Friday, April 8, 2022

2003-2018: Psychiatrists had the highest suicide rate among health professionals

Li, T., Petrik, M. L., Freese, R. L., & Robiner, W. N. (2022). Suicides of psychologists and other health professionals: National Violent Death Reporting System data, 2003–2018. American Psychologist, Apr 2022.

Abstract: Suicide is a prevalent problem among health professionals, with suicide rates often described as exceeding that of the general population. The literature addressing suicide of psychologists is limited, including its epidemiological estimates. This study explored suicide rates in psychologists by examining the National Violent Death Reporting System (NVDRS), the Centers for Disease Control and Prevention’s data set of U.S. violent deaths. Data were examined from participating states from 2003 to 2018. Trends in suicide deaths longitudinally were examined. Suicide decedents were characterized by examining demographics, region of residence, method of suicide, mental health, suicidal ideation, and suicidal behavior histories. Psychologists’ suicide rates are compared to those of other health professionals. Since its inception, the NVDRS identified 159 cases of psychologist suicide. Males comprised 64% of decedents. Average age was 56.3 years. Factors, circumstances, and trends related to psychologist suicides are presented. In 2018, psychologist suicide deaths were estimated to account for 4.9% of suicides among 10 selected health professions. As the NVDRS expands to include data from all 50 states, it will become increasingly valuable in delineating the epidemiology of suicide for psychologists and other health professionals and designing prevention strategies.

Contrary to previous research findings, our findings suggest that third-party observers cannot reliably detect attraction in others

Can third-party observers detect attraction in others based on subtle nonverbal cues? Iliana Samara, Tom S. Roth, Milica Nikolic, Eliska Prochazkova & Mariska E. Kret. Current Psychology, Apr 8 2022.

Abstract: In a series of three studies, we examined whether third-party observers can detect attraction in others based on subtle nonverbal cues. We employed video segments of dates collected from a speed-dating experiment, in which daters went on a brief (approx. 4 min) blind-date and indicated whether they would like to go on another date with their brief interaction partner or not. We asked participants to view these stimuli and indicate whether or not each couple member is attracted to their partner. Our results show that participants could not reliably detect attraction, and this ability was not influenced by the age of the observer, video segment location (beginning or middle of the date), video duration, or general emotion recognition capacity. Contrary to previous research findings, our findings suggest that third-party observers cannot reliably detect attraction in others. However, there was one exception: Recognition rose above chance level when the daters were both interested in their partners compared to when they were not interested.

General discussion

In a series of three experiments, we found no strong evidence supporting the notion that people can reliably detect attraction or its absence in thin video slices of people on a date based on nonverbal subtle emotional cues. However, we found that accuracy was increased based on whether the person presented in the video was attracted to their partner. Specifically, we found that the third-party observers were more accurate in detecting attraction when the daters were attracted to their partners than detecting the absence of attraction when the daters indicated not being attracted to their partner. In addition, recognizing attraction was not influenced by age or length of the stimuli presented.

In accordance with previous findings (e.g., Place et al., 2009), we found that people cannot reliably detect attraction from initial interactions. Given that previous findings have emphasized the importance of subtle nonverbal cues in communicating attraction (e.g., Eibl-Eiblsfeldt, 1989; Keltner & Buswell, 1997), one might question whether the observed low accuracy in detecting attraction might be the result of a low frequency of occurrence of behaviours associated with attraction. In other words, was there sufficient information present in the stimuli themselves that the participants might have picked up? Indeed, we only found minor numerical differences in behaviours associated with attraction (e.g., coyness, genuine smiles) in the First Impression 3-s videos (see Supplemental Material). Thus, the observed low accuracy might result from the low frequency of behaviour occurrence. Nonetheless, our findings replicate previous research (e.g., Place et al., 2009) and further support the notion that people cannot reliably detect attraction when viewing others in the initial phases of their interaction.

Our findings do not provide support for the notion that third-party observers can detect attraction when viewing segments from later phases of a date, which contrasts with previous research (Place et al., 2009). In all experiments, participants performed near chance level independent of the length of the segment (3, 6, or 9 s) or the phase of the interaction (first impression or verbal interaction). Our analyses (see Supplementary Material) of the coded behaviours illustrate that daters that were attracted to their partner exhibited behaviours associated with attraction for a longer duration compared to daters that were not interested in their partner (in videos taken from the middle of the speed date). This finding suggests that the observed low accuracy is not due to the low frequency of behaviour occurrence. Instead, it might be more probable that people cannot detect attraction as third-party observers using thin video slices even when the signs of attraction are there.

