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Physician–child interaction: When children answer physicians’ questions in routine medical encounters
Patient Education and Counseling 87 (2012) 3–9
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Patient Education and Counseling journal homepage: www.elsevier.com/locate/pateducou
Communication Study
Physician–child interaction: When children answer physicians’ questions in routine medical encounters§ Tanya Stivers * UCLA Department of Sociology, USA
A R T I C L E I N F O
A B S T R A C T
Article history: Received 15 December 2010 Received in revised form 6 July 2011 Accepted 8 July 2011
Objective: The objective of the study is to examine predictors of children answering questions during primary care pediatric visits. Methods: Relying on a sample of 322 video-taped community practice encounters, this study identifies predictors of when children answer physicians’ questions. Multi-level multivariate regressions were used to model the relationships among communication and socio-demographic variables and whether or not children answered questions pediatricians asked them. Results: Whereas race and education predict whether physicians select children to answer questions, these factors are not associated with whether children answer physicians’ questions. Instead, a child’s performance is associated with communication practices specific to physician–child interaction such as the grammatical type of question and doctor gaze. Conclusion: Children are less responsive to physicians’ questions than their parents but their failure to answer is predictable and thus can be improved. By increasing their participation in the visit, physicians may (a) secure more information about children’s health and (b) socialize children to be more pro-active patients. Practice implications: Physicians can improve the likelihood that children will answer their questions by (a) asking them social questions early in the visit, (b) phrasing their questions as yes–no questions, and (c) and directing their gaze at the children during each question. ß 2011 Elsevier Ireland Ltd. All rights reserved.
Keywords: Patient–provider communication Conversation analysis Socialization
1. Introduction In pediatric encounters, direct communication between physicians and children is important: it builds rapport, trust and is valued by child patients [1,2]; it socializes the child into the role of patient—what they should know, in particular [3,4]; and children can contribute substantially to these medical encounters [4,5]. Children are uniquely positioned to provide particular types of information to physicians [6–10]. Although some studies argue that parents may be partially responsible for inhibiting their children’s participation [4,11], most studies show that outpatient health care providers spend a meager amount of time interacting with their child patients, with or without the collusion of a parent [5,11–17]. Moreover, relatively little effort has gone into develop-
§ Author note: Portions of this paper were presented at the UCLA Center for Language and Culture 2007 Symposium on Socialization, Interaction and Culture and the 2007 International Meeting on Conversation Analysis in Clinical Encounters at the University of Exeter. Thanks to Ignasi Clemente and John Heritage for comments on earlier drafts of this manuscript. * Corresponding author at: UCLA Department of Sociology, 264 Haines Hall, 375 Portola Plaza, Los Angeles, CA 90095-1551, USA. E-mail address: [email protected].
0738-3991/$ – see front matter ß 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.pec.2011.07.007
ing an account for the circumstances under which physicians become more or less likely to involve children in the medical encounter. Stivers and Majid, relying on a multi-method analysis of video-taped pediatric encounters, argue that physicians involve some children more than others and argue that physicians may be exhibiting an implicit bias against children of particular race and class backgrounds [15]. They argue that differences in children’s sociodemographic backgrounds account for a substantial amount of the variation in whether children are selected by physicians to answer physicians’ questions. Still, that study leaves open the question of whether physician question asking patterns are primarily the result of generalizations from different interactional experiences with children and parents from certain racial and socioeconomic backgrounds. More concretely, are children from lower SES backgrounds or of a minority race simply less likely to answer questions posed to them than their counterparts? If this were the case, physicians would likely internalize this and stop posing questions to children from these backgrounds leading to the findings offered by Stivers and Majid. By contrast, if children are no more likely to answer based on socio-economic or racial background, then we are left with a puzzle and should investigate what other sorts of predictors might explain child participation. This study identifies some of the factors
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
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that predict when children answer questions physicians pose to them and offers several ways in which children’s participation can be increased.
2. Methods 2.1. Design A nested cross-sectional design was employed, consisting of 570 videotaped pediatric encounters for children with upper respiratory tract infection symptoms clustered within 38 pediatricians in 27 community pediatric practices around Los Angeles County conducted between October, 2000 and June, 2001. In the course of analyzing the data with regard to how parents and physicians arrive at a treatment decision [18–20] – the reason for the constraint on URTIs – it became clear that the extent to which children are involved in the encounter varies greatly. A new aim emerged—to identify predictors of child participation in these medical encounters. Conversation analysis was relied on to identify a number of communication behaviors that appeared to be associated with child participation. These were then operationalized for coding to allow a multi-method investigation. The motivation for a multi-method study was to allow for there to be relationships between socio-demographic variables collected through self-administered surveys and communication behaviors identified qualitatively. Quantitative analyses could bring these two sorts of variables together. The first study examined predictors of physician question asking—what predicted whether a physician selected a child rather than a parent to answer a question [15]. The present study represents the counter-part to that initial study. The focus on questions is due to the fact that this is the primary context in which children contribute to the medical visit. Because the present study is specifically interested in child interaction, cases involving children younger than 2-years-and-6-
Fig. 1. Patient selection.
months of age were excluded, yielding 322 visits. The study procedures were reviewed and approved by the University of California, Los Angeles General Campus Institutional Review Board. 2.2. Variables In these data physicians asked a total of 6,609 questions and between 1 and 80 questions in any given visit (mean = 21; median = 18; mode = 12). The distribution is shown in Fig. 1. Four trained assistants coded the videotaped encounters according to the following criteria: who the physician selected (if any) to answer the question, whether and who responded, and whether s/he provided an answer to the question or a non-answer response (e.g., ‘‘I don’t know’’). A 15% random sample of the visits was re-coded by a second coder to test inter-coder reliability. Cohen’s kappa statistic for the selection of coding was .87 indicating almost perfect agreement according to Landis and Koch [21]. Question response coding (both who and response type) was also good, reaching agreement of .72.
Table 1 Question content. Question content typea
Examples
Opening
What’s the matter with you/him/her. Are you sick? Is he sick today? What can I do for you today.
Establishing symptoms
Are you coughing? Is she coughing? Has she had a fever with it, Does he have a runny nose,
Quality of symptoms
How bad is the cough. The drainage is it heavy? Is the cough wet or dry.
7%
Quantity/duration of symptoms
How often is the diarrhea. How many times did she throw up. How long has she been coughing,
6%
Medication/treatment
What have you given her for that. Have you taken any Sudafed or anything like that? Did the Tylenol work last time?
General health
Ever been in the hospital, Does he eat well?
Social/background
How old are you. Where do you go to school. Do you need a bandaid for that?
Examination preparation
Who’s gonna be first. Do you remember the stethoscope? Can I take a listen to your belly?
2%
Illness experience
Does this hurt? (while Dr. pushes on tummy) Does it hurt right now? (about ear) Do you feel like [you’re] having a hard time breathing
6%
a
Coders had good agreement, kappa = .69.
Frequency 8%
21%
18%
8%
24%
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
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Table 2 Participant age and sex. Caregiver sex Caregiver age Child sex Child age Doctor sex
84% mothers present; 20% fathers present, 1% only grandparents 20–72 (mean = 36 years) 50% girls Mean 5 years, 7 months 71% male
Note that in 6% of cases multiple caregivers were present.
Qualitatively identified question topics – ‘‘question content coding’’ – were also coded and are summarized in Table 1. Participant demographics were collected in a self-administered pre-visit survey and are described in Table 2 and Figs. 2–5. Qualitatively identified question formats were also coded. These different formats (e.g., grammatical design) are reviewed in Table 3. How children are selected includes the use of gaze, address terms and register, derived from conversation analysis. This is reviewed in Table 4.
