1.1 Context

Currently standing as one of the fastest growing sectors in the technology industry [1], 37% of UK individuals surveyed currently own and use a wearable activity tracker (WAT) [2], with this most popular in 35–44 year olds [3]. Worldwide, there are an estimated 454 million smartwatch users – a subtype of WATs – with rates increasing yearly [4].Wearable activity trackers are portable electronic monitoring devices which primarily allow individuals to self-track their daily physical activity and health status [5]. Self-tracking often involves continuous monitoring of in-depth bodily information, with the idea of users gaining control to optimise their health behaviours, resulting in the concept of a quantified self [6]. Henriksen et al. [7] identified 423 devices with Fitbit, Garmin, Misfit, Apple and Polar as leading brands. These devices measure and feedback data on various outcomes including step count, distance moved, heart rate, level of activity, and sleep patterns [8], with features falling under the functional domains of monitoring and nudging [9]. WATs typically embed gamification into their user experience, often featuring badges, streaks, and leaderboards to promote both physical activity and WAT engagement [10]. Some WATs include smartphone-based features, coined smartwatches, whereas others allow self-tracking without messaging services.

1.2 WATs as behaviour change interventions

While these devices were first perceived as lifestyle accessories, wearable activity trackers are now viewed as a legitimate tool for health promotion and ill-health prevention by healthcare professionals [9,11]. The majority of quantitative research considers WATs through the lens of interventions, examining their effects on objective measures such as physical activity [12]. In their umbrella review of 39 papers across 163,992 participants, Ferguson et al. [12] examined the impact of wearing a WAT (alongside no other health intervention) on physical activity and health outcomes in all age ranges and both clinical and non-clinical groups. Here, the naturalistic use of WATs was significantly associated with improved physical activity, body composition, and fitness. Across these reviews, using these devices resulted in an additional 1,800 steps, and 40 minutes of walking per day, resulting in participants’ body weight reduced by approximately 1 kg. Notably, quantitative data around behavioural outcomes tends to be mixed with overall results often averaging out as neutral responses [13].

When examining mechanisms behind this health promotion behaviour change, motivation has been discussed heavily in literature [14–18]. Jung and Kang [19] suggested these WATs specifically increase intrinsic motivation of users, highlighting the application of the self-determination theory (SDT) within this context. Within SDT, fitness data tracking was positively related to user autonomy, and in turn, feelings of enjoyment [19]. Organismic Integration Theory, a sub-theory within SDT focussing on the extrinsic motivation types [20] has been used to explain how WATs lead to physical activity promotion in users [21]. Specifically, James, Wallace and Deane [21] reported different preferences in WAT features between intrinsically and extrinsically motivated users; intrinsically motivated preferred social features, whereas extrinsically motivated preferred exercise control features (e.g., exercise prompts, goal management). Although, the COM-B model [22] was also identified as a plausible explanation to WAT use [23,24], alongside 28 other theoretical frameworks, suggesting current lack of clarity around this behaviour [24]. This lack of clarity may exist given the plethora of individuals’ relationships with health and reasons for engaging in WAT use, which in turn may lead to different behaviour change experiences [21].

1.3 The emotional impact of WATs

Qualitative studies in this area have gained traction aiming to understand the multifaceted concept of digitalised health. In their meta-synthesis of 18 studies Sandham et al. [25] concluded that receiving data on health improvement since using a WAT increased user motivation to continue this positive trajectory. Nelson et al. [26] reported that motivation levels peaked three-months following device acquisition due to novelty being replaced with device familiarity, whereas Burford, Golaszewski and Bartholomew [27] concluded that motivation was increased long-term, driven by continuous feelings of accountability and feelings of intrinsic motivation from WAT feedback. Although, in some cases participants appeared to rely on this information for validation, resulting in device embodiment [26]. Nelson et al. [26] compared participants’ WAT-body integration similar to a prosthetic limb, highlighting how natural using these devices became for users, and how dependent some were on them. Similarly, Köhler et al. [9] shared that participants felt this was no longer a removable accessory; suggesting device embodiment and dependence.

