Autobiographical memory of validating and invalidating consultations is associated with recall capacity for health information
Plos.org·July 20, 2026
AI Summary
Patients' ability to recall health information from consultations may be influenced by whether clinicians validate or invalidate their concerns during the appointment. The study examines how clinician behavior and patient emotional responses affect memory retention of medical advice, which is particularly important for managing chronic pain conditions.
Managing chronic pain involves cognitive and emotional challenges that may affect treatment adherence. Patients’ ability to remember clinician advice is therefore important. Clinician behaviours may influence these processes. To investigate whether recounting autobiographical memories of perceived validating (vs. invalidating) healthcare experiences influences subsequent recall of health-related information in people living with chronic pain, 245 adults with chronic pain (≥3 months) were recruited online. Eligibility criteria included: age ≥ 18 years, fluent in English, no hearing difficulties or mental health conditions, and at least one healthcare visit in the previous two years. Participants were quasi-randomly assigned to describe either a validating or invalidating consultation they had previously experienced. Before and after this task, participants rated their pain intensity and pain-related fear. Participants then listened to 20 health messages and were later asked to recall them in an incidental memory test. The primary outcome was incidental recall of health messages, operationalised as the likelihood of recalling each of the 20 messages. Secondary outcomes included pain intensity and pain-related fear. Recall was analysed using a binomial generalized linear mixed-effects model accounting for individual differences (pain intensity, pain-related fear, immersion in the task, age, sex, and pain duration).Participants who described a validating consultation were more likely to recall health messages than those in the invalidating condition (19% higher odds of recalling each message, based on model estimates). The association was not mediated by change in pain-related fear. These findings indicate that remembering validating consultations might boost retention of health information, highlighting clinician-validation as a potential strategy to support cognitive functioning in people living with chronic pain.
Citation: Lee CE, Birkinshaw H, Garner M, Pincus T (2026) Autobiographical memory of validating and invalidating consultations is associated with recall capacity for health information. PLoS One 21(7): e0353615. https://doi.org/10.1371/journal.pone.0353615
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Data Availability: Data is available from https://osf.io/5ksu9.
Funding: This work supported by a joint and equal investment from UKRI [grant number MR/W004151/1] and the charity Arthritis UK (formerly Versus Arthritis) [grant number 22891] through the Advanced Pain Discovery Platform (APDP) initiative. For UKRI, the initiative is led by the Medical Research Council (MRC), with support from the Biotechnology and Biological Sciences Research Council (BBSRC) and the Economic and Social Research Council (ESRC). https://apdp.community/about-us/ https://www.arthritis-uk.org/ TP was a co-applicant on the grant for both funders supporting this work. The funders did not play a role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.
Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: TP provides consultation in psychologically informed practice, contracted to the University of Southampton. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Living with pain poses challenges at individual, interpersonal and societal levels. Beyond pain itself, managing a long-term condition places ongoing cognitive and emotional demands on patients. Many people with chronic pain report difficulties with concentration, attention, memory, and executive functions such as planning, organization, thought-control and goal-directed action [1]. These cognitive difficulties can be distressing and may hinder a patient’s ability to manage their condition [2]. Research has shown that patients who struggle to recall treatment, advice and self-management strategies accurately often have poor adherence with medical advice [3,4].
The Narrow Attentional Resources Hypothesis (NARH), also known as the ‘Capacity-Reduction Hypothesis’ or ‘Attentional Capacity Theory’ [5] suggests that memory deficits associated with chronic pain arise because cognitive resources are reallocated toward emotional and ruminative responses to pain, such as catastrophic thinking, leaving fewer resources available for processing other stimuli [5–7]. Other researchers have focused on emotional regulation [8], finding that higher levels of anxiety correlate with poorer memory [2].
Within the broader context of pain-anxiety, pain-related fear describes fearful thoughts and ruminations about the consequences of pain [9]. According to the NARH, when pain-related fear or anxiety are high, patients may allocate additional cognitive resources to monitoring and anticipating pain, further interfering with memory, attention, and executive functioning [5].
Patient’s fear and anxiety are often closely tied to how their concerns are recognised in clinical encounters [10–13]. A review investigating determinants of treatment adherence in Chronic Pain patients identified clinician-patient relationship quality as important [14]. Clinician validation is defined as explicitly conveying to the patient that their pain experience is understood and believed [15]. It has typically been viewed as a non-specific factor within reassurance frameworks, enhancing the effect of therapeutic interventions [16] and a recent review describes it as necessary for reducing pain-related anxiety and fear [15].
