Volume 33, Issue 2 e13947

RESEARCH ARTICLE

Open Access

Effects of (non)deceptive placebos on reported sleep quality and food cue reactivity

Jonas Potthoff,

Corresponding Author

Jonas Potthoff

[email protected]

orcid.org/0000-0002-3927-7192

Institute of Psychology, University of Graz, Graz, Austria

Correspondence

Jonas Potthoff, Institute of Psychology, University of Graz, Universitaetsplatz 2, 8010, Graz, Austria.

Email: [email protected]

Contribution: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Validation, Visualization, Writing - original draft

Search for more papers by this author

Anne Schienle,

Anne Schienle

Institute of Psychology, University of Graz, Graz, Austria

Contribution: Conceptualization, Project administration, Resources, Supervision, Validation, Writing - original draft, Writing - review & editing

Search for more papers by this author

Jonas Potthoff,

Corresponding Author

Jonas Potthoff

[email protected]

orcid.org/0000-0002-3927-7192

Institute of Psychology, University of Graz, Graz, Austria

Correspondence

Jonas Potthoff, Institute of Psychology, University of Graz, Universitaetsplatz 2, 8010, Graz, Austria.

Email: [email protected]

Contribution: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Validation, Visualization, Writing - original draft

Search for more papers by this author

Anne Schienle,

Anne Schienle

Institute of Psychology, University of Graz, Graz, Austria

Contribution: Conceptualization, Project administration, Resources, Supervision, Validation, Writing - original draft, Writing - review & editing

Search for more papers by this author

First published: 23 May 2023

https://doi.org/10.1111/jsr.13947

Share a link

Email
Wechat
Bluesky

Summary

A lack of sleep can increase appetite, particularly for high-calorie food. The current study tested the effects of an open-label placebo for improving sleep quality and reducing food cue reactivity. In open-label placebo interventions, placebo recipients are informed that they are receiving a placebo without a pharmacologically active substance. Participants (n = 150) were randomly allocated to one of three groups that received either an open-label placebo to improve sleep quality, a deceptive placebo (“melatonin”), or no placebo. The placebo was administered daily before bedtime for 1 week. Sleep quality and reactivity to high-calorie food cues (appetite, visual attention to food images) were assessed. The deceptive placebo (but not the open-label placebo) reduced reported sleep-onset latency. The open-label placebo decreased perceived sleep efficiency. The placebo interventions did not change food cue reactivity. This study demonstrated that open-label placebos do not present an alternative to deceptive placebos for improving sleep quality. The undesirable open-label placebo effects found warrant further exploration.

1 INTRODUCTION

Poor sleep quality not only impacts how tired we are during the day but can also lead to adverse health outcomes, such as an increased appetite for high-calorie foods and subsequent weight gain (Brondel et al., 2010; Gangwisch et al., 2005). Several studies have documented that short sleep duration (< 6 hr per day) is associated with an increase in the incidence of obesity even after controlling for confounding variables like education or physical activity (Hasler et al., 2004; for a review and meta-analysis, see Itani et al., 2017). Furthermore, experimental studies suggest a causal effect of insufficient sleep on overeating (Broussard & Klein, 2022).

To avoid these negative health effects, scientific societies like the National Sleep Foundation recommend 7–9 hr of sleep per day for adults aged 18–64 years (Hirshkowitz et al., 2015). However, in a recent survey on sleep habits conducted in Austria, only about half of the participants reported that they got the recommended amount of sleep (Blume et al., 2020). Nonetheless, for some people even < 6 hr of sleep per night may be sufficient (Hor & Tafti, 2009). Therefore, when studying health outcomes, not only the total sleep duration but also sleep quality (e.g. problems falling asleep or subjectively perceived sleep quality) should be considered (Hinz et al., 2017; van de Langenberg et al., 2022). A meta-analysis has shown that the global subjective sleep quality (as measured by the Pittsburgh Sleep Quality Index [PSQI]; Buysse et al., 1989) has decreased during the COVID-19 pandemic (Scarpelli et al., 2022). This reveals a need for interventions to improve sleep quality that are easy to implement on a large scale.

There is increasing evidence gathered from placebo control groups of clinical trials on primary insomnia that even sham treatments can improve sleep quality (Jiang et al., 2019). Further, a meta-analysis found that deceptive placebo interventions (i.e. where participants were led to believe they had received a sleep-improving medication) could increase not only total sleep duration but also improve subjective sleep quality and decrease the perceived latency of sleep onset (Yeung et al., 2018). However, the use of deceptive placebo interventions presents an ethical dilemma (Annoni, 2018). In addition, deceiving patients may impair the trust relationship between patients and healthcare providers; without trust, a meaningful therapeutic relationship may become very difficult. Despite evidence that placebo effects are substantial and reliable in improving subjective sleep quality, if placebo recipients discover the deception, they may feel deceived or distrustful.

Over the past few years, open-label placebos (OLPs) have been investigated as a potential alternative for leveraging placebo effects without deceiving placebo recipients (von Wernsdorff et al., 2021). In OLP interventions, placebo recipients are fully aware and informed that they are receiving a placebo and not a medication with a pharmacologically active substance. It has been shown that such OLP interventions can, for example, decrease patients' pain or cancer-related fatigue (von Wernsdorff et al., 2021). In healthy participants, OLPs have reduced emotional distress (Guevarra et al., 2020; Schienle et al., 2022), and increased health-promoting behaviours (e.g. the practice of relaxation training; Schienle & Unger, 2021).

