Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2024 May 1.
Published in final edited form as: J Commun Disord. 2023 Apr 14;103:106327. doi: 10.1016/j.jcomdis.2023.106327

Theory-Driven Treatment Modifications: A Discussion on Meeting the Linguistic, Cognitive, and Psychosocial Needs of Individual Clients with Aphasia

Kristen Nunn 1, Sofia Vallila-Rohter 1
PMCID: PMC10247540  NIHMSID: NIHMS1892224  PMID: 37060857

Abstract

There is a growing body of literature demonstrating that language rehabilitation can improve naming impairments for individuals with aphasia. However, there are challenges applying evidence-based research to clinical practice. Well-controlled clinical studies often consist of homogenous samples and exclude individuals who may confound group-level results. Consequently, the findings may not generalize to the diverse clients serviced by speech-language therapists. Within evidence-based guidelines, clinicians can leverage their experiences and theoretical rationale to adapt interventions to meet the needs of individual clients. However, modifications to evidence-based interventions should not alter aspects of treatment that are necessary to produce change within the treatment target. The current discussion paper uses errorless learning, errorful learning, and retrieval practice for naming in aphasia to model how treatment theories can guide clinicians in making theory-informed modifications to interventions. First, we briefly describe the learning mechanisms hypothesized to underlie errorless learning, errorful learning, and retrieval practice. Next, we identify ways clinicians can provide targeted supports to optimize learning for individual clients. The paper ends with a reflection on how well-defined treatment theories can facilitate the generation of practice-based evidence and clinically relevant decision making.

1. Introduction

One in three stroke survivors acquire aphasia (Grönberg et al., 2022). Stroke survivors with aphasia have lower quality of life relative to stroke survivors without aphasia (Ross & Wertz, 2003). This disparity is partly driven by isolation brought on by difficulty communicating with others (Nyström, 2006) making treatments aimed at ameliorating communication challenges of the utmost importance. Meta-analyses support that language therapy ameliorates language impairments for individuals with aphasia (see Fridriksson & Hillis, 2021 for discussion). While research demonstrates that language therapy is an effective treatment for aphasia, evidence-based recommendations on how to individualize interventions based on patient characteristics and adapt interventions within the constraints of a clinical setting remain limited (Greenhalgh et al., 2014).

Often, to isolate treatment effects, researchers administer high doses (Cavanaugh et al, 2021) of complex treatments to a homogenous sample of participants (Greenhalgh et al., 2014; Lemoncello & Ness, 2013). High-intensity and complex treatment designs do not fit within the environmental constraints of a standard clinical practice which are restricted by productivity standards, staffing, and insurance reimbursement (Cavanaugh et al., 2021; Shrubsole et al.,2019). Furthermore, group-level results from efficacy and effectiveness research do not provide clinicians with insight into how individual clients with diverse needs will respond to an intervention (Margison et al., 2000). In clinical practice, all types of clients are serviced, therefore clinicians must adapt evidence-based interventions to align with an individual’s cognitive and linguistic impairment profile, maintain engagement and motivation, all while meeting environmental constraints.

Treatment adaptations fall within evidence-based practice guidelines which allow for clinicians to leverage their clinical expertise to guide the administration of interventions based on clinical experience, theoretical research, and client values (Lemoncello & Ness, 2013). To adapt interventions, clinicians need an understanding of the mechanisms hypothesized to produce change within the system being treated (see discussion Boyle et al., 2021). This way, clinicians can make adaptations to treatments while remaining faithful to the aspects of an intervention necessary to produce the desired results.

In a recent review, Nunn et al. (2023) outlined mechanisms researchers have proposed to underlie treatment gains following errorless learning, errorful learning, and retrieval practice for naming in aphasia. Yet, there was a scarcity of research that outlined how these interventions could be adapted within the theoretical frameworks to meet the diverse needs of individual clients. The current manuscript aims to exemplify how clinicians can integrate existing treatment theories with research within and outside of aphasia to guide clinical decision making. This review is intended to be descriptive rather than prescriptive given that many of the modifications identified in this paper have not been evaluated in aphasia.

2. Mechanisms of Action

Errorless learning, errorful learning, and retrieval practice are three learning approaches broadly defined as: (a) Errorless learning: clients practice naming with maximal clinician-provided supports to promote accuracy (e.g., whole-word repetition); (b) Errorful learning: clients practice naming that is effortful and mirrors everyday contexts with no to minimal clinician-provided supports; (c) Retrieval practice: clients practice effortful retrieval of names from long-term memory within contexts intended to promote successful retrieval such as a familiarization trial, cues, or spacing of training trials. Nunn et al. (2023) identified Hebbian learning, theories of effort, and incremental learning via lexical access as the most frequently identified learning mechanisms hypothesized to be active during errorless learning, errorful learning. These learning mechanisms are summarized below.

2.1. Hebbian Learning

Hebbian learning supposes that repeated patterns of neuronal firing increase the strength and efficiency of those neuronal pathways. Thus, in the context of treatment for aphasia, a linguistic production in response to a stimulus, increases the likelihood of producing that same production in the future. Importantly, stimulus-response associations are strengthened regardless of response accuracy. Thus, pure Hebbian learning is primarily discussed in the context of errorless techniques which prioritize response accuracy with the goal of strengthening correct rather than incorrect patterns of neuronal firing. To account for how Hebbian mechanisms may allow for learning in the presence of errors, Fillingham et al. (2003) posit that Hebbian learning may be supplemented by error-correcting mechanisms (henceforth “gated Hebbian learning”). These mechanisms are thought to be supported by cognitive skills (error-detection, memory, attention, executive functioning) and halt learning in the presence of an error or reinforce corrective-feedback in lieu of the erroneous response (Lambon Ralph & Fillingham, 2007).

