (1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.99 (1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeeting Sleep Guideline\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;\u003cstrong\u003e7 hours per night)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e189 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e185 (95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003ePasos Hacia La Salud I\u003c/h3\u003e\n\u003cp\u003eModel results indicated a significant conditional effect of sleep on the intervention effects on moderate to vigorous physical activity (MVPA) outcomes at follow-up. When sleep was considered dichotomously (meeting the guideline vs. not), results indicate that among those meeting the guideline, those randomized to the intervention group reported 56.91 minutes/week more MVPA at 6-months compared to the control group (SE\u0026thinsp;=\u0026thinsp;14.87, p\u0026lt;.01). There were no significant intervention effects among those not meeting the sleep guideline at baseline (p=.98). Similarly, at 12-months, among those meeting the sleep guideline, participants randomized to the intervention group outperformed control participants (b\u0026thinsp;=\u0026thinsp;30.22, SE\u0026thinsp;=\u0026thinsp;16.04, p=.04), whereas there were no significant between-group differences among those not meeting the sleep guideline (p=.72). Findings are presented in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. A similar pattern was seen with continuous minutes/night of sleep (with significant between-group differences favoring intervention among those reporting longer nighttime sleep (sleep x intervention effect\u0026thinsp;=\u0026thinsp;26.51, SE\u0026thinsp;=\u0026thinsp;10.93, p=.02 at 6 months; sleep x intervention effect\u0026thinsp;=\u0026thinsp;19.01, SE\u0026thinsp;=\u0026thinsp;10.06, p=.04 at 12 months).\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003ePasos Hacia La Salud II\u003c/h2\u003e\n \u003cp\u003eModel results indicated that sleep was a significant moderator of the intervention effect at 18- and 24-months. When sleep was dichotomized, among those meeting the guideline, participants who received the enhanced intervention reported 22 minutes/week more MVPA (p=.10) at 18-months and 36 minutes/week more at 24-months (p=.03) than those who received the original intervention, as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. A similar pattern was seen with continuous minutes/night of sleep (with significant between-group differences favoring the enhanced intervention among those reporting longer nighttime sleep). Specifically, interactions between continuous sleep and intervention assigned were significant at 18 and 24 months (sleep x intervention effect\u0026thinsp;=\u0026thinsp;22.30, SE\u0026thinsp;=\u0026thinsp;1.76, p=.001 at 18 months; sleep x intervention effect\u0026thinsp;=\u0026thinsp;13.41, SE\u0026thinsp;=\u0026thinsp;1.99, p=.001, at 24 months). This pattern of results is similar to those seen in the first RCT.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis secondary analysis aimed to examine whether sleep moderated the intervention effect in two randomized controlled trials (RCTs) testing website-based physical activity (PA) interventions for insufficiently active Latinas. Findings supported our hypothesis, that the intervention effect would be stronger for participants sleeping at least 7 hours per day. In Pasos I, which tested the original intervention against a wellness contact control, those with sufficient sleep benefited from being in the intervention vs. control group at both 6- and 12-months. Those with insufficient sleep, on the other hand, did not benefit from being in the intervention group. In Pasos II, which tested an enhanced version of the intervention against the original intervention, those with sufficient sleep benefited from being in the intervention vs. control group at 18- and 24-months. Those with insufficient sleep, on the other hand, performed similarly at these timepoints regardless of which intervention they received.