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---
license: mit
dataset_info:
- config_name: breq
  features:
  - name: 'Unnamed: 0'
    dtype: int64
  - name: user_id
    dtype: string
  - name: type
    dtype: string
  - name: submitdate
    dtype: string
  - name: breq_amotivation
    dtype: float64
  - name: breq_external_regulation
    dtype: float64
  - name: breq_introjected_regulation
    dtype: float64
  - name: breq_identified_regulation
    dtype: float64
  - name: breq_intrinsic_regulation
    dtype: float64
  - name: breq_self_determination
    dtype: string
  splits:
  - name: train
    num_bytes: 11231
    num_examples: 92
  download_size: 7649
  dataset_size: 11231
- config_name: daily
  features:
  - name: 'Unnamed: 0'
    dtype: string
  - name: id
    dtype: string
  - name: date
    dtype: string
  - name: nightly_temperature
    dtype: string
  - name: nremhr
    dtype: string
  - name: rmssd
    dtype: string
  - name: spo2
    dtype: string
  - name: full_sleep_breathing_rate
    dtype: string
  - name: stress_score
    dtype: string
  - name: sleep_points_percentage
    dtype: string
  - name: exertion_points_percentage
    dtype: string
  - name: responsiveness_points_percentage
    dtype: string
  - name: daily_temperature_variation
    dtype: string
  - name: badgeType
    dtype: string
  - name: calories
    dtype: string
  - name: filteredDemographicVO2Max
    dtype: string
  - name: distance
    dtype: string
  - name: activityType
    dtype: string
  - name: bpm
    dtype: string
  - name: lightly_active_minutes
    dtype: string
  - name: moderately_active_minutes
    dtype: string
  - name: very_active_minutes
    dtype: string
  - name: sedentary_minutes
    dtype: string
  - name: mindfulness_session
    dtype: string
  - name: scl_avg
    dtype: string
  - name: resting_hr
    dtype: string
  - name: sleep_duration
    dtype: string
  - name: minutesToFallAsleep
    dtype: string
  - name: minutesAsleep
    dtype: string
  - name: minutesAwake
    dtype: string
  - name: minutesAfterWakeup
    dtype: string
  - name: sleep_efficiency
    dtype: string
  - name: sleep_deep_ratio
    dtype: string
  - name: sleep_wake_ratio
    dtype: string
  - name: sleep_light_ratio
    dtype: string
  - name: sleep_rem_ratio
    dtype: string
  - name: steps
    dtype: string
  - name: minutes_in_default_zone_1
    dtype: string
  - name: minutes_below_default_zone_1
    dtype: string
  - name: minutes_in_default_zone_2
    dtype: string
  - name: minutes_in_default_zone_3
    dtype: string
  - name: age
    dtype: string
  - name: gender
    dtype: string
  - name: bmi
    dtype: string
  - name: step_goal
    dtype: string
  - name: min_goal
    dtype: string
  - name: max_goal
    dtype: string
  - name: step_goal_label
    dtype: string
  - name: ALERT
    dtype: string
  - name: HAPPY
    dtype: string
  - name: NEUTRAL
    dtype: string
  - name: RESTED/RELAXED
    dtype: string
  - name: SAD
    dtype: string
  - name: TENSE/ANXIOUS
    dtype: string
  - name: TIRED
    dtype: string
  - name: ENTERTAINMENT
    dtype: string
  - name: GYM
    dtype: string
  - name: HOME
    dtype: string
  - name: HOME_OFFICE
    dtype: string
  - name: OTHER
    dtype: string
  - name: OUTDOORS
    dtype: string
  - name: TRANSIT
    dtype: string
  - name: WORK/SCHOOL
    dtype: string
  splits:
  - name: train
    num_bytes: 3513566
    num_examples: 7410
  download_size: 993037
  dataset_size: 3513566
- config_name: hourly
  features:
  - name: 'Unnamed: 0'
    dtype: string
  - name: id
    dtype: string
  - name: date
    dtype: string
  - name: hour
    dtype: string
  - name: temperature
    dtype: string
  - name: badgeType
    dtype: string
  - name: calories
    dtype: string
  - name: distance
    dtype: string
  - name: activityType
    dtype: string
  - name: bpm
    dtype: string
  - name: mindfulness_session
    dtype: string
  - name: scl_avg
    dtype: string
  - name: steps
    dtype: string
  - name: minutes_in_default_zone_1
    dtype: string
  - name: minutes_below_default_zone_1
    dtype: string
  - name: minutes_in_default_zone_2
    dtype: string
  - name: minutes_in_default_zone_3
    dtype: string
  - name: age
    dtype: string
  - name: gender
    dtype: string
  - name: bmi
    dtype: string
  - name: step_goal
    dtype: string
  - name: min_goal
    dtype: string
  - name: max_goal
    dtype: string
  - name: step_goal_label
    dtype: string
  - name: ALERT
    dtype: string
  - name: HAPPY
    dtype: string
  - name: NEUTRAL
    dtype: string
  - name: RESTED/RELAXED
    dtype: string
  - name: SAD
    dtype: string
  - name: TENSE/ANXIOUS
    dtype: string
  - name: TIRED
    dtype: string
  - name: ENTERTAINMENT
    dtype: string
  - name: GYM
    dtype: string
  - name: HOME
    dtype: string
  - name: HOME_OFFICE
    dtype: string
  - name: OTHER
    dtype: string
  - name: OUTDOORS
    dtype: string
  - name: TRANSIT
    dtype: string
  - name: WORK/SCHOOL
    dtype: string
  splits:
  - name: train
    num_bytes: 40337488
    num_examples: 159508
  download_size: 6556319
  dataset_size: 40337488
- config_name: panas
  features:
  - name: 'Unnamed: 0'
    dtype: int64
  - name: user_id
    dtype: string
  - name: type
    dtype: string
  - name: submitdate
    dtype: string
  - name: positive_affect_score
    dtype: int64
  - name: negative_affect_score
    dtype: int64
  splits:
  - name: train
    num_bytes: 20100
    num_examples: 268
  download_size: 5874
  dataset_size: 20100
- config_name: personality
  features:
  - name: 'Unnamed: 0'
    dtype: int64
  - name: user_id
    dtype: string
  - name: type
    dtype: string
  - name: submitdate
    dtype: string
  - name: extraversion
    dtype: float64
  - name: agreeableness
    dtype: float64
  - name: conscientiousness
    dtype: float64
  - name: stability
    dtype: float64
  - name: intellect
    dtype: float64
  - name: gender
    dtype: string
  - name: ipip_extraversion_category
    dtype: string
  - name: ipip_agreeableness_category
    dtype: string
  - name: ipip_conscientiousness_category
    dtype: string
  - name: ipip_stability_category
    dtype: string
  - name: ipip_intellect_category
    dtype: string
  splits:
  - name: train
    num_bytes: 7533
    num_examples: 50
  download_size: 9982
  dataset_size: 7533
- config_name: stai
  features:
  - name: 'Unnamed: 0'
    dtype: int64
  - name: user_id
    dtype: string
  - name: type
    dtype: string
  - name: submitdate
    dtype: string
  - name: stai_stress
    dtype: float64
  - name: stai_stress_category
    dtype: string
  splits:
  - name: train
    num_bytes: 22545
    num_examples: 279
  download_size: 5552
  dataset_size: 22545
- config_name: ttm
  features:
  - name: 'Unnamed: 0'
    dtype: int64
  - name: user_id
    dtype: string
  - name: type
    dtype: string
  - name: submitdate
    dtype: string
  - name: stage
    dtype: string
  - name: ttm_consciousness_raising
    dtype: float64
  - name: ttm_dramatic_relief
    dtype: float64
  - name: ttm_environmental_reevaluation
    dtype: float64
  - name: ttm_self_reevaluation
    dtype: float64
  - name: ttm_social_liberation
    dtype: float64
  - name: ttm_counterconditioning
    dtype: float64
  - name: ttm_helping_relationships
    dtype: float64
  - name: ttm_reinforcement_management
    dtype: float64
  - name: ttm_self_liberation
    dtype: float64
  - name: ttm_stimulus_control
    dtype: float64
  splits:
  - name: train
    num_bytes: 14684
    num_examples: 94
  download_size: 11135
  dataset_size: 14684
configs:
- config_name: breq
  data_files:
  - split: train
    path: breq/train-*
- config_name: daily
  data_files:
  - split: train
    path: daily/train-*
- config_name: hourly
  data_files:
  - split: train
    path: hourly/train-*
- config_name: panas
  data_files:
  - split: train
    path: panas/train-*
- config_name: personality
  data_files:
  - split: train
    path: personality/train-*
- config_name: stai
  data_files:
  - split: train
    path: stai/train-*
- config_name: ttm
  data_files:
  - split: train
    path: ttm/train-*
---