The development and evaluation of OLP interventions for improving sleep quality are still in their infancy. An initial study investigated the effects of OLPs at different dosages on various well-being indicators, including sleep quality (El Brihi et al., 2019). Participants in that study who received OLP treatment (taking for 5 days either one OLP pill in the low-dose group or four pills in the high-dose group) reported better sleep quality compared with a control group that received no treatment. In another study, two OLP interventions were compared that did not differ in the number of pills administered, but in the information given to the placebo recipients (Haas et al., 2022). One group of participants received the information that they would receive a placebo pill without an active ingredient, but then no further information on beneficial placebo effects. The second OLP group was (in addition to receiving a placebo pill) informed: (1) that placebos can have beneficial effects on different symptoms; (2) that the body can respond automatically to the pill even if the person taking the pill knows that it is a placebo; and (3) that a positive attitude towards the placebo is beneficial but not necessary to experience the desired effects. Neither of the two OLP groups showed an improved sleep quality compared with the control group that did not receive any treatment. The authors of that study argue that longer-term OLP interventions (instead of single applications) may be necessary to improve sleep quality.

As mentioned above, there is evidence that deceptive placebos can change the quality, duration and onset latency of sleep (Jiang et al., 2019; Yeung et al., 2018). However, there is mixed evidence for the efficacy of OLP approaches for improving sleep (El Brihi et al., 2019; Haas et al., 2022). The present study is the first to compare the effects of a 1-week deceptive placebo and OLP intervention on sleep quality. Further, based on the associations between sleep quality and eating behaviour (Brondel et al., 2010; Gangwisch et al., 2005), the present study also investigated the effects of these placebo interventions on appetite as well as attention to images of high-calorie food. So far, there has been only some evidence showing that deceptive placebos can decrease food cue reactivity (Hoffmann et al., 2018; Potthoff et al., 2019). However, to our knowledge, there has been no investigation carried out into whether an OLP can achieve the same effects.

It was hypothesized that compared with a control group, the placebos (deceptive, non-deceptive) would increase subjective sleep quality and estimated sleep duration, as well as reduce sleep-onset latency (assessed via the German PSQI; Hinz et al., 2017). Further, the placebos should decrease appetite for high-calorie food as well as visual attention to high-calorie food cues. The present study was preregistered in the Open Science Framework (OSF): https://osf.io/34kcx.

2 METHODS

2.1 Sample

A total of 150 participants (age: M = 29.7 years, SD = 12.1 years; gender: 71% female, 29% male, < 1% other; PSQI sum score before intervention: M = 5.0, SD = 2.7; body mass index [BMI]: M = 22.7 kg/m², SD = 3.7 kg/m²)¹ were invited to participate in a study about sleep and eating behaviour. Exclusion criteria were reported somatic diseases, mental disorders, and medication affecting sleep or eating behaviour. Participants were randomly assigned to one of three groups (each n = 50): an OLP group; a deceptive placebo group; and a control group without placebo intervention. A total of 29 participants did not complete the study (Figure 1). Participants were recruited via posts on social media and at the university campus. The study was approved by the ethics committee of the university (ethics approval code: GZ. 39/73/63 ex 2021/22) and conducted following the Declaration of Helsinki.

Details are in the caption following the image — **FIGURE 1**
Open in figure viewer PowerPoint

Compliance differed significantly only between the control group and open-label placebo (OLP) groups in the baseline assessment [X²(1, N = 100) = 5.26, p = 0.022], with a lower number of participations in the OLP group compared with the control group (which had no dropout at all at this point). Final samples: deceptive placebo: n = 42; OLP: n = 36; control group: n = 43

2.2 Procedure

Participants were invited to a first session, where the general procedure was explained and written informed consent was obtained. Participants in the placebo groups received a bottle with 50 ml of a blue, mint-flavoured spray that was labelled as either a placebo (OLP group) or melatonin (deceptive placebo group). A spray for oral administration was used to mimic common over-the-counter melatonin supplements (Erland & Saxena, 2017). Participants of both placebo groups received a leaflet that explained that the spray (placebo or “melatonin”) would help them to fall asleep faster and to improve overall sleep quality. The deceptive placebo leaflet was based on an over-the-counter melatonin spray leaflet. The OLP group leaflet was based on established recommendations for OLP administration (Kaptchuk et al., 2010) informing participants: (1) that placebos can have beneficial effects on various symptoms; (2) that the body can respond automatically to the placebo; and (3) that an optimistic attitude towards the placebo is beneficial but not necessary (Haas et al., 2022). The control group was provided information about the general procedure of the study.

On the morning after the initial meeting before breakfast, participants completed an online survey including questions concerning demographic information, the PSQI (Hinz et al., 2017), and assessments of both appetite and food cue attention biases (Kakoschke et al., 2015). For the following seven evenings, participants in the placebo groups sprayed two puffs of the liquid on their tongues 30 min before bedtime. Each subsequent morning, all participants estimated the number of hours slept, rated their subjective sleep quality on a seven-point scale (“very good” to “very poor”) and appetite on a five-point scale (“How much would you like to eat something right now?”, from 0 “not at all” to 4 “very much”). After 1 week, the PSQI, appetite and food cue attention biases were reassessed in the morning before breakfast.