From a neuroscience perspective, the efficiency of patterns of neuronal firing is a basis of learning and memory. Thus, the theory of Hebbian plasticity (gated or ungated) is likely applicable to learning and memory in errorless learning, errorful learning, and retrieval practice. Integration of the available research and theory in aphasia suggests that to avoid error-learning clinicians can (1) structure the environment to avoid errors or (2) measure relevant cognitive-linguistic skills and provide targeted supports. There is no consensus as to which of these approaches should be prioritized as both sacrifice treatment ingredients potentially valuable to learning (i.e., challenging yet engaging naming opportunities and accurate naming attempts, respectively).

2.2. Theories of Effort

Two primary theories related to effort emerge in research evaluating errorless learning, errorful learning, and retrieval practice. Theories of ‘effortful retrieval’ are discussed in the context of retrieval practice and propose that effortful yet successful retrieval of information from long-term memory makes information more accessible during future retrieval (Bjork & Bjork, 1992). Memories are proposed to have a storage strength (the lasting strength of an internal representation) and a retrieval strength (accessibility of an internal representation during an instance of retrieval) (Bjork & Bjork, 1992). When a target is retrieved with low retrieval strength (making retrieval more effortful), it is thought that the long-term storage strength of the internal representation is increased to a greater degree than when retrieval strength is high (Bjork & Bjork, 1992). A collection of studies within aphasia suggest that retrieval-based naming interventions which prioritize retrieval that is effortful and successful result in better retention of naming gains compared to errorless (repetition-based) treatment (for review see de Lima et al., 2020). Patra et al. (2022) identified semantic competition as a potential mechanism of action for effortful retrieval in lexical access. Specifically, Patra et al. (2022) consider ‘the dark side of incremental learning in lexical access’ in which during lexical retrieval, the connections between semantics and a target are strengthened (i.e., ‘the light side’) while connections between semantics and a competitor are inhibited (i.e., ‘the dark side’). Semantic competition is hypothesized to result in ‘accelerated relearning’ in which items that are inhibited prior to being strengthened are more retrievable later on relative to items that do not undergo inhibition prior to strengthening (See Storm et al., 2008 for more on accelerated relearning). This hypothesis is preliminary and ongoing research is needed to better understand this model within the context of language rehabilitation.

Alternatively, effort is discussed by some authors as a means to improve engagement and attention in therapy (Conroy et al., 2009a; Lacey et al., 2004; Lacey, 2010). In a single case study, Lacey et al. (2004) proposed that errorless learning resulted in a lack of participant effort with negative consequences for attention and memory. Researchers have modified errorless interventions using cues and spacing to improve effort and ultimately, engagement. When benefits of effort are described as mediating attention and engagement, they are not exclusive to retrieval-based interventions.

Theories of effortful retrieval may apply to aphasia rehabilitation in any instance where individuals must retrieve information from long-term memory with effort e.g., errorful learning, retrieval practice. Theories of effort that discuss engagement, may apply in instances where naming is challenging. Both theories of effort imply that clinicians should aim to maximize retention and/or engagement by creating naming contexts where the production of a target is effortful without completely removing supports necessary for correct productions.

While theories of effortful retrieval aim to achieve effortful and successful retrieval, errors do occur during retrieval practice (e.g., 20% errors in un-cued retrieval trials compared to <2% in errorless trials in Middleton et al., 2015). However, errors occur less frequently than errorful treatments (e.g., 56% in the errorful no feedback condition in McKissock et al., 2007). The relative incidence of errors may be important to consider when a clinician is concerned about reinforcing errors and/or the potential negative psychosocial consequences of errors (discussed in Section 3.3.1).

2.3. Incremental Learning via Lexical Access

Incremental learning via lexical access refers to mechanisms of learning tied to a psycholinguistic model that describes two interactive stages of lexical access (Dell et al., 1997). Incremental learning via lexical access suggests that retrieval practice naming treatment and repeating words activate and strengthen different stages of lexical access to different degrees. Broadly, successful retrieval of a trained word requires semantic-to-word mapping (stage 1) and word-to-phoneme mapping (stage 2). In errorless learning via repetition practice, semantic-to-word mapping is bypassed, thus primarily engaging word-to-phoneme mapping. Consequently, retrieval practice is hypothesized to provide opportunities to strengthen both stages of lexical retrieval while repetition practice prioritizes opportunities to strengthen word-to-phoneme mapping. Preliminary work supports hypotheses set forth by theories of incremental learning via lexical access but clinical applications deserve ongoing evaluation (Schuchard & Middleton, 2018a, 2018b).

Table 1 summarizes the learning mechanisms identified, implications for treatment administration, and relevant client-level attributes that warrant consideration.

Table 1.

Treatment theories and potential implications for individualized treatment.

Mechanism Description Implication Considerations
Hebbian Learning (Gated or Ungated) Errors can be self-reinforcing especially for those with impaired cognition. Reduce errors. If a client presents with impaired cognition, they may be more likely to reinforce errors. In these instances, provide additional supports to reduce errors or support cognition.
Theories of Effort Retrieval from long-term memory that is challenging but accurate makes information more accessible to future retrieval. More broadly, some hypothesize that effortful naming bolsters attention and motivation. Maximize the effort of target production without sacrificing success. Supports required to achieve a desirable level of retrieval difficulty may be moderated by individual-level linguistic and cognitive variables. Clients may be discouraged by difficult retrieval or erroneous naming attempts.
Incremental Learning via Lexical Access Repetition-and retrieval-based treatments primarily involve and thus primarily repair different stages of lexical access. Consider how theories of learning operate within an impaired language system. Error patterns may provide insight into the lexical stage to stimulate during treatment. Repetition practice may provide stimulation of word-to-phoneme mapping on most trials. Retrieval practice may provide stimulation of semantic-to-word mapping.
Open in a new tab

3. Modifications Based on Hypothesized Mechanisms to Promote Learning

Understanding the learning systems hypothesized to underlie errorless learning, errorful learning, and retrieval practice allows for suggestions of how therapy components might be modified to support success at the individual level for people with aphasia (Boyle et al., 2021). We highlight factors relevant to the identified mechanisms (balancing effort and success, cognition, and psychosocial variables). Modifications are speculative and aim to illustrate how treatment theories can guide clinicians in using lower levels of evidence to provide theoretical and rational support when evidence is scarce or does not pertain to a client receiving care.

