Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-2 (of 2 Records) |
Query Trace: Ginsberg JP[original query] |
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Shift Work Adaptation Among Police Officers: The BCOPS Study
Nevels TL , Burch JB , Wirth MD , Ginsberg JP , McLain AC , Andrew ME , Allison P , Fekedulegn D , Violanti JM . Chronobiol Int 2021 38 (6) 1-17 Few studies have examined shiftwork adaptation among police officers or potential differences in disease biomarkers among adapted and maladapted shiftworkers. This study characterized shiftwork adaptation among 430 police officers from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study. Police officers working fixed night shifts with symptoms characteristic of adaptation and maladaptation were identified using latent class analysis (n = 242). Two approaches were applied, one with police-specific symptoms and another using more general symptoms as shiftwork adaptation indicators. Biomarkers of inflammation, heart rate variability, and cardiometabolic risk were then compared between shiftwork adaptation groups, and with officers working day shifts, after adjusting for confounding. When analyses included police-specific symptoms, maladapted shiftworkers (n = 73) had more self-reported stress, sleep disturbances, fatigue, and less social support than adapted shiftworkers (n = 169). Using more general symptoms, maladapted officers (n = 56) reported more stress and depression, and less social support than adapted officers (n = 186). In police-specific models, adjusted (least-squares) means (± standard error) of circulating interleukin-6 (IL-6) concentrations in maladapted officers (0.8 ± 0.1 ln[pg/ml]) were modestly elevated relative to adapted shiftworkers (0.7 ± 0.1 ln[pg/ml], p = .09) and relative to permanent day workers (0.5 ± 0.1 ln[pg/ml], p ≤ 0.01), and leptin levels in maladapted officers (9.6 ± 0.1 ln[pg/ml]) exceeded those in the adapted (9.4 ± 0.1 ln[pg/ml], p ≤ 0.01) and day shift groups (9.4 ± 0.1 ln[pg/ml], p = .03). In the general model, adjusted mean tumor necrosis factor-alpha (TNF-α) concentrations among maladapted officers (5.6 ± 0.23 pg/ml) exceeded the adapted (4.8 ± 0.2 pg/ml, p ≤ 0.01) and day workers (5.0 ± 0.2 pg/ml, p = .04), and insulin among maladapted officers was higher (2.4 ± 0.1 ln[uu/ml]) than the adapted group (1.8 ± 0.1 ln[uu/ml], p = .03). No differences were observed for the other biomarkers. The results suggest that maladaptation among police officers working fixed night shifts may lead to increases in leptin, insulin, IL-6, and TNF-α; however, the cross-sectional design and possible residual confounding preclude interpretation of cause and effect. Prospective studies are planned to further characterize the relationship between shiftwork maladaptation and biomarkers of chronic disease risk in this police officer cohort. |
Iterative development of a tailored mHealth intervention for adolescent and young adult survivors of childhood cancer
Schwartz LA , Psihogios AM , Henry-Moss D , Daniel LC , Ver Hoeve ES , Velazquez-Martin B , Butler E , Hobbie WL , Buchanan Lunsford N , Sabatino SA , Barakat LP , Ginsberg JP , Fleisher L , Deatrick JA , Jacobs LA , O'Hagan B , Anderson L , Fredericks E , Amaral S , Dowshen N , Houston K , Vachani C , Hampshire MK , Metz JM , Hill-Kayser CE , Szalda D . Clin Pract Pediatr Psychol 2019 7 (1) 31-43 Objective: Methods for developing mobile health (mHealth) interventions are not well described. To guide the development of future mHealth interventions, we describe the application of the agile science framework to iteratively develop an mHealth intervention for adolescent and young adult (AYA) survivors of childhood cancer. Method: We created the AYA STEPS mobile app (AYA Self-management via Texting, Education, and Plans for Survivorship) by modifying and integrating 2 existing programs: an online survivorship care plan (SCP) generator and a text messaging self-management intervention for AYA off treatment. The iterative development process involved 3 stages of agile science: (1) formative work, (2) obtaining feedback about the first AYA STEPS prototype, and (3) pilot testing and finalization of a prototype. We determined preferences of AYA stakeholders as well as discovered and addressed technology problems prior to beginning a subsequent randomized controlled trial. Results: AYA survivors reported that the app and the embedded tailored messages related to their health and SCP were easy to use and generally satisfying and beneficial. Usage data supported that AYA were engaged in the app. Technology glitches were discovered in the pilot and addressed. Conclusion: The iterative development of AYA STEPS was essential for creating a consistent and acceptable end user experience. This study serves as one example of how behavioral scientists may apply agile science to their own mHealth research. |
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