2.3 Materials

2.3.1 Pittsburgh Sleep Quality Index

The PSQI (Hinz et al., 2017) assesses seven components of sleep quality (subjective sleep quality; sleep latency; sleep duration; habitual sleep efficiency; sleep disturbances; use of sleep medication; and daytime dysfunction). The items of the original PSQI refer to the previous month (e.g. “During the past month, how would you rate your sleep quality overall?”). The German PSQI has been validated within a community sample of 9284 people (Hinz et al., 2017). A modified instruction for the PSQI was used that matched the duration of the intervention (i.e. 1 week; El Brihi et al., 2019).

The present study focused on PSQI components 2 (sleep-onset latency; based on the estimated minutes it took to fall asleep and frequency of the latency being above 30 min) and 1 (subjective sleep quality; from 0: “very good” to 3 “very bad”) based on the verbal placebo suggestions. Higher values (from 0 to 3) indicate poorer sleep quality and that it takes participants longer to fall asleep.

2.3.2 Appetite and food cue attention bias

Before and after the 1-week intervention, participants reported their general appetite (“How much would you like to eat something right now?”; 0: “not at all”; 4: “very much”) and specific appetite for high-calorie (e.g. pancakes) and low-calorie foods (e.g. fruits). Such single-item Likert-scale assessments of food liking or appetite are a well-established and time-efficient method for recording individual food preferences (Potthoff & Schienle, 2020; van Alebeek et al., 2023). A modified dot-probe task was then employed, using images from the food.pics database (Blechert et al., 2014; Blechert et al., 2019).² This task presented a food- and non-food image pair for either 500 ms or 1500 ms. After each image pair, an arrow appeared in one of the locations (food or non-food). Participants responded to the arrow by pressing either “t” (upwards arrow) or “v” (downwards arrow). In total, 160 trials were conducted (80 high-calorie–non-food pairs and 80 low-calorie–non-food pairs; 80,500 ms trials and 1500 ms trials). Faster reaction times for trials with the arrow appearing in the food location indicate a food cue attention bias (Kakoschke et al., 2015). Trials with 500 ms image-pair duration assessed early, automatic attention biases; 1500 ms trials assessed later, more voluntarily controlled attention (Potthoff & Schienle, 2020).

2.3.3 Statistical analysis

Three by two analyses of variance (ANOVAs) were calculated to test the effects of Intervention (between-subjects: OLP, deceptive placebo, control group) and Time (within-subjects: before and after intervention) on PSQI scores, and food cue attention biases (dot-probe task). Daily sleep and appetite ratings during the intervention were averaged and were compared via ANOVAs with Intervention being the only between-subjects factor. Data from participants who conducted less than half of these daily assessments (n = 21) were excluded from the analysis (Figure 1).

3 RESULTS

3.1 Pittsburgh Sleep Quality Index

3.1.1 Sleep latency (PSQI component 2)

There was a significant medium-sized interaction between Time and Intervention (F_(2,118) = 4.03, p = 0.020, η_part² = 0.064). The deceptive placebo group reported falling asleep faster after the intervention (t₍₄₁₎ = 3.84, p_Holm < 0.001, d = 0.593). This effect was not present in the OLP group (t₍₃₅₎ = −0.312, p_Holm = 0.757, d = −0.052) and control group (t₍₄₂₎ = 0.850, p_Holm = 0.800, d = 0.130). There was a significant but small effect of Time (F_(1,118) = 4.73, p = 0.032, η_part² = 0.039). Sleep-onset latency decreased over time (t₍₁₂₀₎ = 2.26, p =0 .026, d = 0.205). The main effect of Intervention was not significant (F_(2,118) = 0.318, p = 0.728, η_part² = 0.005).

3.1.2 Sleep duration (PSQI component 3)

There was a significant medium-sized interaction Time × Intervention (F_(2,118) = 4.03, p = 0.020, η_part² = 0.064). However, the within-group effects were not significant (placebo: t₍₄₁₎ = 1.95, p_uncorrected = 0.058, d = 0.300; OLP: t₍₃₅₎ = −1.75, p_uncorrected = 0.090, d = −0.291; control: t₍₄₂₎ = 0.703, p_uncorrected = 0.486, d = 0.107). Neither the main effect of Time (F_(1,118) = 0.071, p = 0.790, η_part² = 0.001) nor Intervention (F_(2,118) = 0.668, p = 0.515, η_part² = 0.011) were significant.

3.1.3 Habitual sleep efficiency (PSQI component 4)

The interaction effect (F_(2,118) = 3.81, p = 0.025, η_part² = 0.061) was statistically significant. Habitual sleep efficiency decreased in the OLP group (t₍₃₅₎ = −2.05, p_uncorrected = 0.048, d = −0.342), but there was neither a significant effect in the deceptive placebo group (t₍₄₁₎ = 1.72, p_uncorrected = 0.094, d = 0.265) nor in the control group (t₍₄₂₎ = 0.443, p_uncorrected = 0.660, d = 0.068). Neither the main effect of Time (F_(1,118) = 0.068, p = 0.794, η_part² = 0.001) nor Intervention (F_(2,118) = 0.215, p = 0.807, η_part² = 0.004) were significant.

