Causal explanations for lack of pregnancy applying the common sense model of illness representation to the fertility context

Abstract

Objectives: The current study explored causal explanations for lack of pregnancy and association with help-seeking behaviour. Differences based on gender and country Human Development Index were examined.

Design: A mixed method design was used.

Main outcome measures: Data were drawn from the International Fertility Decision-Making Study, a cross-sectional study of 10,045 individuals (1690 men; 8355 women) from 79 countries. Respondents rated to what extent they believed their lack of pregnancy was due to something they or their partner had done/not done or other factors and described their reasons for making this rating.

Results: Respondents were aged 18–50 (M?=?31.83) years, partnered and had been trying to achieve a pregnancy/father a child for over six months (M?=?2.8 years). Men and women primarily believed their lack of pregnancy was due to medical problems or chance/bad luck. Thematic analysis of textual responses from 29.7% of the sample found that respondents focused on their personal experience or a salient life event when describing the cause of their lack of pregnancy. Women expressed more regret and helplessness about causes than men. Significant country differences were observed.

Conclusions: Individuals may develop inaccurate causal explanations based on their personal experiences. Access to accurate information is necessary to facilitate timely help-seeking.     

Causal attributions for heart disease: A systematic review

Abstract

The aims of this systematic literature review are to describe the pattern of attributions made for the causes of heart disease, and to determine how this pattern varies with the method by which attributions are elicited, and the respondent group.

A search yielded 47 papers and reports, containing 54 datasets. Lifestyle factors and chronic stress were the most common causes cited across all datasets. Attributions to stressors and fate or luck were more likely to be reported in studies that used interval rating scales than in studies that used dichotomous ratings. Cardiac patients were more likely to mention stressors and fate or luck as causes of heart disease; non-patients rated being overweight and hypertensive as more important

The differences observed between the responses of patients and non-patients may be due to actor - observer differences, or to a methodological difference: patients are often asked to report their own experiences whereas non-patients are asked about the general case.     

Response to commentaries on discussion paper Gene–environment interdependence

There is a high measure of agreement on the key issues concerning gene–environment interdependence. Contrary to arguments on the need for direct exact replication of findings, it is suggested that “robust” replication using the same constructs is needed. RCTs have an important role for testing for environmental mediation but cannot be used for environmental risks in childhood that show G×E in relation to adult outcomes. Instead, greater use needs to be made of natural experiments. Experimental methods are needed to study biological mediating mechanisms and these should include both animal models and human brain imaging studies. In addition to further research on G×E, further studies of gene–environment correlations are required. Many challenges remain but the future for gene–environment interdependence is bright.     

Encouraging children to think counterfactually enhances blocking in a causal learning task

According to a higher order reasoning account, inferential reasoning processes underpin the widely observed cue competition effect of blocking in causal learning. The inference required for blocking has been described as modus tollens (if p then q, not q therefore not p). Young children are known to have difficulties with this type of inference, but research with adults suggests that this inference is easier if participants think counterfactually. In this study, 100 children (51 five-year-olds and 49 six- to seven-year-olds) were assigned to two types of pretraining groups. The counterfactual group observed demonstrations of cues paired with outcomes and answered questions about what the outcome would have been if the causal status of cues had been different, whereas the factual group answered factual questions about the same demonstrations. Children then completed a causal learning task. Counterfactual pretraining enhanced levels of blocking as well as modus tollens reasoning but only for the younger children. These findings provide new evidence for an important role for inferential reasoning in causal learning.     

Drawing Causal Inferences Using Propensity Scores: A Practical Guide for Community Psychologists

Confounding present in observational data impede community psychologists’ ability to draw causal inferences. This paper describes propensity score methods as a conceptually straightforward approach to drawing causal inferences from observational data. A step-by-step demonstration of three propensity score methods—weighting, matching, and subclassification—is presented in the context of an empirical examination of the causal effect of preschool experiences (Head Start vs. parental care) on reading development in kindergarten. Although the unadjusted population estimate indicated that children with parental care had substantially higher reading scores than children who attended Head Start, all propensity score adjustments reduce the size of this overall causal effect by more than half. The causal effect was also defined and estimated among children who attended Head Start. Results provide no evidence for improved reading if those children had instead received parental care. We carefully define different causal effects and discuss their respective policy implications, summarize advantages and limitations of each propensity score method, and provide SAS and R syntax so that community psychologists may conduct causal inference in their own research.     

