According to the confidence heuristic, people are confident when they know they are right, and their confidence makes them persuasive. Previous experiments have investigated the confidence–persuasiveness aspect of the heuristic but not the integrated knowledge–confidence–persuasiveness hypothesis. We report 3 experiments to test the heuristic using incentivized interactive decisions with financial outcomes in which pairs of participants with common interests attempted to identify target stimuli after conferring, only 1 pair member having strong information about the target. Experiment 1, through the use of a facial identification task, confirmed the confidence heuristic. Experiment 2, through the use of geometric shapes as stimuli, elicited a much larger confidence heuristic effect. Experiment 3 found similar confidence heuristic effects through both face-to-face and computer-mediated communication channels, suggesting that verbal rather than nonverbal communication drives the heuristic. Suggesting an answer first was typical of pair members with strong evidence and might therefore be a dominant cue that persuades. Our results establish the confidence heuristic with dissimilar classes of stimuli and through different communication channels. Consider a familiar scenario in which two friends, Ava and Ben, are deciding which of two possible restaurants to visit for a meal: Thai Break or Pasta Milestone. Thai Break is cheaper and has food that both would enjoy more than Pasta Milestone. Ben has no relevant knowledge on which to base a preference, whereas Ava has heard reports from her sister, who has eaten at both restaurants and found Thai Break to be much better. It is reasonable to suppose that the outcome would be best for both if they went to Thai Break, second-best for both if they went to Pasta Milestone, and worst for both if they failed to agree and consequently missed out entirely on a meal together. While discussing the options, it is likely that Ava would express a preference with greater confidence than would Ben; and even if she didn’t mention why she preferred Thai Break, it would be in Ben’s interest to interpret her confidence as evidence of superior knowledge and to defer to it. Ava and Ben would therefore probably end up dining at Thai Break.common-interest games in which one outcome Pareto dominates all other possible outcomes, and asymmetric information. The players’ interests coincide, and they are motivated to coordinate their actions, but they have incomplete information of varying reliability about the payoffs associated with the possible outcomes. Examples include life partners deciding between different houses to buy or politicians choosing between political leaders, where agreement is preferable to disagreement, and some jointly agreed on alternatives are typically preferable to others, but the individuals involved have different information about the available alternatives. The heuristic applies to common-interest games with asymmetric information, not to interactions in general. For example, a used-car dealer may tell a potential customer confidently that “this car is good for at least five more years,” but the customer is unlikely to be persuaded by the confidence of the communication because, although the dealer may know more than the customer, the two individuals obviously have diverging, rather than common, interests.According to the confidence heuristic, when people communicate beliefs to one another, they generally express confidence in proportion to their degree of certainty on the basis of their relevant knowledge; and if they have common interests in coordinating their decisions, recipients tend to judge the persuasiveness of the communication according to the confidence with which it is expressed. The formal properties of the confidence heuristic are outlined in the With regard to the type of decision task, No experimental tests of the integrated confidence heuristic have been published to date, and earlier experiments failed to investigate the heuristic as a game-theoretic concept that applies to interactive decision making, treating aspects of it as phenomena of individual decision making. Furthermore, previous research has focused chiefly on the confidence–persuasiveness aspect of the heuristic, omitting the knowledge–confidence aspect. Results have confirmed a general sensitivity of decision makers to communicator confidence . For exaFurther relevant research has been reported by The confidence–persuasiveness aspect of the heuristic has been confirmed in both intellective and judgmental tasks, in relation to questions with and without objectively correct answers and especially among decision makers with inadequate expertise . In simuconfidence heuristic, they were unaware of Research on confidence–persuasiveness effects has also focused on individual judgments or decisions using the Judge-Advisor System e.g., . When PrAlthough it may seem intuitively obvious that people will have higher confidence when they have better evidence, there is a substantial literature showing that people are overconfident in some judgments and underconfident in others, and that there are individual differences in confidence. People differ in meta-cognitive introspective ability to estimate the reliability of their own decisions, and this may relate to differing gray matter volume in the anterior prefrontal cortex and reciprocal projections to and from that area . Recent Our experiments included improved study designs characterized by real interactive decisions with financial incentives, enabling both the knowledge–confidence and the confidence–persuasiveness aspects of the confidence heuristic to be investigated in situations of common interests. More specifically, we report the first comprehensive test of the integrated confidence heuristic across three experiments using different judgmental tasks in common-interest games with asymmetric information. We tested the heuristic with two different stimulus classes, namely faces (Experiment 1) and geometric shapes (Experiments 2 and 3); in all three cases, we predicted that pairs of decision makers with asymmetric information would succeed in coordinating on the target response. Further, in Experiment 3 we examined whether the effectiveness of the confidence heuristic depends on the medium or channel of communication. Specifically, because so much interpersonal communication now takes place through electronic devices, we compared face-to-face (FtF) communication with computer-mediated (CmC) communication (instant messaging). We predicted that dyad members would make better decisions when communicating face-to-face than through instant messaging, because only FtF communication includes a full range of nonverbal information  that may be important in signaling confidence and thereby enabling the confidence heuristic to operate.Our first experiment set out to investigate the confidence heuristic in interactive decisions through the use of a facial recognition task. In line with previous research on eyewitness identification e.g., , 2008, wPairs of participants were asked to make their decisions while one was provided with strong evidence (a good E-FIT likeness of the target) and the other weak evidence (an E-FIT lacking strong resemblance to any of the faces). The pair members were permitted to communicate verbally while both looked at the same set of suspect photos on each trial, without seeing each other’s E-FIT evidence. We tested the hypotheses that evidence strength would affect task-specific confidence and that higher confidence would in turn result in increased persuasiveness, leading to better decisions by both pair members. To monitor the possibility of other factors overriding or enhancing the confidence heuristic, we examined factors that have been shown to influence persuasiveness in communication. We measured assertiveness in case a lack of assertiveness causes some participants to give in to the other pair member even if the other has weak evidence. We measured need for closure and need for cognition to determine whether people who just want to close the decision and reduce their uncertainty, or those who do not want to think deeply about the evidence provided to them, are less influenced by the confidence heuristic and give in to the pair member with weaker evidence. Finally, we investigated effects of age and gender to determine whether older participants are better at using the confidence heuristic because of experience and whether women are better than men at detecting nonverbal cues of confidence.SD = 4.83), who were recruited through posters displayed around the university campus. Payments depended on their own and their partner’s decisions in the task. After they completed the experiment, payoffs across all 23 trials were summed for each individual, and the totals were paid out . We aimed for 50 participants to detect a small to medium effect size (0.3) with 80% power. We terminated data collection after reaching our target sample size, without having conducted any preliminary analyses before stopping. We have reported all measures and conditions, and no data were excluded from the experiments reported in this article. Ethical approval for all three studies was granted by the University of Leicester Psychology Research Ethics Committee.The participants were 56 undergraduate students (28 women and 28 men) with a mean age of 22.09 years , aiming to induce either high or low confidence in each pair member on each trial. The first main dependent variable was self-reported confidence  following each trial, with separate mean confidence scores calculated for trials with strong and weak evidence.A second dependent variable was persuasiveness—the percentage of trials on which pair members successfully persuaded their partners. We had estimates from a pilot study confirming that, in the absence of consultation, strong-evidence pair members would normally choose the target faces that their E-FITs were designed to resemble, and we interpreted the percentage of agreements by weak-evidence pair members with these target choices as a rough-and-ready index of persuasion by the strong-evidence partner, although there remains a 1 in 9 probability that the weak-evidence partner chose it by chance, and not as a result of persuasion, because there were nine faces from which to choose. The degree of agreement on the target faces was an indication of how good the decisions were and was thus our