However, contrasting user experiences were common amongst these qualitative studies. Burford, Golaszewki and Bartholomew [27] highlighted that feedback led to distress in some users. Specifically, one user reported that this feedback ‘made or broke their day.’ Another participant took their smartwatch off on the weekends when step count was lower to avoid feedback, reporting that they ‘can’t handle it’; highlighting the perceived importance of this feedback. Device frustration was also experienced by users, specifically over receiving nudges to move during inflexible periods [17]. In their systematic review of females’ experiences with WATs, Del Busso et al. [18] highlighted the pressure experienced by some individuals to be active and continuously improving. While some studies in this review reported overwhelmingly positive findings, in 3 of the 13 studies reviewed, women reported that perceived stress and pressure from WATs resulted in device avoidance [28–30].

Individual internal conflict around WAT use has appeared in previous literature, although not directly examined. For example, in Toner, Allen-Collinson and Jones’ work, a participant noted the ‘mental trade off’ they perform when receiving a prompt to move (Stan, 35) [17]; navigating conflict around pros and cons of movement. This same participant reported their WAT has led to them doubting their own ability to judge the quality of their sleep, with feedback leading to data mismatches, and in turn, internal conflict.

Perceived fairness, accuracy, and value of feedback determined user reactions to this information, with some users facing what has been coined a data mismatch or data-expectation gap [25,31,32]. This occurs when a mismatch between device detection and expected output has occurred, leading to feelings of frustration and mistrust when experienced [31]. Frustration over forgetting to track exercise or a devices battery running out was reported; further emphasising the importance users placed in obtaining their data, and thus, the conflict faced if a data mismatch was experienced.

1.4 The current study

This study is the first paper directly examining internal conflict of individuals using wearable activity trackers. Internal conflict refers to disagreement between oneself, evoking information processing of two or more conflicting viewpoints such as something being both beneficial and harmful [33]. While internal conflict can deplete time, energy, and rest, is it seen as an expected aspect of everyday life [34].

Building upon the conflict mixed emotional feelings reported within Toner, Allen-Collinson and Jones [17], this study poses the research question; how do individuals experience and navigate internal conflict when using smartwatches? With WATs being integrated into healthcare settings to encourage behaviour change [32,35,36] and initial guidance on WAT usage emerging [37], this work holds important implications.

To gain this insight, the following objectives were proposed;

1. Explore the emotional experiences of smartwatch users in relation to activity tracking, performance feedback and daily monitoring.
2. Examine the internal conflict experienced by smartwatch users in regard to receiving this health feedback.
3. Understand the emotional and behavioural impact of this conflict.

2.1 Ethical statement

Ethical consideration such as anonymity, potential relationships between participants and researcher, and sensitive discussion topics were considered. Ethical approval was gained from the University of Salford ethics board in June 2025; reference 6343. Written informed consent was obtained from all participants prior to interviews being conducted.

2.2 Study design

The current study holds a qualitative, exploratory design using semi-structured interviews to examine this topic. A reflextive, inductive thematic analysis approach was adopted [38]. This allowed for an in-depth understanding into this complex topic of psychological experiences to data provision, building on our current knowledge on wearable health trackers.

2.3 Participants (selection and recruitment)

Participants were aged 18 + individuals who reported at least three-months of consistent wear of an activity tracker. Consistent use was defined as wearing the device almost all of the time, allowing for charging periods. Three months was selected as a minimum duration to ensure that participants had established routines and familiarity with device feedback, allowing reflection on both novelty and emotional impact. While participants were required to have used a WAT for a minimum of three months, however, interviews were not conducted at a standardised time point of use.

Although smartwatches are the most popular type of wearable activity trackers (defined by their integration of messaging and calling features) [39], all WATs were eligible in the current study. Examples of Garmin, Coros, Fitbit, Apple, Samsung and Google Pixel watches were listed, alongside Whoop bands and Oura rings. No restrictions were placed upon the WAT brand, the amount of physical activity completed, or other demographics to promote a heterogenous sample. Given the lack of research in this area, the only exclusion criteria placed were WAT use for less than three months or participants not being comfortable to discuss their use.

The study was advertised in multiple ways. Physical posters were displayed around a northern university where the research team were based. Digital posters were displayed via platforms relating to digital health – specifically via the university portal, LinkedIn and X.

Recruitment continued until construct saturation was reached, with the final sample consisting of 11 participants.. Saturation was determined by no new concepts being introduced in three interviews following theme formation.

