Risk Factors for Depression: Differential Across Age?

Schaakxs, Roxanne; Comijs, Hannie C.; Mast, Roos C. van der; Schoevers, Robert A.; Beekman, Aartjan; Penninx, Brenda W. J. H.

doi:10.1016/j.jagp.2017.04.004

Cited by 111 publications

(62 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The complex bi-directional relationship between pain and depression is well documented in the literature [33][34][35]. Schaakxs et al [36] found that pain, based on a combination of pain intensity and pain disability experienced, was a strong risk factor for depression. Additionally, depression is associated with developing chronic pain [34].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Predictors of persistent prescription opioid analgesic use among people without cancer in Australia

Lalic

Gisev

Bell

et al. 2018

Brit J Clinical Pharma

View full text Add to dashboard Cite

Patient-specific characteristics (older age, prior history of mental health comorbidities and use of non-opioid analgesics) and prescriber choice of initial opioid (transdermal formulation and higher total OMEs) were found to strongly predict persistent use. This information may help prescribers target monitoring and early intervention efforts in order to prevent harms associated with the long-term use of opioids.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Schaakxs et al . found that pain, based on a combination of pain intensity and pain disability experienced, was a strong risk factor for depression. Additionally, depression is associated with developing chronic pain .…”

Section: Discussionmentioning

confidence: 99%

Predictors of persistent prescription opioid analgesic use among people without cancer in Australia

Lalic

Gisev

Bell

et al. 2018

Brit J Clinical Pharma

View full text Add to dashboard Cite

show abstract

“…The long-term disease and treatment process make the patient susceptible to stress (Poole, Dickens, & Steptoe, 2011;Semium, 2006). In addition, the average depression occurs at the age of 40-59 years (Schaakxs et al, 2017). CHD patients with low socioeconomic status were Per sen tas e res pon den (%) found to experience symptoms of depression (Steptoe et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Hubungan Antara Dukungan Sosial Dengan Depresi Pada Pasien Penyakit Jantung Koroner (The Correlation Between Social Support and Depression in Coronary Heart Disease Patient )

Chaerunnisa

Nuraeni

Hernawaty

2018

Journal Nursing Care and Biomolecular

View full text Add to dashboard Cite

Introduction: Depression is a major predictor that decreases the quality of life of patient with Coronary Heart Disease (CHD). One of the factors associated with depression is social support. The relationship between social support and depression in coronary heart disease patients has not been researched yet in Indonesia. This study aims to know the correlation between social support and depression in patients with CAD. Method: This research used descriptive correlation method with cross sectional approach. This study was conducted 77 CHD outpatients in one of the government hospitals. Data were collected through questionnaires. The first is ENRICHD Social Support Inventory (ESSI) questionnaire with validity value r = 0.036-0.663, p <0.01 and Cronbach's α is 0.818. The second is Beck Depression Inventory II (BDI II) questionnaire with validity value r = 0.39-0.52, p <0.01 and Cronbach's α is 0.90. The data is analyzed by univariate (frequency distribution) and bivariate (rank spearman). Result: The results showed that non depression patients were 72.7% and depression patients were 27.3%, with mild depression (14.3%), moderate (7.8%) and severe (5.2%). Patients with high social support were 64.9% and low social supports were 35.1%. The Correlation between social support and depression had a p value of 0,000 (r=-0.467). Conclusion: The correlation between social support and depression was moderate and the direction of the relationship was negative. High social support caused lower depression. Therefore, social support should be improved in order to avoid depression in patient with CHD.

show abstract

“…Other factors can be mediating direction and rate of changes of affectivity over life-span. Netherlands Study of Depression and Anxiety [12] found that number of chronic disease is a risk factor of depression. Understanding the trends and characteristics of the time course development of affectivity over life-span could lead to targeted community and behavioral medicine programs tailored to the necessities of the aging population.…”

Section: Introductionmentioning

confidence: 99%

Life Span Changes in Affectivity and Influence of Gender, Health Self-rate, Morbidity, Memory and Mental Stress

Kaipov¹,

Sanchez-Gonzalez²,

May³

et al. 2018

J Psychiatry

View full text Add to dashboard Cite

Background:The aim of the present study was (i) examine positive and negative affectivity, its rate of change, gender specificity and (ii) explore the association between health self-rating, number of chronic diseases, memory, and mental stress.Methods: Data obtained from the Longitudinal Study of Generation was used to assess participants in 3-year intervals from 1985 to 2000. Positive and negative affect along with health self-rating, morbidity, memory, mental stress were assessed. Results:A total of 2024 participants (aged 16-99 years; 57% Female) were considered for analysis. Linear growth models showed that both positive and negative affect decrease over generations. There was no difference between genders for positive affect; negative affect decreased in higher degree in females than in males. Health self-rates increased along the life span with no gender differences. Morbidity increased; memory did not change over generations in both genders. Mental stress didn't change over generations, but was higher in females. Lower health self-rate was associated with higher negative affect and a deeper drop of positive affect later in life. Higher morbidity was associated with lower positive affect. Memory worsening was associated with a decrease of positive affect. Mental stress was a predictive factor for lower positive and higher negative affect. Conclusion: Possible unfavorable influence of decrease of positive affect with life progression is balanced with concomitant decrease of negative affect. Negative affect seems to be more independent from somatic morbidity than positive affect and has higher gender specificity by being lower in females. No significant association between negative affect and morbidities was found in both intercept and slop.Negative affect low morbidity=2.070-(0.155) × (time)Negative affect high morbidity=1.955 NS -(0.097 NS ) × (time) Positive and negative affect controlling for memoryNo difference in positive affect at baseline at time=0 between people with good and bad memory noted. Worsening memory was associated with more pronounced drop of positive affect at aging, as evident by significant negative slope (Figure 9).Positive affect good memory=5.020-(0.233) × (time) Figure 5: Health self-rate controlling for gender.Figure 6: Memory, health self-rate, morbidity and mental stress controlling for gender.Positive affect worst memory=(4.973 NS )-(0.344**) × (time)No difference was found between people with good or bad memory in both intercept and slope of negative affect.Negative affect good memory=(1.159)-(0.150) × (time) Negative affect worst memory=(1.319 NS )-(0.120 NS ) × (time)

show abstract

Risk Factors for Depression: Differential Across Age?

Cited by 111 publications

References 42 publications

Predictors of persistent prescription opioid analgesic use among people without cancer in Australia

Predictors of persistent prescription opioid analgesic use among people without cancer in Australia

Hubungan Antara Dukungan Sosial Dengan Depresi Pada Pasien Penyakit Jantung Koroner (The Correlation Between Social Support and Depression in Coronary Heart Disease Patient )

Life Span Changes in Affectivity and Influence of Gender, Health Self-rate, Morbidity, Memory and Mental Stress

Contact Info

Product

Resources

About