3.1. Methods to Balance Effortful and Successful Retrieval

Clinicians may support effortful, yet successful productions prioritized within mechanistic accounts of Hebbian plasticity (success) and effortful retrieval. Clinicians may aim to do this to maximize opportunities for correct stimulus-response associations (Hebbian Learning) while also ensuring naming is effortful and thus, enhances long-term retention and/or engagement (Theories of Effort). Retrieval effort and success may depend on individual-level characteristics (e.g., memory abilities) that make retrieval more effortful (Agarwal et al., 2017; Maddox & Balota, 2015; Mulligan & Picklesimer, 2016; Unsworth et al., 2012, c.f., Pan et al., 2015); however, this has not been evaluated in aphasia. Research in rehabilitation and psychology offers means to support clients in achieving a desirable level of naming difficulty.

3.1.1. Schedules of Practice.

Schedules of practice relate to variables that influence the amount of time between training trials of the same item and the intensity of training. Research has been carried out to determine the most effective schedules of practice in neurotypical adults (Balota et al., 2006; Carpenter & DeLosh, 2005; Cull, 2000). Findings offer insights into how the scheduling of trials for individual items within and across sessions might support individuals with aphasia to achieve successful naming while creating a context of effortful retrieval.

Manipulating the time between multiple training trials of an item can influence the difficulty and success of retrieval, with consequences for learning (for review of distributed practice principles in aphasia rehabilitation see Middleton et al., 2020). Spacing an item’s trials during therapy (i.e., incorporating intervening trials before a target is re-encountered) can establish conditions in which a memory trace is fading and thus retrieval is effortful while remaining successful. The amount of spacing required to achieve a desirable level of effort and success may vary across individuals with aphasia considering that memory capacity and forgetting rates can influence the difficulty of retrieval across spacing conditions (Maddox & Balota, 2015).

For language rehabilitation which occurs across the span of multiple sessions, distributed practice principles that take advantage of spacing across sessions may be preferred (Schuchard et al. 2020). In a small sample (n = 9) of people with aphasia, Schuchard et al. (2020) controlled the number of instances an item was named correctly (i.e., criterion of learning) but varied whether the correct naming instances occurred within the same session or across separate sessions. For most comparisons, accuracy was higher at 1-day and 1-week retention intervals when items were spaced across sessions rather than within the same session (Schuchard et al., 2020). Patterns of spacing need additional evaluation in larger samples and at longer retention intervals but may offer insights into ways clinicians can alter treatment schedules to maximize learning.

3.1.2. Cues.

Cues also have the potential to manipulate the desirable difficulty of a task by providing additional information to aid in retrieval while maintaining effort (Dunn & Clare, 2007; Komatsu et al., 2000; Middleton et al., 2015). Studies in aphasia comparing error-reducing and non-error-reducing methods utilized cueing hierarchies to limit error instances (Abel et al., 2005; Conroy et al., 2009a; Lacey et al., 2004). Similarly, studies examining retrieval practice Comparing cued and uncued conditions identified an advantage of the cued condition likely due to increased instances of successful retrieval (Middleton et al., 2015). Cues are frequent in naming interventions for aphasia (Sze et al., 2021) and can be individualized to a client’s language impairment profile (e.g., Abel et al., 2007). In applying cues to promote effort and success for clients with aphasia, clinicians can identify effective cues and increase or decrease cues to balance effort and success.

For individuals with severe aphasia, even maximal cues may result in errors, making it difficult to achieve a balance between effort and success. In these instances, clinicians may combine multiple modifications aimed at promoting successful naming with precautions taken to prevent reinforcing errors. Certainly, it may be that neither errorless learning, errorful learning, or retrieval practice are optimal for achieving a particular client’s goals and alternative approaches or treatment targets may need to be selected in collaboration with the client.

3.1.3. Speed-Accuracy Trade-Off.

In the context of naming, maladaptive speed-accuracy trade-offs may result in overly impulsive or cautious responses which in turn may result in increased error rate or increased communication time, respectively (Evans et al., 2019). The Balancing Effort Accuracy and Response Speed (BEARS) framework for aphasia recognizes that people with aphasia may make sub-optimal adaptations for their language impairment (Evans et al., 2021). BEARS trains individuals to find a balance between effort, accuracy, and speed and skip items they cannot name rather than produce an error. By passing on items clients do not think they can successfully retrieve, instances of unsuccessful retrieval may be minimized while maintaining sufficient effort.

3.2. Methods to Support Cognition for Learning

Memory, attention, and executive skills may support clients in avoiding error-learning (Gated Hebbian Learning). Clinicians may be able to apply techniques adopted from neurorehabilitation and education to support key cognitive abilities during naming interventions for individuals with aphasia.