2.4 Data collection

After providing informed consent for the current study, interviews were arranged. All interviews were conducted by GH, either in-person (n = 4) or online via Microsoft Teams (n = 7). Interviews were conducted between July and September 2025. Interviews were semi-structured, with prompts used to encourage conversation, and their duration ranged from 19 to 82 minutes (M = 48). Questions first asked about demographic data and an overview of WAT use. Discussion then focussed on the impact of smartwatch data on behaviour and emotions, prompting for any conflicting experiences. Next, participants were asked about their perceived accuracy and importance of smartwatch data, prompting for any experienced conflict. Following interview questions, participants received a verbal debrief, reminded of researcher contact details and their right to withdraw. All interviews were recorded via Microsoft Teams and automatically saved to the primary researchers’ password protected OneDrive account.

2.5 Data analysis

Interviews were transcribed automatically through Microsoft Teams and then quality checked byGH.. Braun and Clarke’s [38] six stages of thematic analysis were used to analyse data. Specifically, GH and SJ independently familiarised themselves with eight conducted transcripts and coded this data line-by-line to prevent biases. Coding was completed using Microsoft Word to annotate text. A reflexive, inductive approach was adopted ensure all content was encapsulated from the dataset. Coding was iterative, with the research team revisiting transcripts multiple times as understanding developed. GH and SJ then reviewed their codes together and collaboratively defined and named themes.AG reviewed interview transcripts and the table of quotes to ensure proposed themes well represented conversation. A total of three drafts were proposed before the current theme organisation was agreed upon by the team. Following this agreement, three final interviews were conducted to examine construct saturation. Saturation was determined by no new concepts introduced in these three interviews. Again, these three transcripts were coded independently by GH and SJ, before group agreement that saturation had been reached. All identified quotes were written into a table (see S1 Table), with those most relevant discussed in the main body of this paper. A COREQ checklist was used to ensure transparent reporting of this study [40].

2.6 Reflexivity and research team

The positionality of the research team was considered throughout this project, aiming for any personal biases around this topic to be minimised. The team consisted of three academics across multiple disciplines (psychology and sport science) to ensure wide perspectives of theoretical expertise. GH and AG used a WAT consistently which could have effected their interpretation of data on user experiences, whereas SJ had never owned or used a WAT. While researchers made a conscious effort to code only what was explicitly mentioned in transcripts, having both WAT users and non-users in the team allowed for a balanced perspective. This diversity of experiences promoted active critical reflection around data interpretation and theme formation, ensuring that themes were grounded from the data versus researcher experiences.

No qualities about the research team, other than the university affiliation of the research project, were disclosed to participants to minimise social desirability bias in responses. Although, the study was advertised across the university meaning some may have been aware of a professional background (n = 3 undergraduate students).

3.1 Participant characteristics

The current sample consisted of eleven participants (eight female, three male)with a mean age of 30.73 years (SD = 11.65), and included a range of ethnicities with White-British most common. Participants’ current WATs spread across five brands, with Garmin the most often used. See Table 1 for participant characteristic breakdown. Identifiable information was removed from any discussed quotes and pseudonyms were used in write up.

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Table 1. Participant characteristics.

https://doi.org/10.1371/journal.pdig.0001136.t001

3.2 Thematic analysis

Four themes were identified to reflect participants’ experiences of internal conflict in WAT use; Who knows best?, Who’s in charge?, Who am I without it? and What’s happening to me?. Within these were nine sub-themes (see Fig 1).

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Fig 1. Thematic map.

https://doi.org/10.1371/journal.pdig.0001136.g001

4.1 Key findings and existing literature

The current study built on the concept of the quantified self [6] which arose in WAT users, and answered James et al.’s [21] call to explore data mismatches. Exploring this internal conflict, four themes and nine sub-themes were identified; Who knows best?, Who’s in charge?, Who am I without it? And What’s happening to me?. Data depicted that intense relationships had formed between the WAT and user, in which the user valued WAT feedback highly and used it to make decisions. Given the frequency of use and trust placed in devices, some users expressed a loss of autonomy, bodily intuition and fear around life without their WAT.