measure of performance. We scored agreement by both pair members on any of the other faces as persuasion by the weak-evidence pair member, not only because the pilot data suggested that, without consultation with a partner, the strong-evidence pair member would usually have chosen the target face, but also because the probability of the strong-evidence pair member choosing the same face that the weak-evidence partner chose, purely by chance, is only one in nine.Additionally, we recorded age, gender, gender composition of the participant pairs, closeness of relationship within the participant pairs, assertiveness, need for closure, and need for cognition. Finally, we taped and transcribed the verbal exchanges between pair members in each trial.All participants received a questionnaire booklet with one practice trial and 23 experimental trials that required them to match an E-FIT with one of nine possible suspect photos.The two booklets for each pair were matched so that whenever one pair member viewed a strong E-FIT of the target, the other viewed a weak E-FIT bearing no strong resemblance to any of the faces. The same E-FITs were used twice, shown once to the first pair member and at a different point in the session to the partner. Because each pair member viewed exactly the same stimuli as the other, but at different times, the data enabled us to determine the number of trials on which the opinion of the pair member with strong evidence was accepted by the partner, controlling for individual differences in facial recognition ability and idiosyncratic differences between photos. Each participant was given an example set of nine suspect photos plus an example E-FIT, followed by eight strong-evidence sets (while the partner had weak evidence), eight weak-evidence sets (while the partner had strong evidence), four fillers in which both pair members had strong evidence, and three fillers in which both had weak evidence, in a randomized order. The fillers were included to conceal the evidence strength manipulation.http://pics.psych.stir.ac.uk/). The E-FITs were constructed using custom software used by U.K. police forces. Half of the E-FITs were designed to resemble one of the faces strongly and half to lack strong resemblance to any of the photos, although they could be viewed as weak evidence for one or more of the nontarget faces. The degrees of likeness of the E-FITs to the suspect photos and the degrees of confidence that the participants felt in their identifications were evaluated in a pilot study in which 32 participants rated the resemblance of E-FITs to target faces across 73 trials. The materials were calibrated so that pair members with weak evidence would have an accuracy rate near 11% (pure guessing) and low confidence, whereas pair members with strong evidence would reliably select the target alternative with high confidence. The data from the pilot study showed that, when the evidence was weak, participants chose the target faces on 7.04% of trials and with 29.37% confidence; and when the evidence was strong, they selected the target faces on 73.45% of trials with 70.59% confidence , whereas the weak-evidence E-FITs induced mean confidence of 37.67% when nontarget faces were chosen (range = 31%–47%). The pilot study thus provides a manipulation check confirming not only that we successfully manipulated strong versus weak evidence but also that the strong-evidence E-FITs, when chosen, induced much higher confidence than the weak-evidence E-FITs, without leaving either pair member in complete certainty or complete doubt.complete strangers), 2 (weak acquaintance), 3 (regular acquaintance), 4 (friend), 5 (good friend), and 6 (intimate partner).Because assertiveness could affect persuasiveness and decisiveness, we administered the Rathus Assertiveness Schedule , a 30-itAfter giving informed consent, participants received booklets containing experimental materials. In their own time, they read the task instructions, and the experimenter answered any questions. Participants were fully informed about their options and the financial incentives in the task, and they were aware that the E-FIT evidence provided for solving the task would differ between pair members. For each of 23 decisions, participants were told the following: “If you both choose the same face of the person who did commit the crime, you will get 40p (approximately US$0.50) each”; “If you both choose the same but innocent person, then you get 20p (approximately US$0.25) each”; and “If you choose two different people, then you each get nothing, even if one of you chooses the person who is guilty.”not at all sure that I chose the right person) to 100 (completely sure that I chose the right person). After completing all 23 trials, the payoffs earned in each trial were calculated and paid.Pair members sat on opposite sides of a table, divided by a low partition to hide their test materials from each other but to allow face-to-face communication, and a voice recorder was switched on. For each of the 23 experimental trials , pairs were allowed up to 2 min to discuss which face, from an identical array of nine suspect photos given to both, looked most like the face portrayed in the E-FIT and to record their individual decisions. After circling their decisions on their answer sheets, participants rated how confident they felt that they had chosen the correct answer on a scale, ranging from 0  than when they received weak evidence , F = 51.366, p < .001, , and there was no significant effect of gender . The persuasions were significantly more frequent under the effect of strong evidence  than under weak evidence , F = 56.112, p < .001, , and once again there was no significant effect of gender (BF10 = 0.27). No significant correlations were found between persuasiveness, confidence, and any of the individual difference variables . A Bayesian repeated-measures analysis of variance (ANOVA) showed that none of the individual differences influenced persuasion significantly .On most trials (60.94%), the pair members with strong evidence persuaded their partners with weak evidence to agree with their decisions. The pairs disagreed with each other and chose different alternatives infrequently  were used twice, once in the first two trial blocks and once in the second two, observed changes in confidence cannot be explained by idiosyncratic differences between task materials in different trial blocks. The data showed that after initial stability in the first three trial blocks, there was a small drop in confidence in the last trial block for pair members with both strong evidence (6% lower) and weak evidence (8% lower). From this we conclude that while the efficacy of the confidence heuristic did not change over time, the difficulty of the task began to take its toll on confidence toward the end.Taken together, these results indicate that the pair members with stronger evidence were significantly more confident and more often persuasive than those with weak evidence. This provides support for both aspects of the confidence heuristic. Not only was the confidence heuristic effective, but it appears to have had far more influence on decision making than any individual difference variable that we investigated.I’m pretty sure mine’s Number 3. It’s quite identical; the ears are quite long on my picture, the hair is practically identical to Number 3’s, er . . . I have the same eyebrows and the same mouth and the same expression. Mine’s practically Number 3. . . . I’m quite happy to put down. . . 100% confident, it’s practically, yeah, I’m quite certain that its Number 3.We examined the verbal transcripts for task comprehension, and we classified typical contents in the communications, using a taxonomy of confidence cues provided by In contrast, the following is an example statement indicating low confidence: “I find this very difficult. I have no idea, to be very honest.” Several statements provided qualitative support for the persuasiveness of high confidence shown in the quantitative data. For example: “I’m very dubious about this, but I don’t think he looks like anybody to be very honest, so I would tend to go with what you said, so Number 7.” In some conversations it was clear that pair members could not decide on an answer and were thus happy to go along with their more confident partners. In other situations, weak-evidence pair members with some degree of confidence were persuasive and their strong-evidence partners backed down, perhaps for the sake of group harmony. Pair members sometimes checked how confident their partners felt with questions such as, “Are you sure?” “If you’re quite sure,” “Really?” For example, the conversation between Participant 29 and Participant 30 included the following exchange: “Errm, I mean, you wanna give a percentage about how sure you are about 7 because I would say. . . .” “I’d go for near 75 to 80.” “That’s a lot higher than me, so let’s go 7.”In most cases, participants chose the first answer suggested, these cases outnumbering by around 2.5:1 cases where the first answer was not chosen in the end. It appeared that pair members with strong evidence would often identify the matching face in the array but on some occasions be swayed from their choice by their partners, as their confidence declined over the conversation. Getting in with the first suggested answer seemed to have an important psychological effect; for example, one pair member with weak evidence began the conversation with the following: “Straight away I’d say . . .”; but this participant was interrupted at that point by the partner with strong evidence jumping in and saying “3” before the first pair member’s choice could be voiced. A large proportion of the verbal exchange involved pair members describing their own E-FITs and comparing particular features with their partners’ E-FIT descriptions. Some participants attended to minute details: “Er . . . well if you look at Number 4, you can just make out in the corner of the E-FIT a little stud which could be an earring, ‘cos Number 4’s wearing sort of square earrings.” Consequently, many pairs were cut off prematurely by the 2-min time limit on verbal discussion.Overall, the verbal protocols confirm that the facial identification task provided a useful decision context for testing the confidence heuristic. But the facial stimuli also elicited excessively detailed discussions, including minute descriptions and comparisons of individual facial features, and