3.2.1. Metacognitive Strategies.

When learning in the presence of errors, attention and executive functioning may be important for error-detection and correction (Lambon Ralph & Fillingham, 2007). In other populations with brain injury, such as traumatic brain injury, metacognitive strategies have been successfully applied to compensate for deficits in attention and executive functioning (Cicerone et al., 2019; Kennedy et al., 2008). There is an emerging, yet limited, body of work examining the application of metacognitive strategies to address concomitant cognitive deficits in aphasia (Amaddii et al., 2014; Lee & Sohlberg, 2013; Mayer et al., 2017). Mayer et al. (2017) applied a brain budget protocol with a single individual with aphasia to improve self-monitoring of errors during oral reading. The participant was educated on the limited capacity of processing resources and coached to identify the demands of tasks and signs of cognitive overload. After training, online self-monitoring and self-correction of errors improved (Mayer et al., 2017). Research from psychology suggests that brief rest breaks can improve sustained attention and vigilance (Ariga & Lleras, 2011; Helton & Russell, 2015). Clinicians may be able to support attention by training clients to request breaks as needed thus establishing a client-regulated metacognitive strategy.

3.2.2. Improve Feedback Processing via Motivation and Curiosity.

If an individual cannot self-monitor, feedback may support learners in reinforcing correct alternatives (McClelland, 2014). To learn from feedback, individuals need to process feedback and extract relevant information to update memory. Outside of aphasia, early research finds that motivation can influence the processing of feedback. While implications for aphasia treatment are speculative, this work may provide clinicians with insight into modifiable variables that may promote learning from feedback.

DePasque and Tricomi (2015) found that the processing of feedback in neurotypical adults was enhanced following a brief motivational interview. DePasque and Tricomi (2015) devised a context which would encourage participants to generate positive statements as to why it was important that they perform well on the task. Authors hypothesized that motivation would enhance the neural response to feedback. DePasque and Tricomi (2015) found that motivational interviewing enhanced neural sensitivity to feedback valence (i.e., negative vs. positive feedback). Larger self-reported increases in motivation before and after interviewing were associated with larger increases in learning performance. It may be pertinent to consider how motivational interviewing may interact with one’s perception of negative feedback discussed in section 3.3 (e.g., emphasizing doing well on a task may make negative feedback more distressing). Such issues highlight the need for research specific to aphasia rehabilitation that could evaluate ways to increase the salience of feedback while minimizing potential psychosocial consequences of negative feedback. There may be alternative ways to improve motivation during aphasia treatment, for example, the personal relevance of treatment targets may aid in boosting motivation (Thiessen & Brown, 2021).

3.3. Methods to Reduce Affective Barriers

Negative feedback has been discussed in the aphasia research as being potentially discouraging and harmful to motivation (Abel et al., 2005; Breitenstein et al., 2004; Conroy et al., 2009a, 2009b; Fillingham et al., 2005, 2006; Lacey, 2010; McKissock & Ward, 2007). Conroy et al. (2009a) administered errorless and errorful naming treatment to clients with aphasia. Some participants found errorful treatment frustrating due to difficulty, errors, and negative feedback. Research in psychology and education offers insight into how clinicians may reduce psychosocial barriers during naming interventions.

3.3.1. Reducing Negative Feedback.

While not explored before in aphasia, research in neurotypical adults suggests a learning advantage for self-controlled feedback in which learners indicate whether they would like to receive feedback after each response (Chiviacowsky & Wulf, 2005). Self-controlled feedback is thought to allow participants to tailor feedback to their individual preferences (Chiviacowsky & Wulf, 2005). Summary feedback, or augmented feedback provided about a set of training trials, has been used in motor speech and limb motor control literature (Bislick et al., 2012). Self-controlled and summary feedback provide potential means to reduce feedback frequency while continuing to provide error detection and correction potentially important for learning. There may be individual differences in how to best provide external error detection and correction which will likely depend on client preference and importantly, cognitive-linguistic abilities.

3.3.2. Adjusting Mindsets.

When learners find challenging tasks frustrating or negative feedback to be demoralizing, clinicians can attempt to alter one’s ‘goal orientation’. Learning-oriented individuals prioritize mastering a skill; performance-oriented individuals aim to be accurate and avoid negative judgements (Button et al., 1996). In education, messages communicated by the instructor through the learning environment are hypothesized to influence an individual’s goal orientation (Ames & Archer, 1988; Button et al., 1996). Table 2 demonstrates how clinicians may communicate learning- or performance-oriented ideals.

Table 2.

Learning goals as communicated by the clinical environment: Based on Ames and Archer (1988).

Environmental
feature		 Learning-oriented Performance-oriented
Characterize success as… Progress on a collaboratively set goal High levels of accuracy on a language task
Value… Effort during therapy Accuracy during therapy
Discuss errors as… A standard part of the rehabilitation process A reason to be concerned about your progress
Measure progress as… Personally meaningful advancement towards a collaboratively set goal Performance on normative assessments
Open in a new tab

Brief interventions may also be effective at modifying one’s perception of errors. Negative emotions elicited by negative feedback have been challenged in psychology and adult learning research (Keith & Frese, 2008; Yang et al., 2017). Learners are taught that lower accuracy during training does not always indicate poor performance. Error management training, for example, has been found to enhance emotional regulation and subsequently, learning in the presence of errors (Keith & Frese, 2005). Errors during aphasia rehabilitation may elicit distinctive emotional responses or have different consequences for re-learning compared to healthy adult learners. As evidence develops on how best to support learning in the presence of errors for people with aphasia, research from other fields may offer techniques that can be borrowed, adapted, and evaluated to address existing needs.