3.1.4 Other PSQI components

For the remaining PSQI components (subjective sleep quality, sleep disturbances, sleep medication, daytime disturbances), there were no significant main or interaction effects (all p > 0.05; Table 1).

TABLE 1. PSQI descriptives and ANOVA

Component	Intervention	Pre mean (SD)	Post mean (SD)	ANOVA
1. Subjective sleep quality	Deceptive:	1.02 (0.71)	0.83 (0.70)	Intervention: F_(2,118) = 0.91, p = 0.405, η_part² = 0.015
	OLP	1.10 (0.64)	1.06 (0.63)	Time: F_(1,118) = 3.90, p = 0.051, η_part² = 0.032
	Control	1.09 (0.51)	1.00 (0.54)	Interaction: F_(2,118) = 0.57, p = 0.567, η_part² = 0.010
2. Sleep latency	Deceptive**	1.26 (1.00)	0.81 (0.89)	Intervention: F_(2,118) = 0.32, p = 0.728, η_part² = 0.005
	OLP	0.90 (1.00)	1.00 (0.93)	Time:* F_(1,118) = 4.73, p = 0.032, η_part² = 0.039
	Control	1.00 (0.94)	0.86 (0.80)	Interaction:* F_(2,118) = 4.03, p = 0.020, η_part² = 0.064
3. Sleep duration	Deceptive	0.30 (0.64)	0.12 (0.33)	Intervention: F_(2,118) = 0.67, p = 0.515, η_part² = 0.011
	OLP	0.21 (0.52)	0.39 (0.65)	Time: F_(1,118) = 0.07, p = 0.790, η_part² = 0.001
	Control	0.22 (0.42)	0.16 (0.43)	Interaction:* F_(2,118) = 4.28, p = 0.016, η_part² = 0.068
4. Habitual sleep efficiency	Deceptive	0.65 (0.81)	0.41 (0.73)	Intervention: F_(2,118) = 0.22, p = 0.807, η_part² = 0.004
	OLP*	0.36 (0.71)	0.64 (0.93)	Time: F_(1,118) = 0.07, p = 0.794, η_part² = 0.001
	Control	0.52 (0.84)	0.42 (0.82)	Interaction:* F_(2,118) = 3.81, p = 0.025, η_part² = 0.061
5. Sleep disturbances	Deceptive	0.95 (0.58)	0.95 (0.49)	Intervention: F_(2,118) = 0.41, p = 0.665, η_part² = 0.007
	OLP	1.05 (0.51)	0.89 (0.58)	Time: F_(1,118) = 0.95, p = 0.331, η_part² = 0.008
	Control	1.04 (0.47)	1.05 (0.49)	Interaction: F_(2,118) = 1.42, p = 0.246, η_part² = 0.023
6. Use of sleeping medication	Deceptive	0.05 (0.31)	0.14 (0.65)	Intervention: F_(2,118) = 0.25, p = 0.780, η_part² = 0.004
	OLP	0.05 (0.32)	0.56 (0.33)	Time: F_(1,118) = 0.15, p = 0.702, η_part² = 0.001
	Control	0.17 (0.57)	0.09 (0.43)	Interaction: F_(2,118) = 1.02, p = 0.364, η_part² = 0.017
7. Daytime dysfunction	Deceptive	0.95 (0.79)	1.02 (0.84)	Intervention: F_(2,118) = 0.09, p = 0.913, η_part² = 0.002
	OLP	1.03 (0.71)	0.94 (0.79)	Time: F_(1,118) = 0.07, p = 0.796, η_part² = 0.001
	Control	0.96 (0.76)	0.93 (0.74)	Interaction: F_(2,118) = 0.24, p = 0.785, η_part² = 0.004

Note: Intervention: Deceptive: deceptive placebo group; OLP: open-label placebo group; Control: control group; PSQI scores from 0 (highest sleep quality) to 3 (lowest sleep quality). *p_uncorrected < 0.05, **p_Holm < 0.05 for pairwise comparison within group; *p < 0.05 for effect in ANOVA.

3.2 Daily ratings (sleep duration, subjective sleep quality and appetite)

For the averaged daily ratings, there was no effect of Intervention on the estimated sleep duration (F_(2,125) = 0.12, p = 0.886), sleep quality (F_(2,125) = 0.15, p = 0.862) and appetite (F_(2,125) = 1.76, p = 0.176).

3.3 Food cue attention and specific appetite for high-calorie food

For none of the assessed high-calorie food assessments (food biases in dot-probe task and appetite), the interaction between Time and Intervention was significant (p > 0.638). All participants consistently showed an attention bias towards images of food that was not affected by the intervention, time or type of food depicted in the images (see Supplementary Table S1).

4 DISCUSSION

This study is the first to compare the efficacy of OLPs and deceptive placebos for improving sleep duration and quality. The participants were issued a take-home placebo spray that was administered daily before bedtime over 1 week. After 1 week, the deceptive placebo (“melatonin”) was found to reduce the time it took participants to fall asleep. This effect was not present in the OLP group (and in the control group). Thus, the placebo effect required deception.