Fig. 2. Gross annual household income (2000–2001).
Fig. 5. Physician race/ethnicity.
Table 3 Question format. Question format typea
Examples
Frequency
Wh-
What’s the matter with you/him/her. How bad is the cough.
26%
Alternative question
Is the cough wet or dry. Does it hurt or does it feel funny.
Yes–no interrogative
Does he have a cough? Did the Tylenol work last time? Have you tried giving her an extra pillow at night?
Tag question
He’s not throwing up though is he? She’s not coughing up any green stuff right?
Declarative question
This hurts? ((rising pitch at end)) You just had a birthday? ((rising pitch at end))
Appender
You take a silly pill today? ((silence)) Hm? Mom comments ‘‘It’s just that he’s not. . .’’ doctor appends ‘‘seeming like himself?’’
a
4%
25%
6%
32%
7%
Cohen’s kappa was .82 (excellent) for question format.
2.3. Analysis
Fig. 3. Parent education.
Fig. 4. Parent race/ethnicity.
2.3.1. Analytic background Responses in these data are not analyzable as independent observations, but rather are nested within medical visits, which are further nested within physicians: whether a child answers a question may be influenced by whether the child answered a previous question [12], and doctors may vary in their success in securing answers to questions from children.1 By relying on a Generalized Linear Latent and Mixed Model (GLLAMM) in STATA [22] we allow for these inter-relationships. Without this, we would treat each question as a completely separate entity with no dependencies. This is one model from a class of multilevel or hierarchical statistical models, which take into consideration that there is clustering in the data at more than one level. As the unit of analysis was binary (whether or not the child answered the question asked) a logit model was used to fit the data. For this model we are only interested in cases where children were selected to answer a question, so the model was restricted to those questions. Stivers and Majid’s analysis of doctors’ questioning behavior suggests that physicians treat adults and children differently. The present study shows that there is some interactional basis for this in question–answer sequences in these data: whereas parents 1 Physicians are further clustered within practices, but as there was no reason to assume that whether a child answers a question would vary at the practice level, this was not included.
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
6 Table 4 Overview of question format coding. Selection variable
Examples
Frequency
Kappa
Physician gaze
During the asking of the question the physician looked at the child’s face.
80%
.69
Address term
During the course of asking the question the physician used the child’s name as in ‘‘Robert, how are you feeling today.’’
7%
.90
Child voice register
Do you have an owie? Use of wide pitch range
24%
.23
Although this indicates only ‘‘fair’’ inter-coder reliability, it appears that this is a result of under-coding the behavior. Thus, the cases that were coded are likely to be valid though our ability to detect a relationship may be compromised by the under-coding.
responded to 93% of questions that selected them, children responded to only 65% of questions asked of them (see Table 5) [x2 (2, N = 5,672) = 4.0e + 03, p < .0001]. The two groups provided roughly the same rate of non-answer (e.g., ‘‘I don’t know’’) responses (9%) suggesting that most of the difference between the parent and child groups had to do with the provision of answers versus a failure to respond altogether. Although the findings above suggest that physicians are somewhat justified in their orientation to children as less competent interlocutors than parents, physicians nonetheless ask children questions and ask certain children particularly infrequently (Black children, Latino children of whose parents have relatively low education and younger children). One hypothesis is that through interacting with children from these backgrounds, physicians have learned that these children are less likely to answer their questions than their White, Asian or higher SES counterparts. If this were the case, then we should see that these characteristics should predict whether or not a child answers a physician’s question. By contrast, if these are not predictors of whether or not children answer a question put to them, then it suggests that physician behavior may arise from unjustified assumptions about the ability of certain groups of children to answer questions. In the event that this latter hypothesis is supported, there is potential to seek to change physicians’ behavior through challenging false assumptions and providing evidence about how questions can be asked most effectively. This paper was designed to explore these possibilities. 2.3.2. Children’s answering patterns In building a model of whether or not children answered a question posed to them, we began with all variables that had been predictive of whether physicians selected a child to answer a question as well as any other variables that could be of theoretical interest. Prior to including variables in the model, we tested them bivariately (e.g., child gender, question format, physician gaze) and included those that were significant at the p < .05 level or when there was theoretical justification for their inclusion (e.g., they were predictive of physician’s selection patterns). The independent variables included in this model were question content (what the question was about), parent demographics including parent race (White, Latino, Black or Asian) gender, education and household income. Because education and household income were linearly correlated, income was ultimately not included in this model. Education was included as a 5 level variable (less than 8th grade, 9th grade to HS graduation, some college, Associate’s degree, Table 5 Differences in child versus parent response patterns. Response type None Parent response Child response Total
Parent selected 6.03% (n = 223) 92.89% (n = 3,435) 1.08% (n = 40) 3,698
Child selected 24.11% (n = 476) 10.49% (n = 207) 65.40% (n = 1,291) 1,974
Total 699 3,642 1,331 5,672
College or Postgraduate degree). In addition, education by race was included as an interaction term. Parent gender proved insignificant bivariately and was not included in the final multivariate model. Child age was included in years. Child gender was significant bivariately and was therefore included in the final multivariate model. Physician gender showed no bivariate association with child answering and was not included in the final multivariate model. A variable for physician–parent racial concordance was included under the hypothesis that children might be more likely to answer questions asked by physicians of the same race. Communication variables were included such as whether or not the physician was gazing at the child and whether an address term or child-register was used in asking the question. Both were included as dichotomous variables. Finally, a variable for the presence of more than one caregiver was included. These associations proved significant with question answering bivariately and were therefore included in the final multivariate model. 3. Results 3.1. When children answer questions The results of the multivariate logistic regression are shown in Table 6 as odds ratios with 95% confidence intervals. Of the different levels that were tested, all were significant. Thus, just as Stivers & Majid found that some physicians are more likely to ask children questions, so too are some physicians more likely to secure answers from children. The visit level significance suggests that if a child answers a question s/he may be more likely to continue answering questions. There were six additional predictors of whether a child will answer a question s/he was asked by a doctor (1) child age; (2) child gender; (3) content of the question; (4) question format; (5) whether the physician gazed at the child while asking a question; (6) whether there were multiple caregivers present. 3.1.1. Child age For each additional year of age starting at two-and-a-half, the odds of a child answering a question increase by 19%, independent of what it is about or which question format is used. 3.1.2. Child gender Girls were significantly more likely to answer questions than boys (the odds increased by 63%). 3.1.3. Content of the question (see Table 1) Physicians are most likely to ask children social, preparatory and experience questions. In this analysis we can see that the odds of a child answering increased by 28% if the question was about one of these topics. 3.1.4. Question format (see Table 3) Wh-questions (e.g., ‘‘When did this happen?’’) appeared to be the most difficult type of question for children to answer.
