Cantril Self-Anchoring Striving Scale

Glatzer, Wolfgang; Gulyas, Jennifer

doi:10.1007/978-94-007-0753-5_259

Cited by 39 publications

(27 citation statements)

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“…“difficulty falling asleep”, “awakening during night-time”, “early awakening with difficulty getting back to sleep” and “use of sleeping pills”) and drowsiness (i.e. “being so sleepy at daytime as to need a nap”, “not feeling rested in the morning”, and the Epworth Sleepiness Scale) in ENRICA (39); prevalence and characteristics of pain (ENRICA) (40); history of physician-diagnosed coronary heart disease, congestive heart failure, angina or cancer at any site (all cohorts but EXERNET ), mobility limitations, in ENRICA (41); the Mini-Mental State Examination Score (MMSE) (42) ( ENRICA and ES ); the Cantril’s Ladder of Life Scale (43) ( ENRICA and ES ), and a negative ageing experience scale that ranged from 1 (very positive experience) to 5 (very negative experience) ( ENRICA ).…”

Section: Methodsmentioning

confidence: 99%

Changes in health behaviors, mental and physical health among older adults under severe lockdown restrictions during the COVID-19 pandemic in Spain

García‐Esquinas

Ortol

Gine-Vazquez

et al. 2021

Preprint

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Background: We aimed to examine main changes in health behaviors, mental and physical health among older adults under severe lockdown restrictions during the COVID-19. Methods: We used prospective data from 3041 participants in four cohorts of community-dwelling individuals aged ≥65 years in Spain. Data were obtained using validated questionnaires through a pre-pandemic face-to-face interview and a telephone interview conducted between weeks 7 to 15 after the beginning the COVID-19 lockdown. Lineal or multinomial, as appropriate, regression models with adjustment for the main confounders were used to assess changes in the outcome variables from the pre-pandemic to the confinement period, and to identify their associated factors. Results: On average, the confinement was not associated with a deterioration in lifestyle risk factors (smoking, alcohol intake, diet or weight), except for a decreased physical activity and increased sedentary time, which reversed with the end of confinement. However, chronic pain worsened, and moderate declines in mental health, that did not seem to reverse after restrictions were lifted, were observed. Several subgroups of individuals were at increased risk of developing unhealthier lifestyles or mental health decline with confinement: (i)-males (for physical activity and sedentariness), (ii)-those with greater social isolation (for diet, physical activity, mental health), (iii)-feelings of loneliness (for diet, sleep quality, mental health), (iv)-poor housing conditions (for diet, physical activity, TV viewing time), (v)-unhealthy sleep duration (for physical activity and sedentariness), and (vi-worse overall health or chronic morbidities (for physical activity, screen time, mental health). On the other hand, previously having a greater adherence to the Mediterranean diet and doing more physical activity protected older adults from developing unhealthier lifestyles with confinement. Conclusions: The lockdown during the first wave of the COVID-19 in Spain, which was one of the most restrictive in Europe, only led to minor average changes in health behaviors among older adults. However, mental health was moderately affected. If another lockdown were imposed on this or future pandemics, public health programs should specially address the needs of older individuals with male sex, greater social isolation, poor housing conditions and chronic morbidities, because of their greater vulnerability to the enacted movement restrictions

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Section: Methodsmentioning

confidence: 99%

Changes in health behaviors, mental and physical health among older adults under severe lockdown restrictions during the COVID-19 pandemic in Spain

García‐Esquinas

Ortol

Gine-Vazquez

et al. 2021

Preprint

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“…Gallup regularly conducts public opinion polls and annually conducts interviews with a large number of inhabitants of many different countries. 2 The happiness of the interviewees was assessed with the Cantril Self-Anchoring Striving Scale (Glatzer & Gulyas, 2014). In addition, interviewees were asked about a variety of topics and the obtained data are distilled into six variables that may relate to happiness.…”

Section: Example: World Happiness Datamentioning

confidence: 99%

A tutorial on Bayesian multi-model linear regression with BAS and JASP

et al. 2021

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Linear regression analyses commonly involve two consecutive stages of statistical inquiry. In the first stage, a single ‘best’ model is defined by a specific selection of relevant predictors; in the second stage, the regression coefficients of the winning model are used for prediction and for inference concerning the importance of the predictors. However, such second-stage inference ignores the model uncertainty from the first stage, resulting in overconfident parameter estimates that generalize poorly. These drawbacks can be overcome by model averaging, a technique that retains all models for inference, weighting each model’s contribution by its posterior probability. Although conceptually straightforward, model averaging is rarely used in applied research, possibly due to the lack of easily accessible software. To bridge the gap between theory and practice, we provide a tutorial on linear regression using Bayesian model averaging in , based on the BAS package in . Firstly, we provide theoretical background on linear regression, Bayesian inference, and Bayesian model averaging. Secondly, we demonstrate the method on an example data set from the World Happiness Report. Lastly, we discuss limitations of model averaging and directions for dealing with violations of model assumptions.

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“…Each year Gallup, a research-based consulting company, conducts a series of interviews with inhabitants of multiple countries. During those interviews, the interviewees' happiness is measured using the Cantril Self-Anchoring Striving Scale (Glatzer and Gulyas, 2014), and questions are asked about several other demographic factors. 9 Altogether, a score for Wealth (W),…”

Section: Illustrative Examplementioning

confidence: 99%

A Review of Applications of the Bayes Factor in Psychological Research

Heck¹,

Hoijtink²,

Fu³

et al. 2020

Preprint

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The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The paper is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines.

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Cantril Self-Anchoring Striving Scale

Cited by 39 publications

References 0 publications

Changes in health behaviors, mental and physical health among older adults under severe lockdown restrictions during the COVID-19 pandemic in Spain

Changes in health behaviors, mental and physical health among older adults under severe lockdown restrictions during the COVID-19 pandemic in Spain

A tutorial on Bayesian multi-model linear regression with BAS and JASP

A Review of Applications of the Bayes Factor in Psychological Research

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