To our knowledge, the impact of validation on recall has only been examined in one small experimental study by Carstens et al., [17]. In this study, healthy participants received either validating or invalidating responses from the experimenter during a task involving experimentally induced pain. The validated group demonstrated higher and more accurate recall than the invalidated group. The current study extends this work by examining these effects in individuals living with chronic pain. To closely approximate real-world clinician validation and invalidation, we opted to use participants’ own autobiographical accounts of previous healthcare consultations to reactivate experiences. This reactivation method is widely used in social psychology [18] and is supported by neurological evidence [19]. Importantly, this approach targets perceived validation and invalidation rather than objective features of clinical encounters, as subjective interpretations of interactions shape emotional responses and cognitive interpretations [20,21].
This proof-of-concept study tests the association between perceived validation and invalidation in autobiographical memories of consultations, participants’ recall of health messages, and whether this is mediated by changes in pain-related fear or anxiety. The study has two aims. First, whether recounting a validating consultation compared to an invalidating one, will improve recall of health information. Second, to examine whether this effect is mediated by changes in pain-related fear or anxiety.
Participants were recruited through Prolific, an online research recruitment platform. Prolific maintains a participant pool in which users undergo verification procedures, including identity and location checks, as well as ongoing data quality monitoring [22]. Participants complete pre-screening questions and provide demographic information which researchers may use to advertise studies to eligible participants. Eligibility criteria for this study required participants to be ≥ 18 years, fluent in English, free from hearing difficulties, have completed more than 20 studies on Prolific, and to have experienced chronic pain for more than three months. In addition, participants needed to have visited a healthcare provider within the last two years and be able to listen to audio through computer speakers or headphones. Those reporting mental health conditions were excluded because Prolific does not differentiate between specific diagnoses. This broad category may therefore include individuals with cognitive decline or impairment, as well as those with clinical anxiety disorders, which could confound recall performance [23]. Data collection took place from 8th-30th October 2024. Participants provided written informed consent via checkbox within the study. The study was approved by the University of Southampton Ethics and Research Governance Committee (ERGO: 98387).
To further ensure data quality, two instructional manipulation attention checks were embedded within scales (e.g., “To check you are paying attention, please select ‘always’”) [24]. Within Qualtrics, failed attention checks triggered an automated warning informing participants that two failed checks would result in automatic rejection, in line with Prolific’s Attention Check Policy [25]. Participants who were automatically redirected following this process were treated as withdrawals and were not included in the final dataset. Demographic data were not retrieved from Prolific for these cases.
Submissions were excluded if the entire study was completed implausibly quickly (more than three standard deviations below the mean completion time) or if participants timed out after 77 minutes of inactivity (platform-imposed limit). Participants also completed a retrospective self-report validity check (“Should we use your data?”) and rated their ‘immersion’ in the autobiographical memory task. Finally, an open-ended comment box allowed participants to report interruptions or clarify responses. These procedures maximised the likelihood that participants were genuine individuals living with chronic pain, who had experienced validating and/or invalidating consultations, and who engaged fully with the study.
Participants were asked to read an information sheet and then required to give informed consent via a checkbox before taking part. Participants were informed about what would happen during the study, their right to withdraw, the £3.50 reward for completion and the inclusion of attention check questions. Before the main study, participants completed a pre-screening questionnaire to confirm their eligibility based on self-reported pain status (“You previously responded ‘Yes’ to the question about chronic pain on prolific. For how long have you experienced this pain?”) and to determine condition assignment. They were asked whether they had experienced validation and/or invalidation from a healthcare provider in the past. Those who reported having experienced both were randomly assigned to a condition via Qualtrics using the question randomisation function. The randomiser was programmed to evenly assign participants to one of the two experimental branches: one where they were asked to recount a validating healthcare experience, or one where they were asked to recount an invalidating healthcare experience. Those who had experienced only one were automatically assigned to the corresponding condition branch. Participants who had not experienced chronic pain for more than 3 months, and/or those who did not report either a validating/invalidating were excluded from the study.
A simulated dataset using the simr package in R [26] was used to estimate the power to detect a small-moderate effect (β = 0.2) in a binomial GLMM with 20 recall items per participant. The simulation suggested that a sample of 200 participants would provide 80% power. To account for potential data loss due to inattentive responses, incomplete submissions, or exclusions during quality checks (e.g., AI-generated text, mismatched descriptions, or outlier responses), we aimed for 300 participants.
The study employed a mixed design, with one between-subjects variable (Condition: Validation vs. Invalidation) and one within-subjects variable (Timepoint: Baseline [T1] vs. Post-task [T2]).
