- McLaren, Suzanne, Turner, Jayne, Gomez, Rapson, McLachlan, Angus, Gibbs, Petah
- Authors: McLaren, Suzanne , Turner, Jayne , Gomez, Rapson , McLachlan, Angus , Gibbs, Petah
- Date: 2013
- Type: Text , Journal article
- Relation: Aging & Mental Health Vol. 17, no. 8 (November 2013), p. 1023-1029
- Full Text: false
- Reviewed:
- Description: Objectives: Higher levels of depression have been documented among older adults who reside in an assisted living facility, compared with those who remain in their own homes. The aims of the current study were to test whether the relationship between housing type and depressive symptoms was mediated by a sense of belonging and whether housing type and sense of belonging interact to influence the depressive symptoms among older adults (moderation model).Method: A sample of 257 older adults who lived in their own homes and 166 older adults who lived in an assisted living facility completed the psychological subscale of the Sense of Belonging Instrument and the Center for Epidemiologic Studies Depression Scale.Results: Results showed that a sense of belonging partially mediated the relationship between housing type and depressive symptoms, such that living in a nursing home was associated with lower levels of belonging, and lower levels of belonging were, in turn, associated with higher levels of depressive symptoms. Residing in an assisted living facility was associated with depressive symptoms at low and average levels of belonging.Conclusion: Results highlight the need for more research on the role of sense of belonging as an influencing factor on depressive symptoms among institutionalised older adults for both theoretical and treatment goals.
- Description: C1
Pretreatment attrition and formal withdrawal during treatment and their predictors: An exploratory study of the anxiety online data
- Al-Asadi, Ali, Klein, Britt, Meyer, Denny
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 6 (2014), p. e152
- Full Text:
- Reviewed:
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program.
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program
- Authors: Al-Asadi, Ali , Klein, Britt , Meyer, Denny
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Medical Internet Research Vol. 16, no. 6 (2014), p. e152
- Full Text:
- Reviewed:
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program.
- Description: Although in its infancy, the field of e-mental health interventions has been gaining popularity and afforded considerable research attention. However, there are many gaps in the research. One such gap is in the area of attrition predictors at various stages of assessment and treatment delivery. Objective: This exploratory study applied univariate and multivariate analysis to a large dataset provided by the Anxiety Online (now called Mental Health Online) system to identify predictors of attrition in treatment commencers and in those who formally withdrew during treatment based on 24 pretreatment demographic and personal variables and one clinical measure. Methods: Participants were assessed using a complex online algorithm that resulted in primary and secondary diagnoses in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Those who received a primary or secondary diagnosis of 1 of 5 anxiety disorders (generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and panic disorder) were offered an online 12-week disorder-specific treatment program. Results: Of 9394 potential participants, a total of 3880 clients enrolled and 5514 did not enroll in one of the treatment programs following the completion of pretreatment assessment measures (pretreatment attrition rate: 58.70%). A total of 3199 individuals did not formally withdraw from the 12-week treatment cycle, whereas 142 individuals formally dropped out (formal withdrawal during treatment dropout rate of 4.25%). The treatment commencers differed significantly (P<.001-.03) from the noncommencers on several variables (reason for registering, mental health concerns, postsecondary education, where first heard about Anxiety Online, Kessler-6 score, stage of change, quality of life, relationship status, preferred method of learning, and smoking status). Those who formally withdrew during treatment differed significantly (P=.002-.03) from those who did not formally withdraw in that they were less likely to express concerns about anxiety, stress, and depression; to rate their quality of life as very poor, poor, or good; to report adequate level of social support; and to report readiness to make or were in the process of making changes. Conclusions: This exploratory study identified predictors of pretreatment attrition and formal withdrawal during treatment dropouts for the Anxiety Online program
- Chen, Jiarui, Cross, Wendy, Plummer, Virginia, Lam, Louisa, Tang, Siyuan
- Authors: Chen, Jiarui , Cross, Wendy , Plummer, Virginia , Lam, Louisa , Tang, Siyuan
- Date: 2019
- Type: Text , Journal article , Review
- Relation: Women and Birth Vol. 32, no. 6 (Dec 2019), p. 487-492
- Full Text: false
- Reviewed:
- Description: Background: As the number of immigrants grows, the health of Chinese immigrant women, especially their perinatal health, has gradually attracted public attention. Our review has two main purposes. First, estimate the prevalence of postpartum depressive symptoms in Chinese immigrant women, and then determine risk factors for postpartum depressive symptoms among these women. Methods: The following databases: MEDLINE, Embase, Scopus, Web of Science, PsycINFO and PubMed were used in literature search from their commencements until November 21st 2017. The Joanna Briggs Institute (JBI) Critical Appraisal instruments were used to evaluate the quality of the article. Four studies met the inclusion criteria, contributed to our review and meta-analysis. Result: The prevalence of postpartum depression is high in Chinese immigrant women. Risk factors for postpartum depression in Chinese immigrant women were defined as lack of social support, unstable economic status, and acculturation. Conclusion: There have been few studies on postpartum depression among Chinese immigrant women. Existing studies have shown a high prevalence of postpartum depression in Chinese immigrant women. Moreover, there is an urgent need for studies on postpartum depression among Chinese immigrant women informing better understanding, programs of care and improving the perinatal health status of Chinese immigrant women. (C) 2018 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.
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