It was only recently that research has begun to compare general acceptance and outcome expectations concerning deceptive and non-deceptive placebo treatment (Haas et al., 2021; von Wernsdorff et al., 2021). To produce positive health effects, deception may be necessary for some areas (e.g. depression; Schienle & Jurinec, 2022) but not for others (e.g. pain reduction; Disley et al., 2021). For the domain of sleep quality, future studies need to investigate if the rationale of OLP treatment is clear and plausible for the placebo recipients. In the present study, the deceptive placebo intervention was mimicking melatonin treatment. Melatonin is sold as an over-the-counter dietary supplement, and its use is rising among adults to improve sleep quality (Costello et al., 2014; Xie et al., 2017). Therefore, the deceptive suggestion used in the current experiment may have been very believable and thus effective even in the present sample whose sleep quality was already relatively high before the intervention (Hinz et al., 2017). In contrast, not all participants seemed to have been convinced by the OLP rationale. This can be inferred from the dropout rate immediately after the random group assignment, which was significantly higher in the OLP group (10%) compared with the control group (0%). Future research should investigate factors that potentially affect the attitude towards OLP interventions and motivation to take an OLP (Forkmann et al., 2023).

Habitual sleep efficiency, which is based on the ratio of time spent in bed and hours slept (Buysse et al., 1989), even decreased slightly in the OLP group (but not in the other groups). Furthermore, there was no significant improvement in sleep duration in any of the groups. These findings suggest that the OLP treatment did not have the intended effect of improving sleep duration and efficiency. The PSQI responses of participants even pointed in the opposite direction of the OLP suggestion, with a reduction in sleep efficiency. In OLP interventions, the expectancy or hope that a placebo treatment can improve symptoms must overcome the knowledge that there is no active ingredient in the treatment (Ballou et al., 2017; Kaptchuk, 2018). This discrepancy may cause cognitive dissonance, which may lead, at least in the domain of sleep quality, to unintended effects in some people.

No placebo effects were found for the other components of the PSQI, including subjective sleep quality. Although one other study observed similar effects as in the present investigation (Haas et al., 2022), other studies suggest that OLP interventions may be a promising tool to improve sleep quality (El Brihi et al., 2019; Rogev & Pillar, 2013). Thus, the evidence is mixed. As stated previously, little is known about why OLP interventions sometimes do not produce the desired effects. Variables such as the interaction between the OLP provider and recipient may influence the efficacy of an OLP (Blease et al., 2020). In the present study, the placebo provider and recipient interacted only in an initial session but not during the 1-week intervention. Similarly, Haas et al. (2022) limited the interaction between the placebo provider and recipient by using pre-recorded videos for instruction. In contrast, El Brihi et al. (2019) did have contact with participants during the treatment through reminder emails sent to the participants. Moreover, the authors of that study chose to create a brand name for the OLP (“Plaxibax”); previous research has indicated that branding can increase the effects of deceptive placebos (Faasse et al., 2016). Thus, future research could investigate further the conditions under which OLP effects are fostered.

Participants did not report decreased appetite for high-calorie food, nor did they display decreased attention to food cues as a result of this intervention. While prior research has suggested that lower sleep quality is associated with increased food cravings (Lv et al., 2018), the relatively high sleep quality of our participants (Hinz et al., 2017) might have prevented sleep-problem-associated cravings. It is, however, possible that food cravings might be able to be reduced in samples with severe insomnia or lower sleep quality, which subsequently should reduce appetite for high-calorie foods. Moreover, future studies should explore if certain components of sleep quality are more related to appetite and cravings than others.

The present study has several limitations. First, participants were drawn from a healthy convenience sample. Larger intervention effects may be observed in clinical samples with insomnia. Second, participants of the present study may have been sceptical whether an OLP could further improve their already high sleep quality. Third, subjective components of sleep quality were assessed via the PSQI; for the assessment of take-home placebos, future studies could use sleep trackers to measure physiological correlates of sleep quality. Fourth, additional subjective measures that are not covered by the PSQI like satisfaction with sleep quality (van de Langenberg et al., 2022) should be considered.

In conclusion, the deceptive placebo in the current study decreased sleep latency and thus helped fall asleep faster even in the current sample without severe sleep problems. The OLP was found to not have any desirable effects on sleep quality.

AUTHOR CONTRIBUTIONS

Jonas Potthoff: Conceptualization; data curation; formal analysis; methodology; project administration; validation; visualization; writing – original draft. Anne Schienle: Conceptualization; project administration; resources; supervision; validation; writing – original draft; writing – review and editing.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

Endnotes

¹ ANOVAs did not suggest group differences in age (p = 0.32), gender (p = 0.53), PSQI sum score before intervention (p = 0.72) and BMI (p = 0.72).

² Twenty image pairs (10 high-calorie food with non-food; 10 low-calorie food with non-food): images were matched in colour, complexity, contrast and luminance. For further information and a list of images, see: https://osf.io/9jusb.

Open Research

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in the open science framework at https://osf.io/uvhac/.