\u003c/p\u003e \u003cp\u003eInsufficient sleep can lead to reduced PA through increasing fatigue, altering mood, and reducing motivation [35, 36]. Insufficient sleep can also impair muscle strength [37] as well as recovery after exercise [38], and is associated with sedentary behavior [35, 39]. Thus, in the context of PA interventions, insufficient sleep may lead to barriers that negatively impact participants\u0026rsquo; PA (e.g., feeling too tired to implement intervention strategies). It is also plausible that insufficient sleep may lead participants to engage less with intervention itself (e.g., lower use of the intervention website), particularly among Latinas who report that lack of time as a substantial barrier to PA [40, 41]. However, as prior research in this area has predominantly been observational, more studies are needed.\u003c/p\u003e \u003cp\u003eOur findings, that sleep was a significant moderator of the intervention effect in Pasos II, where all participants received a PA intervention (either the original intervention or an enhanced version), further suggest that the influence of sleep on intervention efficacy could depend on characteristics of the PA intervention. A key difference between the original and enhanced intervention is that for the original intervention, while participants continue to have access to the intervention website, no additional contacts are made after 12 months, whereas for the enhanced intervention participants receive weekly text messages and bi-weekly emails. Our findings suggest that sufficient sleep allowed participants to benefit from the more intensive enhanced intervention particularly during the second year, whereas those with insufficient sleep did not benefit from the additional points of contact and features.\u003c/p\u003e \u003cp\u003eInterestingly, while a majority of the research on sleep and PA has focused on how PA impacts sleep (with findings largely supporting that PA leads to better sleep), studies that have simultaneously examined how sleep impacts PA have found that sleep is a stronger predictor of PA than PA is of sleep [42\u0026ndash;44]. Thus, both baseline and subsequent sleep likely have important implications for PA intervention success. Given our findings, that sleep was an effect modifier for intervention efficacy in two different RCTs with different samples, future PA interventions should consider tailoring intervention content or materials based on characteristics of participant sleep. Indeed, prior research has demonstrated the benefits of tailoring PA interventions based on various participant characteristics including medical conditions [45, 46] and psychological factors [47, 48]. While solely targeting sleep to increase PA is likely insufficient [49, 50], targeting sleep in conjunction with PA may maximize PA benefits.\u003c/p\u003e \u003cp\u003eThe implications of our findings are particularly relevant for PA interventions targeting Latinas. As stated, Latina women are at high risk for both low levels of PA and related health conditions [10\u0026ndash;13]. They are also at greater risk than their non-Hispanic White counterparts to get insufficient amounts of sleep [26, 27]. While most participants in our analysis were classified as meeting the sleep guideline, this was likely a result of the way sleep was measured. Namely, using time in bed and time out of bed overestimates sleep. This is a limitation of the current analysis (i.e., examining sleep was not a primary aim of the parent study and we were limited to self-reported time in and out of bed as a measure of sleep duration). Given that sleep was self-reported, we used self-reported MVPA for consistency. An additional limitation, given that both RCTs targeted insufficiently active Latinas, is that our results may not be generalizable to other populations.\u003c/p\u003e \u003cp\u003eNonetheless, to our knowledge, this is the first study to examine sleep as an effect modifier in a PA intervention. Additional strengths include the use of repeated assessments of PA in a high-risk population of Latina women and our ability to analyze data from two separate RCTs. Along with our findings, this study thus makes a novel contribution to understanding the role of sleep in shaping responses to PA interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTayla von Ash: conceptualization, funding acquisition, methodology, writing \u0026ndash; original draft, writing \u0026ndash; review \u0026amp; editing; Shira Dunsiger: formal analysis, methodology, visualization, writing \u0026ndash; original draft, writing \u0026ndash; review \u0026amp; editing, Belinda O\u0026rsquo;hagan: writing \u0026ndash; original draft, writing \u0026ndash; review \u0026amp; editing; Michael Chidinma Onu: writing \u0026ndash; original draft, writing \u0026ndash; review \u0026amp; editing; Sugandha K. Gupta-Louis: writing \u0026ndash; review \u0026amp; editing; Lauren Connell Bohlen: writing \u0026ndash; review \u0026amp; editing; Tanya J. Benitez: writing \u0026ndash; review \u0026amp; editing; Bess H. Marcus: funding acquisition, resources, supervision, writing \u0026ndash; review \u0026amp; editing\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003e\u0026bull; The studies from which the data came were pre-registered at clinicaltrials.gov (NCT01834287 and NCT03491592).