T. Stivers / Patient Education and Counseling 87 (2012) 3–9 Table 6 Results of multivariate logistic regression for child answering questions.+ Level 1 variables Question content variables Child-topic question Family demographics Child age Female child Parent level of education Race Latino parent Black parent Asian parent Race by education Latino parent/education interaction Black parent/education interaction Asian parent/education Physician sociodemographics Latino physician Black physician Asian physician Non-native speaker of English Physician–parent racial concordance Selection variables Use of gaze with during question Use of child register in question Use of address term in question Presence of more than one caregiver Question format Yes–no interrogative Alternative question Declarative question Appender question Tag question Negative interrogative
OR
95% CI
1.28** ***
1.04, 1.57
1.19 1.63** 1.07
1.11, 1.27 1.23, 2.17 0.86, 1.34
0.59 0.38 0.28
0.25, 1.43 0.10, 1.41 0.05, 1.70
1.11 1.42 1.41
0.83, 1.48 0.90, 2.22 0.83, 2.40
0.90 1.08 0.11 0.96 0.74
0.44, 0.46, 0.69, 0.60, 0.46,
1.85 2.53 1.77 1.55 1.19
1.27* 0.80 1.11 0.46*
1.01, 0.63, 0.77, 0.24,
1.60 1.03 1.60 0.89
1.26 2.09*** 1.30 1.83*** 1.91** 0.42
1.63, 0.72, 1.32, 1.28, 0.84, 0.07,
2.68 2.37 2.36 2.84 1.87 2.47
Context variables
Estimate
Standard error
Level 2: Variance at visit level Level 3: Variance at physician level
0.50*** 0.12*
(0.12) (0.07)
+
model restricted to questions that selected child. Denotes p .05. ** Denotes p .01. *** Denotes p .001. *
Compared to Wh-questions, the odds of a child answering a yes–no interrogative (e.g., ‘‘Did this start on the weekend?’’) increase 2.09 times. Declarative questions (e.g., ‘‘This just started’’) were very similar to yes–no interrogatives: the odds of them being answered increased by 83% relative to Wh-questions. Although rare, appender questions were also more likely to be answered: the odds increased by 91%. Alternative, tag and negative interrogative questions did not significantly differ from Wh-questions. Thus, a question that is phrased as a yes–no question – whether with declarative or interrogative syntax – will generally be more likely to be answered by a child, holding constant what the question is about and how old the child is. 3.1.5. Physician gaze (see Table 4) If a physician gazed at the child at any point in the question asking, the child was more likely to answer: the odds increased by 27%. Although the significance level of this result was borderline, it is nonetheless an extremely powerful result because it such an easy behavior to modify and many physicians are already gazing at their child patients when asking them some of the questions. 3.1.6. Multiple caregivers As predicted, the presence of multiple adult caregivers decreased the likelihood that the child would answer a question asked of him/her. The child is 54% less likely to answer in these cases. In multi-party interaction there is generally more interactional pressure on turn taking such that transitions between turns appear, on balance, to shorten. This is more problematic for
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children who frequently appear to take more time in answering questions than adults. Typically, if a selected individual has difficulty answering a question, another non-selected individual will, if possible, provide an answer [12,23]. Although that is always possible in pediatric triads, the addition of a second caregiver may hasten this process, making it more difficult for the child to retain the floor to provide an answer after a delay. 3.2. Parent behavior A further set of questions is suggested by these data. Could there be something in the way parents of different racial and socioeconomic backgrounds deliver their own responses that leads physicians to ask parents rather than their children questions, in spite of the children’s behavior being rather homogenous across racial and class boundaries? For instance, might parents convey to physicians that they should not be directing their questions to their children but should be addressing questions to the parents? We might then expect that due to differences in approaches to child rearing in Black families, children might be treated as having reduced rights to participate in discussions than in White families [24]. If this were the case, we would expect to see Black parents answering questions that selected their children more often than White parents would. However, this was not the case [x2 (4, N = 1,013) = 3.23, p = 0.52]. There was no association between a parent being Black or White and answering questions that had selected their children. An alternative explanation to the observations that physicians ask certain children less than others is that parent answering behavior is different depending on their race and class. To examine this possibility another multivariate model was constructed in the same way that the model predicting child answering was built. For parallelism, the models are identical except that this model was restricted to cases where the parent, rather than the child, was selected to respond whereas the former model was of cases where children were selected to respond. The results are shown as odds ratios and with 95% confidence intervals in Table 7. The results are very similar to those of the model predicting when children answer. However, parents were less affected by the individual physician and the visit than their children—both levels were nonsignificant in explaining variance within the model. There were four predictors of whether a parent answers a question they were asked by a doctor (1) question format; (2) their child’s age; (3) whether an address term was used; (4) whether the physician was a non-native speaker of English. 3.2.1. Question format As with children, Wh-questions were less likely to be answered. This suggests that if the underlying difference between yes–no and Wh-questions is ‘difficulty’ it is a difficulty that affects interactants broadly and not only children. Compared to Wh-questions, the odds that a parent would answer a yes–no interrogative question went up 62% over the odds that they would answer an interrogatively formatted yes–no question. Declarative questions were very similar to yes–no interrogatives but the effect size was even stronger (122% more likely to be answered). Although rare, appender questions and tag questions were both also more likely to be answered: 58% more likely in both cases. Here the only difference from the pattern observed with children is the slightly stronger effect of declarative questions and that tag questions reach significance in their association with being answered. 3.2.2. Child age Child age had a significant effect such that for each additional year of age the odds of a parent answering a question asked of the child decline by 11%.
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
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Table 7 Results of multivariate logistic regression for parent answering.+
4.1. Discussion
answer a question, of whether a child answered a question posed to them, and of whether a parent was willing to answer questions about them. These findings, combined with the observation that children were categorically less likely than adults to answer questions asked of them, supports the analysis that was made by Stivers & Majid that doctors are attempting to analyze a child’s competence and likelihood of answering questions when they select them to answer. Children do grow more able to answer questions as they get older.2 Second, physicians ask children about particular content areas more often than others, and these are the topics that they are better able, and more likely, to answer questions about. But perhaps more significant is the considerable mismatch this study reveals between the factors that Stivers & Majid reported physicians to rely on when selecting children to answer questions [15] and the factors that were associated with whether children answered their questions: neither parent education nor race (as main effects or interaction terms) was associated with the child’s propensity to answer a physician’s question. It might not be unreasonable for a physician to attribute additional cognitive and/ or interactional competence to a child from a more educated family. As Lareau documents with her ethnographic study, middleclass families appear more likely to rehearse what doctor–patient or other professional interactions will be like and thus could better prepare children to participate in the interaction [25]. However, there was no effect of the parent’s class background (here, education) on children’s display of cognitive and interactional competence as indexed by their propensity to answer questions. Stivers & Majid showed that in these data, physicians selected children differentially on the basis of parent education as it interacted with race. They became more likely to select Latino and African American children only if their parents had significant education. This finding can be understood as an attribution of increased competence—that minority children whose parents are more highly educated might be assessed as more likely to answer questions than a child with less educated parents. However, the physician behavior patterns do not appear to be based in inductive generalizations from their general interactional experiences with families of similar backgrounds as documented in this study. Also in the previous study, physicians were less likely to ask Black children questions relative to other racial groups. Again, if this were analyzable as a negative attribution of competence, this study shows that there is no basis for the attribution in actual child behavior: Black children were just as likely to answer questions as children of other racial backgrounds. Another interesting mismatch was with respect to child gender. Physicians made no attributions of competence on the basis of child gender in the previous study of question-asking, but child gender was a strong predictor of answering in this study. Girls were much more likely than boys to answer physicians’ questions. The only sociodemographic factor that we find to have some basis in actual social behavior is one that is not recognized in physicians’ questioning behavior in these data. An alternative hypothesis that was offered to explain mismatch between predictors of physician question-asking behavior and children’s answering behavior is that certain parents (e.g., Black and less educated Latinos) are in some way preventing children from participating in the encounter. This study restricted its scope to question–answer sequences, but at least in this context, there is no indication of a difference in the way parents manage these sequences. As with the children, parents in these data behave no differently at the micro-interactional level on the basis of race or
In two main respects physicians pitch their questions to interlocutors who are more likely to answer their questions: child age was a predictor of whether a physician selected a child to
2 The fact that this sample only includes children up to the age of 10-years-old leaves open the question of whether this attribution of competence levels off at this age or continues to gradually rise up through adolescence until adulthood.