It may be advantageous for humans to mask what they feel in certain situations, and they often use their cognitive resources to do so (Kret, 2015). This masking might render interpreting nonverbal cues more complex and thus, lead to confusion and awkward social encounters (Abbey, 1982; Abbey & Melby, 1986) when the expressions of the sender are misinterpreted (Burgoon et al., 2002; Grammer, 1990). These factors may be a source of error in people involved in a one-on-one interaction (i.e., a date), given that the high-intensity motivational environment might decrease accurate emotion detection (Maner et al., 2005; Prochazkova et al., 2021).

It has been speculated that the ability to detect attraction in others has an adaptive function, allowing people to collect more information to guide their mating choices (see Simao & Todd, 2002). However, a more parsimonious explanation would be that the ability to detect attraction as a third-party observer is merely a by-product of detecting attraction when faced with a potential mate, which would undoubtedly be a beneficial quality for anyone navigating their romantic environment. However, previous research consistently demonstrates that people cannot detect attraction in others and instead project their interest to a given partner (Lee et al., 2020; Samara, Roth, & Kret, 2020; see also Prochazkova et al., 2021). Thus, it remains possible that people cannot detect attraction above chance level.

Emotions can be efficiently detected from facial expressions (Ekman, 1992). Previous research has shown that basic emotions, such as disgust, fear, and happiness, can be recognized in scenes within 200 ms (Righart & de Gelder, 2008). This effect suggests that detection and recognition of emotional expressions likely rely on quick facial expression processing (see also Meeren, van Heijnsbergen, & de Gelder, 2005, for similar findings on the interaction between facial expressions and body language). Here, we examined whether attraction can be detected as efficiently as other emotions. Given our null findings, we cannot conclude whether indeed attraction can be detected as efficiently as other emotions based on three experiments. Future research should help elucidate how easily and accurately complex emotions like attraction are perceived and processed.

In all experiments, we consistently found that people are likely to detect attraction when the person observed is indeed exhibiting such signals. Indeed, even though attraction cannot be expressed with a single behaviour (Moore, 1985), people likely have experience in decoding such cues and are thus more likely to detect them efficiently. This is further corroborated by our consistent replication of this effect in initial encounters as well as later in the interactions irrespective of video length (3, 6, and 9 s). Date members that were attracted to their partner likely illustrated affiliation more clearly (e.g., see Grammer et al., 1999). In contrast, disinterested partners might have opted to display rejection more subtly (or perhaps not at all), making it more challenging to interpret. However, it should be noted that we did not find robust differences in attraction cues between daters that were interested in their partner compared to daters that were not in the 3-s stimuli, even though a robust difference was found for coy smiles in the 9-s stimuli. An alternative explanation for the finding is that participants were more likely to detect attraction when indeed, participants had a general propensity to respond positively rather than negatively (see Supplemental Material). This could be due to expectancy effects, given that participants were informed that these video segments are from a blind date study. Future research should further investigate the role of expectancy effects in the ability of third-party observers to detect attraction.

This finding directly contrasts with previous research (Hall et al., 2015 Experiment 2). In their study, the authors asked participants to view 1-min segments of others on a date and indicate whether they thought the person on the video was flirting with their partner. Given that the people that report feeling attracted to their partner are also more likely to report flirting (Hall et al., 2015; Experiment 1), this is a reliable indicator of detecting attraction. Furthermore, their results suggest that participants were more accurate in detecting attraction when the person depicted was not flirting than when they were flirting. The authors suggest that these findings could be due to a) the implicit risk of openly displaying interest in another, which would have rendered any flirting difficult to decode, and b) that the probability of flirting in zero-acquaintance settings is relatively low (e.g., Abbey, 1982; Saal et al., 1989); therefore, people might not be familiar with flirting expressions in such settings. We disagree with both of these interpretations. Flirting, in general, is quite ambiguous, as flirting cues are also easily confused with friendliness (Farris et al., 2008; Moore, 2010). Furthermore, previous research has documented several flirting signals in first time-encounters, such as self-grooming (McCormick, Perper, & Jones, 1983), suggesting that these are signals typically exhibited in such situations. Crucially, in a previous study (Prochazkova et al., 2021), it was found that almost half (44%) of the participants reported that they would be interested in going on another date with their partner rendering the reduced-likelihood interpretation unlikely. In short, we consistently show that attraction is detected above the chance level when it is indeed there.

Based on the Perception–Action Model of Empathy (PAM; de Waal & Preston, 2017), we expected that participants with more experience with romantic interactions (i.e., adults) would be more accurate in detecting attraction than participants with less experience with romantic interactions (i.e., children). However, in Experiment 2, we found no substantial differences between adults and children, suggesting that children’s lower accuracy in detecting attraction in Experiment 1 was likely due to cognitive overload.