\u0026bull; The analysis plan was not formally pre-registered.\u0026bull; De-identified data from this study are not available in a public archive. De-identified data from this study will be made available (as allowable according to institutional IRB standards) by emailing the corresponding author.\u0026bull; Analytic code used to conduct the analyses presented in this study are not available in a public archive. They may be available by emailing the corresponding author.\u0026bull; Materials used to conduct the study are not publicly available.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLaMonte MJ, LaCroix AZ, Nguyen S, Evenson KR, Di C, Stefanick ML, et al. Accelerometer-Measured Physical Activity, Sedentary Time, and Heart Failure Risk in Women Aged 63 to 99 Years. JAMA Cardiol. 2024;9(4):336-45.\u003c/li\u003e\n\u003cli\u003ePearce M, Garcia L, Abbas A, Strain T, Schuch FB, Golubic R, et al. Association Between Physical Activity and Risk of Depression: A Systematic Review and Meta-analysis. JAMA Psychiatry. 2022;79(6):550-9.\u003c/li\u003e\n\u003cli\u003eSchuch FB, Vancampfort D, Firth J, Rosenbaum S, Ward PB, Silva ES, et al. Physical Activity and Incident Depression: A Meta-Analysis of Prospective Cohort Studies. 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Am J Epidemiol. 1985;122(5):794-804.\u003c/li\u003e\n\u003cli\u003eSallis JF, Haskell WL, Wood PD, Fortmann SP, Rogers T, Blair SN, Paffenbarger RS, Jr. Physical activity assessment methodology in the Five-City Project. Am J Epidemiol. 1985;121(1):91-106.\u003c/li\u003e\n\u003cli\u003eBaker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to measure functional health literacy. Patient Educ Couns. 1999;38(1):33-42.\u003c/li\u003e\n\u003cli\u003eParker RM, Baker DW, Williams MV, Nurss JR. The test of functional health literacy in adults: a new instrument for measuring patients\u0026apos; literacy skills. J Gen Intern Med. 1995;10(10):537-41.\u003c/li\u003e\n\u003cli\u003eHartman SJ, Dunsiger SI, Bock BC, Larsen BA, Linke S, Pekmezi D, et al. Physical activity maintenance among Spanish-speaking Latinas in a randomized controlled trial of an Internet-based intervention. J Behav Med. 2017;40(3):392-402.\u003c/li\u003e\n\u003cli\u003eBohlen L, Dunsiger, SI, Larsen, BA, Pekmezi, D, Marquez, B, Benitez, TJ, Mendoza-Vasconez, A, Hartman, SJ, Williams, DM, \u0026amp; Marcus, B. Pasos Hacia La Salud II: six-month outcomes of a randomized controlled trial of a theory- and technology-enhanced physical activity intervention for Latina women. (Under review).\u003c/li\u003e\n\u003cli\u003eTeam R. RStudio: Integrated Development for R 2020 [Available from: http://www.rstudio.com/.\u003c/li\u003e\n\u003cli\u003eMcCoy T, Sochan AJ, Spaeth AM. The Relationship between Sleep and Physical Activity by Age, Race, and Gender. Rev Cardiovasc Med. 2024;25(10):378.\u003c/li\u003e\n\u003cli\u003ePalagini L, Bastien CH, Marazziti D, Ellis JG, Riemann D. The key role of insomnia and sleep loss in the dysregulation of multiple systems involved in mood disorders: A proposed model. J Sleep Res. 2019;28(6):e12841.\u003c/li\u003e\n\u003cli\u003eKnowles OE, Drinkwater EJ, Urwin CS, Lamon S, Aisbett B. Inadequate sleep and muscle strength: Implications for resistance training. J Sci Med Sport. 2018;21(9):959-68.\u003c/li\u003e\n\u003cli\u003eDattilo M, Antunes HK, Medeiros A, Monico Neto M, Souza HS, Tufik S, de Mello MT. Sleep and muscle recovery: endocrinological and molecular basis for a new and promising hypothesis. Med Hypotheses. 2011;77(2):220-2.\u003c/li\u003e\n\u003cli\u003eLarsson SC, Hallstrom E, Michaelsson K, Titova OE. Poor sleep is associated with lower physical activity in a population-based cohort of middle-aged and older adults. Sci Rep. 2025;15(1):26012.\u003c/li\u003e\n\u003cli\u003eMartinez SM, Arredondo EM, Perez G, Baquero B. Individual, social, and environmental barriers to and facilitators of physical activity among Latinas living in San Diego County: focus group results. Fam Community Health. 