Level 1 variables
OR
Question content variables Child-topic question Family demographics Child age Female child Parent level of education Race Latino parent Black parent Asian parent Race by education Latino parent/education interaction Black parent/education interaction Asian parent/education Physician sociodemographics Latino physician Black physician Asian physician Non-native speaker of English Physician–parent racial concordance Selection variables Use of gaze with during question Use of child register in question Use of address term in question Presence of more than one caregiver Question format Yes–no interrogative Alternative question Declarative question Appender question Tag question Negative interrogative
95% CI
1.01
0.81, 1.27 ***
0.89 1.15 0.92
0.85, 0.94 0.92, 1.44 0.75, 1.12
1.02 1.38 0.40
0.49, 2.12 0.49, 3.91 0.10, 1.57
1.06 0.96 1.28
0.83, 1.35 0.66, 1.40 0.83, 1.97
0.81 0.77 0.95 1.41 1.05
0.48, 0.49, 0.66, 1.00, 0.74,
1.37 3.91 1.37 2.00 1.48
0.96 0.83 0.35** 0.88
0.82, 0.59, 0.17, 0.58,
1.13 1.18 0.72 1.34
1.62*** 1.09 2.22*** 1.58** 1.58** 0.47
1.28, 0.73, 1.78, 1.06, 1.06, 0.14,
2.06 1.64 2.78 2.34 2.35 1.60
Context variables
Estimate
Standard error
Level 2: Variance at visit level Level 3: Variance at physician level
0.22 0.08
(0.08) (0.04)
+
Model restricted to questions that selected adults. Denotes p .01. *** Denotes p .001. **
3.2.3. Address terms As mentioned earlier, the use of address terms was rare, especially with adults (only 1% of the time). However, it does reach significance here with a rather strong effect. The odds of a parents answering decrease by 65% if that question uses an address term to select them. 3.2.4. Non-native speaking physicians Parents were 41% more likely to answer a question asked by a non-native speaker of English. This variable had been included to rule out the possibility that independent of race parents would find it more difficult to understand a non-native speaker of English and therefore be less likely to answer. However, the result runs counter to that hypothesis. This association did not reach significance for the model predicting child answers. Finally, parents were less affected not only by individual physicians and the visit but also by interactional phenomena such as the use of physician gaze to select them, the topic of the question or the presence of an additional caregiver. And they were unaffected by their child’s gender. 4. Discussion and conclusions
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
class. Parents showed a similar pattern to children in that parents were more reluctant to answer questions about their children as they grew older, and they were more inclined to answer yes–no formatted questions than Wh-formatted questions. Two unexpected predictors were physicians’ use of address terms which were negatively associated with parents answering. This is a result that was neither expected nor is easily interpretable particularly since it was not present for children where address terms were more common. Further qualitative work would be required to understand this relationship. One possible interpretation is that the result was driven not by the use of address terms per se but the contexts in which they are used. For instance, if they were mainly used when securing the parent’s attention was difficult they might otherwise have been less likely to respond. A second unexpected result was the association with physicians who are non-native speakers of English. Although it was only marginally significant, the interpretation is that parents may be more willing to accommodate nonnative speakers and thus ‘‘try harder’’ to answer. This study suggests that there is no evidence that children from particular socioeconomic or racial/ethnic groups are less likely to respond to a question. However, the study does point to interactional resources that are associated with securing a higher rate of child participation—particularly, physician gaze and yes–no question design. This study also underscores a previous finding that a child who can be engaged in an early question–answer sequence will be more likely to answer a subsequent question that establishes the reason for the visit [12]. In this study the significance of the visit level suggests that if a child can be engaged early, then they are more likely to answer other questions asked of them. This level was also significant for whether physicians selected a child to answer. Here we see just how interactive that behavior likely is: a physician who can secure an answer from a child appears to be more likely to ask the child more questions (to which the physician is, again, more likely to get an answer). In this study, physicians only asked children 37% of all of their questions, and children only answered 65% of those questions. Moreover, if a child delays their answer parents are more likely to answer on their behalf [12,23]. However, this study has identified several quite simple resources physicians can use to encourage child participation which might, in turn, increase the likelihood that physicians will ask children questions in the first place. 4.2. Conclusions Most healthy children do not interact with their physicians often but may nevertheless see no other health care providers until they reach adulthood. This may be particularly true for children coming from low socioeconomic family backgrounds, especially those who have reduced access to health care. Their primary care visits with pediatricians may be the only means of socialization into the role of autonomous adult patient that they have. Increasing the amount of interaction between health providers and children may increase child awareness of and ownership of their illnesses and lead children to be more pro-active patients in later life. 4.3. Practice implications As shown here, the two biggest strategies that physicians can employ are asking yes–no questions, whether interrogatively or
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declaratively formatted and gazing at children when they ask their questions. Just one or two yes–no social questions at the beginning of the visit stand to improve the chances of the child answering the first medical question put to them—usually the opening question. If this happens, children are more likely to continue to participate in the encounter, and physicians are more likely to keep asking them questions. These data suggest that this may be even more important for boys since girls are more frequent responders relative to their same age boy counterparts. Encouraging child participation stands to both better socialize the child into the patient role and to ensure that physicians receive all information relevant to the medical visit.