Depending on assigned condition, participants were asked to write about a previous experience (autobiographical memory) in which they felt a clinician had been validating or invalidating about their pain experiences in an open response text box. Participants were not specifically asked to describe a consultation about their pain, but given the context of the preceding questions (about their pain experience and diagnosis) almost all did. Instructions and examples (presented in Table 1) were designed to be as similar as possible between experimental conditions with limited changes in wording to convey the two concepts (validation and invalidation) to minimise any systematic bias.
https://doi.org/10.1371/journal.pone.0353615.t001
The health information recall test featured a list of 20 messages related to general health (not pain specific) initially collected from National Health Service websites [27,28]. Messages were independently reviewed by two members of the research team who identified systematic variation in their linguistic framing. We therefore categorised messages based on functional intent, distinguishing between ‘action-oriented’ messages, which encouraged health-promoting behaviours using motivational or approach-focussed language (e.g., “Drink more water,” “Go for an eye test”), and ‘restriction-oriented’ messages, which discouraged unhealthy or risky behaviours using avoidance-focussed language (e.g., “Avoid junk food,” “Limit alcohol intake”). Where the initial set of messages resulted in disproportionate numbers across categories, messages were adapted or replaced to achieve a balanced distribution between action-oriented and restriction-oriented content (10 per category). We elected to use health messages that reflected real-world general health advice, rather than neutral word stimuli used in previous research [17] to maximise external validity. These decisions were made in discussions with public contributors. Each message was short (M = 4.25 words, SD = 1.46), easy to understand, and related to common aspects of health and wellness, including nutrition, hygiene, mental wellbeing, and safety. Exercise-related advice was excluded, since treatment plans for some pain conditions include various levels of exercise, and as such, this advice may be more salient for some participants than others. This decision was supported by consultations with public contributors, who highlighted that such advice might unintentionally invalidate persons with pain who do not feel able to exercise regularly, which may in turn bias results. The 20 messages were delivered as audio recordings to best approximate they way health advice may be given in clinical settings. Messages were played in a randomised order with a 500 ms pause between messages. Each message was played only once, and the dependent variable (DV) was the likelihood of accurate recall. Instructions for listening to the audio at the encoding phase were “On the next page you will hear an audio clip about ‘general health tips’. The audio may only be played once, so only click play when you are ready and have your speakers turned up. Please don’t write down or otherwise record any of the information.”
Instructions for the test phase were “Now, thinking back to the recording we asked you to listen to earlier, in which some healthcare providers talked about general health tips. Please write down as many of the health tips as you can remember in the boxes below (one per box). More boxes will appear as you fill them in. Don’t worry if you’re not sure about the exact wording or spelling.”
The Pain Anxiety Symptom Scale short-version (PASS-20; [9] was used to assess pain-related anxiety before and after the autobiographical memory task. Participants responded to 20 statements on a 6-point likert-scale from 0 (never) to 5 (always). The PASS-20 measures pain-related anxiety symptoms specific to the experience of chronic pain and includes four subscales: Cognitive, Fear, Escape/avoidance and Physiological Anxiety. It has been found to better predict pain, disability, avoidance and complaints than other more general measures of anxiety in chronic pain populations, has good test-retest reliability (α = .75 −.87) and very high correlations with the original subscales (r = .93 −.97) [9].We selected the two most theoretically appropriate subscales to examine as potential mediators. The Fear subscale was chosen as it aligns most closely with the theoretical frameworks outlined in the literature [9]. The scale includes items such as “When I feel pain I am afraid that something terrible will happen” and “I think that if my pain gets too severe it will never decrease”. It captures anticipatory fear related to pain and its consequences, which is particularly relevant to emotional processing and attentional disruption. The Cognitive subscale was also selected, which captures patients’ perceptions that pain impairs their thinking, including items such as “I can’t think straight when I am, in pain” and “I find it hard to concentrate when I hurt”.
Potential confounding variables included pain intensity ratings, measured using the Numeric Pain Rating Scale (NPRS) [29] where participants rated their current, best, and worst pain over the past 24 hours on an 11-point scale from 0 (no pain) to 10 (worst pain imaginable); the NPRS demonstrates good test-retest reliability for both literate and illiterate individuals with chronic pain (r = .95 and.96, respectively) [30]. Diagnostic uncertainty was assessed with questions about participants’ beliefs regarding their diagnosis and explanation, such as “Do you believe a clear diagnosis was given?” and “Do you agree with the explanation provided?” [31]. Immersion in the autobiographical memory task was measured with a single-item question: “how much did you feel like you were reliving the experience that you described? (e.g., to what extent did you feel the same feelings that you had in that moment?)” rated from 0% (not at all) to 100% (completely). Although this item has not been formally validated, it was included as a theoretically grounded proxy for the subjective experience of reliving the memory (i.e., immersion). Participant age, sex, and pain duration were also recorded as potential confounders.
