Effortful processing refers to mental activity that requires conscious effort. When engaged in thinking about a given subject or performing a task mentally, the individual must concentrate when processing the information related to those tasks. Effortful processing is sometimes referred to as controlled processing.
For example, reading text regarding a complex subject requires concentration. The individual must access long-term memory to process the meaning of the concepts being conveyed and then use them in working memory.
At the same time, the ideas being presented in the passage may be compared to information previously learned and also stored in memory.
Sometimes the ideas being presented will be consistent with what one already knows, or in other cases, not. The point is, the comparison requires cognitive effort.
The process requires a great deal of mental activity. Hence the term, effortful processing.
Effortful Processing vs. Automatic Processing
There are three fundamental differences between effortful and automatic processing.
- First, effortful processing involves actively processing information or elements of a task, whereas automatic processing involves very low levels of mental effort.
- The second difference has to do with the capacity of mental activity. Each individual has a limited amount of cognitive resources that can be devoted to performing mental activity in any given moment. Effortful processing can absorb maximum cognitive capacity, while automatic processing can absorb very little.
- Third, effortful processing necessitates conscious control of attentional recourses. The individual must steer their attention to certain elements of the task in order to perform it correctly.
However, automatic processing requires very little conscious control of attention. In fact, some tasks can be performed unconsciously, with absolutely zero conscious control.
The interesting relationship between effortful and automatic processing is that tasks which began as effortful can become automatic with time and practice.
Take for example, reading. When first learning to read a simple word such as “cat,” a child must think about how to pronounce each letter. This can take time and is performed sequentially, and slowly.
However, after repeatedly reading the word, sometimes over days and weeks, the child can simply see the word and say it aloud. What was once an effortful task has now become automatic.
The task no longer requires a lot of conscious effort and it absorbs very little cognitive capacity.
Effortful Processing Examples
- Reading: In the beginning, reading is an extremely effortful process. It requires the recall of the phonemic symbol of each letter, repeating the mechanical movements involved in pronunciation, and retrieving the meaning of the word from long-term memory.
- Performing Mathematical Calculations: The more advanced the mathematical formula, the greater the mental effort needed to perform the calculation.
- Remembering Names of Acquaintances: Remembering the names of people that are not close friends and that we do not see on a regular basis can be difficult. It requires trying to match a face with a name, information that must be retrieved from somewhere in long-term memory.
- Memorizing a Speech: The process of memorizing a speech or business presentation can take a lot of time and practice. However, if rehearsed enough, the words will flow smoothly during the speech because at that point, the task requires very little effortful processing.
- Learning a Second Language: Depending on how similar the second language is to an individual’s native language, learning a second language can be very challenging. The more similar the languages, the less effortful processing needed.
- Creating a Concept Map: Many students will create a concept map to help them organize their knowledge of a particular subject or concept. This requires retrieving information regarding various concepts, understanding how each is interconnected, and then performing the physical task of constructing the map.
- Method of Loci Mnemonic Strategy: Visualizing a familiar room and then mentally forming associations between concepts and physical objects in that room is a very effective strategy to improve memory. But, it also takes a great deal of effortful processing.
- Playing Chess: Each move on the chess board requires an extremely detailed analysis of the advantages and disadvantages of that move, and in comparison to the possible counter moves of the opponent over the next series of 15-20 future moves.
- Learning to Drive: At first, learning how to drive takes a lot of mental effort and concentration. The driver has to look straight ahead to watch for other cars or pedestrians, monitor their speed, pay attention to road signs and stoplights, and continuously glance in the mirrors to track the movements of other vehicles.
- Learning how to Play a Video Game: In the beginning, playing an unfamiliar video game will require a lot of effortful processing. The images on the screen need to be tracked, the movement of the player’s character needs to be controlled, and the accumulation of points and other data has to be monitored. All of that takes a lot of effortful processing when first learning how to play.
Origins of Effortful Processing
Although Schneider and Chein (2003) suggest that the notion of two types of processing, automatic and controlled, has existed for quite some time (e.g., James, 1890), the term “effortful” or “controlled” processing did not appear in his famous book The Principles of Psychology.
The explicit notion of effortful processing originates from early conceptions of memory and attentional capacity. Kahneman (1973) proposed a capacity model of attention which suggested that there is limited energy available to devote to mental activities.
Kahneman identified three elements in his model: “the completion of a mental activity requires… “effort,” “capacity,” or “attention.”” (p. 9).