One limitation that should be discussed is the fact that our responses were coded in a binary way. This approach was necessary to calculate accuracy based on the responses of the study conducted by Prochazkova et al. (2021), where responses were also coded binary. It could be argued that this approach reduced the variation that would otherwise be shown if responses were coded in a continuous way. This is indeed possible, even though it should be noted that using a scale for attraction and a binary response for another date has been shown to correlate highly (Roth et al., 2021a, 2021b). Nonetheless, future studies using speed-dating paradigms could also employ a continuous response regarding attraction and willingness to go on another date, which can then be used in studies employing third-party observers. In this manner, a more nuanced accuracy scale can be calculated.

In conclusion, here we demonstrate that people might not reliably detect when others are attracted to their partner and when not. Furthermore, we showed that the overall accuracy in detecting attraction is not influenced by age, or the phase of the interaction observed. The only factor that reliably influenced accuracy is whether attraction is indeed present.

Even when all explicit gender-identifying language was stripped from the recommendation letters, a machine learning algorithm was able to predict applicant gender at a rate better than chance

Text Mining for Bias: A Recommendation Letter Experiment. Charlotte S. Alexander. American Business Law Journal, April 6 2022.

Abstract: This article uses computational text analysis to study the form and content of more than 3000 recommendation letters submitted on behalf of applicants to a major U.S. anesthesiology residency program. The article finds small differences in form and larger differences in content. Women applicants' letters were more likely to contain references to acts of service, for example, whereas men were more likely to be described in terms of their professionalism and technical skills. Some differences persisted when controlling for standardized aptitude test scores, on which women and men scored equally on average, and other applicant and letter-writer characteristics. Even when all explicit gender-identifying language was stripped from the letters, a machine learning algorithm was able to predict applicant gender at a rate better than chance. Gender stereotyped language in recommendation letters may infect the entirety of an employer's hiring or selection process, implicating Title VII of the Civil Rights Act of 1964. Not all gendered language differences were large, however, suggesting that small changes may remedy the problem. The article closes by proposing a computationally driven system that may help employers identify and eradicate bias, while also prompting a rethinking of our gendered, racialized, ableist, ageist, and otherwise stereotyped occupational archetypes.

The road to dietary sins is paved with the whisper of justifying self-talk

Examining dietary self-talk content and context for discretionary snacking behaviour: a qualitative interview study. Jordan Rose, Rebecca Pedrazzi & Stephan U. Dombrowski. Health Psychology and Behavioral Medicine, Volume 10, 2022 - Issue 1, Pages 399-414, Apr 7 2022.


Background: Consuming discretionary snack foods high in calories, salt, sugar or fat in between regular meals can have a negative impact on weight management and health. Despite the intention to refrain from discretionary snacking, individuals often report feeling tempted by snack foods. A cognitive process to resolve food choice related tension may be dietary self-talk which is one’s inner speech around dietary choice. This study aimed to understand the content and context of dietary self-talk before consuming discretionary snack foods.

Methods: Qualitative semi-structured interviews based on Think-Aloud methods were conducted remotely. Participants answered open-ended questions and were presented with a list of 37 dietary self-talk items. Interview transcripts were analyzed thematically.

Results: Interviews (n = 18, age: 19–54 years, 9 men, 9 women) confirmed the frequent use of dietary self-talk with all 37 content items endorsed. Reported use was highest for the self-talk items: ‘It is a special occasion’; ‘I did physical activity/exercise today’; and ‘I am hungry’. Three new items were developed, eight items were refined. Identified key contextual themes were: ‘reward’, ‘social’, ‘convenience’, ‘automaticity’, and ‘hunger’.

Conclusions: This study lists 40 reasons people use to allow themselves to consume discretionary snack foods and identifies contextual factors of dietary-self talk. All participants reported using dietary self-talk, with variation in content, frequency and degree of automaticity. Recognising and changing dietary self-talk may be a promising intervention target for changing discretionary snacking behaviour.

Keywords: Dietary self-talkdiscretionary snackeating behavioursnackingthink-aloud methods

4. Discussion

4.1. Principal findings

Dietary self-talk in the context of discretionary snacking behaviour was a commonly reported phenomenon. Individuals seem to regularly use self-talk to resolve conflicts between intentions to eat healthily and to consume a snack high in fat, sugar or salt. This study verified and extended a list of 40 self-talk content items, which highlight the universal thoughts which were recognised as being used to justify discretionary snacking. When participants reflected on dietary self-talk, recurrent contextual themes were the justification of snacks as rewards, social influences of snacking, convenience-based considerations, thoughts on and the evidence of automaticity in relation to dietary self-talk and snacking behaviour and hunger. Although most participants reported intentions to avoid discretionary snacking, dietary self-talk could change these priorities suggesting that self-talk prior to snack choice situations might be a potential target for eating behaviour change interventions.

