Writing a discussion section: how to integrate substantive and statistical expertise

Avoidance of causality outside experiments: Hypotheses from cognitive dissonance reduction

The avoidance of causality in the design, analysis and interpretation of non-experimental studies has often been criticised as an untenable scientific stance, because theories are based on causal relations (and not associations) and a rich set of methodological tools for causal analysis has been developed in recent decades. Psychology researchers (n = 106 with complete data) participated in an online study presenting a causal statement about the results of a fictitious paper on the potential effect of drinking clear water for years on the risk of dementia. Two randomised groups of participants were then asked to reflect on the conflict between the goal of approaching a causal answer and the prevailing norm of avoiding doing so. One of the two groups was also instructed to think about possible benefits of addressing causality. Both groups then responded to a list of 19 items about attitudes to causal questions in science. A control group did this without reflecting on conflict or benefits. Free-text assessments were also collected during reflection, giving some indication of how and why causality is avoided. We condense the exploratory findings of this study into five new hypotheses about the how and why, filtered through what can be explained by cognitive dissonance reduction theory. These concern the cost of addressing causality, the variety of ways in which dissonance can be reduced, the need for profound intervention through teaching and social aspects. Predictions are derived from the hypotheses for confirmation trials in future studies and recommendations for teaching causality. Open data are provided for researchers' own analyses.

Applied relaxation and cortisol secretion: findings from a randomized controlled indicated prevention trial in adults with stress, anxiety, or depressive symptoms

Previous research has shown that relaxation interventions can reduce distress, anxiety, and depression. The exact mechanisms that underlie the efficacy of relaxation interventions remain unresolved. This study aimed to investigate whether applied relaxation (AR) leads to changes in cortisol secretion and whether these effects mediate fewer symptoms due to AR. Data come from a randomized controlled preventive interventional trial (N = 277) with elevated tension/distress, anxiety, or depressive symptomatology. Participants were randomized to an intervention group (IG; n = 139, received AR training), or a non-interventional control group (CG, n = 138). Psychopathological symptoms were assessed with DASS-21 and diagnoses of mental disorders via DIA-X-5. Cortisol was measured as short-term index in saliva (six times/d for 2 d at pre-, post-, and follow-up [FU] assessment) and long-term index in hair samples (once at pre-assessment and FU, respectively). Data were analyzed as pre-specified secondary analyses of the randomized controlled trial (RCT) on completer basis (n = 134 CG, n = 102 IG), using multivariable-adjusted linear regression models and mediation analyses (the DASS-21 change in the IG vs. CG with cortisol (area under the curve [AUC]) as mediator). From pre- to post-assessment, total daily salivary cortisol (AUC) decreased more strongly in the IG vs. CG (β-coefficient: -13.83, 95% confidence interval [CI]: -26.85 to -0.81), but was rendered non-significant when adjusting for pre-assessment AUC. This effect was not found for the cortisol awakening response (CAR) or hair cortisol. There was no evidence for a mediation of cortisol (AUC). These findings provide little support for the idea that cortisol reductions explain the beneficial effects of AR on mental health.

Reporting guidelines for human microbiome research: the STORMS checklist

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

Qualitative Approximations to Causality: Non-Randomizable Factors in Clinical Psychology

Background

Causal quests in non-randomized studies are unavoidable just because research questions are beyond doubt causal (e.g., aetiology). Large progress during the last decades has enriched the methodical toolbox.

Aims

Summary papers mainly focus on quantitative and highly formal methods. With examples from clinical psychology, we show how qualitative approaches can inform on the necessity and feasibility of quantitative analysis and may yet sometimes approximate causal answers.

Results

Qualitative use is hidden in some quantitative methods. For instance, it may yet suffice to know the direction of bias for a tentative causal conclusion. Counterfactuals clarify what causal effects of changeable factors are, unravel what is required for a causal answer, but do not cover immutable causes like gender. Directed acyclic graphs (DAGs) address causal effects in a broader sense, may give rise to quantitative estimation or indicate that this is premature.

Conclusion

No method is generally sufficient or necessary. Any causal analysis must ground on qualification and should balance the harms of a false positive and a false negative conclusion in a specific context.

Using a Manuscript Template to Foster Dissemination of Doctoral Students' Literature Reviews

BACKGROUND

The author was asked to teach a new PhD course, Developing Literature Reviews. The course objective is to have students prepare a structured (e.g., integrative, systematic) literature review manuscript that is suitable for publication submission.

METHOD

Course pedagogy and materials were created, including a novel literature review manuscript template. The template served as a guide for communicating essential section components of a rigorous and reproducible literature review manuscript and allowed for an iterative process and efficient faculty-student evaluation system to simulate the peer-review process. To measure student outcomes, standardized course evaluations were reviewed, and the number of students who were successful in disseminating manuscripts was recorded.

RESULTS

Students' standardized course evaluations were high. Eighteen students published integrative or systematic literature reviews as first author. Eleven students have presented peer-reviewed abstracts at scientific conferences.

CONCLUSION

The template successfully facilitates PhD student dissemination. The Doctor of Nursing Practice student pedagogy may also benefit from the template. [J Nurs Educ. 2021;60(2):111-115.].

The Principles of Biomedical Scientific Writing: Discussion

The discussion section of a scientific paper is supposed to interpret and elucidate the significance of the study findings, highlight current knowledge available on the research problem being investigated, and explain the novel aspects emerging from the findings of the study in moving the field forward. A well-written discussion should provide clear "statements of the main findings", "possible explanations and implications", "strengths and weaknesses of the study and other studies", "unanswered questions", and "suggestions for future research". The authors also need to clarify the external validity of the findings and show how the findings can be generalized. In this review, we focus on the function, content, and organization of the "discussion section" of a hypothesis-testing paper. Beyond providing the most important principles and common strategies for organizing the discussion section, we also discuss metadiscourse, scientific explanation (reasoning and contextualization), and models of scientific explanation.