Supporting Information

REFERENCES

Annoni, M. (2018). The ethics of placebo effects in clinical practice and research. International Review of Neurobiology, 139, 463–484. https://doi.org/10.1016/bs.irn.2018.07.031
10.1016/bs.irn.2018.07.031
PubMed Web of Science® Google Scholar
Ballou, S., Kaptchuk, T. J., Hirsch, W., Nee, J., Iturrino, J., Hall, K. T., Kelley, J. M., Cheng, V., Kirsch, I., Jacobson, E., Conboy, L., Lembo, A., & Davis, R. B. (2017). Open-label versus double-blind placebo treatment in irritable bowel syndrome: Study protocol for a randomized controlled trial. Trials, 18(1), 234. https://doi.org/10.1186/s13063-017-1964-x
10.1186/s13063-017-1964-x
PubMed Web of Science® Google Scholar
Blease, C. R., Bernstein, M. H., & Locher, C. (2020). Open-label placebo clinical trials: Is it the rationale, the interaction or the pill? BMJ Evidence-Based Medicine, 25(5), 159–165. https://doi.org/10.1136/bmjebm-2019-111209
10.1136/bmjebm-2019-111209
PubMed Google Scholar
Blechert, J., Lender, A., Polk, S., Busch, N. A., & Ohla, K. (2019). Food-Pics_Extended-an image database for experimental research on eating and appetite: Additional images, normative ratings and an updated review. Frontiers in Psychology, 10, 307. https://doi.org/10.3389/fpsyg.2019.00307
10.3389/fpsyg.2019.00307
PubMed Web of Science® Google Scholar
Blechert, J., Meule, A., Busch, N. A., & Ohla, K. (2014). Food-pics: An image database for experimental research on eating and appetite. Frontiers in Psychology, 5, 617. https://doi.org/10.3389/fpsyg.2014.00617
10.3389/fpsyg.2014.00617
PubMed Web of Science® Google Scholar
Blume, C., Hauser, T., Gruber, W. R., Heib, D. P., Winkler, T., & Schabus, M. (2020). “How does Austria sleep?” self-reported sleep habits and complaints in an online survey. Sleep & Breathing = Schlaf and Atmung, 24(2), 735–741. https://doi.org/10.1007/s11325-019-01982-5
10.1007/s11325-019-01982-5
PubMed Web of Science® Google Scholar
Brondel, L., Romer, M. A., Nougues, P. M., Touyarou, P., & Davenne, D. (2010). Acute partial sleep deprivation increases food intake in healthy men. The American Journal of Clinical Nutrition, 91(6), 1550–1559. https://doi.org/10.3945/ajcn.2009.28523
10.3945/ajcn.2009.28523
CAS PubMed Web of Science® Google Scholar
Broussard, J. L., & Klein, S. (2022). Insufficient sleep and obesity: Cause or consequence. Obesity (Silver Spring, Md.), 30(10), 1914–1916. https://doi.org/10.1002/oby.23539
10.1002/oby.23539
PubMed Web of Science® Google Scholar
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193–213. https://doi.org/10.1016/0165-1781(89)90047-4
10.1016/0165-1781(89)90047-4
CAS PubMed Web of Science® Google Scholar
Costello, R. B., Lentino, C. V., Boyd, C. C., O'Connell, M. L., Crawford, C. C., Sprengel, M. L., & Deuster, P. A. (2014). The effectiveness of melatonin for promoting healthy sleep: A rapid evidence assessment of the literature. Nutrition Journal, 13, 106. https://doi.org/10.1186/1475-2891-13-106
10.1186/1475-2891-13-106
PubMed Web of Science® Google Scholar
Disley, N., Kola-Palmer, S., & Retzler, C. (2021). A comparison of open-label and deceptive placebo analgesia in a healthy sample. Journal of Psychosomatic Research, 140, 110298. https://doi.org/10.1016/j.jpsychores.2020.110298
10.1016/j.jpsychores.2020.110298
PubMed Web of Science® Google Scholar
El Brihi, J., Horne, R., & Faasse, K. (2019). Prescribing placebos: An experimental examination of the role of dose, expectancies, and adherence in open-label placebo effects. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine, 53(1), 16–28. https://doi.org/10.1093/abm/kay011
10.1093/abm/kay011
PubMed Web of Science® Google Scholar
Erland, L. A. E., & Saxena, P. K. (2017). Melatonin natural health products and supplements: Presence of serotonin and significant variability of melatonin content. Journal of Clinical Sleep Medicine: JCSM: Official Publication of the American Academy of Sleep Medicine, 13(2), 275–281. https://doi.org/10.5664/jcsm.6462
10.5664/jcsm.6462
PubMed Web of Science® Google Scholar
Faasse, K., Martin, L. R., Grey, A., Gamble, G., & Petrie, K. J. (2016). Impact of brand or generic labeling on medication effectiveness and side effects. Health Psychology: Official Journal of the Division of Health Psychology, American Psychological Association, 35(2), 187–190. https://doi.org/10.1037/hea0000282
10.1037/hea0000282
PubMed Web of Science® Google Scholar