this sometimes crowded out and overshadowed the type of comments that are the focus of our investigation, namely those primarily reflecting or expressing degrees of confidence. A related problem was that the facial identification task proved very difficult. Many participants struggled with it, and even pair members with strong evidence occasionally failed to recognize the target face from the E-FIT and thus argued for nontarget alternatives. As a consequence, even when they succeeded in persuading their partners, they may have persuaded them to choose nontarget alternatives, thus earning lower persuasiveness scores and incentive payments than they could have achieved. Furthermore, when strong evidence was not strong enough to induce high confidence, they may have failed to argue for the target face altogether. Overall, the difficulty of the facial identification task may thus have masked the potential strength of the confidence heuristic. To address this problem, we designed a second experiment using simpler stimuli (geometric shapes) and an easier decision task with two rather than nine response alternatives.Experiment 2 was designed to replicate Experiment 1 using a simpler class of stimuli and an easier decision task. We chose elementary geometric shapes that pair members tried to match for size because we wanted to avoid the detailed discussions about individual stimulus features that had occurred in Experiment 1 and, thus, to allow more time for confidence-signaling communication. In addition to the three personality measures used in Experiment 1, we added a measure of dogmatism because SD = 2.90), recruited as in Experiment 1. Out of 41 participant pairs, 21 were mixed gender, 13 were all female, and seven were all male. All participants provided informed consent. Once again, participants received payments depending on their own and their experimental partners’ choices. On each trial, if both pair members coordinated by choosing the target shape to which the strong evidence pointed, then each received 40p (US$0.50); if both chose the same but nontarget shape, then each received 20p (US$0.25); if they chose different shapes, then each received nothing. The payoffs from all trials were added together for the final payments . Considering the large effect size in Experiment 1, and the number of predictors in the regression, we aimed for a minimum of 70 participants to detect a large effect size (0.4) with 95% power. We terminated data collection before performing any preliminary analyses.We tested 82 participants (35 men and 47 women) with a mean age of 19.83 years  to a target shape and rated their confidence in their answers. The materials were calibrated so that pair members with weak evidence would have an accuracy rate near 50% (pure guessing) and low confidence, whereas pair members with strong evidence would reliably select the target answer and have high confidence. The data from the pilot study showed that, when the evidence was weak, participants chose the target shape on 53.00% of trials  with 71.67% confidence. When the evidence was strong, they chose the target shape on 90.50% of trials with 87.83% confidence. With weak evidence, they chose the nontarget alternative on 47.00% of trials with 75.83% confidence; and with strong evidence, they chose the nontarget alternative on 9.50% of trials with 67.00% confidence. The latter result shows that although the vast majority found the task easy when given strong evidence, a few strong-evidence pair members found it hard to select the closest-size shape.Both pair members received paper folders containing two pages of instructions followed by a separate page for each decision trial . Additionally, participants were given a separate answer sheet to record their decisions. On each trial, they were presented with one target shape and two test shapes see . Both paThe task involved identifying the test shape closest in size to the target shape and, if possible, agreeing on the same shape with the other pair member. Participants were incentivized with financial rewards depending on their own and their partners’ choices in the experiment, essentially as in Experiment 1.We used eight different geometric shapes, each presented to every participant pair twice. The order of trials and the order in which participants were presented with either strong or weak evidence were randomized, but each participant completed the same numbers of trials with strong and weak evidence. The 20-item short-form Rokeach Dogmatism Scale  was giveThe procedure used in Experiment 2 was almost identical to Experiment 1, the main difference being the reduced number of 16 experimental trials to lessen boredom.M = 83.89, SD = 10.22) than when they received weak evidence ; F = 101.428, p < .001, , and there was no significant effect of gender on confidence (BF10 = 0.32).The manipulation of evidence strength once again had a significant effect on confidence. When pair members received strong evidence, they reported significantly higher confidence levels . The number of persuasions under the effect of strong evidence  was significantly higher than under weak evidence ; F = 1226.505, p < .001 , and once again there was no significant effect of gender (BF10 = 0.18). Furthermore, persuasiveness and confidence were not significantly affected by any of the individual difference variables .On the vast majority of trials (85.77%), the pair members with strong evidence persuaded those with weak evidence to agree with their decisions. The pairs failed to reach agreement infrequently  and computer-mediated communication (CmC), because this is a factor that has been found to influence persuasiveness in individual decisions . The effWe examined gender differences once again, because the judgment task in this experiment is more quantitative than the task in Experiment 1, and Finally, we examined verbal timing effects. SD = 2.20), recruited as in Experiments 1 and 2 and randomly assigned to 39 participant pairs for testing. Of these, 26 pairs contained two female participants, 11 two male participants, and two mixed genders. We aimed for the pairs to be same gender in case talking with someone of the opposite sex inhibited conversation. All participants provided informed consent. All participants received course credits for taking part; additionally, every participant was paid according to incentive earnings from the decision task . Considering the large effect size in Experiments 1 and 2, two conditions, covariates, and financial cost, we aimed for 75 participants to detect a large effect size (0.5) with 80% power. We terminated data collection before performing any preliminary analyses.The sample consisted of 78 undergraduate psychology students  with a mean age of 19.39 years (The experiment used a 2 (Channel) × 2 (Evidence Strength) mixed model design. Participant pairs were randomly assigned to two different communication channel treatment conditions (between-subjects), either FtF or CmC. Additionally, evidence strength (within-subjects) was manipulated as in Experiment 2. The experiment included six trials with strong evidence and six with weak evidence. The main dependent variables were again persuasiveness and self-reported confidence. To determine whether confidence is communicated by timing of verbal comments, we calculated the percentage of trials on which each pair member spoke first and the percentage of trials on which each pair member suggested an answer first. Finally, we measured several demographic and individual difference variables, namely gender, gender composition of the participant pair, judgmental self-doubt, trait dominance, and the Big Five personality traits.Participants were given paper folders with instructions and decision trials, similar to those used in Experiment 2. Additionally, several paper-based questionnaires were distributed, and participants completed these in random order after finishing the interactive decision task. The questionnaires included a Judgmental Self-Doubt scale , three iIn the FtF condition, the procedure was identical to Experiments 1 and 2. Pair members sat opposite each other with a low partition that enabled face-to-face, verbal conversation but shielded their test materials from each other’s view. In the CmC condition, pairs met briefly and were immediately led into separate rooms; they could not see or hear each other, but written communication was enabled via Slack, an online instant-messaging program. The experimenter gave a signal whenever pair members were required to turn over the page and begin a new decision trial. In this experiment, pairs had up to three minutes to discuss each problem and record their decisions on their individual answer sheets.After completing the required decisions, one decision trial was drawn at random by the experimenter to determine incentive payments. Both pair members received the financial rewards earned on the selected trial. This incentive system is designed to avoid the use of averaging strategies across experimental trials and to ensure that participants treat every trial as a separate decision task that might determine their final payoffs; there is experimental evidence that it achieves this  than when they received weak evidence , F = 34.425, p < .001, . As shown in F = 2.177, p = .144, (BF10 < 1.0), nor did the interaction of evidence strength and communication channel, F = 0.055, p = .816.The manipulation of evidence strength had a significant effect on individuals’ confidence: a mixed ANOVA revealed that when pair members received strong evidence, they reported significantly higher confidence levels  than under weak evidence ; F = 562.592, p < .001, . Surprisingly, communication channel had no significant effect, F = 0.081, p = .776, (BF10 < 1.0), nor did the interaction of evidence strength and communication channel, F = 1.026, p = .314.As is clear in Taken together, these results provide further evidence for the confidence heuristic and extend it across FtF and CmC channels. Contrary to our predictions, we did not find any significant effects of communication channel, with FtF and CmC yielding remarkably similar effects of knowledge on confidence and confidence on persuasiveness. This suggests that it is verbal rather than nonverbal communication of confidence that drives the confidence heuristic, although timing of verbal communication was obviously a significant signal of confidence, as explained in the following text.SD = 23.29) of