A Finite Mixture Model of Growth Trajectories of Physical Activity and Mood Outcomes for Sedentary Women

2.50
Hdl Handle:
http://hdl.handle.net/10755/163552
Category:
Abstract
Type:
Presentation
Title:
A Finite Mixture Model of Growth Trajectories of Physical Activity and Mood Outcomes for Sedentary Women
Author(s):
Nies, Mary; Partridge, T.; Gadelrab, H.
Author Details:
Mary Nies, PhD, RN, FAAN, FAAHB, Professor, Wayne State University, Detroit, Michigan, USA, email: mary.nies@stonybrook.edu; T. Partridge; H. Gadelrab
Abstract:
Purpose: The current study sought to identify classes of growth trajectories of sedentary women physical activity and mood. The study also aims to examine the predictors associated with the classes. Conceptual Framework: A midrange model linking psychosocial determinants, environmental factors and individual factors with physical activity and mood served as the foundation for this intervention study. Sample: The sample consisted of 313 physically sedentary women from the metropolitan communities of states of mid-west between the ages of 30 and 60 years with a mean age of 44.5. Design/Methods: Latent growth mixture modeling was used in MPlus version 2. POMS (mood), time to walk 1 mile, and minutes walked per week were assessed at three times: baseline, six months, and 1 year. Several behavioral, psychological, physiological, environmental, and demographic variables were used as predictors of classes identified using latent growth mixture modeling. The logistic regression analysis was carried out by the logistic procedure in SPSS 11.0 for windows. Results: Two classes (high responders, and non-responders) were identified separately for POMS, time to walk 1 mile, and minutes walked per week. The two-class model fitted the data well with high entropy (ranging from .93 to .98) suggesting that the model classify the class membership with very little ambiguity. Some behavioral, psychological, psychological, and environmental variables were statistically significant (p< .05) in distinguishing between high and non-responders sedentary women. Conclusions: Latent growth mixture modeling is a viable technique for identifying heterogeneous classes of growth trajectories. The current findings suggest that the likelihood of sedentary women to engage in physical activity and benefit from intervention may be associated with some behavioral, psychological, psychological, and environmental variables. These variables may be used as screening factors when selecting women for interventions that will fit into their daily life style, and be most successful for them.
Repository Posting Date:
27-Oct-2011
Date of Publication:
27-Oct-2011
Conference Date:
2005
Conference Name:
17th Annual Scientific Sessions
Conference Host:
Eastern Nursing Research Society
Conference Location:
New York, New York, USA
Description:
�Translational Research for Quality Health Outcomes: Affecting Practice and Healthcare Policy�, held on April 7th -9th at the Roosevelt Hotel, New York
Note:
This is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription. Contact your library for assistance in obtaining the as-published article.

Full metadata record

DC FieldValue Language
dc.type.categoryAbstracten_US
dc.typePresentationen_GB
dc.titleA Finite Mixture Model of Growth Trajectories of Physical Activity and Mood Outcomes for Sedentary Womenen_GB
dc.contributor.authorNies, Maryen_US
dc.contributor.authorPartridge, T.en_US
dc.contributor.authorGadelrab, H.en_US
dc.author.detailsMary Nies, PhD, RN, FAAN, FAAHB, Professor, Wayne State University, Detroit, Michigan, USA, email: mary.nies@stonybrook.edu; T. Partridge; H. Gadelraben_US
dc.identifier.urihttp://hdl.handle.net/10755/163552-
dc.description.abstractPurpose: The current study sought to identify classes of growth trajectories of sedentary women physical activity and mood. The study also aims to examine the predictors associated with the classes. Conceptual Framework: A midrange model linking psychosocial determinants, environmental factors and individual factors with physical activity and mood served as the foundation for this intervention study. Sample: The sample consisted of 313 physically sedentary women from the metropolitan communities of states of mid-west between the ages of 30 and 60 years with a mean age of 44.5. Design/Methods: Latent growth mixture modeling was used in MPlus version 2. POMS (mood), time to walk 1 mile, and minutes walked per week were assessed at three times: baseline, six months, and 1 year. Several behavioral, psychological, physiological, environmental, and demographic variables were used as predictors of classes identified using latent growth mixture modeling. The logistic regression analysis was carried out by the logistic procedure in SPSS 11.0 for windows. Results: Two classes (high responders, and non-responders) were identified separately for POMS, time to walk 1 mile, and minutes walked per week. The two-class model fitted the data well with high entropy (ranging from .93 to .98) suggesting that the model classify the class membership with very little ambiguity. Some behavioral, psychological, psychological, and environmental variables were statistically significant (p< .05) in distinguishing between high and non-responders sedentary women. Conclusions: Latent growth mixture modeling is a viable technique for identifying heterogeneous classes of growth trajectories. The current findings suggest that the likelihood of sedentary women to engage in physical activity and benefit from intervention may be associated with some behavioral, psychological, psychological, and environmental variables. These variables may be used as screening factors when selecting women for interventions that will fit into their daily life style, and be most successful for them.en_GB
dc.date.available2011-10-27T11:09:32Z-
dc.date.issued2011-10-27en_GB
dc.date.accessioned2011-10-27T11:09:32Z-
dc.conference.date2005en_US
dc.conference.name17th Annual Scientific Sessionsen_US
dc.conference.hostEastern Nursing Research Societyen_US
dc.conference.locationNew York, New York, USAen_US
dc.description�Translational Research for Quality Health Outcomes: Affecting Practice and Healthcare Policy�, held on April 7th -9th at the Roosevelt Hotel, New Yorken_US
dc.description.noteThis is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription. Contact your library for assistance in obtaining the as-published article.-
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