Which of the following research methods is best at observing and recording Behaviour in the natural environment without trying to control the situation?

Publisher Summary

Naturalistic observation is a hallmark of scientific inquiry and is central to many empirical data collection efforts. There are two main strengths of this method. The first is that it taps directly into the behavior of interest and does not rely on having to interpret proxies of behaviors such as self-reports. Second, because the behaviors observed occur in natural settings, naturalistic observation has strong construct and face validity; that is, it very likely represents reality than argument that is more difficult to make with other research methods, such as a driving simulator. On the other hand, naturalistic observation as a research method has some drawbacks. The main disadvantage is generalizability. The value of naturalistic observation techniques to any area of traffic psychology is dependent on how well the study is designed and executed. A study with a flawed design will not yield results that are generalizable, and even a well-designed study will not be useful if the observational methods are not valid and reliable. Thus naturalistic observational studies require appropriate study designs, reproducible protocols, extensive observer training, and adequate resources to yield valid and generalizable results.

VI.G. Motor Functions

Naturalistic observations of the patient's gait and upper and lower extremity coordination are an important part of the motor examination. Hand preference should be assessed either through direct inquiry or a formal handedness questionnaire. [Table VI] Motor speed, dexterity, and programming are tested with timed tasks, some of which involve the repetition of a specific motor act [e.g., finger tapping, peg placement] and others involve more complex motor movements [e.g., finger sequencing, sequential hand positions]. Manual grasp strength can be assessed with a hand dynamometer.

Table VI. Motor Functioning

Naturalistic observation

Naturalistic observation is a method that involves observing subjects in their natural environment. The goal is to look at behavior in a natural setting without intervention. This can be applied to tutorial or web-based evaluation if subjects are given a task and asked to go through the process without intervention from the researcher, in order to observe the “natural” way a subject would proceed. Researchers may take notes or tallies of various behaviors they observe. This could also include taking time samplings. For example, in the Mestre [2010] study, time marks were taken to document how long it took students to get to the requested database when they were on the “Online Research Resources Page,” as well as their various unsuccessful attempts. Of value in these types of situations is to understand why students chose the paths they did. This type of observation can then be extended into more robust usability testing that includes debriefing and interviews.

Collecting Audiovisual Records

In naturalistic observation, participants are normally requested to behave in their usual manner, to do whatever they normally do, and to disregard the observer's presence as much as possible. Observational coding can be done in real time, or audiovisual records of behavior can be made using videotape or digital video technology. The presence of an observer-recorder [camera in hand] can be intrusive and may represent a kind of novelty that evokes atypical responses from those observed, a phenomenon termed reactivity. For example, observation may promote socially desirable or appropriate behaviors and suppress socially undesirable or inappropriate behaviors [e.g., adults may display higher than normal rates of positive interactions with children]. Nonetheless, reactivity can be and often is successfully alleviated by observers' spending time in the situation with participants before recording to set participants at ease. Observers must be trained to make audiovisual records that have few [if any] breaks or gaps in the behavior stream, and conventions must be developed and adhered to for filming distances and angles that maximize the possibility of continuously and reliably coding behaviors of interest. Decisions must be made about which actor to focus on when multiple actors cannot be captured simultaneously on audiovisual records, and conventions must be developed to provide [future] coders with important off-camera information. Moreover, audiovisual records of naturally occurring behavior in unstructured settings suffer inherent problems and limitations, and the codes that are developed to score them must take these shortcomings into account.

Early Experience and Attachment Security

Ainsworth's naturalistic observations of infants and families in Uganda directed attention to caregiver sensitivity as the main source of individual differences in attachment organization. Caregiver sensitivity has been operationalized in many ways, but research across diverse social and cultural contexts confirms Ainsworth's initial observations that a secure attachment is fostered by the caregiver's accurate perception of, and prompt and appropriate response to, the infant's needs or distress. Sensitive, synchronous interactions, warmth, and support, especially as infants are developing expectations of how their caregiver will respond, predict infant security. Less sensitive and supportive care in infancy predicts insecure attachment. Caregiving that is intrusive, controlling, or hostile is linked to insecure-avoidant attachments, and caregiving that is inconsistently responsive, or unresponsive, is linked to insecure-resistant attachments. Although the way in which insecure infants organize attachment behavior does not facilitate an optimal balance between exploration and proximity, in the context of a less-supportive caregiving environment, their strategies may be adaptations that allow them to best maintain proximity to a caregiver. For example, avoidant infants are thought to defensively hide their distress, ignore the caregiver, and turn their attention to the environment. If the caregiver has been hostile toward infant's bids for comfort in the past, infants may gradually come to understand that they can better maintain proximity to the caregiver by directing attention away from their attachment needs. Similarly, resistant infants may benefit from intensifying attachment behaviors to engage an inconsistently responsive caregiver.