Hasher and Zacks (1979) explained that in other models being proposed at the time, effortful processing was ascribed different terminology. For instance, Posner and Snyder (1975), used the term conscious effort, while the other predominant model from Schneider and Shiffrin (1977) preferred the term controlled.
Both are:
“processes that require effort and so limit one’s ability to engage simultaneously in other effortful processes” (p. Hasher & Zacks, 1979, p. 362).
Applications of Effortful Processing
1. Effortful Processing Impairments in Depression
Cohen et al. (2001) provide a review of research which identified various difficulties that depressed individuals exhibit when performing nondominant physical tasks involving motor speed and dexterity (Taylor et al. 1981; Merrin, 1985).
Other lines of research have identified difficulties in planning, initiation, and problem-solving in depressed patients (Martin et al, 1981; Elderkin-Thompson et al., 2006) which suggests that impairments of attention and executive functioning are related to major affective disorders such as depression (Weingartner, 1981; Cohen, 2013).
“Patients with major affective disorders seem to have particular difficulty when tasks require effortful processing with demand for focused and sustained attention” (Cohen et al., 2001; p. 386).
This results in, among other areas, difficulty in emotional regulation, which can then disrupt interpersonal relations and the control of impulsive behavior.
McClintock et al. (2010) point out that although research is inconclusive, these difficulties in executive functions may be related to frontal cortical impairment in the cerebral cortex (Kaiser et al., 2003).
2. In Advertising
Advertising professionals understand the role of effortful and automatic processing in the effectiveness of product commercials.
In some cases, a commercial is designed to persuade consumers using facts. The ad presents various statements that point to the quality of the product, highlighting such features as durability and reliability.
In other cases, a commercial may be designed to persuade consumers using more shallow elements such as celebrity endorsement or how the product is a status symbol.
When using the former approach, consumers will engage in effortful processing of the information presented. They will analyze the merits of the information and make a decision based on message content.
In the latter scenario, consumers will rely on automatic processing, which involves very little cognitive effort. A purchase decision will be based more on feelings activated during the ad that indicate the product’s appeal.
A respected theoretical framework on message appeals and effortful versus automatic processing is the Elaboration Likelihood Model (ELM) of persuasion, originally devised by Petty and Cacioppo (1986).
The ELM identifies two routes to persuasion: central and peripheral. The central route involves the message recipient engaging in the critical analysis of the message’s content, while the peripheral route involves very little cognitive processing.
The central route results “…from a person’s careful and thoughtful consideration of the true merits of the information presented…” (p. 125).
While the peripheral route results from “…some simple cue in the persuasion context (e.g., an attractive source) that induces change without necessitating scrutiny of the true merits of the information presented” (p. 125).
3. In Combatting Fake News
The ease of access to misinformation through social media has sparked concern among behavioral scientists and political commentators (Allen et al., 2020).
This has raised serious concerns about the effects of fake news in regards to increasing political polarization, decreasing trust in public institutions, and undermining democracy (Persily2017; Tucker et al., 2018).
The cognitive mediation model (Eveland, 2001) postulates that cognitive evaluation must accompany exposure to news if it is to have an effect on political views or behavior.
Consistent with this reasoning, Shahin et al. (2021) found that elaborating on news content (i.e., engaging in effortful processing), can lead to increased political participation online.
De Zúñiga et al. (2023) suggest that increased elaboration could lead to users rejecting fake news due to their deliberative processing of the message content, helping them recognize fabricated or misleading information.
The results of their survey revealed that:
“Individuals reporting greater elaboration in response to news were more disposed toward corrective actions, suggesting that news elaboration may serve as a buffer against fake news spread” (p. 3444).
These findings provide a conceptual replication of similar research that showed that acceptance of misinformation was due to a lack of effortful processing (Pennycook & Rand, 2019; 2020).
Conclusion
Effortful processing refers to mental activity that requires cognitive effort, conscious attentional control, and absorbs cognitive capacity.
All tasks that require mental activity exist on a continuum. That ranges from necessitating a great deal of cognitive processing, to being automatically processed and requiring zero capacity or attentional focus.
In the beginning, many tasks require maximum effortful processing, but these demands are gradually reduced with repetition.
Depressed individuals may have impaired effortful processing as it relates to executive functions such as planning and problem-solving, in addition to emotional regulation central to interpersonal relations and impulse control.
Effortful processing is also involved in the comprehension and persuasiveness of commercial advertising, news, and acceptance or rejection of fake news.
References
Allen, J., Howland, B., Mobius, M., Rothschild, D., & Watts, D. J. (2020). Evaluating the fake news problem at the scale of the information ecosystem. Science Advances, 6(14), eaay3539.