trials, significantly more frequently than the 26.97% (SD = 23.25) when they had weak evidence, F = 114.605, p < .001, . Communication channel and participants’ gender did not yield significant effects. The second ANOVA showed that pair members spoke first more frequently in the strong-evidence than the weak-evidence condition , F = 42.909, p < .001, , and there was no evidence of any gender or communication channel effects.We carried out two ANOVAs, with communication channel (FtF vs. CmC) and gender as between-subjects factors and evidence strength (strong vs. weak) as a within-subjects factor, on both the percentage of trials on which pair members suggested an answer first and the percentage of trials on which they spoke first. Evidence strength was the only significant factor: when pair members had strong evidence, they suggested the answer first on 73.03%  or just stating something unrelated to the decision . The verbal protocols also revealed that the conversations were very short in this experiment and lacked details or much content. For example, dyad 38’s conversation on shape 6 was typically minimal, starting with Player A saying “A?” followed by a reply from Player B of “A,” and Player A concluding, “Yeah.” Comments that were a bit longer included remarks such as: “It’s just a little smaller,” “B looks slightly bigger,” “They’re both really similar,” “I reckon it’s A too. How confident are you?” Common phrases were “I think it’s A [or B],” “I reckon it’s A [or B],” or just a suggested answer with or without a questioning tone.n), to see which if any individual-difference variables predicted persuasiveness. In the strong-evidence condition, no significant predictors were found. In the weak-evidence condition, openness  and trait dominance  predicted the percentage of persuasions. Thus, participants who were more dominant and less open were more persuasive when they had weak evidence. We performed a similar analysis to assess the predictors of participants’ confidence in their decisions. When evidence was strong, mean confidence was predicted only by the percentage of persuasions , and when evidence was weak, there were no significant predictors.We performed a multiple linear regression analysis, ignoring communication channel , and a similar correlation was found in the weak-evidence condition . In both conditions, persuasions were nonsignificantly related to how often a pair member spoke first. Thus, it appears that giving an answer first is a crucial factor increasing persuasiveness, both when the evidence is strong and when it is weak. It is striking that none of the personality measures that we investigated correlated with how frequently a pair member suggested an answer first. However, in the strong-evidence condition only, participants who had higher dominance scores spoke first more frequently .Correlation analysis showed that, when there was strong evidence, the frequency of persuasions correlated significantly with how frequently the participant suggested an answer first . In Experiment 3, using the same decision task as Experiment 2, the confidence heuristic generated 84.83% of optimal joint decisions. The confidence heuristic effect is clearly powerful and robust when people are motivated by common interests. There were clearly some instances where people failed to communicate their confidence persuasively enough, resulting in suboptimal agreement or disagreement, and these instances deserve further investigation by future researchers.Experiment 1, in which we used a facial identification task with nine response alternatives, yielded the lowest percentage (61%) of optimal joint decisions. In Experiment 2, we therefore used an easier decision task involving size judgments of simple geometric shapes with just two response alternatives, and this yielded 85.77% optimal joint decisions, replicating the main findings of Experiment 1 with a very large confidence–persuasiveness effect size  were significantly related to persuasiveness or confidence. This suggests that persuasiveness was determined chiefly by our experimental manipulation of evidence strength, overwhelming all the personal characteristics that we investigated. However, in Experiment 3 we showed that participants with high trait dominance and low openness were more persuasive when they had weak evidence. This points to circumstances in which the confidence heuristic tends to break down and allow ignorance to overwhelm knowledge. However, this breakdown did not occur in the strong-evidence condition, where personality factors had no significant effect on persuasiveness. Overall, high confidence generated by strong evidence was more influential than any individual difference variable that we investigated in this study.Experiment 3 showed, perhaps surprisingly, that the confidence heuristic operates similarly through both CmC and FtF. This suggests that confidence is communicated primarily through verbal signals and not through facial expressions, gestures, and tone of voice. However, verbal timing effects turned out to be significant: Our data showed that suggesting an answer first was strongly associated with persuasiveness, whether the speaker had strong or weak evidence, confirming findings of heuristic in 1957, conceived it to be a rough-and-ready procedure or rule of thumb for making a decision or forming a judgment, without an exhaustive comparison of all available options, and hence without any guarantee of a correct or optimal result. The decision theorist Herbert Simon, who introduced the term What are the implications of our investigation for future research? Our study raises many questions, some of which we have already mentioned. It is worth drawing attention to a few further unanswered research questions. First, we investigated common-interest games in which pair members were motivated to select the same targets from sets of stimuli. Whether the confidence heuristic operates in the same way when people have mixed motives—when they are motivated partly to compete and partly to cooperate with each other—is open for future researchers to discover. There will undoubtedly be situations in life where people hide their true confidence to gain a competitive advantage. Researchers studying this topic need to bear in mind the cooperative or competitive nature of the situation and whether the participants have reasons to trust or distrust each other.Second, Experiment 1 revealed a possible trend that may also be worth investigating further. When the likely prediscussion difference in confidence between pair members, estimated from confidence ratings of the same materials observed in the pilot study, was relatively small (below about 25%), the pair member with strong evidence tended to be noticeably less persuasive than when the gap was larger. In future studies, it may be possible for researchers to establish a confidence threshold above which speakers tend to be persuasive, or a critical confidence gap between two people that enables the confidence heuristic to function effectively. Finally, researchers could examine cross-cultural differences in this area, as cultural norms around how confident one should appear, for example between Eastern and Western countries, could lead to cultural misunderstandings or lack of coordination and cooperation.The confidence heuristic has important implications for everyday life, because it facilitates the emergence of truth in a cacophony of falsehood and misinformation. We agree with 10.1037/xge0000471.supp


There is a current need to build the capacity of Health Policy and Systems Research + Analysis (HPSR+A) in low and middle-income countries (LMICs) as this enhances the processes of decision-making at all levels of the health system. This paper provides information on the HPSR+A knowledge and practice among producers and users of evidence in priority setting for HPSR+A regarding control of endemic diseases in two states in Nigeria. It also highlights the HPSR+A capacity building needs and interventions that will lead to increased HPSR+A and use for actual policy and decision making by the government and other policy actors.Data was collected from 96 purposively selected respondents who are either researchers/ academia (producers of evidence) and policy/decision-makers, programme/project managers (users of evidence) in Enugu and Anambra states, southeast Nigeria. A pre-tested questionnaire was the data collection tool. Analysis was by univariate and bivariate analyses.The knowledge on HPSR+A was moderate and many respondents understood the importance of evidence-based decision making. Majority of researcher stated their preferred channel of dissemination of research finding to be journal publication. The mean percentage of using HPSR evidence for programme design & implementation of endemic disease among users of evidence was poor (18.8%) in both states. There is a high level of awareness of the use of evidence to inform policy across the two states and some of the respondents have used some evidence in their work.The high level of awareness of the use of HPSR+A evidence for decision making did not translate to the significant actual use of evidence for policy making. The major reasons bordered on lack of autonomy in decision making. Hence, the existing yawning gap in use of evidence has to be bridged for a strengthening of the health system with evidence. Endemic tropical diseases continue to impose a tremendous health burden in resource-poor countries throughout the world, claiming millions of lives annually and inflicting severe morbidity that results in significant losses in economic productivity and social progress . NigeriaAs policy-makers and communities increasingly demand better returns on investments in health, HPSR+A has the potential to enable health system interventions to achieve better value for money. However, the current capacity to undertake HPSR+A and teaching is low in developing countries . Health In order to strengthen health systems using evidence, there is a current need to build the capacity of HPSR+A in LMICs as this encompasses the processes of actual decision-making at all levels of the health system . CapacitIn Nigeria, Universities are central to strengthening and sustaining HPSR+A capacity. They not only produce knowledge through research but are also mandated to teach the next generation of policy-makers, health professionals, and researchers . HoweverStrengthening the capacity of producers and users of research