References [1] Lewis CC, Pantell RH, Sharp L. Increasing patient knowledge, satisfaction, and involvement: randomized trial of a communication intervention. Pediatrics 1991;88:351–8. [2] Byczkowski TL, Kollar LM, Britto MT. Family experiences with outpatient care: do adolescents and parents have the same perceptions. J Adolesc Health 2010;47:92–8. [3] Tates K, Meeuwesen L, Bensing J. ‘I’ve come for his throat’: roles and identities in doctor–parent–child communication. Child Care Health Dev 2002;28:109– 16. [4] Nova C, Vegni E, Moja EA. The physician–patient–parent communication: a qualitative perspective on the child’s contribution. Patient Educ Couns 2005;58:327–33. [5] Tates K, Meeuwesen L. Doctor–parent–child communication. A (re)view of the literature. Soc Sci Med 2001;52:839–51. [6] Athreya BH, Silverman BK. Pediatric physical diagnosis. Norwalk, CT: Appleton-Century-Crofts; 1985. [7] Seidel HM, Ball JW, Dains JE, Benedict GW. Mosby’s guide to physical examination, 3rd ed., New York: Mosby; 1995. [8] Bickley L, Szilagyi PG. Physical examination and history taking, 6th ed., Philadelphia: Lippincott; 2002. [9] Rylance G. Making decisions with children. Br Med J 1996;312:794. [10] Alderson P, Montgomery J. Health care choices: making decisions with children. London: Institute for Policy Research; 1996. [11] Aronsson K, Rundstro¨m B. Child discourse and parental control in pediatric consultations. Text 1988;8:159–89. [12] Stivers T. Negotiating who presents the problem: next speaker selection in pediatric encounters. J Commun 2001;51:1–31. [13] Pantell RH, Steward TJ, Dias JK, Wells P, Ross AW. Physician communication with children and parents. Pediatrics 1982;70:396–402. [14] van Dulmen AM. Children’s contributions to pediatric outpatient encounters. Pediatrics 1998;102:563–8. [15] Stivers T, Majid A. Questioning children: interactional evidence of implicit bias in medical interviews. Soc Psychol Q 2007;70:424–41. [16] Wissow LS, Roter D, Bauman LJ, Crain E, Kercsmar C, Weiss K, et al. Patient– provider communication during the emergency department care of children with asthma. The National Cooperative Inner-City Asthma Study, National Institute of Allergy and Infection Diseases, NIH, Bethesda, MD. Med Care 1998;36:1439–50. [17] Tates K, Meeuwesen L. ‘Let Mum have her say’: turntaking in doctor–parent– child communication. Patient Educ Couns 2000;40:141–62. [18] Mangione-Smith R, Elliott MN, Stivers T, McDonald L, Heritage J, McGlynn EA. Racial/ethnic variation in parent expectations for antibiotics: implications for public health campaigns. Pediatrics 2004;113:e385–94. [19] Stivers T. Non-antibiotic treatment recommendations: delivery formats and implications for parent resistance. Soc Sci Med 2005;60:949–64. [20] Mangione-Smith R, Elliott MN, Stivers T, McDonald LL, Heritage J. Ruling out the need for antibiotics: are we sending the right message? Arch Pediatr Adolesc Med 2006;160:945–52. [21] Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159–74. [22] Rabe-Hesketh S, Skrondal A. Multilevel and longitudinal modeling using Stata. College Station, TX: Stata Press; 2005. [23] Stivers T, Robinson JD. A preference for progressivity in interaction. Lang Soc 2006;35:367–92. [24] Moten CP. Child-rearing practices in African American families. In: Everett JE, editor. Child welfare revisited: an Africentric perspective. Piscataway, NJ: Rutgers University Press; 2004. [25] Lareau A. Unequal childhoods: class race and family life. Berkeley: University of California Press; 2003.
Contents lists available at ScienceDirect
Patient Education and Counseling journal homepage: www.elsevier.com/locate/pateducou
Communication Study
Physician–child interaction: When children answer physicians’ questions in routine medical encounters§ Tanya Stivers * UCLA Department of Sociology, USA
A R T I C L E I N F O
A B S T R A C T
Article history: Received 15 December 2010 Received in revised form 6 July 2011 Accepted 8 July 2011
Objective: The objective of the study is to examine predictors of children answering questions during primary care pediatric visits. Methods: Relying on a sample of 322 video-taped community practice encounters, this study identifies predictors of when children answer physicians’ questions. Multi-level multivariate regressions were used to model the relationships among communication and socio-demographic variables and whether or not children answered questions pediatricians asked them. Results: Whereas race and education predict whether physicians select children to answer questions, these factors are not associated with whether children answer physicians’ questions. Instead, a child’s performance is associated with communication practices specific to physician–child interaction such as the grammatical type of question and doctor gaze. Conclusion: Children are less responsive to physicians’ questions than their parents but their failure to answer is predictable and thus can be improved. By increasing their participation in the visit, physicians may (a) secure more information about children’s health and (b) socialize children to be more pro-active patients. Practice implications: Physicians can improve the likelihood that children will answer their questions by (a) asking them social questions early in the visit, (b) phrasing their questions as yes–no questions, and (c) and directing their gaze at the children during each question. ß 2011 Elsevier Ireland Ltd. All rights reserved.
Keywords: Patient–provider communication Conversation analysis Socialization
1. Introduction In pediatric encounters, direct communication between physicians and children is important: it builds rapport, trust and is valued by child patients [1,2]; it socializes the child into the role of patient—what they should know, in particular [3,4]; and children can contribute substantially to these medical encounters [4,5]. Children are uniquely positioned to provide particular types of information to physicians [6–10]. Although some studies argue that parents may be partially responsible for inhibiting their children’s participation [4,11], most studies show that outpatient health care providers spend a meager amount of time interacting with their child patients, with or without the collusion of a parent [5,11–17]. Moreover, relatively little effort has gone into develop-
§ Author note: Portions of this paper were presented at the UCLA Center for Language and Culture 2007 Symposium on Socialization, Interaction and Culture and the 2007 International Meeting on Conversation Analysis in Clinical Encounters at the University of Exeter. Thanks to Ignasi Clemente and John Heritage for comments on earlier drafts of this manuscript. * Corresponding author at: UCLA Department of Sociology, 264 Haines Hall, 375 Portola Plaza, Los Angeles, CA 90095-1551, USA. E-mail address: [email protected].
0738-3991/$ – see front matter ß 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.pec.2011.07.007
ing an account for the circumstances under which physicians become more or less likely to involve children in the medical encounter. Stivers and Majid, relying on a multi-method analysis of video-taped pediatric encounters, argue that physicians involve some children more than others and argue that physicians may be exhibiting an implicit bias against children of particular race and class backgrounds [15]. They argue that differences in children’s sociodemographic backgrounds account for a substantial amount of the variation in whether children are selected by physicians to answer physicians’ questions. Still, that study leaves open the question of whether physician question asking patterns are primarily the result of generalizations from different interactional experiences with children and parents from certain racial and socioeconomic backgrounds. More concretely, are children from lower SES backgrounds or of a minority race simply less likely to answer questions posed to them than their counterparts? If this were the case, physicians would likely internalize this and stop posing questions to children from these backgrounds leading to the findings offered by Stivers and Majid. By contrast, if children are no more likely to answer based on socio-economic or racial background, then we are left with a puzzle and should investigate what other sorts of predictors might explain child participation. This study identifies some of the factors
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
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that predict when children answer questions physicians pose to them and offers several ways in which children’s participation can be increased.
2. Methods 2.1. Design A nested cross-sectional design was employed, consisting of 570 videotaped pediatric encounters for children with upper respiratory tract infection symptoms clustered within 38 pediatricians in 27 community pediatric practices around Los Angeles County conducted between October, 2000 and June, 2001. In the course of analyzing the data with regard to how parents and physicians arrive at a treatment decision [18–20] – the reason for the constraint on URTIs – it became clear that the extent to which children are involved in the encounter varies greatly. A new aim emerged—to identify predictors of child participation in these medical encounters. Conversation analysis was relied on to identify a number of communication behaviors that appeared to be associated with child participation. These were then operationalized for coding to allow a multi-method investigation. The motivation for a multi-method study was to allow for there to be relationships between socio-demographic variables collected through self-administered surveys and communication behaviors identified qualitatively. Quantitative analyses could bring these two sorts of variables together. The first study examined predictors of physician question asking—what predicted whether a physician selected a child rather than a parent to answer a question [15]. The present study represents the counter-part to that initial study. The focus on questions is due to the fact that this is the primary context in which children contribute to the medical visit. Because the present study is specifically interested in child interaction, cases involving children younger than 2-years-and-6-
Fig. 1. Patient selection.
months of age were excluded, yielding 322 visits. The study procedures were reviewed and approved by the University of California, Los Angeles General Campus Institutional Review Board. 2.2. Variables In these data physicians asked a total of 6,609 questions and between 1 and 80 questions in any given visit (mean = 21; median = 18; mode = 12). The distribution is shown in Fig. 1. Four trained assistants coded the videotaped encounters according to the following criteria: who the physician selected (if any) to answer the question, whether and who responded, and whether s/he provided an answer to the question or a non-answer response (e.g., ‘‘I don’t know’’). A 15% random sample of the visits was re-coded by a second coder to test inter-coder reliability. Cohen’s kappa statistic for the selection of coding was .87 indicating almost perfect agreement according to Landis and Koch [21]. Question response coding (both who and response type) was also good, reaching agreement of .72.