Participants accessed the study on Qualtrics via a link on Prolific using a laptop, desktop, or mobile device. Functional audio was required, as the recall task was delivered via audio recordings, and participants could also listen to study instructions and descriptions if preferred. This accessibility adaptation was developed based on feedback from public contributors during pilot testing.
Baseline [T1]: Participants first completed a series of baseline assessments including demographic information, details about their pain condition (any diagnoses, duration, affected areas), diagnostic uncertainty, and numeric pain ratings (current/best/worst pain levels over the last 24hrs). They also completed the PASS-20 questionnaire. A momentary body awareness questionnaire [32] was administered at this stage as part of a separate study not related to the present research question. This measure assessed self-reported awareness of bodily sensations across seven domains (heartbeat, breathing, posture, skin, muscles, stomach/intestines, and joints) on a 0 (not at all) to 10 (very much) scale. Participants were then offered a short break before proceeding to the next phase of the study.
Experimental Task: Next, participants completed the autobiographical memory writing task, in which they wrote about a past experience of perceived validation or invalidation from a healthcare provider, depending on their assigned condition. Participants were required to write a minimum of 500 characters, and the “Next” button appeared only after 3 minutes, ensuring sufficient engagement with the task. However, participants were allowed to spend as much additional time as needed to complete their response.
Post task [T2]: Measures completed at T2 followed immediately after the experimental task within the same study session, with no intervening delay between phases. Participants answered follow-up questions about the healthcare provider and setting they had described and completed the same body awareness questionnaire again (part of the separate study as described above). Participants then listened to 20 audio health messages (identical for all participants) in a randomized order. Randomisation was used to minimise any serial position effects. They subsequently rated their pain and completed the PASS-20 for a second time. Participants then completed two untimed cognitive tasks: a word association task, in which they typed the first word that came to mind in response to neutral or pain-related prompts (part of a separate study and not analysed here), and the incidental recall task, in which they wrote down the health messages they remembered from earlier. At the end of the study, participants rated how immersed they had felt in their past experience during their participation. Participants also were given the opportunity to provide any additional information or comments (optional).
Finally, participants were directed to a debriefing screen which offered information about the study aims, resources for further reading and support links for participants who may have found the reflective writing task emotionally distressing. The study took approximately 30 minutes and participants were paid £3.50 upon completion.
From the very beginning, this study was shaped by input from a group of public contributors (individuals with lived experience) [33]. Their involvement was essential in defining the study goals and aims, and in highlighting important factors to consider in our analysis, such as the duration of participants’ pain and their current pain levels. They also influenced the study design by advising on clearer wording, font choices to improve readability, and offering audio instructions alongside written ones to make participation easier.
To explore whether recounting a validating experience influenced recall accuracy at T2, data were analysed using binomial generalized linear mixed models (GLMMs) implemented in the ‘lme4’ package [34] in R [35]. A binomial GLMM was appropriate because recall was measured for each of the 20 items per participant. Modelling at the item level captures individual differences in memory performance and accounts for the nested structure of items within participants, providing more precise estimates than collapsing responses into a single score per person. Following recommendations by Barr and colleagues [36] the starting model included the ‘maximal’ random effects structure justified by the experimental design to best account for systematic noise. The ‘buildmer’ package [37] was used to identify the best-fitting model. This package ranks predictors by their contribution to model fit and applies a backward elimination procedure, removing variables that do not significantly improve the model. This approach helps to avoid overfitting, retaining only variables associated with meaningful patterns in the data.
Data collection was initially planned for 300 participants, but was stopped at 288 due to reduced participant availability on Prolific. Prior to data processing, participants’ written descriptions of validating and invalidating experiences, as well as their self-reported diagnoses, were carefully checked to ensure relevance and completeness. At this point, 12 descriptions were flagged by researchers as potentially AI-generated due to a high degree of similarity in structure and content. These cases were subsequently reviewed in consultation with the Prolific team following guidance for detecting bots or AI-generated responses [38] and were removed. An additional 3 datasets were removed where the descriptions did not match the prompts given to the participant (e.g., the participant did not describe a validating/invalidating experience or described something other than a visit with a healthcare provider about their pain). Responses to the retrospective self-report validity check were examined, and no participants indicated that their data should not be used; therefore, no additional exclusions were made. Examples of autobiographical descriptions from each group are provided in S1 Appendix.