Amazeen, M. A., Thorson, E., Muddiman, A., & Graves, L. (2018). Correcting political and consumer misperceptions: The effectiveness and effects of rating scale versus contextual correction formats. Journalism & Mass Communication Quarterly, 95(1), 28–48. https://doi.org/10.1177/1077699016678186
Cohen, R., Lohr, I., Paul, R., & Boland, R. (2001). Impairments of attention and effort among patients with major affective disorders. The Journal of Neuropsychiatry and Clinical Neurosciences, 13(3), 385-395.
Cohen, R. A. (2013). The neuropsychology of attention. Springer Science & Business Media.
de Zúñiga, H. G., Goyanes, M., & Skurka, C. (2023). Understanding fake news corrective action: A mixed-method approach. International Journal of Communication, 17, 23.
Elderkin-Thompson, V., Mintz, J., Haroon, E., Lavretsky, H., & Kumar, A. (2006). Executive dysfunction and memory in older patients with major and minor depression. Archives of Clinical Neuropsychology, 21, 669-676.
Eveland, W. P., Jr. (2001). The cognitive mediation model of learning from the news: Evidence from nonelection, off-year election, and presidential election contexts. Communication Research, 28(5), 571–601.
Hammar, Å., & Årdal, G. (2012). Effortful information processing in patients with major depression—A 10-year follow-up study. Psychiatry Research, 198(3), 420-423.
Hartlage, S., Alloy, L. B., Vázquez, C., & Dykman, B. (1993). Automatic and effortful processing in depression. Psychological Bulletin, 113(2), 247.
Hasher, L., & Zacks, R. T. (1979). Automatic and effortful processes in memory. Journal of Experimental Psychology: General, 108(3), 356.
Kahneman, D. (1973). Attention and effort (Vol. 1063, pp. 218-226). Englewood Cliffs, NJ: Prentice-Hall.
Kaiser, S., Unger, J., Kiefer, M., Markela, J., Mundt, C., & Weisbrod, M. (2003). Executive control deficit in depression: Event-related potentials in a go/no go task. Psychiatry Research: Neuroimaging, 122, 169 –184.
Martin, D. J., Oren, Z., & Boone, K. (1991). Major depressives’ and dysthymics’ performance on the Wisconsin Card Sorting Test. Journal of Clinical Psychology, 47(5), 684-690.
McClintock, S. M., Husain, M. M., Greer, T. L., & Cullum, C. M. (2010). Association between depression severity and neurocognitive function in major depressive disorder: a review and synthesis. Neuropsychology, 24(1), 9.
Merrin, E. L. (1985). Motor and sighting dominance in schizophrenia and affective disorder: Evidence for right-hand grip strength prominence in paranoid schizophrenia and bipolar illness. The British Journal of Psychiatry, 146(5), 539-544.
Pennycook, G., & Rand, D. G. (2019). Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition, 188, 39–50.
Pennycook, G., & Rand, D. G. (2020). Who falls for fake news? The roles of bulls**t receptivity, overclaiming, familiarity, and analytic thinking. Journal of Personality, 88(2), 185–200.
Persily, N. (2017). The 2016 US Election: Can democracy survive the internet?. Journal of democracy, 28(2), 63-76.
Posner, M. I., Snyder, C. R., & Solso, R. (2004). Attention and cognitive control. Cognitive Psychology: KeyRreadings, 205, 55-85.
Petty, R.E. and Cacioppo, J.T. (1986). The Elaboration Likelihood Model of Persuasion. Advances in Experimental Social Psychology, 19, 123-205.
https://doi.org/10.1016/S0065-2601(08)60214-2
Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 1–66.
Shahin, S., Saldaña, M., & Gil de Zúñiga, H. (2021). Peripheral elaboration model: The impact of incidental news exposure on political participation. Journal of Information Technology & Politics, 18(2), 148–163.
Taylor, M. A., Redfield, J., & Abrams, R. (1981). Neuropsychological dysfunction in schizophrenia and affective disease. Biological Psychiatry, 16, 467–478.
Tucker, J. A., Guess, A., Barberá, P., Vaccari, C., Siegel, A., Sanovich, S., … & Nyhan, B. (2018). Social media, political polarization, and political disinformation: A review of the scientific literature. Political polarization, and political disinformation: a review of the scientific literature (March 19, 2018).
Wang, C. E., Brennen, T., & Holte, A. (2006). Automatic and effortful processing of self‐statements in depression. Cognitive Behaviour Therapy, 35(2), 117-124.