3.3.3. Modifying Target Difficulty.

In addition to reducing the frequency of negative feedback, increasing the incidence of positive feedback may improve affect or influence goal pursuit (Fishbach et al., 2010; Kim & Lee, 2019). Adding items a participant can name accurately is a method in research studies to improve morale (e.g., McKissock & Ward, 2007). Continued retrieval of learned items would not only increase positive feedback but may also improve retention (e.g., Friedman et al., 2017). There are likely many ways in which target difficulty can be manipulated. For example, consider target complexity; atypical category items can be more difficult to name than typical category items (e.g., in the category fabric “burlap” is less typical than “cotton”). Target modifications may have implications beyond naming difficulty which should also be carefully considered (see Kiran & Thompson, 2003 for discussion on target comlpexity and generalization)

4. Discussion

Evidence for language rehabilitation is growing; however, given the diversity of clients’ language and cognitive profiles and environmental demands, it is unrealistic to have high levels of evidence as to which interventions are best for each client considering their language and cognitive profiles, personal preferences, and the clinical environment. To facilitate clinicians in aligning interventions to individuals, researchers can specify the mechanisms hypothesized to be active during an intervention. Thus, clinicians can possess a clear understanding of how an intervention works and adapt interventions in ways that align with the underlying treatment theory. The Rehabilitation Treatment Specification System (RTSS) provides a standardized language to delineate mechanisms of action improving the accessibility of this information (Hart et al., 2018). Additionally, the RTSS provides a means for researchers to hypothesize which treatment ingredients are responsible for producing change within the treated system which may aid clinicians in identifying aspects of interventions amenable to alteration. Well-specified treatment may enable clinicians to operationalize clinical decision making in a way that can be individualized per client and clinical setting. Figure 2 is an example of a decision tree, a potential product of enabling clinicians to integrate the best available evidence, well-specified treatment mechanisms, and clinical experience.

Figure 2.

Figure 2.

Open in a new tab

Clinical decision-making trees: A potential product of leveraging well-specified learning mechanisms to enable clinicians to align treatments to individuals.

The modifications illustrated in this paper demonstrate how clinicians can leverage theory to fill evidence gaps which may arise when the available evidence cannot guide clinicians on how to tailor an intervention to an individual. Many clinicians likely make some of the described modifications to interventions to address the complex needs of clients. Practice based evidence is one way in which clinicians contribute to closing knowledge gaps by systematically evaluating the effectiveness of such theory-driven modifications. Practice based evidence compliments evidence-based practice and allows clinicians to assess how the best available evidence operates within their setting with an individual client (Margison et al., 2000). Broadly, practice based evidence involves (1) creating a theory-driven treatment plan that meets the client’s needs and fits within the constraints of the clinical context, (2) collecting high-quality data on the outcomes, and (3) making adaptations as warranted. Data within practice can then inform the development of efficacy research that considers clinically relevant findings (Barkham & Mellor-Clark, 2003).

5. Conclusion

As the evidence-base in aphasia rehabilitation continues to grow, researchers and clinicians can work in partnership to develop theoretically sound and practical interventions. Researchers can conduct studies valuable to clinicians by using frameworks such as the RTSS that attempt to improve the uptake of evidence-based interventions and improve fidelity to key aspects of treatment (Hart et al., 2018). Well-specified treatment theories can enable clinicians to tailor evidence-based interventions to an individual client and setting, both with unique characteristics. High quality data collected within practice can support clinical decision making and return to researchers to inform clinically meaningful research questions.

Figure 1.

Figure 1.

Open in a new tab

Potential methods to individualize treatments considering the proposed mechanisms of action.

Highlights.

  1. Errorless, errorful and retrieval practice prioritize success and effort differently

  2. Different mechanisms of action may underly errorless, errorful and retrieval practice

  3. Mechanisms of action may guide how treatments can be modified to meet client needs

  4. Effort, accuracy, cognition, and affect may influence learning during treatment

  5. Clinicians can modify interventions to optimize learning considering treatment theory

Acknowledgement

We thank Dr. Erica Middleton (Moss Research Rehabilitation Institute) for providing feedback on the manuscript.

Funding Statement:

This work was supported by the National Institute on Deafness and Other Communication Disorders of the National Institute of Health [grant number R21DC019203]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Health.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References:

  1. Abel S, Schultz A, Radermacher I, Willmes K, & Huber W (2005). Decreasing and increasing cues in naming therapy for aphasia. Aphasiology, 19(9), 831–848. 10.1080/02687030500268902 [DOI] [Google Scholar]
  2. Abel S, Willmes K, & Huber W (2007). Model-oriented naming therapy: Testing predictions of a connectionist model. Aphasiology, 21(5), 411–447. 10.1080/02687030701192687 [DOI] [Google Scholar]
  3. Agarwal PK, Finley JR, Rose NS, & Roediger III HL (2017). Benefits from retrieval practice are greater for students with lower working memory capacity. Memory, 25(6), 764–771. 10.1080/09658211.2016.1220579 [DOI] [PubMed] [Google Scholar]
  4. Amaddii L, Centorrino S, Cambi J, & Passali D (2014). Communication skills and thalamic lesion: Strategies of rehabilitation. Otolaiyngologia Polska, 68(4), 174–179. 10.1016/j.otpol.2014.04.002 [DOI] [PubMed] [Google Scholar]
  5. Ames C, & Archer J (1988). Achievement goals in the classroom: Students’ learning strategies and motivation processes. Journal of Educational Psychology, 80(3), 260–267. [Google Scholar]
  6. Ariga A, & Lleras A (2011). Brief and rare mental “breaks” keep you focused: Deactivation and reactivation of task goals preempt vigilance decrements. Cognition, 118(3), 439–443. 10.1016/j.cognition.2010.12.007 [DOI] [PubMed] [Google Scholar]
  7. Balota DA, Duchek JM, Sergent-Marshall SD, & Roediger III HL (2006). Does expanded retrieval produce benefits over equal-interval spacing? Explorations of spacing effects in healthy aging and early stage Alzheimer’s disease. Psychology and Aging, 21(1), 19–31. 10.1037/0882-7974.21.1.19 [DOI] [PubMed] [Google Scholar]
  8. Barkham M, & Mellor-Clark J (2003). Bridging evidence-based practice and practice-based evidence: Developing a rigorous and relevant knowledge for the psychological therapies. Clinical Psychology & Psychotherapy, 10(6), 319–327. 10.1002/cpp.379 [DOI] [Google Scholar]
  9. Bislick LP, Weir PC, Spencer K, Kendall D, & Yorkston KM (2012). Do principles of motor learning enhance retention and transfer of speech skills? A systematic review. Aphasiology, 26(5), 709–728. 10.1080/02687038.2012.676888 [DOI] [Google Scholar]
  10. Bjork RA, & Bjork EL (1992). A new theory of disuse and an old theory of stimulus fluctuation. In Healy A, Kosslyn S, & Shiffrin R (Eds.), Learning Processes to Cognitive Processes: Essays in Honor of William K. Estes (Vol. 2, pp. 35–67). Erlbaum. [Google Scholar]
  11. Boyle M, Gordon JK, Harnish SM, Kiran S, Martin N, Rose ML, & Salis C (2021). Evaluating cognitive-linguistic approaches to interventions for aphasia within the rehabilitation treatment specification system. Archives of Physical Medicine and Rehabilitation, S0003999321015537. 10.1016/j.apmr.2021.07.816 [DOI] [PubMed] [Google Scholar]
  12. Breitenstein C, Kamping S, Jansen A, Schomacher M, & Knecht S (2004). Word learning can be achieved without feedback: Implications for aphasia therapy. Restorative Neurology & Neuroscience, 22(6), 445–458. [PubMed] [Google Scholar]
  13. Button S, Mathieu J, & Zajac D (1996). Goal orientation in organizational research: A conceptual and empirical foundation. Organizational Behavior and Human Decision Processes, 67(1), 26–48. 10.1006/obhd.1996.0063 [DOI] [Google Scholar]
  14. Carpenter SK, & DeLosh EL (2005). Application of the testing and spacing effects to name learning. Applied Cognitive Psychology, 19(5), 619–636. 10.1002/acp.1101 [DOI] [Google Scholar]
  15. Cavanaugh R, Kravetz C, Jarold L, Quique Y, Turner R, & Evans WS (2021). Is there a research-practice dosage gap in aphasia rehabilitation? American Journal of Speech-Language Pathology, 30(5), 2115–2129. 10.1044/2021_AJSLP-20-00257 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Chiviacowsky S, & Wulf G (2005). Self-controlled feedback is effective if it is based on the learner’s performance. Research Quarterly for Exercise and Sport, 76(1), 42–48. 10.1080/02701367.2005.10599260 [DOI] [PubMed] [Google Scholar]
  17. Cicerone KD, Goldin Y, Ganci K, Rosenbaum A, Wethe JV, Langenbahn DM, Malec JF, Bergquist TF, Kingsley K, Nagele D, Trexler L, Fraas M, Bogdanova Y, & Harley JP (2019). Evidence-based cognitive rehabilitation: Systematic review of the literature from 2009 through 2014. Archives of Physical Medicine and Rehabilitation, 100(8), 1515–1533. 10.1016/j.apmr.2019.02.011 [DOI] [PubMed] [Google Scholar]
  18. Conroy P, Sage K, & Lambon Ralph MA (2009a). The effects of decreasing and increasing cue therapy on improving naming speed and accuracy for verbs and nouns in aphasia. Aphasiology, 23(6), 707–730. 10.1080/02687030802165574 [DOI] [Google Scholar]
  19. Conroy P, Sage K, & Lambon Ralph MA (2009b). Errorless and errorful therapy for verb and noun naming in aphasia. Aphasiology, 23(11), 1311–1337. 10.1080/02687030902756439 [DOI] [Google Scholar]
  20. Cull WL (2000). Untangling the benefits of multiple study opportunities and repeated testing for cued recall. Applied Cognitive Psychology, 14(3), 215–235. [DOI] [Google Scholar]
  21. de Lima MFR, Cavendish BA, de Deus JS, & Buratto LG (2020). Retrieval practice in memory- and language-impaired populations: A systematic review. Archives of Clinical Neuropsychology, 35(7), 1078–1093. 10.1093/arclin/acaa035 [DOI] [PubMed] [Google Scholar]
  22. Dell GS, Schwartz MF, Martin N, Saffran EM, & Gagnon DA (1997). Lexical access in aphasic and non-aphasic speakers. Psychological Review, 104(4), 801–838. 10.1037/0033-295X.104.4.801 [DOI] [PubMed] [Google Scholar]
  23. DePasque S, & Tricomi E (2015). Effects of intrinsic motivation on feedback processing during learning. NeuroImage, 119, 175–186. 10.1016/j.neuroimage.2015.06.046 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Dunn J, & Clare L (2007). Learning face-name associations in early-stage dementia: Comparing the effects of errorless learning and effortful processing. Neuropsychological Rehabilitation, 17(6), 735–754. https://doi.org/oi: 10.1080/09602010701218317 [DOI] [PubMed] [Google Scholar]
