Search for authorsSearch for similar articles
4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      When Love Hurts – Mental and Physical Health Among Recently Divorced Danes

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The last decades of research have consistently found strong associations between divorce and adverse health outcomes among adults. However, limitations of a majority of this research include (a) lack of “real-time” research, i.e., research employing data collected very shortly after juridical divorce where little or no separation periods have been effectuated, (b) research employing thoroughly validated and population-normed measures against which study results can be compared, and (c) research including a comprehensive array of previously researched sociodemographic- and divorce-related variables. The current cross-sectional study, including 1,856 recently divorced Danes, was designed to bridge these important gaps in the literature. Mental and physical health were measured using the Short Form 36 (SF-36)-2. Analyses included correlational analyses, t-test comparisons, and hierarchical multiple regression analyses. The study found that the health-related quality of life of Danish divorcees was significantly worse than the comparative background population immediately following divorce. Across gender, higher levels of divorce conflict were found to predict worse mental health, and worse physical health for women, even when controlling for other socio-demographic variables and divorce characteristics. Among men, lower age and higher income predicted better physical health, while more children, more previous divorces, participant divorce initiation, new partner status, and lower levels of divorce conflict predicted better mental health. Among women, higher income, fewer previous divorces, new partner status, and lower levels of divorce conflict predicted better physical health while higher income, participant divorce initiation, new partner status, and lower levels of divorce conflict predicted better mental health. The findings underscore the relevance of providing assistance to divorcees who experience higher levels of divorce conflict immediately following divorce, in seeking to reduce potential long-term negative health effects of divorce.

          Related collections

          Most cited references56

          • Record: found
          • Abstract: not found
          • Article: not found

          Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Principled missing data methods for researchers

            The impact of missing data on quantitative research can be serious, leading to biased estimates of parameters, loss of information, decreased statistical power, increased standard errors, and weakened generalizability of findings. In this paper, we discussed and demonstrated three principled missing data methods: multiple imputation, full information maximum likelihood, and expectation-maximization algorithm, applied to a real-world data set. Results were contrasted with those obtained from the complete data set and from the listwise deletion method. The relative merits of each method are noted, along with common features they share. The paper concludes with an emphasis on the importance of statistical assumptions, and recommendations for researchers. Quality of research will be enhanced if (a) researchers explicitly acknowledge missing data problems and the conditions under which they occurred, (b) principled methods are employed to handle missing data, and (c) the appropriate treatment of missing data is incorporated into review standards of manuscripts submitted for publication.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              How can I deal with missing data in my study?

              Missing data in medical research is a common problem that has long been recognised by statisticians and medical researchers alike. In general, if the effect of missing data is not taken into account the results of the statistical analyses will be biased and the amount of variability in the data will not be correctly estimated. There are three main types of missing data pattern: Missing Completely At Random (MCAR), Missing At Random (MAR) and Not Missing At Random (NMAR). The type of missing data that a researcher has in their dataset determines the appropriate method to use in handling the missing data before a formal statistical analysis begins. The aim of this practice note is to describe these patterns of missing data and how they can occur, as well describing the methods of handling them. Simple and more complex methods are described, including the advantages and disadvantages of each method as well as their availability in routine software. It is good practice to perform a sensitivity analysis employing different missing data techniques in order to assess the robustness of the conclusions drawn from each approach.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                30 November 2020
                2020
                : 11
                : 578083
                Affiliations
                Department of Public Health, University of Copenhagen , Copenhagen, Denmark
                Author notes

                Edited by: Tea L. Trillingsgaard, Aarhus University, Denmark

                Reviewed by: Lisbeth Loft, University of Copenhagen, Denmark; Frode Thuen, Western Norway University of Applied Sciences, Norway

                *Correspondence: Gert Martin Hald, ghald@ 123456sund.ku.dk

                This article was submitted to Personality and Social Psychology, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2020.578083
                7734469
                40eb09da-fe6c-42ae-9462-27810f46c31f
                Copyright © 2020 Sander, Strizzi, Øverup, Cipric and Hald.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 June 2020
                : 09 November 2020
                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 55, Pages: 11, Words: 0
                Funding
                Funded by: Carlsbergfondet 10.13039/501100002808
                Award ID: CF16-0094
                Categories
                Psychology
                Original Research

                Clinical Psychology & Psychiatry
                divorce,divorce intervention,mental health,physical health,danes
                Clinical Psychology & Psychiatry
                divorce, divorce intervention, mental health, physical health, danes

                Comments

                Comment on this article