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      Daily support seeking as coping strategy in dual-smoker couples attempting to quit

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      Psychology & Health
      Routledge

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          Abstract

          Objective

          Smoking cessation is a stressful event and lapses are frequent. The dynamic model of relapse has been criticized for not integrating interpersonal factors as phasic influences. Seeking social support, as a coping strategy to deal with cravings, may help to refrain from smoking.

          Design

          Overall, 83 heterosexual dual-smoker couples reported on their craving, the extent of seeking social support from one’s partner regarding smoking cessation, and their number of cigarettes smoked in smartphone-based end-of-day diaries, from a joint self-set quit date on across 22 consecutive days.

          Main outcome measure

          Number of cigarettes smoked.

          Results

          Multilevel analyses indicated that on days with higher-than-average levels of craving, male and female smokers reported more cigarettes smoked. Higher-than-usual support seeking was related to fewer cigarettes smoked that same day. For women only, we found a within-person interaction between craving and support seeking on smoking. On days with higher-than-average support-seeking, the effect of craving on smoking was attenuated.

          Conclusion

          Findings confirm the relevance of interpersonal processes in the relapse process, such as support seeking as coping behavior. Further, as a ‘first act’ in initiating supportive interactions, support seeking is an important piece in the social support process and a promising target for interventions.

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          Most cited references68

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          Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

          Summary Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning. Funding Bill & Melinda Gates Foundation.
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            Random effects structure for confirmatory hypothesis testing: Keep it maximal.

            Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F 1 and F 2 tests, and in many cases, even worse than F 1 alone. Maximal LMEMs should be the 'gold standard' for confirmatory hypothesis testing in psycholinguistics and beyond.
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              Social relationships and health.

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                Author and article information

                Journal
                Psychol Health
                Psychol Health
                Psychology & Health
                Routledge
                0887-0446
                1476-8321
                21 May 2021
                2022
                21 May 2021
                : 37
                : 7
                : 811-827
                Affiliations
                Department of Psychology, University of Zurich , Zurich, Switzerland
                Author notes
                CONTACT Philipp Schwaninger philipp.schwaninger@ 123456psychologie.uzh.ch Department of Psychology, Applied Social and Health Psychology, University of Zurich , Binzmuehlestrasse 14 / Box 14, Zürich8050, Switzerland Supplemental data for this article can be accessed online at https://doi.org/10.1080/08870446.2021.1913157
                Author information
                https://orcid.org/0000-0001-8202-3078
                https://orcid.org/0000-0003-2453-1925
                https://orcid.org/0000-0002-5078-3539
                https://orcid.org/0000-0003-0184-5921
                Article
                1913157
                10.1080/08870446.2021.1913157
                9344997
                34019454
                1f3c77fa-98a6-47bb-a9b7-cfbe27073888
                © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

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                Page count
                Figures: 1, Tables: 2, Pages: 17, Words: 10550
                Categories
                Research Article
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                Clinical Psychology & Psychiatry
                Clinical Psychology & Psychiatry

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