  25. Evans WS, Cavanaugh R, Quique Y, Boss E, Starns JJ, & Hula WD (2021). Playing with BEARS: Balancing effort, accuracy, and response speed in a semantic feature verification anomia treatment game. Journal of Speech, Language, and Hearing Research, 64(8), 3100–3126. 10.1044/2021_JSLHR-20-00543 [DOI] [PubMed] [Google Scholar]
  26. Evans WS, Hula WD, & Starns JJ (2019). Speed-accuracy trade-offs and adaptation deficits in aphasia: Finding the "sweet spot” between overly cautious and incautious responding. American Journal of Speech-Language Pathology, 28(1S), 259–277. 10.1044/2018_AJSLP-17-0156 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Fillingham J, Hodgson C, Sage K, & Lambon Ralph MA (2003). The application of errorless learning to aphasic disorders: A review of theory and practice. Neuropsychological Rehabilitation, 13(3), 337–363. 10.1080/09602010343000020 [DOI] [PubMed] [Google Scholar]
  28. Fillingham J, Sage K, & Lambon Ralph M (2005). Treatment of anomia using errorless versus errorful learning: Are frontal executive skills and feedback important? International Journal of Language & Communication Disorders, 40(4), 505–523. 10.1080/13682820500138572 [DOI] [PubMed] [Google Scholar]
  29. Fillingham J, Sage K, & Lambon Ralph MA (2006). The treatment of anomia using errorless learning. Neuropsychological Rehabilitation, 16(2), 129–154. 10.1080/09602010443000254 [DOI] [PubMed] [Google Scholar]
  30. Fishbach A, Eyal T, & Finkelstein SR (2010). How positive and negative feedback motivate goal pursuit: Feedback motivates goal pursuit. Social and Personality Psychology Compass, 4(8), 517–530. 10.1111/j.1751-9004.2010.00285.x [DOI] [Google Scholar]
  31. Fridriksson J, & Hillis AE (2021). Current approaches to the treatment of post-stroke aphasia. Journal of Stroke, 23(2), 183–201. 10.5853/jos.2020.05015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Friedman RB, Sullivan KL, Snider SF, Luta G, & Jones KT (2017). Leveraging the test effect to improve maintenance of the gains achieved through cognitive rehabilitation. Neuropsychology, 31(2), 220–228. 10.1037/neu0000318 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Greenhalgh T, Howick J, & Maskrey N (2014). Evidence based medicine: A movement in crisis? British Medical Journal, 348(1963). 10.1136/bmj.g3725 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Grönberg A, Henriksson I, Stenman M, & Lindgren AG (2022). Incidence of Aphasia in bIschemic Stroke. Neuroepidemiology, 56(3), 174–182. 10.1159/000524206 [DOI] [PubMed] [Google Scholar]
  35. Hart T, John Whyte, Dijkers M, Packel A, Turkstra L, Zanca J, Ferraro M, Chen C, & Van Stan J (2018). Manual for rehabilitation treatment specification. https://acrm.org/acrm-communities/rehabilitation-treatment-specification/manual-for-rehabilitation-treatment-specification/ [Google Scholar]
  36. Helton WS, & Russell PN (2015). Rest is best: The role of rest and task interruptions on vigilance. Cognition, 134, 165–173. 10.1016/j.cognition.2014.10.001 [DOI] [PubMed] [Google Scholar]
  37. Keith N, & Frese M (2005). Self-regulation in error management training: Emotion control and metacognition as mediators of performance effects. Journal of Applied Psychology, 90(4), 677–691. 10.1037/0021-9010.90.4.677 [DOI] [PubMed] [Google Scholar]
  38. Keith N, & Frese M (2008). Effectiveness of error management training: A meta-analysis. Journal of Applied Psychology, 93(1), 59–69. 10.1037/0021-9010.93.1.59 [DOI] [PubMed] [Google Scholar]
  39. Kennedy MRT, Coelho C, Turkstra L, Ylvisaker M, Moore Sohlberg M, Yorkston K, Chiou H-H, & Kan P-F (2008). Intervention for executive functions after traumatic brain injury: A systematic review, meta-analysis and clinical recommendations. Neuropsychological Rehabilitation, 18(3), 257–299. 10.1080/09602010701748644 [DOI] [PubMed] [Google Scholar]
  40. Kim EJ, & Lee KR (2019). Effects of an examiner’s positive and negative feedback on self-assessment of skill performance, emotional response, and self-efficacy in Korea: A quasi-experimental study. BMC Medical Education, 19, 1–7. 10.1186/s12909-019-1595-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Kiran S, & Thompson CK (2003). The role of semantic complexity in treatment of naming deficits: Training semantic categories in fluent aphasia by controlling exemplar typicality. Journal of Speech and Hearing Research, 46(4), 773–787. 10.1044/1092-4388(2003/061) [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Komatsu S-Ι, Mimura M, Kato M, Wakamatsu N, & Kashima H (2000). Errorless and effortful processes involved in the learning of face-name associations by patients with alcoholic Korsakoff’s syndrome. Neuropsychological Rehabilitation, 10(2), 113–132. 10.1080/096020100389200 [DOI] [Google Scholar]
  43. Lacey E (2010). Generalization and maintenance in aphasia rehabilitation [Dissertation]. Georgetown University. [Google Scholar]
  44. Lacey E, Glezer L, Lott S, & Friedman R (2004). The role of effort in errorless and errorful learning. Brain and Language, 91(1), 189–190. 10.1016/j.bandl.2004.06.097 [DOI] [Google Scholar]
  45. Lambon Ralph MA, & Fillingham JK (2007). The importance of memory and executive function in aphasia: Evidence from the treatment of anomia using errorless and errorful learning. In Meyer AS, Wheeldon LR, & Krott A (Eds.), Advances in Behavioural Brain Science. Automaticity and Control in Language Processing, (pp. 193–216). Psychology Press. [Google Scholar]
  46. Lee JB, & Sohlberg MM (2013). Evaluation of attention training and metacognitive facilitation to improve reading comprehension in aphasia. American Journal of Speech-Language Pathology, 22(2), S318–S333. 10.1044/1058-0360(2013/12-0099) [DOI] [PubMed] [Google Scholar]