Table 1 Question content. Question content typea
Examples
Opening
What’s the matter with you/him/her. Are you sick? Is he sick today? What can I do for you today.
Establishing symptoms
Are you coughing? Is she coughing? Has she had a fever with it, Does he have a runny nose,
Quality of symptoms
How bad is the cough. The drainage is it heavy? Is the cough wet or dry.
7%
Quantity/duration of symptoms
How often is the diarrhea. How many times did she throw up. How long has she been coughing,
6%
Medication/treatment
What have you given her for that. Have you taken any Sudafed or anything like that? Did the Tylenol work last time?
General health
Ever been in the hospital, Does he eat well?
Social/background
How old are you. Where do you go to school. Do you need a bandaid for that?
Examination preparation
Who’s gonna be first. Do you remember the stethoscope? Can I take a listen to your belly?
2%
Illness experience
Does this hurt? (while Dr. pushes on tummy) Does it hurt right now? (about ear) Do you feel like [you’re] having a hard time breathing
6%
a
Coders had good agreement, kappa = .69.
Frequency 8%
21%
18%
8%
24%
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
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Table 2 Participant age and sex. Caregiver sex Caregiver age Child sex Child age Doctor sex
84% mothers present; 20% fathers present, 1% only grandparents 20–72 (mean = 36 years) 50% girls Mean 5 years, 7 months 71% male
Note that in 6% of cases multiple caregivers were present.
Qualitatively identified question topics – ‘‘question content coding’’ – were also coded and are summarized in Table 1. Participant demographics were collected in a self-administered pre-visit survey and are described in Table 2 and Figs. 2–5. Qualitatively identified question formats were also coded. These different formats (e.g., grammatical design) are reviewed in Table 3. How children are selected includes the use of gaze, address terms and register, derived from conversation analysis. This is reviewed in Table 4.
Fig. 2. Gross annual household income (2000–2001).
Fig. 5. Physician race/ethnicity.
Table 3 Question format. Question format typea
Examples
Frequency
Wh-
What’s the matter with you/him/her. How bad is the cough.
26%
Alternative question
Is the cough wet or dry. Does it hurt or does it feel funny.
Yes–no interrogative
Does he have a cough? Did the Tylenol work last time? Have you tried giving her an extra pillow at night?
Tag question
He’s not throwing up though is he? She’s not coughing up any green stuff right?
Declarative question
This hurts? ((rising pitch at end)) You just had a birthday? ((rising pitch at end))
Appender
You take a silly pill today? ((silence)) Hm? Mom comments ‘‘It’s just that he’s not. . .’’ doctor appends ‘‘seeming like himself?’’
a
4%
25%
6%
32%
7%
Cohen’s kappa was .82 (excellent) for question format.
2.3. Analysis
Fig. 3. Parent education.
Fig. 4. Parent race/ethnicity.
2.3.1. Analytic background Responses in these data are not analyzable as independent observations, but rather are nested within medical visits, which are further nested within physicians: whether a child answers a question may be influenced by whether the child answered a previous question [12], and doctors may vary in their success in securing answers to questions from children.1 By relying on a Generalized Linear Latent and Mixed Model (GLLAMM) in STATA [22] we allow for these inter-relationships. Without this, we would treat each question as a completely separate entity with no dependencies. This is one model from a class of multilevel or hierarchical statistical models, which take into consideration that there is clustering in the data at more than one level. As the unit of analysis was binary (whether or not the child answered the question asked) a logit model was used to fit the data. For this model we are only interested in cases where children were selected to answer a question, so the model was restricted to those questions. Stivers and Majid’s analysis of doctors’ questioning behavior suggests that physicians treat adults and children differently. The present study shows that there is some interactional basis for this in question–answer sequences in these data: whereas parents 1 Physicians are further clustered within practices, but as there was no reason to assume that whether a child answers a question would vary at the practice level, this was not included.
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
6 Table 4 Overview of question format coding. Selection variable
Examples
Frequency
Kappa
Physician gaze
During the asking of the question the physician looked at the child’s face.
80%
.69
Address term
During the course of asking the question the physician used the child’s name as in ‘‘Robert, how are you feeling today.’’
7%
.90
Child voice register
Do you have an owie? Use of wide pitch range
24%
.23
Although this indicates only ‘‘fair’’ inter-coder reliability, it appears that this is a result of under-coding the behavior. Thus, the cases that were coded are likely to be valid though our ability to detect a relationship may be compromised by the under-coding.
responded to 93% of questions that selected them, children responded to only 65% of questions asked of them (see Table 5) [x2 (2, N = 5,672) = 4.0e + 03, p < .0001]. The two groups provided roughly the same rate of non-answer (e.g., ‘‘I don’t know’’) responses (9%) suggesting that most of the difference between the parent and child groups had to do with the provision of answers versus a failure to respond altogether. Although the findings above suggest that physicians are somewhat justified in their orientation to children as less competent interlocutors than parents, physicians nonetheless ask children questions and ask certain children particularly infrequently (Black children, Latino children of whose parents have relatively low education and younger children). One hypothesis is that through interacting with children from these backgrounds, physicians have learned that these children are less likely to answer their questions than their White, Asian or higher SES counterparts. If this were the case, then we should see that these characteristics should predict whether or not a child answers a physician’s question. By contrast, if these are not predictors of whether or not children answer a question put to them, then it suggests that physician behavior may arise from unjustified assumptions about the ability of certain groups of children to answer questions. In the event that this latter hypothesis is supported, there is potential to seek to change physicians’ behavior through challenging false assumptions and providing evidence about how questions can be asked most effectively. This paper was designed to explore these possibilities. 2.3.2. Children’s answering patterns In building a model of whether or not children answered a question posed to them, we began with all variables that had been predictive of whether physicians selected a child to answer a question as well as any other variables that could be of theoretical interest. Prior to including variables in the model, we tested them bivariately (e.g., child gender, question format, physician gaze) and included those that were significant at the p < .05 level or when there was theoretical justification for their inclusion (e.g., they were predictive of physician’s selection patterns). The independent variables included in this model were question content (what the question was about), parent demographics including parent race (White, Latino, Black or Asian) gender, education and household income. Because education and household income were linearly correlated, income was ultimately not included in this model. Education was included as a 5 level variable (less than 8th grade, 9th grade to HS graduation, some college, Associate’s degree, Table 5 Differences in child versus parent response patterns. Response type None Parent response Child response Total
Parent selected 6.03% (n = 223) 92.89% (n = 3,435) 1.08% (n = 40) 3,698
Child selected 24.11% (n = 476) 10.49% (n = 207) 65.40% (n = 1,291) 1,974
Total 699 3,642 1,331 5,672
College or Postgraduate degree). In addition, education by race was included as an interaction term. Parent gender proved insignificant bivariately and was not included in the final multivariate model. Child age was included in years. Child gender was significant bivariately and was therefore included in the final multivariate model. Physician gender showed no bivariate association with child answering and was not included in the final multivariate model. A variable for physician–parent racial concordance was included under the hypothesis that children might be more likely to answer questions asked by physicians of the same race. Communication variables were included such as whether or not the physician was gazing at the child and whether an address term or child-register was used in asking the question. Both were included as dichotomous variables. Finally, a variable for the presence of more than one caregiver was included. These associations proved significant with question answering bivariately and were therefore included in the final multivariate model. 3. Results 3.1. When children answer questions The results of the multivariate logistic regression are shown in Table 6 as odds ratios with 95% confidence intervals. Of the different levels that were tested, all were significant. Thus, just as Stivers & Majid found that some physicians are more likely to ask children questions, so too are some physicians more likely to secure answers from children. The visit level significance suggests that if a child answers a question s/he may be more likely to continue answering questions. There were six additional predictors of whether a child will answer a question s/he was asked by a doctor (1) child age; (2) child gender; (3) content of the question; (4) question format; (5) whether the physician gazed at the child while asking a question; (6) whether there were multiple caregivers present. 3.1.1. Child age For each additional year of age starting at two-and-a-half, the odds of a child answering a question increase by 19%, independent of what it is about or which question format is used. 3.1.2. Child gender Girls were significantly more likely to answer questions than boys (the odds increased by 63%). 3.1.3. Content of the question (see Table 1) Physicians are most likely to ask children social, preparatory and experience questions. In this analysis we can see that the odds of a child answering increased by 28% if the question was about one of these topics. 3.1.4. Question format (see Table 3) Wh-questions (e.g., ‘‘When did this happen?’’) appeared to be the most difficult type of question for children to answer.