is arguably a sustainable strategy for developing the field of HPSR+A in Africa than relying on training in high-income countries . As bothThis paper provides information on the levels of involvement in HPSR+A (among producers of research evidence) and use of research evidence for decision making (among users of evidence) for the control of endemic diseases in two states in Nigeria. It also highlights potential interventions for improving capacity to undertake and use HPSR+A in policy and decision making.A quantitative study design was used to collect information from purposively selected respondents who are either researchers/academia (producers of evidence) and policymakers, programme/project managers (users of evidence) in Enugu and Anambra states. A survey questionnaire was administered to 96 respondents in both states.Enugu and Anambra states are situated in south-east Nigeria. Based on the 2006 census, and an annual growth rate of 2.8%, Enugu state is estimated to have a population of 3.3million people while Anambra state has 4.2million people . The heaRespondents were purposively selected based on their roles and involvement in endemic disease control in the selected States. They included, i) researchers from universities and research organizations, ii) programme managers for endemic diseases, malaria and maternal and child health, iii) policymakers and senior healthcare managers in State Ministry of Health and affiliated health agencies, iv) data management officers in the Ministry of Health, v) representatives of civil society organizations, and vi) media representatives.Data was collected data using two different questionnaires for the two categories of respondents (producers and users of research evidence). The questionnaires were designed for this study and reviewed by experts in HPSR+A to ensure contents were valid. They were then were pre-tested for construct validity on similar respondents in Ebonyi state (a neighbouring state) 2 weeks prior to being used to collect data. Feedback from respondents on clarity of questions were used to revise and simplify the questions and options.The questionnaire for producers of research evidence was used to elicit information on their levels of involvement in HPSR+A (including enablers and constraints), proportion of research time spent in HPSR+A, methods of communication of research findings, level of engagement with policymakers and uptake of research findings for decision making. The questionnaire for users of evidence elicited information on individual and organizational patterns of use of evidence for policy and decision making. It also explored policymakers’ demand for and capacity to initiate research, as well as factors that have enabled or constrained evidence-based decision making. Both questionnaires were also used to collect information on respondents’ personal characteristics such as age, gender, professional cadre and role in organization.Univariate analysis was used to summarize categorical variables, while bivariate analysis was undertaken to determine the relationship between respondents’ personal characteristics and their level of involvement in generating and/or using research evidence for decision making. Findings are presented in tables and narratives.The personal characteristics of respondents are presented in Table The rest of the findings are reported separately for producers and users of evidence.p = 0.02). The major enablers/motivators to involvement in HPSR+A were personal interest (52%) and mentorship (40%). The major constraint was lack of funds or research grants (62%).Table With respect to research priority setting, 52% of respondents stated that their research priorities are sometimes informed by the needs of policymakers, and 46% reported that they had undertaken research that was conceived through direct engagement with decision makers.Figure Table p 0.01).Table Relationship between personal characteristics of producers of evidence and proportion of research time spent on HPSR+A is presented in Table Over 95% of users of evidence reported that they were aware that research evidence could be used for decision making. Table Percentage of times decisions were made based on research evidence are summarized in Table Figure Table The higher proportion of producers of research evidence involved in HPSR+A in Enugu state could be explained by the influence of Health Policy Research Group which is a foremost organization known for generating research evidence in health policy and systems analysis, as well as training potential HPSR+A researchers. Enablers for involvement in HPSR+A include personal interest, mentorship, promotion and availability of research grants. On the flip-side, respondents reported that lack of funds, lack of interest, lack of mentorship and lack of educational resources were major constraints to getting involved in HPSR+A. These results are in concordance with other studies that have highlighted funding, mentorship and opportunities for training as key drivers for building capacity of researchers in the field of HPSR+A , 12–14.Majority of the users of evidence (decision/policymakers) in both states were aware that research evidence should inform policy decisions, and a few reported they had in the past requested for research evidence or initiated research for policy/strategy development and program implementation/review. This could be attributed to increasing global attention and support for evidence-informed decision making in health. The proportion of users who reported actually using research evidence in decision making was not as robust, and their reasons were mainly lack of awareness of HPSR evidence and lack of autonomy in decision making. The former reason is irrespective of the fact that considerable numbers of producers of research evidence in both States reported that their research is informed by health policy and program priorities of users of evidence. Poor access to research evidence and limited decision space have been previously reported as constraints to evidence-based decision making , 17.There seemed to be a clear channel for gathering evidence for decision making in both States. Whereas producer of research evidence preferred journal publications, conferences and feedback workshops for dissemination of research findings, users of evidence appeared to value policymaker workshops, partners’ meetings and short courses as important channels for communicating/receiving research evidence. The preference for journal publication among producers of evidence is due to high visibility and academic staff appraisal requirements which are both critical for career progression of university lecturers. The observed mismatch in communication of research evidence has been underscored as a major constraint to GRIPP . Hence cFinally, although, users of evidence in both States perceived research dissemination and GRIPP activities to be very important, their capacity to participate in these activities was poor, and has been linked to low demand for high-quality research outputs . This unThe study elicited information from a diverse group of respondents who represent the two vital categories of actors needed for getting research evidence into policy and practice, and uses quantitative research method which has not been extensively applied in evaluating capacity needs for HPSR+A. Notwithstanding that it focuses on two Nigerian states, findings could be applied in settings with similar contexts. The application of quantitative method alone is a major limitation because it does not allow in-depth exploration of the subject matter. However, other authors have examined HPSR+A capacity needs using qualitative research methods. This paper also highlights a knowledge gap of respondents’ views of what could be done to ensure optimal integration of research evidence into policy and practice in the control of endemic diseases. This could form the basis for further study.There are gaps in capacity to produce and use evidence for decision making in control of endemic diseases in Nigeria. Involvement of researchers in HPSR+A is constrained by lack of funding, limited numbers of mentors and inadequate training opportunities. Poor uptake of research evidence in policymaking is hindered by poor access to research evidence and lack of autonomy in decision making. There is the need to invest in capacity building activities in order to develop a critical mass of users and producers of evidence in HPSR+A for better control of endemic diseases.


In primary care, patients present with multimorbidity and a wide spectrum of undifferentiated illnesses, which makes the application of evidence-based practice (EBP) principles more challenging than in other practice contexts.The goal of this study was to explore the experiences and understanding of family physicians (FP) in primary care with regard to EBP and the implementation of evidence-based guidelines.The study was conducted in Cape Town primary care facilities and South African university departments of Family Medicine.For this phenomenological, qualitative study, 27 purposefully selected FPs from three groups were interviewed: senior academic FPs; local FPs in public-sector practice; and local FPs in private-sector practice. Data were analysed using the framework method with the assistance of ATLAS.ti, version 6.1.Guideline development should be a more inclusive process that incorporates more evidence from primary care. Contextualisation should happen at an organisational level and may include adaptation as well as the development of practical or integrated tools. Organisations should ensure synergy between corporate and clinical governance activities. Dissemination should ensure that all practitioners are aware of and know how to access guidelines. Implementation should include training that is interactive and recognises individual practitioners’ readiness to change, as well as local barriers. Quality improvement cycles may reinforce implementation and provide feedback on the process.Evidence-based practice is currently limited in its capacity to inform primary care. The conceptual framework provided illustrates the key steps in guideline development, contextualisation, dissemination, implementation and evaluation, as well as the interconnections between steps and barriers or enablers to progress. The framework may be useful for policymakers, health care managers and practitioners in similar settings. Practitioners need research