Mechanisms of behaviour were examined within the sub-theme What’s happening to me?. WATs increased motivation to lead an active lifestyle in some participants, strengthening the conclusions of existing literature [14–18,25]. The current findings depart from previous literature by examining the user experience in depth. Uncertainty was expressed around how a WAT led to behaviour change, specifically around the type of motivation experienced. Positive WAT feedback motivated users to continue their health-related behaviour; strengthening the findings of Burford, Golaszewski and Bartholomew [27] who reported that feeling validated via positive WAT feedback increased intrinsic motivation. This aspect of our findings supports the COM-B model, with feedback highlighting improvement likely to increase reflective motivation, and in turn, fuel the target behaviour [22]. Although, participants also detailed their WAT increased activity via feeling pressured which may not directly fit this model of behaviour. One could reframe feeling pressure to receive positive WAT feedback into being motivated to avoid negative feedback to map findings onto the COM-B model. However, this does not fully capture the authority these devices had over user’s behaviour and the drive participants expressed over avoiding negative feedback rather than performing the behaviours such as sleep and physical activity for their benefits. This drive to avoid negative feedback led to participants hacking their feedback by removing devices at times, with these users reporting satisfaction over this despite not meeting their personal goals. These findings may better align with the stress appraisal theory which distinguishes between challenge appraisals – when users see opportunity for positive growth – versus threat appraisals – where asks are deemed as potentially harmful [41]. In this context, seeing health progress from their WAT’s data may highlight opportunity for further growth, in turn leading to further motivation and positive health behaviour, whereas seeing a decline in health may bring threat, resulting in feelings of pressure and overwhelm.

These experiences highlighted a WAT consisted of conflicting intervention functions simultaneously; incentivisation was provided if users gained positive feedback, but coercion was experienced with many users performing behaviours simply to avoid being ‘told off’. These findings are notable, supporting the conclusions of an umbrella review Ferguson et al. [12] that WATs increase physical activity, whilst stressing the importance of examining the mechanisms behind this behaviour change. All participants in the current study were full-time WAT users, and none had intentionally paused their device use. The theme perceived success comes with compromise showed that users felt a negative emotional impact was justified for improved health. However, current WAT users were only recruited in this study. Valuable future insight could be gained from those who no longer use a WAT, particularly given the reporting that stress from WATs can lead to device avoidance [28–30].

Participants expressed difficult understanding their behaviour given device embodiment had occurred; strengthening this concept proposed by Nelson et al. [26]. Nelson et al. [26] reported device use becoming natural behaviour and leading to dependence; findings matched in our study. Similarly, Köhler et al. [9] reported that participants no longer viewed WATs as removable accessories. This was encapsulated within the theme Who am I without it?, with sub-themes of device embodiment and fear over device removal. These findings highlight the clear need for education around problematic use of WATs in order to reduce the risk of digital dependence and its associated negative consequences.

Device embodiment perhaps explained why mechanisms of behaviour were difficult for users to unpick, suggesting a blurring of intrinsic and extrinsic motivation. Furthermore, WATs may target different forms of motivation simultaneously. In their study on current wearable fitness trackers, Nuss and Li [42] found that users scored highly on both introjected (avoiding punishment, feelings of guilt) and integrated (congruence with one’s values, feelings of volition) forms of motivation. The present study corroborates these findings, as some participants reflected on the pressure to meet the goals outlined by their WAT, but other perceived such goals to align with internal goals. Furthermore, a prominent finding in the present study was how initial motivations behind the purchase of a WAT was that it aligned with participants’ pre-existing exercise habits or values around the importance of exercise. However, with time, this more autonomous form of motivation was influenced by feelings of pressure to meet goals. This was highlighted by Nuss and Li [42] amongst former users, who note that WATs can result in decrease in autonomous motivation due to external rewards and feedback, engaging with the WAT out of pressures to complete goals rather than personal choice. Similarly, Steel [43] found that WAT users also transitioned from more autonomous forms of motivation to introjected. Previous research identified the importance of WATs in quantifying participants physical activity [42], resulting in decreased motivation to exercise when tracking is not available [44]. Current findings support this, with participants reporting physical activity as ‘not counting’ if it has not been recorded; a concept labelled as the dependency effect [27].