T. Stivers / Patient Education and Counseling 87 (2012) 3–9 Table 6 Results of multivariate logistic regression for child answering questions.+ Level 1 variables Question content variables Child-topic question Family demographics Child age Female child Parent level of education Race Latino parent Black parent Asian parent Race by education Latino parent/education interaction Black parent/education interaction Asian parent/education Physician sociodemographics Latino physician Black physician Asian physician Non-native speaker of English Physician–parent racial concordance Selection variables Use of gaze with during question Use of child register in question Use of address term in question Presence of more than one caregiver Question format Yes–no interrogative Alternative question Declarative question Appender question Tag question Negative interrogative
OR
95% CI
1.28** ***
1.04, 1.57
1.19 1.63** 1.07
1.11, 1.27 1.23, 2.17 0.86, 1.34
0.59 0.38 0.28
0.25, 1.43 0.10, 1.41 0.05, 1.70
1.11 1.42 1.41
0.83, 1.48 0.90, 2.22 0.83, 2.40
0.90 1.08 0.11 0.96 0.74
0.44, 0.46, 0.69, 0.60, 0.46,
1.85 2.53 1.77 1.55 1.19
1.27* 0.80 1.11 0.46*
1.01, 0.63, 0.77, 0.24,
1.60 1.03 1.60 0.89
1.26 2.09*** 1.30 1.83*** 1.91** 0.42
1.63, 0.72, 1.32, 1.28, 0.84, 0.07,
2.68 2.37 2.36 2.84 1.87 2.47
Context variables
Estimate
Standard error
Level 2: Variance at visit level Level 3: Variance at physician level
0.50*** 0.12*
(0.12) (0.07)
+
model restricted to questions that selected child. Denotes p .05. ** Denotes p .01. *** Denotes p .001. *
Compared to Wh-questions, the odds of a child answering a yes–no interrogative (e.g., ‘‘Did this start on the weekend?’’) increase 2.09 times. Declarative questions (e.g., ‘‘This just started’’) were very similar to yes–no interrogatives: the odds of them being answered increased by 83% relative to Wh-questions. Although rare, appender questions were also more likely to be answered: the odds increased by 91%. Alternative, tag and negative interrogative questions did not significantly differ from Wh-questions. Thus, a question that is phrased as a yes–no question – whether with declarative or interrogative syntax – will generally be more likely to be answered by a child, holding constant what the question is about and how old the child is. 3.1.5. Physician gaze (see Table 4) If a physician gazed at the child at any point in the question asking, the child was more likely to answer: the odds increased by 27%. Although the significance level of this result was borderline, it is nonetheless an extremely powerful result because it such an easy behavior to modify and many physicians are already gazing at their child patients when asking them some of the questions. 3.1.6. Multiple caregivers As predicted, the presence of multiple adult caregivers decreased the likelihood that the child would answer a question asked of him/her. The child is 54% less likely to answer in these cases. In multi-party interaction there is generally more interactional pressure on turn taking such that transitions between turns appear, on balance, to shorten. This is more problematic for
7
children who frequently appear to take more time in answering questions than adults. Typically, if a selected individual has difficulty answering a question, another non-selected individual will, if possible, provide an answer [12,23]. Although that is always possible in pediatric triads, the addition of a second caregiver may hasten this process, making it more difficult for the child to retain the floor to provide an answer after a delay. 3.2. Parent behavior A further set of questions is suggested by these data. Could there be something in the way parents of different racial and socioeconomic backgrounds deliver their own responses that leads physicians to ask parents rather than their children questions, in spite of the children’s behavior being rather homogenous across racial and class boundaries? For instance, might parents convey to physicians that they should not be directing their questions to their children but should be addressing questions to the parents? We might then expect that due to differences in approaches to child rearing in Black families, children might be treated as having reduced rights to participate in discussions than in White families [24]. If this were the case, we would expect to see Black parents answering questions that selected their children more often than White parents would. However, this was not the case [x2 (4, N = 1,013) = 3.23, p = 0.52]. There was no association between a parent being Black or White and answering questions that had selected their children. An alternative explanation to the observations that physicians ask certain children less than others is that parent answering behavior is different depending on their race and class. To examine this possibility another multivariate model was constructed in the same way that the model predicting child answering was built. For parallelism, the models are identical except that this model was restricted to cases where the parent, rather than the child, was selected to respond whereas the former model was of cases where children were selected to respond. The results are shown as odds ratios and with 95% confidence intervals in Table 7. The results are very similar to those of the model predicting when children answer. However, parents were less affected by the individual physician and the visit than their children—both levels were nonsignificant in explaining variance within the model. There were four predictors of whether a parent answers a question they were asked by a doctor (1) question format; (2) their child’s age; (3) whether an address term was used; (4) whether the physician was a non-native speaker of English. 3.2.1. Question format As with children, Wh-questions were less likely to be answered. This suggests that if the underlying difference between yes–no and Wh-questions is ‘difficulty’ it is a difficulty that affects interactants broadly and not only children. Compared to Wh-questions, the odds that a parent would answer a yes–no interrogative question went up 62% over the odds that they would answer an interrogatively formatted yes–no question. Declarative questions were very similar to yes–no interrogatives but the effect size was even stronger (122% more likely to be answered). Although rare, appender questions and tag questions were both also more likely to be answered: 58% more likely in both cases. Here the only difference from the pattern observed with children is the slightly stronger effect of declarative questions and that tag questions reach significance in their association with being answered. 3.2.2. Child age Child age had a significant effect such that for each additional year of age the odds of a parent answering a question asked of the child decline by 11%.
