Psychosocial factors and maternal wellbeing: An exploratory path analysis

2011 ◽  
Vol 48 (6) ◽  
pp. 725-731 ◽  
Author(s):  
Fei-Wan Ngai ◽  
Sally Wai-Chi Chan
Keyword(s):  
Path Analysis ◽  
Psychosocial Factors ◽  
Maternal Wellbeing

scholarly journals Longitudinal predictors of subjective recovery in psychosis

2016 ◽  
Vol 209 (1) ◽  
pp. 48-53 ◽  
Author(s):  
Heather Law ◽  
Nick Shryane ◽  
Richard P. Bentall ◽  
Anthony P. Morrison
Keyword(s):  
Path Analysis ◽  
Social Functioning ◽  
Psychosocial Factors ◽  
Predictive Factors ◽  
Service User ◽  
Psychiatric Symptoms ◽  
Negative Emotion ◽  
Self Esteem ◽  
Recovery Score

BackgroundResearch has highlighted the importance of recovery as defined by the service user, and suggests a link to negative emotion, although little is known about the role of negative emotion in predicting subjective recovery.AimsTo investigate longitudinal predictors of variability in recovery scores with a focus on the role of negative emotion.MethodParticipants (n=110) with experience of psychosis completed measures of psychiatric symptoms, social functioning, subjective recovery, depression, hopelessness and self-esteem at baseline and 6 months later. Path analysis was used to examine predictive factors for recovery and negative emotion.ResultsSubjective recovery scores were predicted by negative emotion, positive self-esteem and hopelessness, and to a lesser extent by symptoms and functioning. Current recovery score was not predicted by past recovery score after accounting for past symptoms, current hopelessness and current positive self-esteem.ConclusionsPsychosocial factors and negative emotion appear to be the strongest longitudinal predictors of variation in subjective recovery, rather than psychiatric symptoms.

Psychosocial factors and glycemic control in insulin-naïve and insulin-experienced people with type 2 diabetes: a path analysis model

2017 ◽  
Vol 38 (3) ◽  
pp. 289-297 ◽  
Author(s):  
Rokhsareh Aghili ◽  
Martin Ridderstråle ◽  
Amir Farshchi ◽  
Ameneh Ebrahim Valojerdi ◽  
Zahra Banazadeh ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Path Analysis ◽  
Psychosocial Factors ◽  
Analysis Model ◽  
Path Analysis Model

Psychosocial factors in pregnancy and birthweight: Path analysis

2016 ◽  
Vol 42 (7) ◽  
pp. 822-830 ◽  
Author(s):  
Mahrokh Dolatian ◽  
Zohreh Mahmoodi ◽  
Hamid Alavi-Majd ◽  
Farnoosh Moafi ◽  
Maryam Ghorbani ◽  
...  
Keyword(s):  
Path Analysis ◽  
Psychosocial Factors ◽  
In Pregnancy

scholarly journals Path Analysis: Effect of Gestational Factors, Psychosocial Factors, and Maternal Class-Room Program on Toddler Growth

2016 ◽  
Vol 01 (01) ◽  
pp. 53-61
Author(s):  
Gita Ayu Indria ◽  
◽  
Bhisma Murti ◽  
Yulia Lanti Retno Dewi ◽  
◽  
...  
Keyword(s):  
Path Analysis ◽  
Psychosocial Factors ◽  
Class Room

Relationship of Sense of Coherence to Other Psychosocial Indices

2004 ◽  
Vol 20 (4) ◽  
pp. 227-236 ◽  
Author(s):  
Sara Holmberg ◽  
Anders Thelin ◽  
Eva-Lena Stiernström
Keyword(s):  
Social Support ◽  
Psychosocial Factors ◽  
Sense Of Coherence ◽  
Living Conditions ◽  
Strong Negative Correlation ◽  
Cross Sectional ◽  
Positive Correlation ◽  
Work Related ◽  
Job Demand ◽  
The Mean

Summary: The concept of “sense of coherence” (SOC) has been widely recognized since it was first introduced by Antonovsky. The originality and usefulness of the SOC scale and its relation to other psychosocial measures has been the subject of lively debate. The aim of this paper was to test for associations between SOC and work-related psychosocial factors (mainly the Job Demand-Control model), general living conditions, education, and social network factors. Cross-sectional data from a population-based sample of 1782 rural males from nine counties in Sweden were analyzed with a multiple regression technique. The subjects were occupationally active at inclusion and the mean age was 50 years (range 40-60). SOC was assessed with the original 29-item questionnaire. Psychosocial variables and lifestyle factors were assessed using questionnaires and structured interviews. The mean SOC among the subjects was 152.3 (standard deviation, 19.4). A strong negative correlation was found between SOC and job demand, whereas a positive correlation with job control was demonstrated. A positive correlation with general living conditions and with social support was also found. However, there was no correlation to education and occupation. Thus, SOC was shown to be strongly correlated to work-related psychosocial factors and social support, but independent of sociodemographic factors.

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