evidence for the whole range of diagnostic, prognostic, interventional and phenomenological questions that arise within this context.6 Concern has also been raised that research is often conducted in areas outside of primary care with limited generalisability.7 In addition research evidence from the primary care setting is often of poor quality8 and evidence derived from randomised controlled trials constitutes only a portion of the real knowledge that is needed.9The principles of evidence-based practice (EBP), however, are not as easily applied in primary care as in the biomedical and more disease-centred context of hospital care, where the process of evidence-based medicine (EBM) was originally developed.10 Primary health care (PHC) is complex and uncertainty is common.11 In addition, knowledge of complexity is critical in the management of patients with comorbidity in PHC practice12 and makes both research and delivery of care particularly challenging.13Complexity theory has influenced the philosophical discourse of family medicine and provides tools to understand the consultation.14 Clinical practice guidelines, however, struggle to deal with complexity and to guide decision-making in the face of comorbidity.One of the most common ways of synthesising and presenting the latest evidence to clinicians is in the form of clinical practice guidelines. As EBP grew, more and more guidelines were prepared and disseminated, many for use in primary care. Clinical practice guidelines respond to wide variations in practice, excessive cost, substandard outcomes and new evidence, which could have a significant impact on patient management.16 Although a quality evidence-based guideline has the potential to achieve this, it may only succeed if ‘as much attention is paid to the dissemination and implementation phase as to its original development’.17Clinical practice guidelines have been shown to change clinical practice and improve patient outcomes.19 In developing countries up to 60% of guidelines that are available centrally may be absent in more peripheral settings.20Poor dissemination of guidelines results in poor availability at the point of care and therefore little impact on health care delivery.21 Even in well-resourced settings implementation may be patchy, and large variations in practice remain.23 It is not clear whether guideline developers, managers of health organisations or practitioners should be responsible for implementation, and implementation is often poorly funded.24Guideline implementation is an active, planned and tailored process, which addresses barriers to change.25 and more could be done to adapt guidelines to local settings.26 Engaging the users of the guidelines in implementation has been recommended,27 but the most effective strategies for implementation remain unknown. Multifaceted interventions were thought to be more effective, but recent evidence suggests otherwise.29 Implementation should go beyond staff education to look at the organisation of care and teamwork. Staff education should embrace different learning styles and principles of adult education.30Understanding the knowledge, attitudes and perspectives of practitioners can improve their adherence to guideline recommendations33 Educational outreach or ‘academic detailing’ in primary care has been shown to be effective in the local context.36 Barriers to guideline implementation include time constraints, lack of motivation and clinical inertia,38 inappropriate evidence, the capability and preferences of the health care providers, and the capacity of the health care setting.39Enablers of guideline implementation include feedback, educational outreach, face-to-face training of practitioners by professional experts and quality improvement cycles.40; decision-making on the basis of experience, evidence and knowledge of the patient’s story41; goal-orientated care42; plan–do–study–act cycles43; and using problem-solving techniques.44 Effective clinical decision-making therefore requires a holistic approach that accepts unpredictability and uncertainty, good communication skills; and good judgment to balance competing interests.45The integration of evidence-based decision-making with the complexity of primary care may require additional tools such as using an empirical trial of treatmentIn South Africa, little is known about the attitudes and behaviour of primary care practitioners towards EBP and the implementation of clinical practice guidelines. This research aimed to explore the experiences and understanding of family physicians (FPs) in South African primary care with regard to EBP and the implementation of evidence-based guidelines in practice.46This was a phenomenological, qualitative study using semi-structured interviews.In the public sector of the Cape Town metropole, FPs were appointed at community health centres where they were the senior clinicians in multidisciplinary teams that included medical officers, clinical nurse practitioners, pharmacists and other allied health professionals. Their job description included leadership of clinical governance, and one of the expected activities was implementation of clinical guidelines. In the private sector, FPs were mostly in solo practice. Some of the FPs were also involved with the clinical training of under- or postgraduate students and were linked to universities. Public sector facilities served the majority of the uninsured population, while the private sector served those with insurance or able to make out-of-pocket payments. Family physicians were trained by academic departments at eight different universities in South Africa and these departments employed full-time academic FPs at the level of senior lecturer or professor. In Cape Town, Stellenbosch University and the University of Cape Town were training FPs.Purposeful sampling was used to select 8–12 FPs from three different groups: senior academic FPs affiliated to universities in South Africa; local FPs in the public sector; and local FPs in private practice. All the local FPs selected had some involvement with the universities in the Cape Town metropole as this would ensure some exposure to EBP and guideline implementation. Recruitment procedures also drew upon snowball sampling, as interviewees suggested other FPs who had the capacity to contribute to the phenomenon of interest.All interviews were conducted face-to-face and were digitally recorded by the researcher in the interviewee’s workplace. One interview was conducted in Afrikaans and all other interviews in English. An interview guide consisting of broad open questions and topics for exploration was used to generate discussion rather than to elicit answers to specific questions. Features of the particular context  were explored. This included the attitudes of colleagues in the public and private sector towards EBP and guideline implementation, the style of leadership in their practices as well as features of the strategies used for dissemination and implementation of guidelines. Other areas explored were the concept of evidence; FPs’ views of the barriers to guideline implementation; their views on how best to implement guidelines; anecdotal experience in practice and the role of the patient in clinical decision-making.48 which involved the following steps:All interviews were transcribed verbatim and were returned to the interviewees for member checking. Analysis used the framework method,Familiarisation: The researcher immersed himself in the transcripts by reading, rereading and listening to the original recorded interviews and referring to field notes taken during the interviews in order to become familiar with the data.Identification of a thematic index: The researcher created a list of codes and organised them into categories based on a detailed analysis of a sample of the transcripts. Codes were identified inductively from the data and organised in relation to the aim and objectives of the study.Indexing: The transcripts were systematically coded using the thematic index and with the assistance of a qualitative data analysis software program, ATLAS.ti, version 6.1.49Charting: Codes related to a particular category (family as designated by ATLAS.ti) were then collated together in ATLAS.ti and the output saved or printed.Interpretation: The charts were used to interpret the data and identify emerging themes. Connections between different themes, the range and strengths of different opinions within themes as well as contradictions were reflected on. The researcher searched for alternative explanations and potential negative cases. A reflexive report was referred to in an attempt to remain neutral and receptive to the data during this phase of the analysis. The reflexive notes dealt with any assumptions, predispositions, biases and perspectives of the researcher with regard to EBP and guideline implementation.In the following two paragraphs, I provide a very brief summary of self in relation to the research conducted, in an attempt to reflexively outline the potential predispositions that could have influenced the way the research was planned, conducted, analysed and interpreted.I worked in the PHC sector of the Cape Town metropole for a period of 20 years consecutively from 1986 to 2006 and rotated through many of the Community Health Centres (CHCs) in the Cape Town metropole. During this time I became well aware of the scope of practice and areas of potential weakness in the health system. Weaknesses noted and that prompted this research included the wide variation in practice; opinion based practice ; a paucity of implemented evidence-based guidelines to assist health care workers, particularly in the management of diseases of chronic lifestyle; the inability to incorporate current evidence in decision-making (even where evidence-based guidelines were available); the generally poor quality of care as perceived by patients and medical staff; and the lack of continuity of care coupled with the ongoing frustrations of an ever-increasing workload within a resource-constrained context of practice. It was clear that no formal implementation process for guidelines existed and practitioners were in most instances not even aware of available guidelines.I pursued postgraduate studies and completed a master’s degree in Family Medicine and Primary Care at Stellenbosch University in December 1995 and returned to practice in the same metro district health systems as a senior family physician for a period of 10 