However, in contrast to previous research that identifies the ways WATs support autonomy [19,39], many participants in the presented study reflected on how their needs for autonomy were blocked by their WAT. Jung and Kang [19] posit that a user’s control over the WAT and how data is used supports feelings of autonomy. Yet, whilst WATs have been discussed in their ability to provide users with choice over goals or activity type, the present study indicates that WATs are perceived to govern participants’ behaviour, to the point where a loss of their own autonomy was reported.

Participants often trusted device data over bodily intuition, so much so they questioned how they’d know anything without their WAT data. This highlighted a major consequence of the quantified self, with users becoming reliant on these devices to make behavioural decisions; suggesting that intuitive exercise was not practiced in these users. Additionally, some WAT indicators are not scientifically validated, such as stress, sleep and training readiness scores, meaning bodily feeling may be disregarded for a metric which lacks objectivity and rigour. Given those with greater body appreciation tend to exercise intuitively [45], this may suggest a future intervention route to reduce the loss of body intuition. Furthermore, Ramsey [45] reported those engaging in the highest levels of exercise had low body appreciation, with a focus on weight and appearance, suggesting a fixation on health, and in this case WAT data, may be linked to low body image. While this needs further exploration, the current study did identify that some WAT users had an unhealthy relationship around exercise.

Given the reported trust participants placed in these devices and loss of bodily intuition, conflict was experienced when data mismatches arose. Frustration or upset was experienced as users were forced to acknowledge the trust placed in these devices, supporting user reactions within Dritsa and Houben [31]. Typically, a WAT’s judgement was adopted given their perceived expertise. For example, users reported feeling well rested until they viewed a low sleep score, which left them feeling tired. The self-fulfilling prophecy appears relevant here [45,46], suggesting users changed how they felt, and in turn how they behaved, depending on the data they received from their WAT. No research combining this theory with WAT use exists to our knowledge, highlighting an area for future research.

4.2 Study strengths, limitations, and implications

As with all research, the current study had its limitations. Despite containing incredibly rich data, the current study had a small participant size gained via convenience sample. Data saturation was reached during interviews meaning we would expect no themes to be introduced if further participants were recruited. However, a different sampling method may have gained (less keen people coming forwards). The eligibility criteria of the current study was current, full-time WAT users. This sample allowed for in-depth insight to be gained around the novel topic of internal conflict in WAT use, standing as the first study on this to our knowledge. Although, individuals who no longer use a WAT may provide a useful perspective in future research, particularly given that device cessation may have occurred due to this conflict arising.

Brands were varied in the current study, with four worn by participants (Garmin, Apple, Fitbit and Coros). This may reflect the popularity of wearables in the current UK climate, although, a wider range of WAT brands may have been beneficial for diverse experiences. Similarly, device heterogeneity occurred with all users wearing watch-based WATs. WATs in the form of rings or wrist straps without a display screen were not owned by these participants. Given embodiment and dependence occurred from repeated on-screen notifications, user experiences around conflict may differ in these device types and should be considered in future literature. Finally, this cross-sectional study examined experience at one-time point, requiring users to reflect on complex experience in one sitting. Given emotions are ever-changing and conflict may arise and be resolved in very short durations, research examining conflict at repeated time points is recommended. For example, Ecological Momentary Assessment (EMA) has been used to gain health behaviour understanding and may allow for greater learnings on conflict experience and resolution over time [47,48].

The current study holds many valuable implications. A user profile emerged from data, with WAT users tending to be competitive, driven by numbers, and already focussed on health improvement. Given their perceived importance of a WAT in their health journey, guidance would be beneficial alongside the purchasing of a WAT around what constitutes as healthy use. For example, information around device accuracy and recommendations to consider provided data from a critical lens may benefit these users. WATs are beginning to be integrated into NHS healthcare settings as health promotion tools. The current study questions the introduction of these tools, with some WAT users facing conflict and negative emotion around device use. While physical effects appear to stand, the emotional toll identified in this study can question whether this is an ethical decision. WATs have been shown as effective tools for increasing activity levels and in turn weight loss [12], and therefore may be an excellent tool for some individuals, a patient’s personality and attitudes around health should be used to form judgement on whether WAT use will be emotionally beneficial. This recommendation is crucial given the long-term impact WATs may have on their users; many reported simply removing their device would not reverse negative emotional outcomes, with this knowledge gain and bodily awareness difficult to forget.