Forkmann, K., Müßgens, D., Hashim, A., & Bingel, U. (2023). Worth a try—a survey on the general acceptance of open-label placebos. Journal of Psychosomatic Research, 165, 111096. https://doi.org/10.1016/j.jpsychores.2022.111096
10.1016/j.jpsychores.2022.111096
PubMed Web of Science® Google Scholar
Gangwisch, J. E., Malaspina, D., Boden-Albala, B., & Heymsfield, S. B. (2005). Inadequate sleep as a risk factor for obesity: Analyses of the NHANES I. Sleep, 28(10), 1289–1296. https://doi.org/10.1093/sleep/28.10.1289
10.1093/sleep/28.10.1289
PubMed Web of Science® Google Scholar
Guevarra, D. A., Moser, J. S., Wager, T. D., & Kross, E. (2020). Placebos without deception reduce self-report and neural measures of emotional distress. Nature Communications, 11(1), 3785. https://doi.org/10.1038/s41467-020-17654-y
10.1038/s41467-020-17654-y
CAS PubMed Web of Science® Google Scholar
Haas, J. W., Rief, W., & Doering, B. K. (2021). Open-label placebo treatment: Outcome expectations and general acceptance in the lay population. International Journal of Behavioral Medicine, 28(4), 444–454. https://doi.org/10.1007/s12529-020-09933-1
10.1007/s12529-020-09933-1
PubMed Web of Science® Google Scholar
Haas, J. W., Winkler, A., Rheker, J., Doering, B. K., & Rief, W. (2022). No open-label placebo effect in insomnia? Lessons learned from an experimental trial. Journal of Psychosomatic Research, 158, 110923. https://doi.org/10.1016/j.jpsychores.2022.110923
10.1016/j.jpsychores.2022.110923
PubMed Web of Science® Google Scholar
Hasler, G., Buysse, D. J., Klaghofer, R., Gamma, A., Ajdacic, V., Eich, D., Rössler, W., & Angst, J. (2004). The association between short sleep duration and obesity in young adults: A 13-year prospective study. Sleep, 27(4), 661–666. https://doi.org/10.1093/sleep/27.4.661
10.1093/sleep/27.4.661
PubMed Web of Science® Google Scholar
Hinz, A., Glaesmer, H., Brähler, E., Löffler, M., Engel, C., Enzenbach, C., Hegerl, U., & Sander, C. (2017). Sleep quality in the general population: Psychometric properties of the Pittsburgh sleep quality index, derived from a German community sample of 9284 people. Sleep Medicine, 30, 57–63. https://doi.org/10.1016/j.sleep.2016.03.008
10.1016/j.sleep.2016.03.008
PubMed Web of Science® Google Scholar
Hirshkowitz, M., Whiton, K., Albert, S. M., Alessi, C., Bruni, O., DonCarlos, L., Hazen, N., Herman, J., Adams Hillard, P. J., Katz, E. S., Kheirandish-Gozal, L., Neubauer, D. N., O'Donnell, A. E., Ohayon, M., Peever, J., Rawding, R., Sachdeva, R. C., Setters, B., Vitiello, M. V., & Ware, J. C. (2015). National Sleep Foundation's updated sleep duration recommendations: Final report. Sleep Health, 1(4), 233–243. https://doi.org/10.1016/j.sleh.2015.10.004
10.1016/j.sleh.2015.10.004
PubMed Web of Science® Google Scholar
Hoffmann, V., Lanz, M., Mackert, J., Müller, T., Tschöp, M., & Meissner, K. (2018). Effects of placebo interventions on subjective and objective markers of appetite-a randomized controlled trial. Frontiers in Psychiatry, 9, 706. https://doi.org/10.3389/fpsyt.2018.00706
10.3389/fpsyt.2018.00706
PubMed Web of Science® Google Scholar
Hor, H., & Tafti, M. (2009). Physiology. How much sleep do we need? Science (New York, N.Y.), 325(5942), 825–826. https://doi.org/10.1126/science.1178713
10.1126/science.1178713
PubMed Web of Science® Google Scholar
Itani, O., Jike, M., Watanabe, N., & Kaneita, Y. (2017). Short sleep duration and health outcomes: A systematic review, meta-analysis, and meta-regression. Sleep Medicine, 32, 246–256. https://doi.org/10.1016/j.sleep.2016.08.006
10.1016/j.sleep.2016.08.006
PubMed Web of Science® Google Scholar
Jiang, B., He, D., & Gao, Z. (2019). Efficacy and placebo response of multimodal treatments for primary insomnia: A network meta-analysis. Clinical Neuropharmacology, 42(6), 197–202. https://doi.org/10.1097/WNF.0000000000000369
10.1097/WNF.0000000000000369
CAS PubMed Web of Science® Google Scholar
Kakoschke, N., Kemps, E., & Tiggemann, M. (2015). Combined effects of cognitive bias for food cues and poor inhibitory control on unhealthy food intake. Appetite, 87(3), 358–364. https://doi.org/10.1016/j.appet.2015.01.004
10.1016/j.appet.2015.01.004
PubMed Web of Science® Google Scholar
Kaptchuk, T. J. (2018). Open-label placebo: Reflections on a research agenda. Perspectives in Biology and Medicine, 61(3), 311–334. https://doi.org/10.1353/pbm.2018.0045