2009;32(1):22-33.\u003c/li\u003e\n\u003cli\u003eBenitez TJ, Artigas E, Larsen B, Joseph RP, Pekmezi D, Marquez B, et al. Barriers and Facilitators to Muscle-Strengthening Activity Among Latinas in the U.S.: Results From Formative Research Assessments. Int J Behav Med. 2024;31(2):292-304.\u003c/li\u003e\n\u003cli\u003eBaron KG, Reid KJ, Zee PC. Exercise to improve sleep in insomnia: exploration of the bidirectional effects. J Clin Sleep Med. 2013;9(8):819-24.\u003c/li\u003e\n\u003cli\u003eHolfeld B, Ruthig JC. A longitudinal examination of sleep quality and physical activity in older adults. J Appl Gerontol. 2014;33(7):791-807.\u003c/li\u003e\n\u003cli\u003eLambiase MJ, Gabriel KP, Kuller LH, Matthews KA. Temporal relationships between physical activity and sleep in older women. Med Sci Sports Exerc. 2013;45(12):2362-8.\u003c/li\u003e\n\u003cli\u003eMa JK, West CR, Martin Ginis KA. 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Digit Health. 2022;8:20552076221115017.\u003c/li\u003e\n\u003cli\u003eKline CE LL, Seres RJ, Miewald JM, Hall MH, Buysse DJ. Improved sleep quality does not result in increased daytime activity in older adults with insomnia. Med Sci Sports Exerc. 2014;46.\u003c/li\u003e\n\u003cli\u003eWest SD, Kohler M, Nicoll DJ, Stradling JR. The effect of continuous positive airway pressure treatment on physical activity in patients with obstructive sleep apnoea: A randomised controlled trial. Sleep Med. 2009;10(9):1056-8.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1 and 2","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8809571/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8809571/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cu\u003eBackground\u003c/u\u003e: Regular physical activity (PA) improves health across various domains, reducing the risk of cardiovascular disease and certain forms of cancer while improving mental health. Latinas have high rates of inactivity and are disproportionately burdened by health conditions associated with regular PA. Thus, research is needed to elucidate determinants of success in PA interventions in this population. Sleep is a health behavior that has an established bidirectional relationship to PA, yet it remains unclear how sleep may moderate PA intervention efficacy.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePurpose\u003c/u\u003e: This study examines sleep as a moderator of the intervention effect on PA outcomes in two randomized controlled trials among sedentary Latinas.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eMethods\u003c/u\u003e: Using a series of generalized mixed effects models with subject-specific intercepts, we tested whether nighttime sleep duration moderated intervention effects on PA outcomes. Analyses were run separately on data from two studies to help establish consistency of findings across two similar participant populations.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eResults\u003c/u\u003e: Results indicated that nighttime sleep duration (whether operationalized continuously or dichotomously based on guidelines) was a significant moderator of intervention effects on PA outcomes over time, p’s\u0026lt;.05. Across studies, women who reported more nightly sleep, showed greater benefits from intervention vs. control (in Study 1) and enhanced vs. original intervention (in Study 2).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConclusions\u003c/u\u003e: To our knowledge, this is the first study to examine sleep as an effect modifier of PA intervention success. Findings suggest that sufficient sleep allows Latinas to benefit more from PA interventions and also additional points of contact and features.\u003c/p\u003e","manuscriptTitle":"Sleep as an effect modifier for physical activity intervention efficacy: secondary analysis of data from two randomized controlled trials","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 09:29:12","doi":"10.21203/rs.3.rs-8809571/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e6c30f4-b6a2-46fd-953d-4285debfd472","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T01:53:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 09:29:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8809571","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8809571","identity":"rs-8809571","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}