Experimental intervention studies support a causal link between sensitivity and security. Multiple studies indicate that by providing support and training to improve parenting sensitivity, infant attachment security can be enhanced. Importantly, this finding generalizes to dyads in challenging ecological contexts and to infants with more difficult predispositions such as an irritable temperament. Overall, however, relations between sensitivity and security are modest [i.e., sensitivity does not explain all of the variability in attachment security], and additional predictors of security that operate independently of sensitivity, or that moderate the effects of sensitivity, should be explored.

Caregiver sensitivity is less clearly related to attachment disorganization. Rather, disorganized attachment is associated with parenting that induces fear in the infant. Disorganization is more prevalent in samples with abuse or neglect and in samples with high levels of parental depression and unresolved loss. Patterns of affective communication that result from frightened or frightening caregiver behavior [e.g., contradictory emotional cues, withdrawal] also correspond to infant disorganization.

Structured observations

Although naturalistic observations generally yield findings with high ecological validity, oftentimes it may be difficult to observe social behaviors of key interest because they occur at low frequency or out of the range of the observer. To address these challenges, structured or analogue observation can be used, in which circumstances are created that will increase the opportunity to observe the behavior of interest in a more controlled setting. Such work has often been conducted within a research setting. For example, to examine children’s peer group entry strategies, Putallaz [1983] had two experimental confederates who were of the same gender and of about the same age as the participant play a game. The participant was then sent into the room, and the child’s behaviors when attempting to join the ongoing interaction were observed. In a study that focused on children’s responses to ambiguous provocation, Hudley and Graham [1993] set up a game involving two participants who had a chance to win a prize. However, the conditions of the game were such that the children’s ability to win was thwarted. Of interest was how the participants would interpret and respond to the provocation, given that it appeared that the other peer had caused the loss.

Structured observations can be especially useful when assessing adolescents’ peer interactions, given that the majority of adolescents’ everyday social interactions occur in more private, less easily observable settings. The Contextual Assessment of Social Skills [CASS; Ratto, Turner-Brown, Rupp, Mesibov, & Penn, 2011] is a role-play assessment of conversational skills for adolescents and young adults that can be used with typically developing individuals, as well as those with high-functioning autism spectrum disorder [ASD]. In the CASS, participants engage in two 3-min role play conversations with two different confederates [unfamiliar peers] who are of the opposite gender. In the first interaction, the confederate shows social interest and engagement. In the second interaction, the confederate displays boredom and disengagement. The conversations are recorded, and participants’ verbal and nonverbal behaviors are coded in 10 categories [e.g., asking questions, topic changes, overall involvement, overall quality of rapport]. Asking questions and topic changes are coded as behavioral counts, whereas the other categories are scored by two trained raters on a scale of 1 [low] to 7 [high]. Ratto et al. [2011] found that the internal consistency of the CASS was quite high, and interrater reliability was adequate.

Although primarily used in the research context, structured observations also can be used clinically. However, the clinician must be aware of confidentiality concerns and informed consent requirements. Given these challenges, particularly regarding bringing confederates into the clinical setting, it may be easier for the clinician to set up structured interactions outside of the clinic in ways that uphold the client’s confidentiality. For example, a client who has social anxiety might be asked to initiate a conversation with a stranger in a public setting while the clinician observes.

2 Do Cell-Phone Conversations Increase the Crash Risk?

There are several methodologies that have been used to address this question. Each methodology has strengths and weaknesses. Converging evidence from the different techniques provides a definitive answer to the question [“YES”].

The simplest method uses naturalistic observations to see how their driving behavior is altered with the concurrent use of a cell phone to dial, talk, or text. In one such study, we observed over 1700 drivers as they approached a residential intersection with four-way stop signs. We determined through observation whether the drivers were or were not using their cell phone as they approached the intersection and whether they came to a complete stop [as required by law] before proceeding through the intersection.1 The resulting data are presented in Table 1.

Table 1. Frequency Totals for the 2 [Cell Phone in Use Vs. Cell Phone Not in Use] × 2 [Stopping Violation Vs. No Violation] Observational Study of Four-Way Stop Sign Compliance.

For drivers not using a cell phone, the majority stopped in accordance with traffic laws. By contrast, for the drivers who were observed talking on their cell phone as they approached the intersection, the majority failed to stop in accordance with traffic laws. For drivers not using a cell phone, the odds ratio for failing to stop was 0.27, whereas the odds ratio for failing to stop for drivers who were using their cell phone was 2.93. This 10-fold increase in failing to stop was significant [χ2[1] = 129.8, p