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
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Table 7 Results of multivariate logistic regression for parent answering.+
4.1. Discussion
answer a question, of whether a child answered a question posed to them, and of whether a parent was willing to answer questions about them. These findings, combined with the observation that children were categorically less likely than adults to answer questions asked of them, supports the analysis that was made by Stivers & Majid that doctors are attempting to analyze a child’s competence and likelihood of answering questions when they select them to answer. Children do grow more able to answer questions as they get older.2 Second, physicians ask children about particular content areas more often than others, and these are the topics that they are better able, and more likely, to answer questions about. But perhaps more significant is the considerable mismatch this study reveals between the factors that Stivers & Majid reported physicians to rely on when selecting children to answer questions [15] and the factors that were associated with whether children answered their questions: neither parent education nor race (as main effects or interaction terms) was associated with the child’s propensity to answer a physician’s question. It might not be unreasonable for a physician to attribute additional cognitive and/ or interactional competence to a child from a more educated family. As Lareau documents with her ethnographic study, middleclass families appear more likely to rehearse what doctor–patient or other professional interactions will be like and thus could better prepare children to participate in the interaction [25]. However, there was no effect of the parent’s class background (here, education) on children’s display of cognitive and interactional competence as indexed by their propensity to answer questions. Stivers & Majid showed that in these data, physicians selected children differentially on the basis of parent education as it interacted with race. They became more likely to select Latino and African American children only if their parents had significant education. This finding can be understood as an attribution of increased competence—that minority children whose parents are more highly educated might be assessed as more likely to answer questions than a child with less educated parents. However, the physician behavior patterns do not appear to be based in inductive generalizations from their general interactional experiences with families of similar backgrounds as documented in this study. Also in the previous study, physicians were less likely to ask Black children questions relative to other racial groups. Again, if this were analyzable as a negative attribution of competence, this study shows that there is no basis for the attribution in actual child behavior: Black children were just as likely to answer questions as children of other racial backgrounds. Another interesting mismatch was with respect to child gender. Physicians made no attributions of competence on the basis of child gender in the previous study of question-asking, but child gender was a strong predictor of answering in this study. Girls were much more likely than boys to answer physicians’ questions. The only sociodemographic factor that we find to have some basis in actual social behavior is one that is not recognized in physicians’ questioning behavior in these data. An alternative hypothesis that was offered to explain mismatch between predictors of physician question-asking behavior and children’s answering behavior is that certain parents (e.g., Black and less educated Latinos) are in some way preventing children from participating in the encounter. This study restricted its scope to question–answer sequences, but at least in this context, there is no indication of a difference in the way parents manage these sequences. As with the children, parents in these data behave no differently at the micro-interactional level on the basis of race or
In two main respects physicians pitch their questions to interlocutors who are more likely to answer their questions: child age was a predictor of whether a physician selected a child to
2 The fact that this sample only includes children up to the age of 10-years-old leaves open the question of whether this attribution of competence levels off at this age or continues to gradually rise up through adolescence until adulthood.
Level 1 variables
OR
Question content variables Child-topic question Family demographics Child age Female child Parent level of education Race Latino parent Black parent Asian parent Race by education Latino parent/education interaction Black parent/education interaction Asian parent/education Physician sociodemographics Latino physician Black physician Asian physician Non-native speaker of English Physician–parent racial concordance Selection variables Use of gaze with during question Use of child register in question Use of address term in question Presence of more than one caregiver Question format Yes–no interrogative Alternative question Declarative question Appender question Tag question Negative interrogative
95% CI
1.01
0.81, 1.27 ***
0.89 1.15 0.92
0.85, 0.94 0.92, 1.44 0.75, 1.12
1.02 1.38 0.40
0.49, 2.12 0.49, 3.91 0.10, 1.57
1.06 0.96 1.28
0.83, 1.35 0.66, 1.40 0.83, 1.97
0.81 0.77 0.95 1.41 1.05
0.48, 0.49, 0.66, 1.00, 0.74,
1.37 3.91 1.37 2.00 1.48
0.96 0.83 0.35** 0.88
0.82, 0.59, 0.17, 0.58,
1.13 1.18 0.72 1.34
1.62*** 1.09 2.22*** 1.58** 1.58** 0.47
1.28, 0.73, 1.78, 1.06, 1.06, 0.14,
2.06 1.64 2.78 2.34 2.35 1.60
Context variables
Estimate
Standard error
Level 2: Variance at visit level Level 3: Variance at physician level
0.22 0.08
(0.08) (0.04)
+
Model restricted to questions that selected adults. Denotes p .01. *** Denotes p .001. **
3.2.3. Address terms As mentioned earlier, the use of address terms was rare, especially with adults (only 1% of the time). However, it does reach significance here with a rather strong effect. The odds of a parents answering decrease by 65% if that question uses an address term to select them. 3.2.4. Non-native speaking physicians Parents were 41% more likely to answer a question asked by a non-native speaker of English. This variable had been included to rule out the possibility that independent of race parents would find it more difficult to understand a non-native speaker of English and therefore be less likely to answer. However, the result runs counter to that hypothesis. This association did not reach significance for the model predicting child answers. Finally, parents were less affected not only by individual physicians and the visit but also by interactional phenomena such as the use of physician gaze to select them, the topic of the question or the presence of an additional caregiver. And they were unaffected by their child’s gender. 4. Discussion and conclusions
T. Stivers / Patient Education and Counseling 87 (2012) 3–9
class. Parents showed a similar pattern to children in that parents were more reluctant to answer questions about their children as they grew older, and they were more inclined to answer yes–no formatted questions than Wh-formatted questions. Two unexpected predictors were physicians’ use of address terms which were negatively associated with parents answering. This is a result that was neither expected nor is easily interpretable particularly since it was not present for children where address terms were more common. Further qualitative work would be required to understand this relationship. One possible interpretation is that the result was driven not by the use of address terms per se but the contexts in which they are used. For instance, if they were mainly used when securing the parent’s attention was difficult they might otherwise have been less likely to respond. A second unexpected result was the association with physicians who are non-native speakers of English. Although it was only marginally significant, the interpretation is that parents may be more willing to accommodate nonnative speakers and thus ‘‘try harder’’ to answer. This study suggests that there is no evidence that children from particular socioeconomic or racial/ethnic groups are less likely to respond to a question. However, the study does point to interactional resources that are associated with securing a higher rate of child participation—particularly, physician gaze and yes–no question design. This study also underscores a previous finding that a child who can be engaged in an early question–answer sequence will be more likely to answer a subsequent question that establishes the reason for the visit [12]. In this study the significance of the visit level suggests that if a child can be engaged early, then they are more likely to answer other questions asked of them. This level was also significant for whether physicians selected a child to answer. Here we see just how interactive that behavior likely is: a physician who can secure an answer from a child appears to be more likely to ask the child more questions (to which the physician is, again, more likely to get an answer). In this study, physicians only asked children 37% of all of their questions, and children only answered 65% of those questions. Moreover, if a child delays their answer parents are more likely to answer on their behalf [12,23]. However, this study has identified several quite simple resources physicians can use to encourage child participation which might, in turn, increase the likelihood that physicians will ask children questions in the first place. 4.2. Conclusions Most healthy children do not interact with their physicians often but may nevertheless see no other health care providers until they reach adulthood. This may be particularly true for children coming from low socioeconomic family backgrounds, especially those who have reduced access to health care. Their primary care visits with pediatricians may be the only means of socialization into the role of autonomous adult patient that they have. Increasing the amount of interaction between health providers and children may increase child awareness of and ownership of their illnesses and lead children to be more pro-active patients in later life. 4.3. Practice implications As shown here, the two biggest strategies that physicians can employ are asking yes–no questions, whether interrogatively or
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declaratively formatted and gazing at children when they ask their questions. Just one or two yes–no social questions at the beginning of the visit stand to improve the chances of the child answering the first medical question put to them—usually the opening question. If this happens, children are more likely to continue to participate in the encounter, and physicians are more likely to keep asking them questions. These data suggest that this may be even more important for boys since girls are more frequent responders relative to their same age boy counterparts. Encouraging child participation stands to both better socialize the child into the patient role and to ensure that physicians receive all information relevant to the medical visit.
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