10.1353/pbm.2018.0045
PubMed Web of Science® Google Scholar
Kaptchuk, T. J., Friedlander, E., Kelley, J. M., Sanchez, M. N., Kokkotou, E., Singer, J. P., Kowalczykowski, M., Miller, F. G., Kirsch, I., & Lembo, A. J. (2010). Placebos without deception: A randomized controlled trial in irritable bowel syndrome. PLoS One, 5(12), e15591. https://doi.org/10.1371/journal.pone.0015591
10.1371/journal.pone.0015591
CAS PubMed Web of Science® Google Scholar
Lv, W., Finlayson, G., & Dando, R. (2018). Sleep, food cravings and taste. Appetite, 125, 210–216. https://doi.org/10.1016/j.appet.2018.02.013
10.1016/j.appet.2018.02.013
PubMed Web of Science® Google Scholar
Potthoff, J., Jurinec, N., & Schienle, A. (2019). Placebo effects on visual food Cue reactivity: An eye-tracking investigation. Frontiers in Psychiatry, 10, 525. https://doi.org/10.3389/fpsyt.2019.00525
10.3389/fpsyt.2019.00525
PubMed Web of Science® Google Scholar
Potthoff, J., & Schienle, A. (2020). Time-course analysis of food cue processing: An eye-tracking investigation on context effects. Food Quality and Preference, 84(4), 103936. https://doi.org/10.1016/j.foodqual.2020.103936
10.1016/j.foodqual.2020.103936
Web of Science® Google Scholar
Rogev, E., & Pillar, G. (2013). Placebo for a single night improves sleep in patients with objective insomnia. The Israel Medical Association Journal: IMAJ, 15(8), 434–438.
PubMed Web of Science® Google Scholar
Scarpelli, S., Zagaria, A., Ratti, P.-L., Albano, A., Fazio, V., Musetti, A., Varallo, G., Castelnuovo, G., Plazzi, G., & Franceschini, C. (2022). Subjective sleep alterations in healthy subjects worldwide during COVID-19 pandemic: A systematic review, meta-analysis and meta-regression. Sleep Medicine, 100, 89–102. https://doi.org/10.1016/j.sleep.2022.07.012
10.1016/j.sleep.2022.07.012
PubMed Web of Science® Google Scholar
Schienle, A., & Jurinec, N. (2022). Open-label placebos as adjunctive therapy for patients with depression. Contemporary Clinical Trials Communications, 28, 100948. https://doi.org/10.1016/j.conctc.2022.100948
10.1016/j.conctc.2022.100948
PubMed Web of Science® Google Scholar
Schienle, A., & Unger, I. (2021). Open-label placebo treatment to improve relaxation training effects in healthy psychology students: A randomized controlled trial. Scientific Reports, 11(1), 13073. https://doi.org/10.1038/s41598-021-92579-0
10.1038/s41598-021-92579-0
CAS PubMed Web of Science® Google Scholar
Schienle, A., Unger, I., & Schwab, D. (2022). Changes in neural processing and evaluation of negative facial expressions after administration of an open-label placebo. Scientific Reports, 12(1), 6577. https://doi.org/10.1038/s41598-022-10567-4
10.1038/s41598-022-10567-4
PubMed Web of Science® Google Scholar
van Alebeek, H., Kahveci, S., Rinck, M., & Blechert, J. (2023). Touchscreen-based approach-avoidance responses to appetitive and threatening stimuli. Journal of Behavior Therapy and Experimental Psychiatry, 78, 101806. https://doi.org/10.1016/j.jbtep.2022.101806
10.1016/j.jbtep.2022.101806
PubMed Web of Science® Google Scholar
van de Langenberg, S. C. N., Kocevska, D., & Luik, A. I. (2022). The multidimensionality of sleep in population-based samples: A narrative review. Journal of Sleep Research, 31(4), e13608. https://doi.org/10.1111/jsr.13608
10.1111/jsr.13608
PubMed Web of Science® Google Scholar
von Wernsdorff, M., Loef, M., Tuschen-Caffier, B., & Schmidt, S. (2021). Effects of open-label placebos in clinical trials: A systematic review and meta-analysis. Scientific Reports, 11(1), 3855. https://doi.org/10.1038/s41598-021-83148-6
10.1038/s41598-021-83148-6
PubMed Web of Science® Google Scholar
Xie, Z., Chen, F., Li, W. A., Geng, X., Li, C., Meng, X., Feng, Y., Liu, W., & Yu, F. (2017). A review of sleep disorders and melatonin. Neurological Research, 39(6), 559–565. https://doi.org/10.1080/01616412.2017.1315864
10.1080/01616412.2017.1315864
CAS PubMed Web of Science® Google Scholar
Yeung, V., Sharpe, L., Glozier, N., Hackett, M. L., & Colagiuri, B. (2018). A systematic review and meta-analysis of placebo versus no treatment for insomnia symptoms. Sleep Medicine Reviews, 38, 17–27. https://doi.org/10.1016/j.smrv.2017.03.006
10.1016/j.smrv.2017.03.006
PubMed Web of Science® Google Scholar

Volume33, Issue2

April 2024

e13947

Effects of (non)deceptive placebos on reported sleep quality and food cue reactivity

Summary

1 INTRODUCTION