years. I was also appointed as a full-time senior lecturer in the Division of Family Medicine and Primary Care, Stellenbosch University, in January 2007 and was mainly involved in the formal training of undergraduate and postgraduate students in EBP during family medicine training attachments. As a proponent of EBP, my main focus of teaching was EBP at the point of care, and I taught the EBP process, searching for clinical research evidence, critical appraisal and the application of evidence in clinical decision-making. Therefore, my background knowledge of EBP could have impacted on the qualitative analysis performed.Permission was granted by the Health Research Ethics Committee of Stellenbosch University (project number: N07/03/066) and permission was obtained from the Metro District Health Systems of the Western Cape to conduct this research study.A total of 27 FPs were interviewed from three groups: 10 were academic FPs affiliated to departments of family medicine nationally, 10 were FPs in the Cape Town public sector and 7 were FPs from the private sector.Family physicians felt that research evidence forms an important component of decision-making in clinical practice. However, rigorously prepared quality evidence, derived from contexts other than primary care, might not be directly applicable and could be limited in its ability to influence practice. On the other hand, badly conducted research from the primary care setting might be equally unhelpful:‘Well, I think for me, the best evidence would be evidence that comes from research done in the context where I work, and not necessarily done in a setting that’s not relevant to where I work.’ (FP9)To deal with patient problems effectively required an awareness of the whole person and their illness experience with issues such as patient values, expectations, beliefs and concerns in addition to considerations of clinical evidence and cost-effectiveness. It was clear that FPs recognised the limitations of EBM in addressing the problems with which patients present and the need for different forms of research evidence to inform their practice:‘Evidence-based medicine, because we’re using a scientific method, it’s mainly looking at the biomedical side of issues. It doesn’t delve much into the psychosocial, cultural, political and administrative issues involved in patient care. So, in other words it’s limited.’ (FP3)Family physicians felt that guideline recommendations needed to be more relevant to the inherent uncertainties, multimorbidity and undifferentiated nature of primary care:‘In primary healthcare, which is my home, we are riddled with a lot of uncertainties, and that is the nature of our discipline. So, it is particularly important to be able to access evidence for the kind of problems that we encounter. It is critical for us that we have some evidence for what we do, especially because most of what we see doesn’t really have state-of-the-art evidence, but we always do our best to access whatever evidence there is around us.’ (FP1)Family physicians had some ambivalence and uncertainty about the potential for guidelines to improve health outcomes as they recognised that these outcomes were influenced by multiple factors and that evidence generated for a study population might not always translate to an effect for individual patients:‘It is difficult to say that it will definitely lead to improved health outcomes. That is difficult to say. I would expect it would lead to improved health outcomes, but I won’t say definitely and promise someone, even a patient, that it will definitely.’ (FP7)Family physicians felt that guideline development teams should include representatives of district health services, primary care and patients, and not only so-called experts. All members of such an inclusive group have different types of expertise on what is relevant and useful evidence. Respondents felt that primary care practitioners should become more involved in providing the relevant research required to address the gaps in their knowledge and assist in the formal development of the guideline. However, this would be extremely challenging given the current workload they have to deal with:‘Although in my experience in our country, I have found that most guidelines are developed by subspecialists without involvement of primary care providers. That for me creates an impression that the specialists, or subspecialists, are relied upon to give direction to primary care providers. Not that I have a problem with that, but I feel that primary care providers must also be involved in the drawing up of these guidelines. But then that also means that primary healthcare providers must also be involved in research activities, because to be able to say to people, ‘this is what we experience in primary healthcare’, one should be doing research in one’s environment.’ (FP2)Family physicians felt that qualitative research was underutilised as this form of research could provide unique contextual insight into important areas such as how to improve adherence of patients to medication, or how to get primary care practitioners to change their behaviour in clinical practice:‘We are very good at doing qualitative work. We bring it on board and say these are the reasons why our patients are struggling with adherence. These are the reasons why our patients are not able to keep up with lifestyle modifications. In that way, the guideline will come out much, much richer and much, much more relevant to our context.’ (FP3)Although FPs felt that guideline development should be more inclusive, they also thought that the underlying synthesis and critical appraisal of the research evidence should be a national process led by South African universities:a] national protocol or national guideline, once it is made, it would be nice for especially the academic departments to take it up and look at the evidence on which this was made …’ (FP12)‘So, my personal feeling is even  … So, we have various sources of guidelines, and then our referral hospital, which is Paarl Hospital, also have their own set of local guidelines, from which they want us to prescribe. So, there’s not really uniformity or a structured way that we can decide this is the one we should stick to.’ (FP15)‘In our setting we don’t have a structured way of the guidelines being presented. There are guidelines coming from the Department of Health and from other sources … There are the national guidelines which come out with the SAMJ . From the simplest being that sometimes what is being proposed in the guideline takes more time, and often in government facilities you are pressed for time. So if you would make it relevant to asthma, the guideline says that you must check inhaler techniques, you must check the person’s understanding of the use of medication, and the junior medical officer, instead of following those steps, would just write up the medication to have a quick consultation.’ (FP17)‘I think there are various reasons for that [Respondents felt that practitioners must feel confident about the usefulness of their guideline. This means having a sense of cognitive resonance, the feeling of a positive emotional response and confidence that what is being recommended for patients is useful and effective:‘So for me it’s about having that comfort, a lack of dissonance, the freedom of anxiety in prescribing a treatment plan, prescribing a medication or a system of treatment for that patient, knowing that it comes with tangible proof that it’s effective and that it’s working.’ (FP1)Some FPs stressed the importance of all practitioner groups within the organisation being consistent in following the same guidelines. Such consistency may be difficult to achieve, especially as the development paths of clinical nurse practitioners (CNPs) and doctors are separate. In addition, tension exists between standardisation of care on the one hand and patients’ individual requirements on the other.Formal and ongoing training on the use of a new guideline was essential to successful implementation:‘Now, one thing about guidelines, I find if I have had some training, some form of a workshop in the line of a guideline, my chances of using and adhering to that guideline is much, much better, than just by a guideline being passed down from the Department of Health and it ends up in my pigeonhole.’ (FP15)Training should not be seen as a process of telling practitioners what recommendations must now be followed, but a more interactive and collaborative process that recognises the autonomy of practitioners and their choice and control over deciding what is a priority for or applicable to their clinical practice. Providing evidence that the guideline has made a difference elsewhere would also be helpful. Training should involve all practitioners involved in patient care, for example, both nurses and doctors:‘They need to hopefully be motivated in a positive way where they see it in the true spirit of quality improvement and it’s a team process and it’s for the greater good of their community that they serve. I think one cannot make it just a clinical process. There is a bit of human emotion and human motivation behind it, and there should also be a form of feedback. So I think once they buy in, they should also have say in the process of implementation, and also be involved with the feedback of each step of implementation so that they know how their own behaviour has hopefully benefitted the implementation process.’ (FP4)Respondents thought that junior doctors and clinical nurse practitioners utilised guidelines more closely. Doctors may view the guideline as a guide to more autonomous practice, whereas CNPs may view it as a set of rules to be obeyed and strictly adhered to. In addition, guidelines could be useful for older doctors, particularly those who have not kept up to date with new developments and whose practice can be considered outdated:‘I think a great value of the guidelines is to update people’s knowledge. I have the experience of working with colleagues who have just done their internship, and their practice is very close to the guideline, and then I work in clinics with general practitioners who have practised for 30 years, and their practice and prescription is quite different, and sometimes even dangerous, if you compare it to the guidelines.’ (FP15)Implementation of new guidelines could be sabotaged by delay in the availability of resources. Coordination was needed between those responsible for dissemination and implementation of new guidelines with those responsible for managing the health services. Sometimes FPs might need to proactively advocate for alignment of corporate  and clinical governance (e.g. best practice) to ensure successful implementation:‘One of our challenges we experience is that the new guideline would come out, and say a new treatment or an intervention would be promoted, but there would be a lagging time for that medication to become available. Then the department has to adjust budgets to make it available and do this, and often there is a gap before you can actually practice what the guideline says. The inhalant corticosteroids are an example of that. It took quite a while before it became freely available, especially in the setting of our district hospital.’ (FP15)Respondents felt that readiness to change was a huge problem in a busy and already overburdened primary care setting and different levels of readiness were reported among members of staff:‘I think that’s an innate challenge in being human. You want to rely on what’s familiar, and it’s always challenging to change one’s own lifestyle and behaviours, even if it’s part of your professional work. Some people like to stick to what they know and what they’re comfortable with.’ (FP4)Practitioners often find it extremely difficult to change their ways of practice, especially when they feel that control is being taken away from them or the perception remains that their current way of practising had been successful:‘If you have been practising things for years, you’ve been taught to do things in a certain way and suddenly somebody comes and puts evidence in front of you and tells you that what you have been doing for the last 10 years has actually been harmful to your patients, or it’s not good for them, it can be very difficult for that practitioner to accept that.’ (FP7)For many practitioners what is required may constitute a profound change in their thinking and approach to patient care and accepting the need for such a radical change may increase their reluctance to embrace the change:‘Well, I think the paradigm shift that we sometimes have to make, because for many years we were told that this or that treatment or intervention is the best and now we have to change. I think for people who have got established practices, they often would find it very difficult to change. If they have used something that for them has worked, people are reluctant to change. So I think that is a big barrier. However, if the evidence is compelling that it doesn’t work, and then I think it is good.’ (FP2)Respondents felt that one of the central roles of FPs was clinical governance, which entails implementing and adhering to evidence-based guidelines. There could be a tension between the desire to engage with people around implementing the guidelines and the need to audit adherence to the rules:‘One can come up with quality improvement projects, for example, or audit. You can tell all your people in your practice that we will audit your work based on the guidelines that we have in place, because the whole idea of the guidelines is that we practise almost in a similar fashion and we use resources in a cost-effective manner.’ (FP19)Respondents felt that quality improvement cycles work if target standards have been agreed to and owned through the guideline implementation process and the process feels reflective and appreciative rather than judgemental and critical. Good quality feedback should include feedback from patients who are on the receiving end of care. A team process was encouraged and the feedback should serve to provide ongoing motivation (not punitive action) so that ultimately practitioners are more likely to change their clinical practice:‘So you need to have a feedback system, which is going to go in both directions, from whoever is coordinating its implementation with the staff who are going to have to implement it, with the patients as well, who are going to be the receivers of care.’ (FP7)The key findings are summarised in a conceptual framework see , which i50 a variety of quantitative and qualitative methods need to be embraced52 and strategies identified to engage primary care providers more in priority research.53Primary care researchers agree with the findings of this study that more clinical research needs to be conducted in primary care,57The need to formulate a more inclusive group of stakeholders in guideline development has also been recognised elsewhere and the role of patients is well recognised as they bring experiential expertise and tacit knowledge from their perspective as users of health services.58 Similar integrated tools are being prepared for children and community health workers. Integrated tools may also be able to consider comorbidity and how to balance multiple or diverse recommendations. Attention is given to the scope of practice of different primary care practitioners, such as clinical nurse practitioners and doctors, and includes all the practitioners who might be managing the condition.Contextualisation of guidelines in the Western Cape Province has included an integrative process that combines individual guidelines into one decision-support tool that is disseminated further. This process has been led by a university-based knowledge translation unit. The Practical Approach to Care Kit guideline integrates primary care recommendations into algorithms for all the common presenting symptoms and chronic conditions in adults.59 Information technology has created new opportunities for electronically disseminating guidelines. National primary care guidelines are now available as an application that can be downloaded onto a cell phone or tablet.60 Studies have also looked at the use of automated guidelines that support the decision-making process.61 Ensuring awareness among all relevant practitioners of a new guideline is essential for successful implementation.62There may also be a need for a more formal analysis of the target group and setting before disseminating guidelines.24 and only a small number of studies report on the cost of the guideline development–dissemination–adoption process.24Dissemination alone, however, is not sufficient to ensure implementation. Availability of funding for formal implementation is often just assumed and taken for granted,63 Evidence on behaviour change should inform the design of training sessions.64 Implementation strategies should provide evidence for the importance of change in terms of patient outcomes.65Training on new guidelines should be interactive, collaborative and in the form of workshops rather than didactic lectures.66 and, despite an emphasis on improving clinical processes and quality, most of this effort was experienced negatively, with staff identifying values such as not sharing information, confusion, power and hierarchy. Improving the quality of care may require transformation of the leadership style.67The health services should create a learning environment, encourage teamwork and have formal strategies for guideline implementation. Health services in the Cape Town metropole may lack capacity for innovation and evolution21 Strategies should be tailored to locally identified barriers.68 A number of barriers have been identified by respondents who reported time constraints, lack of financial resources, a focus on cost reduction and incongruence between corporate and clinical governance activities to be major barriers to guideline implementation in an overburdened primary care setting , moderately effective (e.g. audit and feedback) and relatively strong (reminder systems and multiple interventions). setting . High wo71 Monitoring and evaluation of guideline implementation may provide evidence of impact on health outcomes as well as feedback on the process of guideline contextualisation, dissemination and implementation.Quality improvement cycles linked to guideline recommendations may be a way of reinforcing implementation as well as monitoring progress . EngagemAlthough academic FPs nationally and FPs in public and private practice were interviewed, the FPs in practice were only from the Cape Town metropole and thus are not representative of the whole country. This could limit the transferability of the findings to South Africa as a whole.The framework of guideline development, contextualisation, dissemination, implementation and evaluation should be considered by the relevant stakeholders involved in each step of the process to guide their contribution and address likely barriers and enablers.The study identified the need to support more primary care research in order to contribute to an appropriate evidence base for guideline development and to address the wide variety of practice-related questions with different methodological approaches.Evidence-based practice is limited in its capacity to inform primary care and a combination of qualitative and quantitative research is necessary to improve our understanding of the complexity of primary care. The research findings have been summarised in a stepwise conceptual model of guideline development, contextualisation, dissemination, implementation, monitoring and evaluation. Guideline development should be a national, more inclusive process that incorporates evidence from the primary care context. Guideline contextualisation should happen at an organisational level and may include adaptation of the guideline as well as the development of more practical or integrated tools tailored to the specific organisational context. Organisations should ensure synergy between corporate and clinical governance activities. Dissemination should ensure that all practitioners are aware of the guideline or adapted tools and know how to access them. Implementation should include training that is interactive and in a workshop format that recognises the need to address individual practitioners’ readiness to change as well as local barriers. Quality improvement cycles may reinforce implementation, monitor progress and provide feedback to the whole process of guideline implementation. Universities have a role to play with the health services in scrutinising and synthesising evidence during the development stage, translating evidence into practical tools during contextualisation and in training of staff during implementation. The proposed model may be useful for policymakers, health care managers and practitioners who are considering the use of guidelines in similar settings.