- PAPER: https://www.nature.com/articles/s41597-022-01764-x

BREQ-2. For the BREQ-2 scale, each item is again assigned to a factor on which that item is scored (i.e., of the
fve factors: (1) Amotivation, (2) External regulation, (3) Introjected regulation, (4) Identifed regulation, (5)
Intrinsic regulation). Once scores are assigned to all of the items, we calculate each user’s mean for every factor, according to the scoring instructions (http://exercise-motivation.bangor.ac.uk/breq/brqscore.php). We also
create a categorical variable describing the self-determination level for each user, namely the maximum scoring
factor.
PANAS. For the PANAS scale, each item contributes to one of two afect scores (i.e. (1) Positive Afect Score,
or (2) Negative Afect Score). Once items are assigned to a factor, we sum up the item scores per factor as per
the scoring instructions (https://ogg.osu.edu/media/documents/MB%20Stream/PANAS.pdf). Scores can range
from 10 to 50, with higher scores representing higher levels of positive or negative afect, respectively.


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64b29494689a9a230135dc2c/69IOcxj7mz3DRKz2Zw89D.png)

TTM. For the TTM scale, each user is assigned a stage of change (i.e., of the fve stages: (1) Maintenance, (2)
Action, (3) Preparation, (4) Contemplation, or (5) Precontemplation) based on their response to the respective scale. Regarding the Processes of Change for Physical Activity, each item is assigned to a factor on which
that item is scored (i.e., of the 10 factors: (1) Consciousness Raising, (2) Dramatic Relief, (3) Environmental
Reevaluation, (4) Self Reevaluation, (5) Social Liberation, (6) Counterconditioning, (7) Helping Relationships,
(8) Reinforcement Management, (9) Self Liberation, or (10) Stimulus Control). Once scores are assigned to all
of the items, we calculate each user’s mean for every factor, according to the scoring instructions (https://hbcrworkgroup.weebly.com/transtheoretical-model-applied-to-physical-activity.html).

S-STAI. For the S-STAI scale, we initially reverse scores of the positively connotated items, and then total the scoring weights, resulting in the STAI score (the higher the score the more stressed the participant feels) as per the scoring instructions (https://oml.eular.org/sysModules/obxOML/docs/id_150/State-Trait-Anxiety-Inventory.pdf).
To assign some interpretation to the numerical value, we also create a categorical variable, assigning each user
to a STAI stress level (i.e., of three levels, (1) below average, (2) average, or (3) above average STAI score). Note
that due to human error, the S-STAI scale was administered with a 5-point Likert scale instead of a 4-point one.
During processing, we convert each item to a 4-point scale in accordance with the original.