4.2. Strengths and weaknesses of the study

Little research to date has specifically explored the uses and content of dietary self-talk before eating snacks that are high in calories, salt, sugar or fat. This study revised and extended a previously developed list of dietary self-talk items, systematically capturing self-reported thought content (see Table 2). The self-talk items were formulated at a general level, rather than a specific level (e.g. ‘I did physical activity/exercise’ rather than ‘I went for a run’), allowing participants to project their own personal situations onto the item. The high level of recognition of all self-talk items suggests that the level of formulation might have been appropriate.

Several weaknesses should be kept in mind when interpreting the results of this research. Although the self-talk items were developed with input from the Italian, UK and Canadian participants, their content relevance in different cultural contexts is unknown. Moreover, the current list is the first attempt to catalogue a general dietary self-talk content around snacking and will require further refinement and extension. Individuals may also use idiosyncratic self-talk items which are specific to them and do not generalise to others; these will not have been included in the list. The groupings of the self-talk items were undertaken by the authors and different categorisations might exist (De Witt Huberts, Evers, & De Ridder, 2014; Verhoeven, Adriaanse, de Vet, Fennis, & de Ridder, 2015). Finally, the self-reported recognition of the self-talk content was high in participants, but it is not clear whether the self-talk content are thoughts that are experienced in the moment of the snacking choice context, or whether these are used as post-hoc justifications for behaviour that has already occurred.

4.3. Relation to other studies

The current study complements other research which has examined cognitions around food-based temptations. These cognitions are often referred to by different labels, such as justifications (De Witt Huberts et al., 2014; Verhoeven et al., 2015), reasons (De Witt Huberts et al., 2014; Verhoeven et al., 2015) or compensatory health beliefs (Knäuper, Rabiau, Cohen, & Patriciu, 2004).

The current study suggests dietary self-talk as one potential explanation for eating behaviour that conflicts with previous intentions. Dietary self-talk might be added to existing mechanisms of giving into temptations such as ‘attentional bias’ and ‘temporal discounting’ (Appelhans et al., 2016). In line with the goal conflict model of eating (Stroebe et al., 2013), most participants reported intentions to make healthy decisions; however, at the opportunity of eating a discretionary snack food, they reported often justifying snacking with the use of dietary self-talk. Figure 2 applies the goal conflict model of eating behaviour to a snacking context and integrates dietary self-talk as a possible mechanism, which leads to the consumption of discretionary snacks.

Figure 2. Dietary self-talk integrated into the goal conflict model of eating (Stroebe et al., 2013) applied to the discretionary snacking context.

In this model, the presence of discretionary snacks leads to the activation of the discretionary snacking goal. Dietary self-talk facilitates the activation of the discretionary snacking goal, while simultaneously inhibiting the healthy eating goal, leading to the increased likelihood of snack consumption.

Some of the content of the 40 dietary self-talk items has been captured previously in the concept of compensatory health beliefs (Knäuper et al., 2004). Compensatory health beliefs are a cognitive mechanism used in the presence of failing to resist temptations and have been defined ‘as beliefs that certain unhealthy (but pleasurable) behaviours can be compensated for by engaging in healthy behaviours’, p. 608 (Knäuper et al., 2004). Evidence suggests that compensation-based beliefs are formed during the moments of dietary conflict, and can lead to the consumption of discretionary snack foods (Kronick & Knäuper, 2010). There is some overlap between compensatory health beliefs such as ‘Breaking a diet today may be compensated for by starting a new diet tomorrow’ and the dietary self-talk items such as ‘I will start being healthier later’. However, the current list of dietary self-talk items differs from compensatory health beliefs in at least three ways. First, the dietary self-talk items go beyond compensation-based cognitions, covering additional cognitions, such as momentary based justifications including social occasions (‘It would be rude to refuse the snack’), emotions (‘I don’t care anymore/Whatever’) or rationalisations (‘This snack is cheap/on offer’). Second, the current list of dietary self-talk items is specific to the behaviour of consuming snack foods that are tempting, compared to the application of general compensatory health beliefs across several different health behaviour contexts. Third, the dietary self-talk items are thought content specific. Even when compensatory health beliefs are assessed as behaviour specific items (e.g. ‘To what extent did you think that you would compensate your snack, for example, by a subsequent sport session or with eating less the next time?’) (Amrein, Scholz, & Inauen, 2021), this differs from compensatory-related items in the dietary self-talk list, which attempt to provide a closer capture of the precise thought content (e.g. ‘Just this snack. I won’t have a snack later’).