Reducing Youth Access to Alcohol: Findings from a Community-Based Randomized Trial

Underage drinking continues to be an important public health problem and a challenge to the substance abuse prevention field. Community-based interventions designed to more rigorously control underage access to alcohol through retailer education and greater enforcement of underage drinking laws have been advocated as potentially effective strategies to help address this problem, but studies designed to evaluate such interventions are sparse. To address this issue we conducted a randomized trial involving 36 communities to test the combined effectiveness of five interrelated intervention components designed to reduce underage access to alcohol. The intervention was found to be effective in reducing the likelihood that retail clerks would sell alcohol to underage-looking buyers, but did not reduce underage drinking or the perceived availability of alcohol among high school students. Post hoc analyses, however, revealed significant associations between the level of underage drinking law enforcement in the intervention communities and reductions in both 30-day use of alcohol and binge drinking. The findings highlight the difficulty in reducing youth drinking even when efforts to curtail retail access are successful. Study findings also suggest that high intensity implementation of underage drinking law enforcement can reduce underage drinking. Any such effects of enhanced enforcement on underage drinking appear to be more directly attributable to an increase in perceived likelihood of enforcement and the resultant perceived inconveniences and/or sanctions to potential drinkers, than to a reduction in access to alcohol per se.     

Temporal information and children's and adults' causal inferences

Three experiments examined whether children and adults would use temporal information as a cue to the causal structure of a three-variable system, and also whether their judgements about the effects of interventions on the system would be affected by the temporal properties of the event sequence. Participants were shown a system in which two events B and C occurred either simultaneously (synchronous condition) or in a temporal sequence (sequential condition) following an initial event A. The causal judgements of adults and 6–7-year-olds differed between the conditions, but this was not the case for 4-year-olds' judgements. However, unlike those of adults, 6–7-year-olds' intervention judgements were not affected by condition, and causal and intervention judgements were not reliably consistent in this age group. The findings support the claim that temporal information provides an important cue to causal structure, at least in older children. However, they raise important issues about the relationship between causal and intervention judgements.     

The double-edged sword of pedagogy: Instruction limits spontaneous exploration and discovery

Motivated by computational analyses, we look at how teaching affects exploration and discovery. In Experiment 1, we investigated children’s exploratory play after an adult pedagogically demonstrated a function of a toy, after an interrupted pedagogical demonstration, after a naïve adult demonstrated the function, and at baseline. Preschoolers in the pedagogical condition focused almost exclusively on the target function; by contrast, children in the other conditions explored broadly. In Experiment 2, we show that children restrict their exploration both after direct instruction to themselves and after overhearing direct instruction given to another child; they do not show this constraint after observing direct instruction given to an adult or after observing a non-pedagogical intentional action. We discuss these findings as the result of rational inductive biases. In pedagogical contexts, a teacher’s failure to provide evidence for additional functions provides evidence for their absence; such contexts generalize from child to child (because children are likely to have comparable states of knowledge) but not from adult to child. Thus, pedagogy promotes efficient learning but at a cost: children are less likely to perform potentially irrelevant actions but also less likely to discover novel information.     

When good evidence goes bad: the weak evidence effect in judgment and decision-making

An indispensable principle of rational thought is that positive evidence should increase belief. In this paper, we demonstrate that people routinely violate this principle when predicting an outcome from a weak cause. In Experiment 1 participants given weak positive evidence judged outcomes of public policy initiatives to be less likely than participants given no evidence, even though the evidence was separately judged to be supportive. Experiment 2 ruled out a pragmatic explanation of the result, that the weak evidence implies the absence of stronger evidence. In Experiment 3, weak positive evidence made people less likely to gamble on the outcome of the 2010 United States mid-term Congressional election. Experiments 4 and 5 replicated these findings with everyday causal scenarios. We argue that this “weak evidence effect” arises because people focus disproportionately on the mentioned weak cause and fail to think about alternative causes.