  47. Lemoncello R, & Ness B (2013). Evidence-based practice & practice-based evidence applied to adult, medical speech-language pathology. Perspectives on Gerontology, 18(1), 14–26. 10.1044/gero18.1.14 [DOI] [Google Scholar]
  48. Maddox GB, & Balota DA (2015). retrieval practice and spacing effects in young and older adults: An examination of the benefits of desirable difficulty. Memory & Cognition, 43(5), 760–774. 10.3758/s13421-014-0499-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Margison FR, Barkham M, Evans C, McGrath G, Clark JM, Audin K, & Connell J (2000). Measurement and psychotherapy: Evidence-based practice and practice-based evidence. British Journal of Psychiatry, 177(2), 123–130. 10.1192/bjp.177.2.123 [DOI] [PubMed] [Google Scholar]
  50. Mayer JF, Mitchinson SI, & Murray LL (2017). Addressing concomitant executive dysfunction and aphasia: Previous approaches and the new brain budget protocol. Aphasiology, 31(7), 837–860. 10.1080/02687038.2016.1249333 [DOI] [Google Scholar]
  51. McClelland JL (2014). Learning to discriminate English /r/ and /l/ in adulthood: Behavioral and modeling studies. Studies in Language Science: Journal of Japanese Society for Language Science, 13, 32–52. [Google Scholar]
  52. McKissock S, & Ward J (2007). Do errors matter? Errorless and errorful learning in anomic picture naming. Neuropsychological Rehabilitation, 17(3), 355–373. 10.1080/09602010600892113 [DOI] [PubMed] [Google Scholar]
  53. Middleton EL, Schuchard J, & Rawson KA (2020). A review of the application of distributed practice principles to naming treatment in aphasia. Topics in Language Disorders, 40(1), 36–53. 10.1097/TLD.0000000000000202 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Middleton EL, Schwartz MF, Rawson KA, & Garvey K (2015). Test-enhanced learning versus errorless learning in aphasia rehabilitation: Testing competing psychological principles. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41(4), 1253–1261. 10.1037/xlm0000091 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Mulligan NW, & Picklesimer M (2016). Attention and the testing effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(6), 938–950. 10.1037/xlm0000227 [DOI] [PubMed] [Google Scholar]
  56. Nunn K, Vallila-Rohter S, & Middleton EL (2023). Errorless, errorful, and retrieval practice for naming treatment in aphasia: A scoping review of learning mechanisms and treatment ingredients. Journal of Speech and Hearing Research, 66(2), 668–687. 10.1044/2022_JSLHR-22-00251 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Nyström M (2006). Aphasia – an existential loneliness: A study on the loss of the world of symbols. International Journal of Qualitative Studies on Health and Well-Being, 1(1), 38–49. 10.1080/17482620500501883 [DOI] [Google Scholar]
  58. Pan SC, Pashler H, Potter ZE, & Rickard TC (2015). Testing enhances learning across a range of episodic memory abilities. Journal of Memory and Language, 83, 53–61. 10.1016/j.jml.2015.04.001 [DOI] [Google Scholar]
  59. Patra A, Traut HJ, Stabile M, & Middleton EL (2022). Effortful retrieval practice effects in lexical access: A role for semantic competition. Language, Cognition and Neuroscience, 4–16. 10.1080/23273798.2022.2027991 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Ross K, & Wertz R (2003). Quality of life with and without aphasia. Aphasiology, 17(4), 355–364. 10.1080/02687030244000716 [DOI] [Google Scholar]
  61. Schuchard J, & Middleton EL (2018a). The roles of retrieval practice versus errorless learning in strengthening lexical access in aphasia. Journal of Speech, Language, and Hearing Research, 61(7), 1700–1717. 10.1044/2018_JSLHR-L-17-0352 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Schuchard J, & Middleton EL (2018b). Word repetition and retrieval practice effects in aphasia: Evidence for use-dependent learning in lexical access. Cognitive Neuropsychology, 35(5–6), 271–287. 10.1080/02643294.2018.1461615 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Schuchard J, Rawson KA, & Middleton EL (2020). Effects of distributed practice and criterion level on word retrieval in aphasia. Cognition, 198, 1–13. 10.1016/j.cognition.2020.104216 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Shrubsole K, Worrall L, Power E, & O’Connor DA (2019). Barriers and facilitators to meeting aphasia guideline recommendations: What factors influence speech pathologists’ practice? Disability and Rehabilitation, 41(13), 1596–1607. 10.1080/09638288.2018.1432706 [DOI] [PubMed] [Google Scholar]
  65. Storm BC, Bjork EL, & Bjork RA (2008). Accelerated relearning after retrieval-induced forgetting: The benefit of being forgotten. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34(1), 230–236. 10.1037/0278-7393.34.1.230 [DOI] [PubMed] [Google Scholar]
  66. Sze WP, Hameau S, Warren J, & Best W (2021). Identifying the components of a successful spoken naming therapy: A meta-analysis of word-finding interventions for adults with aphasia. Aphasiology, 35(1), 33–72. 10.1080/02687038.2020.1781419 [DOI] [Google Scholar]
  67. Thiessen A, & Brown J (2021). Personalization of restorative and compensatory treatments for people with aphasia: A review of the evidence. Topics in Language Disorders, 41(3), 269–281. 10.1097/TLD.0000000000000253 [DOI] [Google Scholar]
  68. Unsworth N, McMillan BD, Brewer GA, & Spillers GJ (2012). Everyday attention failures: An individual differences investigation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(6), 1765–1772. 10.1037/a0028075 [DOI] [PubMed] [Google Scholar]
  69. Yang C, Potts R, & Shanks DR (2017). Metacognitive unawareness of the errorful generation benefit and its effects on self-regulated learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 73(7), 1073–1092. 10.1037/xlm0000363 [DOI] [PubMed] [Google Scholar]

RESOURCES