The findings of the current study are similar to Verhoeven et al.’s (2015) study examining reasons for unhealthy snacking, which developed the 35 item reasons to snack inventory. (Verhoeven et al., 2015) The inventory asks individuals to rate the frequency of various reasons for consuming an unhealthy snack (e.g. ‘because it is a party or a birthday’, or ‘because you are watching a movie’). These reasons were grouped into six categories using factor analysis: opportunity induced eating, coping with negative emotions, enjoying a special occasion, rewarding oneself, social pressure, and gaining energy. There are several similarities between the reasons to snack inventory and thedietary self-talk list including both individual items and broad categories. Several individual items are similar in content (e.g. ‘Because you deserve it’ vs. ‘I accomplished something. I deserve it’). Moreover, several categories are similar in nature (e.g. ‘Social pressure’ vs. ‘Social Occasions/Social Rituals’) further validating the potentially broad nature of many of the cognitions and identified categories. However, there are some differences in some of the content, categories and focus. For example, the ‘functional/rationalisations’ category (e.g. ‘You only live once’, or ‘This snack is just small’) did not feature in the reasons to snack inventory (Verhoeven et al., 2015). Moreover, dietary self-talk items are phrased as ‘in the moment’ statements which are intended to represent individual thoughts in snack temptation contexts, whereas the reasons to snack inventory list general snack motives that are not specifically tied to a temptation context.

Several studies have systematically developed lists of behaviour change concepts, including theoretical domains (Michie et al., 2005), behaviour change techniques, methods and strategies (Hartmann-Boyce, Aveyard, Koshiaris, & Jebb, 2016; Knittle et al., 2020; Kok et al., 2016; Michie et al., 2013) environment changing targets (Hollands et al., 2017), modes and forms of intervention delivery (Dombrowski, O’Carroll, & Williams, 2016; Marques et al., 2020) and decision making processes such as heuristics and biases (Gigerenzer & Gaissmaier, 2011; Tversky & Kahneman, 1974). These lists inform research to systematically understand and change behaviour relevant processes. The current dietary self-talk list adds to this literature providing a more specialised list, by focusing on one particular phenomenon (i.e. self-talk) for one specific behaviour (i.e. discretionary snacking), in a specific situation (i.e. temptation resulting from conflicting intentions). Moreover, the themes identified around – accounts of and reflects on – dietary self-talk provide additional contextual information surrounding the phenomenon, enriching the ability to interpret individual items and groupings.

4.4. Implications and future research

There are several areas of future research. The current 40 items dietary self-talk list requires confirmation, extension and quantification. Future research might examine dietary self-talk when it occurs ‘in the moment’ during snacking temptation contexts. Moreover, understanding the quantity and variability of dietary self-talk and its relation to behaviour and behaviour-related outcomes would be useful.

It is likely that the self-talk items are used in combination and future research might examine the clustering of some of the self-talk content items. This might be specifically relevant in certain contexts. For example, the feeling of hunger was a key theme identified in reflections on self-talk and seemed to give rise to the use of a variety of self-talk. The themes identified in this study might present a starting point for examining contextual factors triggering the combinations of self-talk items.

Given the seemingly general nature of some of the self-talk content, research focusing on the origin and function of general self-talk items might reveal how individuals come to embrace and use certain cognitions to overcome situations of temptation in favour of the health impairing behaviour.

Self-talk is an everyday occurrence and other behavioural domains where intention conflicts occur might be a target for future study. Potential areas for identifying the content of temptation related behavioural self-talk might, for example, be physical activity, alcohol consumption or sleep.

There are some areas of potential application of the current list of dietary self-talk items. The list could be used to inform the use of behaviour change interventions, such as coping planning based techniques like the volitional help sheet (Armitage, 2015), which aims to help to overcome situations of temptations by linking these to goal-directed responses in line with health-relevant intention.

In addition, interventions might focus on changing the style of the self-talk items that people typically use. An experiential study, for example, found that when participants are asked to engage in ‘distance self-talk’ (i.e. referring to themselves in the third person and by name) enhanced the pursuit of eating healthier compared to ‘immersed self-talk’ (i.e. referring to themselves in the first person).

Finally, participants’ contextual accounts and reflections largely suggested a lack of an ongoing internal dialogue when using dietary self-talk, with self-talk leading to a swift enactment of the snacking behaviour. Interventions might promote both the recognition of dietary self-talk when it occurs and the introduction of self-talk using counter arguments which could bolster health enhancing intentions.